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Cells
Volume 13
Issue 4
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Cells, Volume 13, Issue 4 (February-2 2024) – 74 articles

Cover Story (view full-size image): Vasoactive intestinal peptides (VIPs) are widely distributed in the central and peripheral nervous, digestive and respiratory systems. VIPs contribute to an extensive range of physiological and pathological processes and control neuronal, epithelial, and endocrine cell function. In the current publication, we focused our studies on VIPs and VIP receptor-induced esophageal inflammation and remodeling. Our findings provided evidence that eosinophilic and mast cell accumulation in response to nerve cell-derived mediator VIP and receptor CRTH2 interaction promotes motility disfunction in eosinophilic esophagitis (EoE). Most importantly, we showed that eosinophil and mast cell accumulation, which are directly responsible for esophageal motility dysfunction improves  following CRTH2 antagonist treatment in experimentally induced chronic EoE. View this paper
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17 pages, 5900 KiB  
Article
In Vitro Glioblastoma Model on a Plate for Localized Drug Release Study from a 3D-Printed Drug-Eluted Hydrogel Mesh
by Behnad Chehri, Kaiwen Liu, Golnaz Vaseghi, Amir Seyfoori and Mohsen Akbari
Cells 2024, 13(4), 363; https://doi.org/10.3390/cells13040363 - 19 Feb 2024
Cited by 4 | Viewed by 2857
Abstract
Glioblastoma multiforme (GBM) is an aggressive type of brain tumor that has limited treatment options. Current standard therapies, including surgery followed by radiotherapy and chemotherapy, are not very effective due to the rapid progression and recurrence of the tumor. Therefore, there is an [...] Read more.
Glioblastoma multiforme (GBM) is an aggressive type of brain tumor that has limited treatment options. Current standard therapies, including surgery followed by radiotherapy and chemotherapy, are not very effective due to the rapid progression and recurrence of the tumor. Therefore, there is an urgent need for more effective treatments, such as combination therapy and localized drug delivery systems that can reduce systemic side effects. Recently, a handheld printer was developed that can deliver drugs directly to the tumor site. In this study, the feasibility of using this technology for localized co-delivery of temozolomide (TMZ) and deferiprone (DFP) to treat glioblastoma is showcased. A flexible drug-loaded mesh (GlioMesh) loaded with poly (lactic-co-glycolic acid) (PLGA) microparticles is printed, which shows the sustained release of both drugs for up to a month. The effectiveness of the printed drug-eluting mesh in terms of tumor toxicity and invasion inhibition is evaluated using a 3D micro-physiological system on a plate and the formation of GBM tumoroids within the microenvironment. The proposed in vitro model can identify the effective combination doses of TMZ and DFP in a sustained drug delivery platform. Additionally, our approach shows promise in GB therapy by enabling localized delivery of multiple drugs, preventing off-target cytotoxic effects. Full article
(This article belongs to the Special Issue Cell Death Mechanisms and Therapeutic Opportunities in Glioblastoma)
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Figure 1

Figure 1
<p>Schematic view of the (<b>A</b>) Emulsion solvent evaporation technique for fabrication of TMZ-loaded PLGA microparticles with high encapsulation efficiency and (<b>B</b>) bioink preparation. (<b>C</b>) 3D printing of alginate mesh containing TMZ-encapsulated PLGA microparticles using a handheld printer. (<b>D</b>) 3D-printed alginate mesh, including drug-encapsulated microparticles. (<b>E</b>) 3-in-1 3D culture plate with microwells and inserted 3D-printed mesh for localized drug release study. (<b>F</b>) Schematic side view of the 3D tumoroid culture plate with the pattern of formed spheroids inside the microwells. (<b>G</b>–<b>I</b>) Invasion process illustration of glioblastoma tumoroids within the collagen ECM hydrogel over time.</p> Full article ">Figure 2
<p>SEM micrographs of various synthesized microparticles. (<b>A</b>) 5% PLGA synthesized microparticles encapsulated with (i) DFP and (ii) TMZ. (<b>B</b>) 10% PLGA synthesized microparticles encapsulated with (i) DFP and (ii) TMZ. (<b>C</b>) 15% PLGA synthesized microparticles encapsulated with (i) DFP and (ii) TMZ. The scale bar is 300 µm.</p> Full article ">Figure 3
<p>(<b>A</b>) Overview of various release profiles of DFP for various PLGA concentrations in ACSF. (<b>B</b>) Overview of various release profiles of DFP for various PLGA concentrations in DMEM fabricated with the w/o/w method. (<b>C</b>) Overview of various release profiles of TMZ for various PLGA concentrations in ACSF. (<b>D</b>) Overview of various release profiles of TMZ for various PLGA concentrations in DMEM fabricated with the o/o method. Cum.con: Cumulative concentration.</p> Full article ">Figure 4
<p>(<b>A</b>–<b>I</b>) Micrographs of alginate meshes printed using various particle concentrations (1, 3, and 6 mg/mL) and under different printing parameters. (<b>J</b>) Overview of various release profiles of TMZ for various alginate-to-particle ratios in DMEM. (<b>K</b>) Overview of various release profiles of TMZ for various alginate-to-particle ratios in ACSF.</p> Full article ">Figure 5
<p>(<b>A</b>,<b>B</b>) Live/dead imaging of the tumoroids with different treatment conditions on days 1 and 5, respectively. (i) DFP, and DFP + TMZ treatment with different microparticle loading: (ii) 1 mg/mL, (iii) 3 mg/mL, (iv) 6 mg/mL. Normalized fluorescent intensity of the live and dead cell population in tumoroids under different treatment conditions is measured through ImageJ analysis and compared on day one and day five, depicted in panels (<b>A</b>,<b>B</b>), respectively. (<b>C</b>,<b>D</b>) Quantitative cell viability of the tumoroids screened with different treatment conditions using presto-blue assay (D: DFP and D + T: DFP + TMZ with varying concentrations inside the 3D-printed mesh) on day 1 and 5, respectively. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and ns = not significant. (<b>E</b>–<b>J</b>) Flow cytometry live/dead analysis of the population of cells within treated tumoroids with different GlioMesh conditions on day 5.</p> Full article ">Figure 6
<p>(<b>A</b>–<b>F</b>) Live/dead imaging of the tumoroids invasion with different treatment conditions on day 5. (<b>F</b>) Quantified normalized invasion length of tumoroids under different treatment conditions on day 5 (D: DFP; T: TMZ microparticles; D + T: DFP + TMZ microparticles with varying concentrations inside the 3D-printed mesh). (<b>G</b>) Normalized invasion length of the tumoroids in different treatment conditions on day 5; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001. (<b>H</b>) Normalized number of invaded cells/areas in different treatment conditions of the U251 tumoroids.</p> Full article ">
12 pages, 2370 KiB  
Article
Comparison of the Single Cell Immune Landscape between Subjects with High Mycobacterium tuberculosis Bacillary Loads during Active Pulmonary Tuberculosis and Household Members with Latent Tuberculosis Infection
by Supitcha Kamolratanakul, Wassawon Ariyanon, Kanyarat Udompornpitak, Thansita Bhunyakarnjanarat, Asada Leelahavanichkul, Jittima Dhitavat, Polrat Wilairatana and Wiwat Chancharoenthana
Cells 2024, 13(4), 362; https://doi.org/10.3390/cells13040362 - 19 Feb 2024
Viewed by 2290
Abstract
It is unclear how the immune system controls the transition from latent tuberculosis (TB) infection (LTBI) to active pulmonary infection (PTB). Here, we applied mass spectrometry cytometry time-of-flight (CyTOF) analysis of peripheral blood mononuclear cells to compare the immunological landscapes in patients with [...] Read more.
It is unclear how the immune system controls the transition from latent tuberculosis (TB) infection (LTBI) to active pulmonary infection (PTB). Here, we applied mass spectrometry cytometry time-of-flight (CyTOF) analysis of peripheral blood mononuclear cells to compare the immunological landscapes in patients with high tuberculous bacillary load PTB infections and LTBI. A total of 32 subjects (PTB [n = 12], LTBI [n = 17], healthy volunteers [n = 3]) were included. Participants with active PTBs were phlebotomized before administering antituberculosis treatment, whereas participants with LTBI progressed to PTB at the time of household screening. In the present study, CyTOF analysis identified significantly higher percentages of mucosal-associated invariant natural killer T (MAIT NKT) cells in subjects with LTBI than in those with active PTB and healthy controls. Moreover, 6 of 17 (35%) subjects with LTBI progressed to active PTB (LTBI progression) and had higher proportions of MAIT NKT cells and early NKT cells than those without progression (LTBI non-progression). Subjects with LTBI progression also showed a tendency toward low B cell levels relative to other subject groups. In conclusion, MAIT NKT cells were substantially more prevalent in subjects with LTBI, particularly those with progression to active PTB. Full article
(This article belongs to the Special Issue Tuberculosis: From Pathogenesis to Targeted Therapies)
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Figure 1

Figure 1
<p>Flowchart of subjects included in the study. LTBI, latent tuberculosis infection; TB-HIV, tuberculosis, and human immunodeficiency virus co-infection.</p> Full article ">Figure 2
<p>Immune profile characteristics determined by CyTOF analysis. Heatmap showing the percent frequency of immune cell subsets in healthy subjects (H) (n = 3) and subjects with active pulmonary tuberculosis (PTB) (n =12), and latent tuberculosis with non-progression to PTB (LTBI-NP) (n = 11), and latent tuberculosis with progression to PTB (LTBI-PG) (n = 6). (<b>A</b>). (<b>B</b>–<b>Q</b>) Violin plots showing the proportions of T cells (CD4<sup>+</sup> T cells, CD8<sup>+</sup> T cells) (green), B cells (red), unconventional T cells (mucosal-associated invariant T (MAIT) cell and γδT cells), and natural killer (NK) cells (blue) subgroups. It is observed that the negative values in the violin plot correspond to estimations of data values as a result of kernel density estimation. Bold and dashed lines in violin plots represent median and quartile values, respectively, for each comparison (* <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.005). mDC, myeloid dendritic cells; pDC, plasmacytoid dendritic cells.</p> Full article ">Figure 3
<p>The relative distribution of natural killer (NK) cells (CD14<sup>−</sup>CD3<sup>−</sup>CD123<sup>−</sup>CD66b<sup>−</sup>CD45RA<sup>+</sup>CD56<sup>dim+</sup>CD57<sup>−&gt;+</sup>) among experimental groups: Healthy. (<b>A</b>), active PTB (<b>B</b>), LTBI progression (<b>C</b>), LTBI non-progression (<b>D</b>). The plots represent individuals of each group pooled (blue and red represent early NK cells (CD56) and late NK cells (CD57), respectively).</p> Full article ">Figure 4
<p>Comparison of the relative distribution of natural killer (NK) cells (CD14<sup>−</sup>CD3<sup>−</sup>CD123<sup>−</sup>CD66b<sup>−</sup>CD45RA<sup>+</sup>CD56<sup>dim+</sup>CD57<sup>−&gt;+</sup>) between participants who were (<b>A</b>) non-responders (smear positive, n = 4) and (<b>B</b>) treatment responders (smear-negative, n = 14). The plots represent individuals of each group pooled (blue and red represent early NK cells (CD56) and late NK cells (CD57), respectively).</p> Full article ">
17 pages, 1133 KiB  
Review
Signaling Pathways of AXL Receptor Tyrosine Kinase Contribute to the Pathogenetic Mechanisms of Glioblastoma
by Alberto Repici, Alessio Ardizzone, Fabiola De Luca, Lorenzo Colarossi, Angela Prestifilippo, Gabriele Pizzino, Irene Paterniti, Emanuela Esposito and Anna Paola Capra
Cells 2024, 13(4), 361; https://doi.org/10.3390/cells13040361 - 19 Feb 2024
Cited by 1 | Viewed by 3473
Abstract
Brain tumors are a diverse collection of neoplasms affecting the brain with a high prevalence rate in people of all ages around the globe. In this pathological context, glioblastoma, a form of glioma that belongs to the IV-grade astrocytoma group, is the most [...] Read more.
Brain tumors are a diverse collection of neoplasms affecting the brain with a high prevalence rate in people of all ages around the globe. In this pathological context, glioblastoma, a form of glioma that belongs to the IV-grade astrocytoma group, is the most common and most aggressive form of the primary brain tumors. Indeed, despite the best treatments available including surgery, radiotherapy or a pharmacological approach with Temozolomide, glioblastoma patients’ mortality is still high, within a few months of diagnosis. Therefore, to increase the chances of these patients surviving, it is critical to keep finding novel treatment opportunities. In the past, efforts to treat glioblastoma have mostly concentrated on customized treatment plans that target specific mutations such as epidermal growth factor receptor (EGFR) mutations, Neurotrophic Tyrosine Receptor Kinase (NTRK) fusions, or multiple receptors using multi-kinase inhibitors like Sunitinib and Regorafenib, with varying degrees of success. Here, we focused on the receptor tyrosine kinase AXL that has been identified as a mediator for tumor progression and therapy resistance in various cancer types, including squamous cell tumors, small cell lung cancer, and breast cancer. Activated AXL leads to a significant increase in tumor proliferation, tumor cell migration, and angiogenesis in different in vitro and in vivo models of cancer since this receptor regulates interplay with apoptotic, angiogenic and inflammatory pathways. Based on these premises, in this review we mainly focused on the role of AXL in the course of glioblastoma, considering its primary biological mechanisms and as a possible target for the application of the most recent treatments. Full article
(This article belongs to the Special Issue Glioblastoma Cell: From Cellular and Molecular Mechanisms to Innovative Therapy)
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Figure 1

Figure 1
<p>The basic structure and signaling pathway of AXL.</p> Full article ">Figure 2
<p>AXL functions in glioblastoma.</p> Full article ">
21 pages, 8614 KiB  
Article
Pharmacological Stimulation of Soluble Guanylate Cyclase Counteracts the Profibrotic Activation of Human Conjunctival Fibroblasts
by Bianca Saveria Fioretto, Irene Rosa, Elena Andreucci, Rita Mencucci, Mirca Marini, Eloisa Romano and Mirko Manetti
Cells 2024, 13(4), 360; https://doi.org/10.3390/cells13040360 - 18 Feb 2024
Cited by 1 | Viewed by 2234
Abstract
Conjunctival fibrosis is a serious clinical concern implicated in a wide spectrum of eye diseases, including outcomes of surgery for pterygium and glaucoma. It is mainly driven by chronic inflammation that stimulates conjunctival fibroblasts to differentiate into myofibroblasts over time, leading to abnormal [...] Read more.
Conjunctival fibrosis is a serious clinical concern implicated in a wide spectrum of eye diseases, including outcomes of surgery for pterygium and glaucoma. It is mainly driven by chronic inflammation that stimulates conjunctival fibroblasts to differentiate into myofibroblasts over time, leading to abnormal wound healing and scar formation. Soluble guanylate cyclase (sGC) stimulation was found to suppress transforming growth factor β (TGFβ)-induced myofibroblastic differentiation in various stromal cells such as skin and pulmonary fibroblasts, as well as corneal keratocytes. Here, we evaluated the in vitro effects of stimulation of the sGC enzyme with the cell-permeable pyrazolopyridinylpyrimidine compound BAY 41-2272 in modulating the TGFβ1-mediated profibrotic activation of human conjunctival fibroblasts. Cells were pretreated with the sGC stimulator before challenging with recombinant human TGFβ1, and subsequently assayed for viability, proliferation, migration, invasiveness, myofibroblast marker expression, and contractile properties. Stimulation of sGC significantly counteracted TGFβ1-induced cell proliferation, migration, invasiveness, and acquisition of a myofibroblast-like phenotype, as shown by a significant downregulation of FAP, ACTA2, COL1A1, COL1A2, FN1, MMP2, TIMP1, and TIMP2 mRNA levels, as well as by a significant reduction in α-smooth muscle actin, N-cadherin, COL1A1, and FN-EDA protein expression. In addition, pretreatment with the sGC stimulator was capable of significantly dampening TGFβ1-induced acquisition of a contractile phenotype by conjunctival fibroblasts, as well as phosphorylation of Smad3 and release of the proinflammatory cytokines IL-1β and IL-6. Taken together, our findings are the first to demonstrate the effectiveness of pharmacological sGC stimulation in counteracting conjunctival fibroblast-to-myofibroblast transition, thus providing a promising scientific background to further explore the feasibility of sGC stimulators as potential new adjuvant therapeutic compounds to treat conjunctival fibrotic conditions. Full article
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Figure 1

Figure 1
<p>The sGC stimulator BAY 41-2272 does not affect human conjunctival fibroblast viability and inhibits TGFβ1-induced cell proliferation. (<b>A</b>) Representative annexin V/PI flow cytometry assay plots of conjunctival fibroblasts at the basal condition and challenged with recombinant human TGFβ1 alone, BAY 41-2272 1 μM or 10 μM alone, or TGFβ1 added 2 h after preincubation with BAY 41-2272 1 µM or 10 µM. The upper left (Q1) quadrant represents annexin V<sup>−</sup>/PI<sup>+</sup> necrotic cells, the upper right (Q2) quadrant annexin V<sup>+</sup>/PI<sup>+</sup> late apoptotic cells, the lower left (Q3) quadrant annexin V<sup>−</sup>/PI<sup>−</sup> viable cells, and the lower right (Q4) quadrant annexin V<sup>+</sup>/PI<sup>−</sup> early apoptotic cells. (<b>B</b>) Mean ± SEM percentage of viable cells (Q3) is reported for each experimental point. (<b>C</b>) Cell proliferation assessed with WST-1 colorimetric assay. Cell proliferation at basal condition was set to 100%, and the other results were normalized accordingly. Bars represent the mean ± SEM of triplicate determinations from three cell lines. ### <span class="html-italic">p</span> &lt; 0.001 and # <span class="html-italic">p</span> &lt; 0.05 vs. basal condition, ** <span class="html-italic">p</span> &lt; 0.01 and * <span class="html-italic">p</span> &lt; 0.05 vs. TGFβ1 (Tukey’s test). SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 2
<p>The sGC stimulator BAY 41-2272 inhibits TGFβ1-induced acquisition of a profibrotic myofibroblast-like phenotype by human conjunctival fibroblasts. (<b>A</b>) Representative phase-contrast photomicrographs of conjunctival fibroblasts cultured at the basal condition and challenged with recombinant human TGFβ1 or BAY 41-2272 10 µM alone, or TGFβ1 added 2 h after preincubation with BAY 41-2272 10 µM. (<b>B</b>) Representative fluorescence photomicrographs of conjunctival fibroblasts stained for F-actin with Alexa 488-conjugated phalloidin (green) and immunostained for vinculin (red). Nuclei are counterstained with DAPI (blue). Higher magnifications are shown in the small bottom panels. Scale bar: 200 μm (<b>A</b>), 50 μm (<b>B</b>), 25 μm (<b>B</b>, bottom panels). (<b>C</b>) Quantification of cell confluency 48 h after stimulation. Bars represent the mean ± SEM of triplicate determinations of the percentage of cell confluency. ## <span class="html-italic">p</span> &lt; 0.01 vs. basal condition, * <span class="html-italic">p</span> &lt; 0.05 vs. TGFβ1 (Tukey’s test). DAPI, 4′,6-diamidino-2-phenylindole; F-actin, filamentous actin; SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 3
<p>The sGC stimulator BAY 41-2272 significantly reduces the TGFβ1-induced capability of human conjunctival fibroblasts to re-establish monolayer integrity after wounding. Wound-healing ability was assessed in cells at the basal condition and after treatment with TGFβ1, TGFβ1 and BAY 41-2272 10 µM, or BAY 41-2272 alone. Representative phase-contrast photomicrographs of the scratched area at 0 and 24 h are shown. Scale bar: 400 μm. Wound margins are drawn in black. Bars represent the mean ± SEM of triplicate determinations of the percentage of wound healing after 24 h. ### <span class="html-italic">p</span> &lt; 0.001 vs. basal condition, *** <span class="html-italic">p</span> &lt; 0.001 vs. TGFβ1 (Tukey’s test). SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 4
<p>The sGC stimulator BAY 41-2272 significantly reduces TGFβ1-induced migration and invasiveness of human conjunctival fibroblasts. Representative images of the filters with migrated (chemotaxis) and invasive (chemoinvasion) cells stained with Diff-Quik are shown. Scale bar: 100 μm. Histograms represent the results of quantitative analysis of chemotaxis and chemoinvasion expressed as the number of migrated or invasive cells per field. Data are the means ± SEM of three independent experiments performed in duplicate with three cell lines. ### <span class="html-italic">p</span> &lt; 0.001 and # <span class="html-italic">p</span> &lt; 0.05 vs. basal condition, ** <span class="html-italic">p</span> &lt; 0.01 and * <span class="html-italic">p</span> &lt; 0.05 vs. TGFβ1 (Tukey’s test). SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 5
<p>The sGC stimulator BAY 41-2272 significantly decreases TGFβ1-induced expression of genes encoding profibrotic activation/myofibroblast markers in human conjunctival fibroblasts. Gene expression of <span class="html-italic">FAP</span> (gene encoding fibroblast activation protein), <span class="html-italic">ACTA2</span> (gene encoding α-smooth muscle actin), <span class="html-italic">COL1A1</span> (gene encoding type I collagen α-1 chain), <span class="html-italic">COL1A2</span> (gene encoding type I collagen α-2 chain), <span class="html-italic">FN1</span> (gene encoding fibronectin 1), <span class="html-italic">MMP2</span> (gene encoding matrix metalloproteinase-2), <span class="html-italic">TIMP1</span> (gene encoding tissue inhibitor of metalloproteinases (TIMP)-1), and <span class="html-italic">TIMP2</span> (gene encoding TIMP-2) was measured by real-time quantitative PCR. For each gene, basal expression was set to 1, and the other results were normalized to this value. 18S ribosomal RNA was used as a reference gene. Histograms represent the mean ± SEM of triplicate determinations from three cell lines. ### <span class="html-italic">p</span> &lt; 0.001, ## <span class="html-italic">p</span> &lt; 0.01, and # <span class="html-italic">p</span> &lt; 0.05 vs. basal condition, *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, and * <span class="html-italic">p</span> &lt; 0.05, vs. TGFβ1 (Tukey’s test). SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 6
<p>The sGC stimulator BAY 41-2272 significantly reduces TGFβ1-induced protein expression of profibrotic activation/myofibroblast markers in human conjunctival fibroblasts. Representative immunoblots for α-SMA, N-cadherin, COL1A1, and FN-EDA. For normalization, α-actinin, GAPDH, or α-tubulin were used as loading controls. The molecular weight (kDa) of each protein is shown. Histograms represent the mean ± SEM of optical density in arbitrary units (a.u.). ### <span class="html-italic">p</span> &lt; 0.001, ## <span class="html-italic">p</span> &lt; 0.01, and # <span class="html-italic">p</span> &lt; 0.05 vs. basal condition, *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, and * <span class="html-italic">p</span> &lt; 0.05 vs. TGFβ1 (Tukey’s test). α-SMA, α-smooth muscle actin; COL1A1, α-1 chain of type I collagen; FN-EDA, fibronectin containing extra domain A; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 7
<p>The sGC stimulator BAY 41-2272 significantly diminishes TGFβ1-induced α-SMA expression and incorporation into stress fibers and COL1A1 synthesis in human conjunctival fibroblasts. Representative fluorescence photomicrographs of cells immunostained for α-SMA (green) and COL1A1 (red) are shown. Nuclei are counterstained with DAPI (blue). Scale bar = 50 μm. α-SMA, α smooth muscle actin; COL1A1, α-1 chain of type I collagen; DAPI, 4′,6-diamidino-2-phenylindole; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 8
<p>The sGC stimulator BAY 41-2272 significantly dampens the TGFβ1-induced contractile ability of human conjunctival fibroblasts. Representative wells of the collagen gel contraction assay are shown. Every experimental point was performed in triplicate. Histograms represent the mean ± SEM of gel sizes expressed as the percentage of those observed in wells with cells at basal condition. ### <span class="html-italic">p</span> &lt; 0.001 vs. basal condition, ** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ1 (Tukey’s test). SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 9
<p>The sGC stimulator BAY 41-2272 significantly reduces TGFβ1-induced Smad3-dependent canonical TGFβ1 signaling in human conjunctival fibroblasts. Representative immunoblots for p-Smad3, total Smad3, p-ERK1/2, and total ERK1/2 are shown. α-actinin was used as a loading control for normalization. The molecular weight (kDa) of each protein is shown. Bars represent the mean ± SEM of optical density in arbitrary units (a.u.). ### <span class="html-italic">p</span> &lt; 0.001 and ## <span class="html-italic">p</span> &lt; 0.01 vs. basal condition, * <span class="html-italic">p</span> &lt; 0.05 vs. TGFβ1 (Tukey’s test). p-ERK1/2, phosphorylated-ERK1/2; p-Smad3, phosphorylated-Smad3; SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">Figure 10
<p>The sGC stimulator BAY 41-2272 significantly lowers TGFβ1-induced gene expression and secretion of proinflammatory cytokines in human conjunctival fibroblasts. (<b>A</b>) Gene expression of <span class="html-italic">IL1B</span> (gene encoding IL-1β) and <span class="html-italic">IL6</span> (gene encoding IL-6) was evaluated by real-time quantitative PCR. 18S ribosomal RNA was used as a reference gene. The basal level of each gene was set to 1, and the other results were normalized to this value. (<b>B</b>) Protein levels of IL-1β and IL-6 were measured in culture supernatants by enzyme-linked immunosorbent assay and expressed as a percentage of those at basal condition. Bars represent the mean ± SEM of triplicate determinations from three cell lines. ### <span class="html-italic">p</span> &lt; 0.001 and ## <span class="html-italic">p</span> &lt; 0.01 vs. basal condition, *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, and * <span class="html-italic">p</span> &lt; 0.05 vs. TGFβ1 (Tukey’s test). IL, interleukin; SEM, standard error of the mean; sGC, soluble guanylate cyclase; TGFβ1, transforming growth factor β1.</p> Full article ">
6 pages, 194 KiB  
Editorial
Advances in Red Blood Cells Research
by Anna Bogdanova and Lars Kaestner
Cells 2024, 13(4), 359; https://doi.org/10.3390/cells13040359 - 18 Feb 2024
Viewed by 2513
Abstract
This Editorial ‘Advances in Red Blood Cell Research’ is the preface for the special issue with the same title which files 14 contributions listed in Table 1 [...] Full article
(This article belongs to the Collection Advances in Red Blood Cells Research)
13 pages, 6527 KiB  
Communication
Effect of LDL Extracted from Human Plasma on Membrane Stiffness in Living Endothelial Cells and Macrophages via Scanning Ion Conductance Microscopy
by Diana Kiseleva, Vasilii Kolmogorov, Vadim Cherednichenko, Ulyana Khovantseva, Anastasia Bogatyreva, Yuliya Markina, Petr Gorelkin, Alexander Erofeev and Alexander Markin
Cells 2024, 13(4), 358; https://doi.org/10.3390/cells13040358 - 18 Feb 2024
Cited by 3 | Viewed by 1822
Abstract
Mechanical properties of living cells play a crucial role in a wide range of biological functions and pathologies, including atherosclerosis. We used low-stress Scanning Ion-Conductance Microscopy (SICM) correlated with confocal imaging and demonstrated the topographical changes and mechanical properties alterations in EA.hy926 and [...] Read more.
Mechanical properties of living cells play a crucial role in a wide range of biological functions and pathologies, including atherosclerosis. We used low-stress Scanning Ion-Conductance Microscopy (SICM) correlated with confocal imaging and demonstrated the topographical changes and mechanical properties alterations in EA.hy926 and THP-1 exposed to LDL extracted from CVD patients’ blood samples. We show that the cells stiffened in the presence of LDL, which also triggered caveolae formation. Endothelial cells accumulated less cholesterol in the form of lipid droplets in comparison to THP-1 cells based on fluorescence intensity data and biochemical analysis; however, the effect on Young’s modulus is higher. The cell stiffness is closely connected to the distribution of lipid droplets along the z-axis. In conclusion, we show that the sensitivity of endothelial cells to LDL is higher compared to that of THP-1, triggering changes in the cytoskeleton and membrane stiffness which may result in the increased permeability of the intima layer due to loss of intercellular connections and adhesion. Full article
(This article belongs to the Special Issue Lipids, Their Receptors and Signaling in Development and Diseases)
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<p>(<b>A</b>) Mechanical properties of endothelial cell line EA.hy926 in control plates and LDL treated plates with confocal images of lipid droplets accumulation; (<b>B</b>) mechanical properties of PMA-induced THP-1 macrophages in control plates and LDL treated plates with confocal images of lipid droplets accumulation; (<b>C</b>) statistical analysis of the difference in Young’s modulus and the effect of BDP 630/650 on membrane stiffness. The small decrease in the stiffness of the endothelial cell membrane caused by the lipid dye is not statistically significant; (<b>D</b>) fluorescence intensity measured by correlative SICM and normalized cholesterol-to-protein ratio for EA.hy926 and PMA-induced THP-1 macrophages in control plates andLDL treated plates.</p> Full article ">
20 pages, 2652 KiB  
Review
Regulatory B Cells—Immunopathological and Prognostic Potential in Humans
by Johanna Veh, Carolin Ludwig, Hubert Schrezenmeier and Bernd Jahrsdörfer
Cells 2024, 13(4), 357; https://doi.org/10.3390/cells13040357 - 18 Feb 2024
Cited by 10 | Viewed by 3558
Abstract
The aim of the following review is to shed light on the putative role of regulatory B cells (Bregs) in various human diseases and highlight their potential prognostic and therapeutic relevance in humans. Regulatory B cells are a heterogeneous group of B lymphocytes [...] Read more.
The aim of the following review is to shed light on the putative role of regulatory B cells (Bregs) in various human diseases and highlight their potential prognostic and therapeutic relevance in humans. Regulatory B cells are a heterogeneous group of B lymphocytes capable of suppressing inflammatory immune reactions. In this way, Bregs contribute to the maintenance of tolerance and immune homeostasis by limiting ongoing immune reactions temporally and spatially. Bregs play an important role in attenuating pathological inflammatory reactions that can be associated with transplant rejection, graft-versus-host disease, autoimmune diseases and allergies but also with infectious, neoplastic and metabolic diseases. Early studies of Bregs identified IL-10 as an important functional molecule, so the IL-10-secreting murine B10 cell is still considered a prototype Breg, and IL-10 has long been central to the search for human Breg equivalents. However, over the past two decades, other molecules that may contribute to the immunosuppressive function of Bregs have been discovered, some of which are only present in human Bregs. This expanded arsenal includes several anti-inflammatory cytokines, such as IL-35 and TGF-β, but also enzymes such as CD39/CD73, granzyme B and IDO as well as cell surface proteins including PD-L1, CD1d and CD25. In summary, the present review illustrates in a concise and comprehensive manner that although human Bregs share common functional immunosuppressive features leading to a prominent role in various human immunpathologies, they are composed of a pool of different B cell types with rather heterogeneous phenotypic and transcriptional properties. Full article
(This article belongs to the Special Issue Exclusive Review Papers in "Cellular Immunology")
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<p>Main subtypes of human regulatory B cells. (<b>A</b>) IL-10+ regulatory B cells (Bregs) inhibit the Th1, Th17 and CD8+ T cell response, convert naïve CD4+ T cells into regulatory T cell populations and modulate pro-inflammatory cells of the innate immune system, such as macrophages, NK cells and dendritic cells via secretion of IL-10. (<b>B</b>) GrB+ regulatory B cells (GraB cells) inhibit the response of Th1 and Th17 cells and reduce the proliferation of T cells by reducing their proliferation through GrB-mediated enzymatic cleavage of the ζ-chain of their T cell receptor. (<b>C</b>) TGF-β+ Bregs act similarly to IL-10+ Bregs on naïve CD4+ T cells, generating FoxP3+ Tregs and inducing anergy in CD4+ and CD8+ T cells. (<b>D</b>) IL-35+ Bregs can promote tolerance in the context of chronic infections by supporting both IL-35-producing Tregs and their own generation. Abbreviations: Breg = regulatory B cell, CD = cluster of differentiation, DC = dendritic cell, GraB cell = GrB-secreting regulatory B cell, GrB = granzyme B, IFN = interferon, IL = interleukin, M∅ = macrophage, NK cell = natural killer cell, NO = nitric oxide, pDC = plasmacytoid dendritic cell, TGF = transforming growth factor, Th = T helper cell, TNF = tumor necrosis factor, tolDC = tolerogenic dendritic cell, Treg = regulatory T cell, ↑ = upregulation, ↓ = downregulation. Figures were prepared using BioRender (Agreement number: UA2659WLGL).</p> Full article ">Figure 2
<p>Suppressive mechanisms of human regulatory B cells. Like regulatory T cells, the currently known subpopulations of human regulatory B cells (Bregs) utilize numerous different mechanisms for their immunosuppressive activity. These include the secretion of soluble molecules such as the cytokines IL-10, IL-35 or TGF-β as well as the cytotoxic enzyme granzyme B (GrB). On the other hand, molecules expressed on the surface of Bregs also play a major role in inhibiting immune responses. These molecules can be enzymes such as CD39, CD73 or IDO, which convert certain substrates in such a way that this results in the inhibition of certain immune cells. On the other hand, molecules that require direct contact with corresponding complementary ligands on other immune cells are also involved in the immunosuppressive effect of Bregs. These include antigen-presenting molecules such as CD1d or MHC II, costimulatory molecules such as CD80, CD86 or CD40 or ligands for so-called “death receptors” such as Fas or PD-1. Key inducers of Bregs include cytokines such as IL-21 and IL-10, the B cell receptor (BCR) and Toll-like receptors (TLRs). Abbreviations: ADO = adenosine, AMP = adenosine monophosphate, ATP = adenosine triphosphate, BCR = B cell receptor, Breg = regulatory B cell, CD = cluster of differentiation, DC = dendritic cell, FasL = Fas ligand, GrB = granzyme B, ICOSL = inducible costimulator ligand, IDO = indoleamine 2,3-dioxygenase, IFN = interferon, IL = interleukin, iTCR = invariant T cell receptor, M∅ = macrophage, MHC = major histocompatibility complex, NK cell = natural killer cell, NKT = natural killer T cell, PD-L1 = programmed cell death ligand-1, TCR = T cell receptor, TGF = transforming growth factor, Th = T helper cell, TLR = toll-like receptor, TNF = tumor necrosis factor, Treg = regulatory T cell, ↓ = downregulation. Figures were generated using BioRender (Agreement number: UA2659WLGL).</p> Full article ">Figure 3
<p>Development of granzyme B-secreting regulatory B cells as deviation of their IL-21-dependent differentiation into plasma cells. Complete activation of CD4<sup>+</sup> T cells requires simultaneous stimulation of the T cell receptor (TCR) via MHC/peptide complexes and of CD28 by costimulatory molecules such as CD80 or CD86 on antigen-presenting cells (APC). When T cells are fully activated, they secrete IL-21 and express large amounts of CD40L on their surface, which enables them to initiate differentiation of B cells into antibody-producing plasma cells. In certain situations, the TCR of CD4<sup>+</sup> T cells can be activated without simultaneous co-stimulation via CD28. As an example, the HIV protein Nef is able to directly activate T cells via the TCR in the absence of professional APC. This results in incomplete activation of T helper cells, which react with secretion of IL-21 but no relevant upregulation of CD40L. After interaction with such incompletely activated T helper cells, BCR-stimulated B cells develop into GrB<sup>+</sup> B cells with regulatory potential (GraB cells) instead of plasma cells. Abbreviations: BCR = B cell receptor, CD = cluster of differentiation, GraB cell = GrB-secreting regulatory B cell, GrB = granzyme B, IL = interleukin, MHC = major histocompatibility complex, PMA = Phorbol-12-Myristate-13-Acetate. Figures were generated using BioRender (Agreement number: UA2659WLGL).</p> Full article ">
12 pages, 14056 KiB  
Article
New Insights on the Male and Female Reproductive Organs of Centrorhynchus globocaudatus (Acanthocephala), Intestinal Parasite of Birds of Prey
by Bahram Sayyaf Dezfuli, Flavio Pironi, Emanuele Rossetti and Holger Herlyn
Cells 2024, 13(4), 356; https://doi.org/10.3390/cells13040356 - 18 Feb 2024
Viewed by 1795
Abstract
Acanthocephalans are dioecious parasites that gain sexual maturity in the alimentary canal of their definitive hosts (gnathostome vertebrates). This initial survey by light and transmission electron microscopy was conducted on the functional organization of the ovarian balls and uterine bell in mature females [...] Read more.
Acanthocephalans are dioecious parasites that gain sexual maturity in the alimentary canal of their definitive hosts (gnathostome vertebrates). This initial survey by light and transmission electron microscopy was conducted on the functional organization of the ovarian balls and uterine bell in mature females and on Saefftigen’s pouch and the copulatory bursa in males. We studied these structures via the example of Centrorhynchus globocaudatus (Palaeacanthocephala) in Falco tinnunculus and Buteo buteo, from the Province of Ferrara (Northern Italy). Our study confirms that the ovarian balls have surface microvilli and consist of a multinucleate supporting syncytium and a cellular region with oogonial syncytium, single germ cells, zygotes, and shelled eggs. Germ cells are embedded in the supporting syncytium. The ultrastructural features of these components and data on fertilization, shell formation, and release from the ovarian ball, alongside insights into the likely egg sorting function of the uterine bell, are provided. We also present light and electron microscopy observations of Saefftigen’s pouch and a suggestion regarding its hydrostatic functioning in the eversion of the copulatory bursa. Full article
(This article belongs to the Section Reproductive Cells and Development)
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Graphical abstract

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<p>Inseminated female acanthocephalans of <span class="html-italic">Centrorhynchus globocaudatus.</span> (<b>A</b>) Longitudinal section through fully mature female body; free ovarian ball (arrow) encircled by numerous eggs. Note extension of the ligament sac (curved arrows) from the base of the receptacle in anterior part of body (a) to the posterior end (p) of female body and point of its disruption (thick arrow). Giemsa staining; scale bar, 200 µm. (<b>B</b>) Immature female; numerous ovarian balls are still within the lining of the ligament sac (thick arrows) and some are loosely attached to it (arrows). Alcian Blue/PAS staining; scale bar, 100 µm. (<b>C</b>) Free ovarian balls in a fully mature female trunk; some eggs including acanthors (arrows) are in the periphery and few (thick arrows) in the inner region of the ovarian balls. Alcian Blue/PAS staining; scale bar, 50 µm. (<b>D</b>) Free ovarian balls (arrows) are surrounded by numerous shelled developmental stages. Giemsa staining; scale bar, 50 µm. (<b>E</b>) Mounted female <span class="html-italic">C. globocaudatus</span>; transition of uterine bell into tube-like uterus (arrow). The organ is surrounded by several shelled acanthors (arrowheads). Scale bar, 100 µm. (<b>F</b>) Posterior end of mounted female. A shelled acanthor (thin arrow) enters the inner opening of uterine bell; two acanthors (arrowheads) inside the uterine bell. Uterus (thick arrow) and genital opening (curved arrow) are visible. All the reproductive organs are surrounded by their envelopes inside the genital sheath (brackets); scale bar, 100 µm.</p> Full article ">Figure 2
<p>Male acanthocephalan <span class="html-italic">Centrorhynchus globocaudatus.</span> (<b>A</b>) Longitudinal section of the posterior end shows inverted copulatory bursa and juxtaposition of Saefftigen’s pouch (arrow) and campanulate part of the bursa (arrowheads). Note the opening of the bursa (curved arrow). Alcian Blue/PAS staining; scale bar, 50 µm. (<b>B</b>) Close contact between pouch (arrow) and bursa (arrowheads); opening of the bursa is evident (curved arrow). Alcian Blue/PAS staining; scale bar, 50 µm (<b>C</b>). Micrograph shows posterior end of male with fully everted bursa (arrowheads), spongy aspect of pouch (arrow), and contact of pouch’s stalk (thick arrow) and campanulate part of bursa. Alcian Blue/PAS staining; scale bar, 200 µm. (<b>D</b>) Semi-thin section of terminal part of male body with inverted bursa (arrowheads) and opening of the bursa (curved arrow). Toluidine blue staining; scale bar, 100 µm.</p> Full article ">Figure 3
<p>Transmission electron micrographs of the ovarian balls in inseminated female <span class="html-italic">Centrorhynchus globocaudatus.</span> (<b>A</b>) Section of half of a mature free-floating ovarian ball; internal multinucleate support syncytium (SS), oogonial syncytium (OS), and peripheral germ cell region with oogonial cell (OC), primary oocytes (thick arrows), and inseminated mature oocytes with shells (arrows) are visible. Microvilli (arrowheads) cover the surface of the ovarian ball; scale bar, 1 µm. (<b>B</b>) High magnification of periphery of the OB; primary oocyte (thick arrow) with eccentric nucleus, mature oocyte with shell (arrow), and microvilli (arrowheads) cover the surface of the ovarian ball; scale bar, 3.8 µm. (<b>C</b>) Micrograph showing the penetration of the spermatozoon into the mature oocyte; sections of the flagellum (arrow) and numerous electron-dense membrane-bound granules (curved arrows) and microvilli (arrowheads) on the surface of the OB; primary oocyte (thick arrow) with eccentric nucleus; scale bar, 2 µm. (<b>D</b>) Inseminated mature oocyte with shell in formation (thick arrows); within the cytoplasm, well-developed rough endoplasmic reticulum (arrow) and numerous electron-dense membrane-bound granules (arrowheads) and clusters of mitochondria are visible (curved arrows); scale bar, 0.7 µm. (<b>E</b>) In the cytoplasm of the mature oocyte, each membrane-bound granule has an amorphous electron-dense region (thick arrows) and granular region (arrows); curved arrows show mitochondria; scale bar, 0.5 µm.</p> Full article ">Figure 4
<p>Electron microscope images of ovarian balls in fecundated female <span class="html-italic">Centrorhynchus globocaudatus.</span> (<b>A</b>) Spermatozoa flagella (arrows) are embedded in the support syncytium (SS); penetration of spermatozoa into ovarian ball via microvillous surface (thick arrows); inseminated mature oocyte (asterisk) with completed shell; scale bar, 0.8 µm. (<b>B</b>) Penetration of microvillous OB surface by sperm flagella (thick arrows); flagellum (arrows) embedment in the SS is visible; two inseminated mature oocytes (asterisks) present with numerous electron-dense membrane-bound granules; scale bar, 5 µm. (<b>C</b>) Micrograph showing mainly the middle region of an OB with several SS nuclei (arrows) and some primary oocytes (asterisks); scale bar, 5 µm. (<b>D</b>) High magnification of the middle region of the OB; aspect of the multinucleate SS is evident; abundant heterochromatin laid on the inner membrane side of some of its nuclei (arrows); scale bar, 1 µm. (<b>E</b>) Inseminated mature oocyte (asterisk) with completed shell shortly before disruption of very thin peripheral SS envelope (arrowheads) and release from the OB. Note flagellum (arrow) embedment in SS; scale bar, 3.3 µm. (<b>F</b>) Periphery of an OB; some inseminated mature oocytes (asterisks) with shells in formation are peripherally enveloped by a very thin SS layer (arrowheads); after rupturing of the envelope, shelled eggs leave the organ; two free acanthors (arrows) near the OB; scale bar, 3 µm.</p> Full article ">Figure 5
<p>Transmission electron micrographs of sections of mature male <span class="html-italic">Centrorhynchus globocaudatus</span> posterior ends. (<b>A</b>) Contact between Saefftigen’s pouch (asterisk), vesicula seminalis (VS), and cement reservoir (CR). Each organ has its own lining; often, there is only a narrow distance between these organs (arrows); scale bar, 5 µm. (<b>B</b>) Micrograph shows most of the spongy Saefftigen’s pouch (asterisk) in vicinity of the copulatory bursa (arrow); in interface region between both organs appears to be tissue of almost identical aspect to the main portion of Saefftigen’s pouch (thick arrows); scale bar, 2 µm. (<b>C</b>) High magnification underscores the spongy aspect of Saefftigen’s pouch, filled with some electron-dense matrix (arrowheads); pouch is delimited by its own lining (arrows); scale bar, 0.5 µm. (<b>D</b>) Posterior end of male with portion of the pouch (arrowheads) in proximity to the inverted bursa (arrow); opening of the bursa (asterisk); scale bar, 5 µm. (<b>E</b>) Higher magnification of (<b>D</b>): in interface region between pouch (arrowhead) and bursa (arrow), occurrence of genital sheath (thick arrows) is evident; opening of the bursa (asterisk); scale bar, 2 µm.</p> Full article ">
14 pages, 2053 KiB  
Article
Anti-Apoptotic and Anti-Inflammatory Properties of Grapefruit IntegroPectin on Human Microglial HMC3 Cell Line
by Miriana Scordino, Giulia Urone, Monica Frinchi, Chiara Valenza, Angela Bonura, Chiara Cipollina, Rosaria Ciriminna, Francesco Meneguzzo, Mario Pagliaro, Giuseppa Mudò and Valentina Di Liberto
Cells 2024, 13(4), 355; https://doi.org/10.3390/cells13040355 - 18 Feb 2024
Cited by 3 | Viewed by 1899
Abstract
In this study, we investigated the beneficial effects of grapefruit IntegroPectin, derived from industrial waste grapefruit peels via hydrodynamic cavitation, on microglia cells exposed to oxidative stress conditions. Grapefruit IntegroPectin fully counteracted cell death and the apoptotic process induced by cell exposure to [...] Read more.
In this study, we investigated the beneficial effects of grapefruit IntegroPectin, derived from industrial waste grapefruit peels via hydrodynamic cavitation, on microglia cells exposed to oxidative stress conditions. Grapefruit IntegroPectin fully counteracted cell death and the apoptotic process induced by cell exposure to tert-butyl hydroperoxide (TBH), a powerful hydroperoxide. The protective effects of the grapefruit IntegroPectin were accompanied with a decrease in the amount of ROS, and were strictly dependent on the activation of the phosphoinositide 3-kinase (PI3K)/Akt cascade. Finally, IntegroPectin treatment inhibited the neuroinflammatory response and the basal microglia activation by down-regulating the PI3K- nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB)- inducible nitric oxide synthase (iNOS) cascade. These data strongly support further investigations aimed at exploring IntegroPectin’s therapeutic role in in vivo models of neurodegenerative disorders, characterized by a combination of chronic neurodegeneration, oxidative stress and neuroinflammation. Full article
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<p>Effects of grapefruit IntegroPectin (G) on HMC3 cell viability. (<b>A</b>) Concentration–effect of G treatment (24 h) on cell viability, evaluated via MTT assay. (<b>B</b>) Time-course of G treatment (1 mg/mL) effects on cell viability, assessed via MTT assay.</p> Full article ">Figure 2
<p>Protective and antioxidant effects of grapefruit IntegroPectin (G). (<b>A</b>) Concentration–response effects of TBH treatment (24 h) on HMC3 cell viability, evaluated via MTT assay. (<b>B</b>) Quantification of cell viability via MTT test in untreated (Ctrl) cells, cells treated with TBH (200 µM, 24 h), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h), and G alone (1 mg/mL, 24 h). (<b>C</b>) DCF fluorescence intensity quantification, an index of intracellular ROS generation, in Ctrl cells, cells treated with TBH (200 µM, 24 h), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h), and G alone (1 mg/mL, 24 h). (<b>D</b>) Representative pictures of DAPI nuclear staining in Ctrl cells, cells treated with TBH (200 µM, 24 h), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h), and G alone (1 mg/mL, 24 h). Tukey test: ## <span class="html-italic">p</span> &lt; 0.01, #### <span class="html-italic">p</span> &lt; 0.0001 as compared with Ctrl group. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. Scale bar: 100 μm.</p> Full article ">Figure 3
<p>Anti-apoptotic effects of grapefruit IntegroPectin. (<b>A</b>) Representative plot indicating the percentage of Annexin V<sup>-</sup> PI<sup>-</sup> cells (on the lower left quadrant), Annexin V<sup>+</sup> PI<sup>-</sup> cells (on the lower right quadrant), PI<sup>+</sup> Annexin V<sup>-</sup> cells (on the upper left quadrant) and PI<sup>+</sup> Annexin V<sup>+</sup> cells (on the upper right quadrant) of different conditions: untreated sample (Ctrl), sample treated with TBH (200 µM, 24 h), sample co-treated with TBH (200 µM, 24 h) and IntegroPectin (G) (1 mg/mL, 24 h), and sample treated with IntegroPectin (G) alone (1 mg/mL, 24 h). (<b>B</b>) Histogram showing the cumulative Annexin V<sup>-</sup> PI<sup>-</sup> cell (viable cells) percentages from all the experiments. (<b>C</b>) Histogram showing the cumulative Annexin V<sup>+</sup> PI<sup>-</sup> cell percentages (apoptotic cells) from all the experiments. (<b>D</b>) Representative images of Caspase-3 and β-actin western blotting bands and histogram of Caspase-3 normalized to β-actin Optical density in Ctrl cells, cells treated with TBH (200 µM, 24 h), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h), and G alone (1 mg/mL, 24 h). Tukey test: # <span class="html-italic">p</span> &lt; 0.05 as compared to Ctrl group; * <span class="html-italic">p</span> &lt; 0.05. AU (Arbitrary Units).</p> Full article ">Figure 4
<p>Modulation of MAPK/ERK and PI3K/Akt pathways by grapefruit IntegroPectin. (<b>A</b>) Representative images of phosphorylated (p)-ERK1/2 and β-Actin western blotting bands and histogram of p-ERK1/2 normalized to β-Actin Optical density in untreated (Ctrl) cells, cells treated with TBH (200 µM, 24 h), TBH (200 µM, 24 h) + IntegroPectin (G) (1 mg/mL, 24 h), and G alone (1 mg/mL, 24 h). (<b>B</b>) Quantification of cell viability via MTT test in Ctrl cells, cells treated with TBH (200 µM, 24 h), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h) + PD98059 (30 µM), and PD98059 (30 µM) only. PD98059 was administered 1 h before grapefruit IntegroPectin and TBH exposure. (<b>C</b>) Representative images of phosphorylated (p)-Akt and β-Actin western blotting bands and histogram of p-Akt normalized to β-Actin Optical density in Ctrl cells, cells treated with TBH (200 µM, 24 h), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h), and G (1 mg/mL, 24 h) alone. (<b>D</b>) Quantification of cell viability via MTT test in Ctrl cells, cells treated with TBH (200 µM, 24 h), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h 10), TBH (200 µM, 24 h) + G (1 mg/mL, 24 h) + LY294002 (10 µM), and LY294002 (10 µM) only. LY294002 was administered 1 h before grapefruit IntegroPectin and TBH exposure. Tukey test: # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, #### <span class="html-italic">p</span> &lt; 0.0001 as compared to Ctrl group; * <span class="html-italic">p</span> &lt; 0.05, **** <span class="html-italic">p</span> &lt; 0.0001. AU (Arbitrary Units).</p> Full article ">Figure 5
<p>Modulation of inflammatory mediators and pathways by grapefruit IntegroPectin. Real-time PCR of IL-6 (<b>A</b>), IL-1β (<b>B</b>) and iNOS (<b>C</b>) mRNA levels in untreated (Ctrl) cells and cells treated with IntegroPectin (G) (1 mg/mL, 4 h). Representative images of phosphorylated (p)-ERK1/2 (<b>D</b>), p-Akt (<b>E</b>), p-NF-kB (<b>F</b>) and β-Actin western blotting bands and histogram of p-ERK1/2 (<b>D</b>), p-Akt (<b>E</b>) and p-NF-kB (<b>F</b>) normalized to β-Actin Optical density in Ctrl cells and cells treated with IntegroPectin (G) (1 mg/mL, 4 h). <span class="html-italic">t</span>-test: # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, as compared to Ctrl group. AU (Arbitrary Units).</p> Full article ">
15 pages, 1573 KiB  
Review
Quantum Dot Imaging Agents: Haematopoietic Cell Interactions and Biocompatibility
by Leigh Naylor-Adamson, Thomas W. Price, Zoe Booth, Graeme J. Stasiuk and Simon D. J. Calaminus
Cells 2024, 13(4), 354; https://doi.org/10.3390/cells13040354 - 18 Feb 2024
Cited by 2 | Viewed by 2106
Abstract
Quantum dots (QDs) are semi-conducting nanoparticles that have been developed for a range of biological and non-biological functions. They can be tuned to multiple different emission wavelengths and can have significant benefits over other fluorescent systems. Many studies have utilised QDs with a [...] Read more.
Quantum dots (QDs) are semi-conducting nanoparticles that have been developed for a range of biological and non-biological functions. They can be tuned to multiple different emission wavelengths and can have significant benefits over other fluorescent systems. Many studies have utilised QDs with a cadmium-based core; however, these QDs have since been shown to have poor biological compatibility. Therefore, other QDs, such as indium phosphide QDs, have been developed. These QDs retain excellent fluorescent intensity and tunability but are thought to have elevated biological compatibility. Herein we discuss the applicability of a range of QDs to the cardiovascular system. Key disease states such as myocardial infarction and stroke are associated with cardiovascular disease (CVD), and there is an opportunity to improve clinical imaging to aide clinical outcomes for these disease states. QDs offer potential clinical benefits given their ability to perform multiple functions, such as carry an imaging agent, a therapy, and a targeting motif. Two key cell types associated with CVD are platelets and immune cells. Both cell types play key roles in establishing an inflammatory environment within CVD, and as such aid the formation of pathological thrombi. However, it is unclear at present how and with which cell types QDs interact, and if they potentially drive unwanted changes or activation of these cell types. Therefore, although QDs show great promise for boosting imaging capability, further work needs to be completed to fully understand their biological compatibility. Full article
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<p>QD size results in emission spectra changes. QDs can fluoresce due to the activity of electrons. As a photon hits a semiconductor, an electron is excited from the valance band (outermost electron orbital of an atom that electrons occupy) to the conduction band (electron orbital that energised electrons can move to). The distance between these two bands is known as the band gap. Narrow band gaps of QDs shift optical properties to lower energies, which result in longer wavelengths [<a href="#B3-cells-13-00354" class="html-bibr">3</a>]. Created with BioRender.com.</p> Full article ">Figure 2
<p>Applications of QDs within the haematopoietic system and atherosclerosis. Select applications of QD types for atherosclerosis can include (<b>A</b>) prevention of plaque growth [<a href="#B32-cells-13-00354" class="html-bibr">32</a>], (<b>B</b>) imaging of the affected sites including atherosclerotic plaque and damaged endothelium [<a href="#B30-cells-13-00354" class="html-bibr">30</a>], and (<b>C</b>) anticoagulant activity and plaque imaging [<a href="#B33-cells-13-00354" class="html-bibr">33</a>]. These applications utilise various QD types, including lead sulphide, cadmium tellurium, and selenium QDs. Created with BioRender.com.</p> Full article ">
21 pages, 1999 KiB  
Review
Cellular Senescence, Mitochondrial Dysfunction, and Their Link to Cardiovascular Disease
by Maria Camacho-Encina, Laura K. Booth, Rachael E. Redgrave, Omowumi Folaranmi, Ioakim Spyridopoulos and Gavin D. Richardson
Cells 2024, 13(4), 353; https://doi.org/10.3390/cells13040353 - 17 Feb 2024
Cited by 13 | Viewed by 5395
Abstract
Cardiovascular diseases (CVDs), a group of disorders affecting the heart or blood vessels, are the primary cause of death worldwide, with an immense impact on patient quality of life and disability. According to the World Health Organization, CVD takes an estimated 17.9 million [...] Read more.
Cardiovascular diseases (CVDs), a group of disorders affecting the heart or blood vessels, are the primary cause of death worldwide, with an immense impact on patient quality of life and disability. According to the World Health Organization, CVD takes an estimated 17.9 million lives each year, where more than four out of five CVD deaths are due to heart attacks and strokes. In the decades to come, an increased prevalence of age-related CVD, such as atherosclerosis, coronary artery stenosis, myocardial infarction (MI), valvular heart disease, and heart failure (HF) will contribute to an even greater health and economic burden as the global average life expectancy increases and consequently the world’s population continues to age. Considering this, it is important to focus our research efforts on understanding the fundamental mechanisms underlying CVD. In this review, we focus on cellular senescence and mitochondrial dysfunction, which have long been established to contribute to CVD. We also assess the recent advances in targeting mitochondrial dysfunction including energy starvation and oxidative stress, mitochondria dynamics imbalance, cell apoptosis, mitophagy, and senescence with a focus on therapies that influence both and therefore perhaps represent strategies with the most clinical potential, range, and utility. Full article
(This article belongs to the Topic Inflammation: The Cause of all Diseases 2.0)
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<p>Common characteristics that define mitotic and post-mitotic senescent cells. DNA Damage Response (DDR) and Cyclin Dependant Kinase Inhibitors (Cdkis).</p> Full article ">Figure 2
<p>Illustrates mitochondrial reactive oxygen species (mtROS) production within the electron transport chain (ETC). Electrons, initially provided by NADH in complex I and FADH2 in complex II, traverse through ubiquinone to reach complex III. Subsequently, they move to complex IV via cytochrome c, where they combine with molecular oxygen to generate water. Proton-pumping activities by complex I, complex III, and complex IV into the intermembrane space establish a proton gradient crucial for ATP synthesis. During oxidative phosphorylation, electron leakage occurs, leading to the interaction with molecular oxygen and the formation of superoxide (O<sub>2</sub><b><sup>−·</sup></b>). Complex I and complex III serve as the primary sites for ROS production within the mitochondria, while complex II also contributes. Complex III directs superoxide production both towards the matrix and the intermembrane space, whereas complex I and complex II exclusively produce ROS towards the matrix. Key components and molecules involved include coenzyme Q (CoQ), cytochrome c (Cyt c), electrons (e−), protons (H+), adenosine diphosphate (ADP), adenosine triphosphate (ATP), reduced (NADH) and oxidized (NAD+) nicotinamide adenine dinucleotide, flavin adenine dinucleotide (FAD), oxygen (O<sub>2</sub>).</p> Full article ">Figure 3
<p>Mitochondrial dysfunction contributes to cardiovascular disease through apoptosis and senescence. Mitochondrial dysfunction and increased ROS production promote DNA damage, both chromosomal and mitochondrial. DNA damage leads to p53 activation and a cell-fate decision between apoptosis and senescence. In apoptotic cells p53 induces mitochondrial outer membrane permeabilization via formation of the apoptotic pore which allows cytochrome c release, activation of the caspase cascade, and cell death. While not yet completely understood, but perhaps as a result as less severe stress, DNA damage and p53 can lead to expression of the p21 (a negative regulator of apoptosis and the cell cycle), activation of the p16 pathway, or activation of both p21 and p16 pathways resulting in cellular senescence. Upregulation of pro-survival pathways in senescent cells suppresses apoptotic pore formation leading to miMOMP, sublethal apoptosis and the release of mtDNA into the cytoplasm. mtDNA fragments are sensed by the cGAS-STING pathway, upregulating expression of inflammatory mediators. Sublethal activation of the caspase cascade may also promote additional DNA damage. A combination of apoptosis and senescence will drive pathological myocardial remodelling.</p> Full article ">
15 pages, 15420 KiB  
Review
Software Tools for 2D Cell Segmentation
by Ping Liu, Jun Li, Jiaxing Chang, Pinli Hu, Yue Sun, Yanan Jiang, Fan Zhang and Haojing Shao
Cells 2024, 13(4), 352; https://doi.org/10.3390/cells13040352 - 17 Feb 2024
Cited by 2 | Viewed by 3067
Abstract
Cell segmentation is an important task in the field of image processing, widely used in the life sciences and medical fields. Traditional methods are mainly based on pixel intensity and spatial relationships, but have limitations. In recent years, machine learning and deep learning [...] Read more.
Cell segmentation is an important task in the field of image processing, widely used in the life sciences and medical fields. Traditional methods are mainly based on pixel intensity and spatial relationships, but have limitations. In recent years, machine learning and deep learning methods have been widely used, providing more-accurate and efficient solutions for cell segmentation. The effort to develop efficient and accurate segmentation software tools has been one of the major focal points in the field of cell segmentation for years. However, each software tool has unique characteristics and adaptations, and no universal cell-segmentation software can achieve perfect results. In this review, we used three publicly available datasets containing multiple 2D cell-imaging modalities. Common segmentation metrics were used to evaluate the performance of eight segmentation tools to compare their generality and, thus, find the best-performing tool. Full article
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<p>An example of raw images and preprocessing result of DSB2018 datasets (<b>left</b>), Cellpose_cyto datasets (<b>center</b>), and PhC-C2DL-PSC datasets (<b>right</b>).</p> Full article ">Figure 2
<p>Some representative sections of the segmentation masks obtained after preprocessing the DSB2018 dataset as shown in (<b>A</b>–<b>D</b>). (<b>E</b>) shows the average cell numbers, and the suffix “*” indicates that the software had only successfully made segmentation predictions on preprocessed images. (<b>F</b>) shows FP/TP/FN values, and the prefix “un_” indicates that the software operates on non-preprocess images.</p> Full article ">Figure 3
<p>Some representative sections of the segmentation masks obtained after preprocessing the Cellpose_cyto dataset as shown in (<b>A</b>–<b>F</b>). (<b>G</b>) shows the cell numbers, and the suffix “*” indicates that the software had only successfully made segmentation predictions on preprocessed images. And (<b>H</b>) shows FP/TP/FN values, and the prefix “un_” indicates that the software operates on non-preprocess images.</p> Full article ">Figure 4
<p>Some representative sections of the segmentation masks obtained after preprocessing the PhC-C2DL-PSC dataset as shown in (<b>A</b>,<b>B</b>). (<b>C</b>) shows the cell numbers, and (<b>D</b>) shows FP/TP/FN values, and the prefix “un_ ” indicates that the software operates on non-preprocess images.</p> Full article ">
19 pages, 2702 KiB  
Article
The Development and Characterization of a Next-Generation Oncolytic Virus Armed with an Anti-PD-1 sdAb for Osteosarcoma Treatment In Vitro
by Theresa A. Higgins, Daniel J. Patton, Isabella M. Shimko-Lofano, Timothy L. Eller, Roberto Molinari, Maninder Sandey, Aliaa Ismail, Bruce F. Smith and Payal Agarwal
Cells 2024, 13(4), 351; https://doi.org/10.3390/cells13040351 - 17 Feb 2024
Viewed by 2339
Abstract
Osteosarcoma (OS) is a primary bone malignancy characterized by an aggressive nature, limited treatment options, low survival rate, and poor patient prognosis. Conditionally replicative adenoviruses (CRAds) armed with immune checkpoint inhibitors hold great potential for enhanced therapeutic efficacy. The present study aims to [...] Read more.
Osteosarcoma (OS) is a primary bone malignancy characterized by an aggressive nature, limited treatment options, low survival rate, and poor patient prognosis. Conditionally replicative adenoviruses (CRAds) armed with immune checkpoint inhibitors hold great potential for enhanced therapeutic efficacy. The present study aims to investigate the anti-tumor efficacy of CAV2-AU-M2, a CAV2-based CRAd armed with an anti-PD-1 single-domain antibody (sdAb), against OS cell lines in vitro. The infection, conditional replication, cytopathic effects, and cytotoxicity of CAV2-AU-M2 were tested in four different OS cell lines in two-dimensional (2D) and three-dimensional (3D) cell cultures. CAV2-AU-M2 showed selective replication in the OS cells and induced efficient tumor cell lysis and death. Moreover, CAV2-AU-M2 produced an anti-PD-1 sdAb that demonstrated effective binding to the PD-1 receptors. This study demonstrated the first CRAd armed with an anti-PD-1 sdAb. This combined approach of two distinct immunotherapies is intended to enhance the anti-tumor immune response in the tumor microenvironment. Full article
(This article belongs to the Special Issue New Advances in Cellular Immunotherapy)
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<p>CAV2-AU-M2’s infectious and cytolytic properties in canine osteosarcoma cells in 2D culture. Canine OS cell lines (D17, CF11, D22, and MC-KOS) and NCF cells were infected with CAV-AU-M2 at MOI of 100, and the DsRed fluorescent signal and cytopathic effects in cells were visualized using inverted fluorescent microscopy (Keyence) at 72 h post-infection at 10× magnification. (<b>A</b>) DsRed expression. (<b>B</b>) Cytopathic effect in infected cells. This is a representation of three independent experiments.</p> Full article ">Figure 2
<p>LDH release assay in 2D culture. (<b>A</b>) LDH release was measured in cells infected with CAV-AUM2 at MOI of 0, 10, 100, and 1000. LDH release was measured every 24 h post-infection up to 72 h. (<b>A</b>) Canine OS cell lines (D17, CF11, D22, and MC-KOS). (<b>B</b>) NCFs. These values are the average of three independent experiments.</p> Full article ">Figure 3
<p>CAV2-AU-M2’s infectious and cytolytic properties in canine osteosarcoma cells in 3D culture. Spheroids were formed from all canine OS cell lines (D17, CF11, D22, and MC-KOS) and NCF cells. Spheroids were infected with CAV-AU-M2 at MOI of 100 and the DsRed fluorescent signal and spheroid shrinkage in cells was visualized using inverted fluorescent microscopy (Keyence) at 72 h post-infection at 10× magnification. (<b>A</b>) Size decrease and cytopathic effect comparison between infected and non-infected spheroids on day 7; (<b>B</b>) DsRed expression on day 0, 4, and 7 post-infection in spheroids. This is a representation of three independent experiments.</p> Full article ">Figure 4
<p>LDH release assay in 3D culture. (<b>A</b>) LDH release was measured in spheroids infected with CAV-AU-M2 at MOI of 0, 100, and 1000. LDH release was measured at 96 and 168 h post-infection. (<b>A</b>) Canine OS cell lines (D17, CF11, D22, and MC-KOS); (<b>B</b>) NCFs. These values are the average of three independent experiments.</p> Full article ">Figure 5
<p>Functional properties of anti-PD-1 sdAb isolated from osteosarcoma cell lysates (CLs) and media infected with CAV2-AU-M2 virus. (<b>A</b>) Western blot analysis. Purified anti-PD-1 D5 sdAb was used as a positive control. Anti-PD-1 sdAb protein levels were measured via Western blotting using mouse anti-6x-His (Thermo) primary antibody and IRDye 800 CW goat anti-mouse (LI-COR) secondary antibody. (<b>B</b>) Flow cytometry analysis of anti-PD-1 sdAb binding to PD-1 receptor with cell count on the <span class="html-italic">y</span>-axis and fluorescence on the <span class="html-italic">x</span>-axis. Binding of anti-PD-1 sdAb purified from cell media collected from osteosarcoma cell lines (D17, CF11, MC-KOS, and D22) infected with CAV2-AU-M2 was compared with uninfected and CAV2-AU-M1-infected cells. (<b>C</b>) Flow cytometry analysis of anti-PD-1 sdAb binding to PD-1 receptor. Binding of anti-PD-1 sdAb purified from cell lysates collected from osteosarcoma cell lines (D17, CF11, MC-KOS, and D22) infected with CAV2-AU-M2 was compared with uninfected and CAV2-AU-M1-infected cells. (<b>D</b>) Flow cytometry analysis of PD-1/PD-L1 binding inhibition by anti-PD-1 sdAb. Inhibition of binding of PD-L1 to PD-1 by anti-PD-1 sdAb purified from cell media collected from osteosarcoma cell lines (D17, CF11, MC-KOS, and D22) infected with CAV2-AU-M2. (<b>E</b>) Flow cytometry analysis of PD-1/PD-L1 binding inhibition by anti-PD-1 sdAb. Inhibition of binding of PD-L1 to PD-1 by anti-PD-1 sdAb purified from cell lysates collected from osteosarcoma cell lines (D17, CF11, MC-KOS, and D22) infected with CAV2-AU-M2. CL, cell lysate; CM, cell media; NI, no infection.</p> Full article ">
21 pages, 1940 KiB  
Review
Subtype Transdifferentiation in Human Cancer: The Power of Tissue Plasticity in Tumor Progression
by Monica Fedele, Laura Cerchia and Sabrina Battista
Cells 2024, 13(4), 350; https://doi.org/10.3390/cells13040350 - 17 Feb 2024
Cited by 1 | Viewed by 2999
Abstract
The classification of tumors into subtypes, characterized by phenotypes determined by specific differentiation pathways, aids diagnosis and directs therapy towards targeted approaches. However, with the advent and explosion of next-generation sequencing, cancer phenotypes are turning out to be far more heterogenous than initially [...] Read more.
The classification of tumors into subtypes, characterized by phenotypes determined by specific differentiation pathways, aids diagnosis and directs therapy towards targeted approaches. However, with the advent and explosion of next-generation sequencing, cancer phenotypes are turning out to be far more heterogenous than initially thought, and the classification is continually being updated to include more subtypes. Tumors are indeed highly dynamic, and they can evolve and undergo various changes in their characteristics during disease progression. The picture becomes even more complex when the tumor responds to a therapy. In all these cases, cancer cells acquire the ability to transdifferentiate, changing subtype, and adapt to changing microenvironments. These modifications affect the tumor’s growth rate, invasiveness, response to treatment, and overall clinical behavior. Studying tumor subtype transitions is crucial for understanding tumor evolution, predicting disease outcomes, and developing personalized treatment strategies. We discuss this emerging hallmark of cancer and the molecular mechanisms involved at the crossroads between tumor cells and their microenvironment, focusing on four different human cancers in which tissue plasticity causes a subtype switch: breast cancer, prostate cancer, glioblastoma, and pancreatic adenocarcinoma. Full article
(This article belongs to the Section Cell Signaling)
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<p>Schematic representation of molecules and signaling pathways involved in the luminal to-basal-like transition of breast cancer. FOXA1, Forkhead box protein A1; MRTFA, Myocardin-related transcription factor A; ERα, estrogen receptor alpha; LSD1, lysine-specific demethylase 1; LCN2, lipocalin 2; IFI27, interferon alpha-inducible protein 27; LATS1, Large Tumor Suppressor 1. Created with BioRender.</p> Full article ">Figure 2
<p>Schematic representation of molecules involved in the neuroendocrine transdifferentiation of prostate cancer. Molecules in red are inactivated or downregulated; molecules in green are amplified, activated, or overexpressed. CRPC, castration-resistant prostate cancer; NEPC, neuroendocrine prostate cancer; AR, androgen receptor; SYP, synaptoohysin; CHGA, chromogranin A; ENO2, enolase 2; AURKA, aurora A kinase; MUC1, mucin 1; FOXA1/2, Forkhead box protein A1/2; ADT, androgen deprivation therapy; BRN2. Created with BioRender.</p> Full article ">Figure 3
<p>Schematic representation of the effects of tumor microenvironment on the proneural-to-mesenchymal transition in glioblastoma. CCL2 and 5, C-C motif chemokine ligand 2 and 5; CXCL12, CXC motif chemokine ligand 12; CSF-1, macrophage colony-stimulating factor 1; sEV, small extracellular vesicle; TAM, tumor associated macrophage. Created with BioRender.</p> Full article ">Figure 4
<p>Schematic representation of the major molecules involved in the acinar-to-ductal transdifferentiation in pancreatic ductal adenocarcinoma initiation. Molecules in red are inactivated or downregulated; molecules in green are amplified, activated, or overexpressed. TNF-α, transforming growth factor-α; MMP, metalloprotease; Hpa2, heparanase; PTF1a, pancreas associated transcription factor 1a; MIST1, muscle, intestine, and stomach expression 1; NFAT, nuclear factor of activated T cells; ATDC, ataxia-telangiectasia group D-complementing. Created with BioRender.</p> Full article ">
19 pages, 6394 KiB  
Article
Real-Time Multiphoton Intravital Microscopy of Drug Extravasation in Tumours during Acoustic Cluster Therapy
by Jessica Lage Fernandez, Sofie Snipstad, Astrid Bjørkøy and Catharina de Lange Davies
Cells 2024, 13(4), 349; https://doi.org/10.3390/cells13040349 - 16 Feb 2024
Viewed by 1989
Abstract
Optimising drug delivery to tumours remains an obstacle to effective cancer treatment. A prerequisite for successful chemotherapy is that the drugs reach all tumour cells. The vascular network of tumours, extravasation across the capillary wall and penetration throughout the extracellular matrix limit the [...] Read more.
Optimising drug delivery to tumours remains an obstacle to effective cancer treatment. A prerequisite for successful chemotherapy is that the drugs reach all tumour cells. The vascular network of tumours, extravasation across the capillary wall and penetration throughout the extracellular matrix limit the delivery of drugs. Ultrasound combined with microbubbles has been shown to improve the therapeutic response in preclinical and clinical studies. Most studies apply microbubbles designed as ultrasound contrast agents. Acoustic Cluster Therapy (ACT®) is a novel approach based on ultrasound-activated microbubbles, which have a diameter 5–10 times larger than regular contrast agent microbubbles. An advantage of using such large microbubbles is that they are in contact with a larger part of the capillary wall, and the oscillating microbubbles exert more effective biomechanical effects on the vessel wall. In accordance with this, ACT® has shown promising therapeutic results in combination with various drugs and drug-loaded nanoparticles. Knowledge of the mechanism and behaviour of drugs and microbubbles is needed to optimise ACT®. Real-time intravital microscopy (IVM) is a useful tool for such studies. This paper presents the experimental setup design for visualising ACT® microbubbles within the vasculature of tumours implanted in dorsal window (DW) chambers. It presents ultrasound setups, the integration and alignment of the ultrasound field with the optical system in live animal experiments, and the methodologies for visualisation and analysing the recordings. Dextran was used as a fluorescent marker to visualise the blood vessels and to trace drug extravasation and penetration into the extracellular matrix. The results reveal that the experimental setup successfully recorded the kinetics of extravasation and penetration distances into the extracellular matrix, offering a deeper understanding of ACT’s mechanisms and potential in localised drug delivery. Full article
(This article belongs to the Special Issue Recent Advances in Intravital and Live Cell Imaging)
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<p>(<b>a</b>) The dorsal window (DW) chamber positioned on the back of the nude mouse. (<b>b</b>) A zoomed view of the window shows the vasculature beneath the cover glass in the tumour implanted in the chamber. (<b>c</b>) Experimental workflow: The surgical implantation of DW was performed on the 1st day, 24 h after the tumour cells were implanted on the DW; after 10 to 12 days of growth, the tumours were images by IVM.</p> Full article ">Figure 2
<p>Acoustic Cluster Therapy (ACT<sup>®</sup>) microclusters are injected intravenously, and two ultrasound steps are applied to the tumour. The first step, activation, creates a large microbubble. The second step, enhancement, causes the large microbubble to oscillate, which leads to biomechanical effects on the vessel walls.</p> Full article ">Figure 3
<p>Illustration of the cone-based (<b>a</b>) and the water tank-based (<b>b</b>) ultrasound setups and the imaging setup.</p> Full article ">Figure 4
<p>Illustration of the design of the mouse holder immersed in the water tank. The upper view shows the dimensions of the mouse bed and the dorsal window (DW) hole. The frontal view shows the thickness of the mouse holder. The side view displays the angle of the mouse bed seen from the right side of the holder and the water level.</p> Full article ">Figure 5
<p>Picture of the cone-based experimental setup (<b>a</b>). Schematic of the ultrasound-imaging setup indicating the position of the transducer, the DW chamber, and the objective (not to scale) (<b>b</b>). Pressure profile from the transducer in the cone-based setup obtained by acoustic characterisation with a hydrophone scanning system (<b>c</b>).</p> Full article ">Figure 6
<p>Image of the water tank-based experimental setup (<b>a</b>). Schematical representation of the design of the water tank-based ultrasound setup (<b>b</b>). Pressure profile from the transducer obtained by acoustic characterisation with a hydrophone scanning system (<b>c</b>).</p> Full article ">Figure 7
<p>Real-time multiphoton intravital microscopy (MP-IVM) showing a microbubble and erythrocytes in the vasculature of an OHS tumour during ACT<sup>®</sup> (<b>a</b>). The scale bar represents 100 μm. Zoomed-in view of the area outlined by dotted lines in panel (<b>a</b>), highlighting a microbubble and erythrocytes (<b>b</b>). The scale bar represents 20 μm.</p> Full article ">Figure 8
<p>Time series of real-time MP-IVM during ACT<sup>®</sup> showing a microbubble lodged at a branching point and dextran extravasation (<b>a</b>). Colour-coded temporal representation of a zoomed-in view of the extravasation area, showing the temporal behaviour of the dextran before ACT<sup>®</sup> (<b>b</b>) and extravasation during treatment (<b>c</b>). Time 0 is the onset of ultrasound.</p> Full article ">Figure 9
<p>The relative mean intensity of dextran as a function of time intravascularly (<b>a</b>) and extravascularly (<b>b</b>) of two extravasation events. The figure shows when the bubble was lodged in the vasculature and when normal flow was restored. The relative mean intensity corresponds to ROIs containing the intravascular space and vicinity in the extravascular tissue. The intensity is presented relative to the background signal.</p> Full article ">Figure 10
<p>Distance map illustrating the penetration of dextran (<b>a</b>). Graph showing the penetration distance of dextran into the extravascular tissue as a function of time for the fast extravasation (<b>b</b>) and the slow extravasation (<b>c</b>).</p> Full article ">
18 pages, 4256 KiB  
Article
Dental Pulp Cell Transplantation Combined with Regenerative Endodontic Procedures Promotes Dentin Matrix Formation in Mature Mouse Molars
by Jorge Luis Montenegro Raudales, Yuta Okuwa and Masaki Honda
Cells 2024, 13(4), 348; https://doi.org/10.3390/cells13040348 - 16 Feb 2024
Viewed by 2132
Abstract
Regenerative endodontic procedures (REPs) are promising for dental pulp tissue regeneration; however, their application in permanent teeth remains challenging. We assessed the potential combination of an REP and local dental pulp cell (DPC) transplantation in the mature molars of C57BL/6 mice with (REP [...] Read more.
Regenerative endodontic procedures (REPs) are promising for dental pulp tissue regeneration; however, their application in permanent teeth remains challenging. We assessed the potential combination of an REP and local dental pulp cell (DPC) transplantation in the mature molars of C57BL/6 mice with (REP + DPC group) or without (REP group) transplantation of DPCs from green fluorescent protein (GFP) transgenic mice. After 4 weeks, the regenerated tissue was evaluated by micro-computed tomography and histological analyses to detect odontoblasts, vasculogenesis, and neurogenesis. DPCs were assessed for mesenchymal and pluripotency markers. Four weeks after the REP, the molars showed no signs of periapical lesions, and both the REP and REP + DPC groups exhibited a pulp-like tissue composed of a cellular matrix with vessels surrounded by an eosin-stained acellular matrix that resembled hard tissue. However, the REP + DPC group had a broader cellular matrix and uniquely contained odontoblast-like cells co-expressing GFP. Vasculogenesis and neurogenesis were detected in both groups, with the former being more prominent in the REP + DPC group. Overall, the REP was achieved in mature mouse molars and DPC transplantation improved the outcomes by inducing the formation of odontoblast-like cells and greater vasculogenesis. Full article
(This article belongs to the Special Issue Oral Tissue Stem Cells in Regenerative Dentistry)
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<p>Regenerative endodontic procedure (REP) and dental pulp cell (DPC) transplantation. (<b>A</b>) C57BL/6 mouse mandibular molar. (<b>B</b>) The pulp cavity was accessed using a 1/4 round bur. (<b>C</b>) Mesial and distal root canals were instrumented with #6, #8, and #10 K files. (<b>D</b>) Root canals were irrigated with 3% ethylenediaminetetraacetic acid and 3% NaClO. (<b>E</b>) Intracanal bleeding was provoked by over-instrumentation of the canals with the K files. (<b>F</b>) DPCs (1 × 10<sup>5</sup>) were transplanted after intracanal bleeding (REP + DPC group) or the canals were left untreated (REP group). (<b>G</b>) Mineral trioxide aggregate was placed on the pulp cavity. (<b>H</b>) The cavity was sealed with composite resin. (<b>I</b>) Timeline of the experimental design. μCT, microcomputed tomography; GFP, green fluorescent protein; w, week.</p> Full article ">Figure 2
<p>Isolation and characteristic analysis of mouse dental pulp cells (DPCs). (<b>A</b>) Dental pulp tissue was extracted from the mandibular molars of 5-day-old green fluorescent protein (GFP) transgenic mice. The tissue was incubated in enzymatic medium and DPCs were cultured in stem cell medium at 37 °C in a CO<sub>2</sub>-humidified incubator. (<b>B</b>) Morphological appearance and GFP expression of cultured DPCs after 1 day of culture (upper panels) and after the first passage (lower panels). Left panels are phase-contrast images (low magnification) and right panels are immunofluorescent images (high magnification). Scale bars = 100 µm. (<b>C</b>) Representative images of immunofluorescent staining of vimentin and cytokeratin in DPCs at 3rd passage. Scale bars = 100 µm (including the negative control) and 50 µm in the magnified area of the merged image. (<b>D</b>) Total number of vimentin+ (V+), vimentin+/cytokeratin+ (V+/C+), and cytokeratin+ (C+) cells quantified from 10 fields of vision with a 20× objective lens. Data are presented as means ± standard error of three different experiments using DPCs at passage 3. * <span class="html-italic">p</span> &lt; 0.05. (<b>E</b>) Expression of stem cell marker genes detected by gel electrophoresis from three different samples of DPCs at the second and third passages. Mouse embryonic stem cells (mESCs) were used as a positive control. In the <span class="html-italic">Oct4</span> row, the order for samples #1 and #4 is reversed. (<b>F</b>) Representative images of immunohistochemical staining of KLF4 in DPCs at the fourth passage. Scale bars = 100 µm and 50 µm in the magnified panel on the right and negative control. Quantification of KLF4-positive cells in DPCs from 10 fields of vision at high magnification from two independent experiments per passage time. Data are presented as means ± standard error of the mean.</p> Full article ">Figure 3
<p>Micro-computed tomography (µCT) analysis of regenerative endodontic procedure (REP)- and REP + dental pulp cell (DPC)-treated molars. (<b>A</b>) Representative µCT images of sagittal sections and three-dimensional reconstructed images of molars from the REP (<b>A</b>) and REP + DPC (<b>C</b>) groups at 1 and 4 weeks after treatment. Measurement of the periodontal ligament (PDL) space (mm<sup>2</sup>) in the periapical area of the mesial and distal roots at 1 and 4 weeks in the (<b>B</b>) REP- (n = 22) and (<b>D</b>) REP + DPC-treated (n = 24) molars. Data are presented as means ± standard errors of the means. ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 4
<p>Representative images of the regenerated tissue in the regenerative endodontic procedure (REP) and REP + dental pulp cell (DPC) groups. (<b>A</b>) Regenerated pulp-like tissue in the REP group (distal root) comprising a cell-rich zone in the center of the canal with blood vessels surrounded by a thick eosin-stained cell-poor (CP) zone that resembles hard tissue. (<b>B</b>) In the REP + DPC group, the cell-rich zone is larger with abundant vessels, surrounded by a lining of eosin-stained tissue containing cells (n = 8 per group). Scale bars = 200 µm and 50 µm in the magnified panels on the right. De: dentin, CP: cell-poor zone, Ce: cementum. Asterisks: vessels, stars: regenerated dentin-like tissue; arrows: cells embedded in dentin-like tissue.</p> Full article ">Figure 5
<p>Detection of odontoblast-like cells in the regenerated dental pulp-like tissue. Representative images of hematoxylin and eosin (H&amp;E)-stained sections and immunohistochemistry (IHC) sections stained with nestin, osteopontin (OPN), and green fluorescent protein (GFP) antibodies, as well as osteocalcin. Nestin (odontoblast marker) is not detected in regenerative endodontic procedure (REP) groups, whereas in the REP + dental pulp cell (DPC) groups, the regenerated tissue contains nestin-stained cells that co-express GFP (arrows). OPN and osteocalcin were detected in both groups, with the former being more abundant in the cellular matrix of the REP + DPC group (n = 6 per group). Scale bars = 50 µm (arrows indicate nestin and GFP co-expressing cells). 4′,6-diamidino-2-phenylindole: DAPI, Osteopontin: OPN.</p> Full article ">Figure 6
<p>Vascularization in the regenerated dental pulp tissue. (<b>A</b>) Representative images of tissue sections from the regenerative endodontic procedure (REP) and REP + dental pulp cell (DPC) groups stained with CD31 antibody. Scale bar = 50 µm. (<b>B</b>) Quantification of vessel-like structures stained with CD31 and their diameter. Data are presented as means ± standard error of the mean (n = 6 per group). * <span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Representative immunofluorescent images of green fluorescent protein (GFP)- and CD31-stained samples (n = 3, one section per sample of the REP + DPC group). Arrows indicate GFP-expressing cells in the vicinity of CD31-stained vessels. Scale bar = 20 µm. Hematoxylin and eosin: H&amp;E, 4′,6-diamidino-2-phenylindole: DAPI, cluster of differentiation 31: CD31.</p> Full article ">Figure 7
<p>Neurogenesis in regenerated dental pulp tissue. (<b>A</b>) Representative images of tissue sections from the regenerative endodontic procedure (REP) and REP + dental pulp cell (DPC) groups stained with neurofilament-L (NF-L) antibody. Arrows indicate NF-L-stained structures. Scale bar = 50 µm. (<b>B</b>) Comparison of the number of nerve fibers between the two groups. Data are presented as means ± standard error of the mean (n = 5 per group). (<b>C</b>) Representative immunofluorescence images of neurofilament-L and green fluorescent protein (GFP) double-stained samples (n = 3). Arrows indicate GFP-expressing cells. Scale bar = 100 µm and 50 µm in the magnified panel. NF-L: Neurofilament-L.</p> Full article ">
16 pages, 1656 KiB  
Review
Understanding Developmental Cell Death Using Drosophila as a Model System
by Ruchi Umargamwala, Jantina Manning, Loretta Dorstyn, Donna Denton and Sharad Kumar
Cells 2024, 13(4), 347; https://doi.org/10.3390/cells13040347 - 16 Feb 2024
Cited by 1 | Viewed by 3079
Abstract
Cell death plays an essential function in organismal development, wellbeing, and ageing. Many types of cell deaths have been described in the past 30 years. Among these, apoptosis remains the most conserved type of cell death in metazoans and the most common mechanism [...] Read more.
Cell death plays an essential function in organismal development, wellbeing, and ageing. Many types of cell deaths have been described in the past 30 years. Among these, apoptosis remains the most conserved type of cell death in metazoans and the most common mechanism for deleting unwanted cells. Other types of cell deaths that often play roles in specific contexts or upon pathological insults can be classed under variant forms of cell death and programmed necrosis. Studies in Drosophila have contributed significantly to the understanding and regulation of apoptosis pathways. In addition to this, Drosophila has also served as an essential model to study the genetic basis of autophagy-dependent cell death (ADCD) and other relatively rare types of context-dependent cell deaths. Here, we summarise what is known about apoptosis, ADCD, and other context-specific variant cell death pathways in Drosophila, with a focus on developmental cell death. Full article
(This article belongs to the Special Issue Drosophila Models in Autophagy and Aging)
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<p>Conservation of apoptotic machinery across phylogeny. In <span class="html-italic">C. elegans</span>, the BH3-only protein, EGL-1, inhibits the prosurvival factor, CED-9. This releases CED-4 which forms the apoptosome and promotes autocatalytic cleavage of CED-3 into an active caspase, thereby eventuating in cell death. <span class="html-italic">Drosophila</span> apoptosis proceeds with RHG proteins inhibiting Diap1, leading to Dark apoptosome-mediated activation of Dronc. Activation of downstream effector caspases, Drice and Dcp-1, signals cellular demise. In mammals, BH3-only proteins inhibit BCL-2 prosurvival activity, allowing activated BAX/BAK proteins to trigger mitochondrial outer membrane permeabilisation (MOMP). Cytochrome <span class="html-italic">c</span> release coordinates APAF-1 apoptosome formation and enables caspase-9 activation, subsequently promoting cell death in a caspase-3 and -7-dependent manner. Extrinsic lethal stimuli recognised by death receptors (TNFR, FAS) activate caspase-8, leading to caspase-3 and -7 activation and cell death. Truncation of BID to tBID by caspase-8 can also trigger MOMP and feed into intrinsic apoptotic pathways. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p> Full article ">Figure 2
<p>The molecular machinery of autophagy. Autophagy is an evolutionarily conserved process comprising (1) intiation, (2) nucleation, (3) expansion, and (4) fusion and degradation. Under basal or optimal cell conditions, mTORC1 remains active and phosphorylates Atg13, thereby preventing recruitment of Atg1. Cellular stressors including nutrient deprivation or energy depletion inactive mTORC1, thereby enabling formation of the Atg1 initiation complex (Atg1, Atg13, Atg17, Atg101). Nucleation occurs upon Atg1-dependent phoshophorylation and recruitment of Atg9, as well as the PtdIns3K complex (VPS15, VPS34, Atg6, Atg14). Expansion of the autophagosome relies on two ubiquitin-like conjugation systems—Atg12 and Atg8a. Conjugation of Atg16 to Atg5-Atg12 forms an E3-like complex that recruits the E2-like Atg3 to facilitate attachment of PE to Atg8a (Atg8a-PE) at the autophagosomal membrane. Fusion of autophagosomes to lysosomes relies on tethering proteins (SNAREs) and lysosomal membrane proteins (RAB7), forming an autolysosome within which lysosomal acid hydrolases degrade sequestered proteins and organelles. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p> Full article ">Figure 3
<p>Regulatory mechanisms underlying developmental PCD in <span class="html-italic">Drosophila</span>. Ecdysone, produced in the prothoracic glands from dietary cholesterol, circulates in haemolymph and transcriptionally upregulates ecdysone-responsive genes (<span class="html-italic">BrC</span>, <span class="html-italic">E74</span>, <span class="html-italic">E75</span>) in target tissues. Subsequent transcription of autophagy and apoptotic genes coordinates tissue deletion at multiple stages of <span class="html-italic">Drosophila</span> development. Downregulation of PI3K signalling inhibits mTORC1, thereby activating autophagy. Dpp signalling blocks ecdysone production and transcription of ecdysone-response genes, and must therefore be downregulated to trigger ADCD. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p> Full article ">
24 pages, 1047 KiB  
Review
Harnessing Pyroptosis for Cancer Immunotherapy
by Christopher M. Bourne and Cornelius Y. Taabazuing
Cells 2024, 13(4), 346; https://doi.org/10.3390/cells13040346 - 16 Feb 2024
Cited by 7 | Viewed by 4503
Abstract
Cancer immunotherapy is a novel pillar of cancer treatment that harnesses the immune system to fight tumors and generally results in robust antitumor immunity. Although immunotherapy has achieved remarkable clinical success for some patients, many patients do not respond, underscoring the need to [...] Read more.
Cancer immunotherapy is a novel pillar of cancer treatment that harnesses the immune system to fight tumors and generally results in robust antitumor immunity. Although immunotherapy has achieved remarkable clinical success for some patients, many patients do not respond, underscoring the need to develop new strategies to promote antitumor immunity. Pyroptosis is an immunostimulatory type of regulated cell death that activates the innate immune system. A hallmark of pyroptosis is the release of intracellular contents such as cytokines, alarmins, and chemokines that can stimulate adaptive immune activation. Recent studies suggest that pyroptosis promotes antitumor immunity. Here, we review the mechanisms by which pyroptosis can be induced and highlight new strategies to induce pyroptosis in cancer cells for antitumor defense. We discuss how pyroptosis modulates the tumor microenvironment to stimulate adaptive immunity and promote antitumor immunity. We also suggest research areas to focus on for continued development of pyroptosis as an anticancer treatment. Pyroptosis-based anticancer therapies offer a promising new avenue for treating immunologically ‘cold’ tumors. Full article
(This article belongs to the Special Issue Role of Inflammasome Activation in Innate and Adaptive Immunity)
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<p>Overview of pyroptosis mechanisms and pyroptosis-based therapeutics. (<b>A</b>) Schematic of the canonical inflammasome pathway. Inflammasome oligomerization activates caspase-1, which cleaves and activates IL-1β, IL-18, and GSDMD. Therapeutic strategies like the synthesized glutathione (GSH)-responsive GSDMD protein cages tethered to an attenuated <span class="html-italic">Salmonella typhimurium</span> (VNP) strain (VNP-GD), the NLRP3 activating nanovaccine, and the DPP inhibitors Val-boroPro and ARI-4175 activate caspase-1 to treat cancer. (<b>B</b>) Schematic of the human non-canonical inflammasome pathway. Caspases-4/5 detect intracellular LPS and convert IL-18 and GSDMD to their active forms, while deactivating IL-1β. (<b>C</b>) Schematic of the apoptotic pathways that induce gasdermin-mediated cell death. DNA damage by chemotherapeutics, targeted small molecules, photodynamic triggers, oncolytic viruses (OVs) and the nanoparticle approach (NanoCD) induce apoptotic caspase activation. Caspases-3, and -8, cleave GSDME or GSDMC respectively to induce apoptosis. Caspases-8/9 can also activate caspase-3 to execute GSDME-mediated pyroptosis. (<b>D</b>) Cytotoxic lymphocytes inject granzymes into target cells. Granzyme B cleave GSDME and Granzyme A cleaves GSDMB to induce pyroptosis. (<b>E</b>) Next-generation nanoparticle approaches deliver activated gasdermin proteins to directly induce pyroptosis. Image created with Biorender.</p> Full article ">
16 pages, 306 KiB  
Review
Complexity of the Genetic Background of Oncogenesis in Ovarian Cancer—Genetic Instability and Clinical Implications
by Marek Murawski, Adam Jagodziński, Aleksandra Bielawska-Pohl and Aleksandra Klimczak
Cells 2024, 13(4), 345; https://doi.org/10.3390/cells13040345 - 15 Feb 2024
Cited by 4 | Viewed by 3886
Abstract
Ovarian cancer is a leading cause of death among women with gynecological cancers, and is often diagnosed at advanced stages, leading to poor outcomes. This review explores genetic aspects of high-grade serous, endometrioid, and clear-cell ovarian carcinomas, emphasizing personalized treatment approaches. Specific mutations [...] Read more.
Ovarian cancer is a leading cause of death among women with gynecological cancers, and is often diagnosed at advanced stages, leading to poor outcomes. This review explores genetic aspects of high-grade serous, endometrioid, and clear-cell ovarian carcinomas, emphasizing personalized treatment approaches. Specific mutations such as TP53 in high-grade serous and BRAF/KRAS in low-grade serous carcinomas highlight the need for tailored therapies. Varying mutation prevalence across subtypes, including BRCA1/2, PTEN, PIK3CA, CTNNB1, and c-myc amplification, offers potential therapeutic targets. This review underscores TP53’s pivotal role and advocates p53 immunohistochemical staining for mutational analysis. BRCA1/2 mutations’ significance as genetic risk factors and their relevance in PARP inhibitor therapy are discussed, emphasizing the importance of genetic testing. This review also addresses the paradoxical better prognosis linked to KRAS and BRAF mutations in ovarian cancer. ARID1A, PIK3CA, and PTEN alterations in platinum resistance contribute to the genetic landscape. Therapeutic strategies, like restoring WT p53 function and exploring PI3K/AKT/mTOR inhibitors, are considered. The evolving understanding of genetic factors in ovarian carcinomas supports tailored therapeutic approaches based on individual tumor genetic profiles. Ongoing research shows promise for advancing personalized treatments and refining genetic testing in neoplastic diseases, including ovarian cancer. Clinical genetic screening tests can identify women at increased risk, guiding predictive cancer risk-reducing surgery. Full article
(This article belongs to the Special Issue Genetic Disorders in Breast and Ovarian Cancer)
13 pages, 6059 KiB  
Article
Morphological Changes of 3T3 Cells under Simulated Microgravity
by Minh Thi Tran, Chi Nguyen Quynh Ho, Son Nghia Hoang, Chung Chinh Doan, Minh Thai Nguyen, Huy Duc Van, Cang Ngoc Ly, Cuong Phan Minh Le, Huy Nghia Quang Hoang, Han Thai Minh Nguyen, Han Thi Truong, Quan Minh To, Tram Thi Thuy Nguyen and Long Thanh Le
Cells 2024, 13(4), 344; https://doi.org/10.3390/cells13040344 - 15 Feb 2024
Cited by 5 | Viewed by 2480
Abstract
Background: Cells are sensitive to changes in gravity, especially the cytoskeletal structures that determine cell morphology. The aim of this study was to assess the effects of simulated microgravity (SMG) on 3T3 cell morphology, as demonstrated by a characterization of the morphology of [...] Read more.
Background: Cells are sensitive to changes in gravity, especially the cytoskeletal structures that determine cell morphology. The aim of this study was to assess the effects of simulated microgravity (SMG) on 3T3 cell morphology, as demonstrated by a characterization of the morphology of cells and nuclei, alterations of microfilaments and microtubules, and changes in cycle progression. Methods: 3T3 cells underwent induced SMG for 72 h with Gravite®, while the control group was under 1G. Fluorescent staining was applied to estimate the morphology of cells and nuclei and the cytoskeleton distribution of 3T3 cells. Cell cycle progression was assessed by using the cell cycle app of the Cytell microscope, and Western blot was conducted to determine the expression of the major structural proteins and main cell cycle regulators. Results: The results show that SMG led to decreased nuclear intensity, nuclear area, and nuclear shape and increased cell diameter in 3T3 cells. The 3T3 cells in the SMG group appeared to have a flat form and diminished microvillus formation, while cells in the control group displayed an apical shape and abundant microvilli. The 3T3 cells under SMG exhibited microtubule distribution surrounding the nucleus, compared to the perinuclear accumulation in control cells. Irregular forms of the contractile ring and polar spindle were observed in 3T3 cells under SMG. The changes in cytoskeleton structure were caused by alterations in the expression of major cytoskeletal proteins, including β-actin and α-tubulin 3. Moreover, SMG induced 3T3 cells into the arrest phase by reducing main cell cycle related genes, which also affected the formation of cytoskeleton structures such as microfilaments and microtubules. Conclusions: These results reveal that SMG generated morphological changes in 3T3 cells by remodeling the cytoskeleton structure and downregulating major structural proteins and cell cycle regulators. Full article
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<p>Proliferation of 3T3 cells in control and SMG groups. (<b>A</b>,<b>B</b>) Cell morphology of 3T3 cells in control and SMG groups. (<b>C</b>,<b>D</b>) FCS values for control and SMG groups (<span class="html-italic">n</span> = 5). (<b>E</b>) Gravite<sup>®</sup> operation in CO<sub>2</sub> incubator. Scale bar = 223.64 µm.</p> Full article ">Figure 2
<p>Analysis of 3T3 nuclear morphology. (<b>A</b>) Nuclear intensity value/cell (<span class="html-italic">n</span> = 24). (<b>B</b>) Nuclear shape value (<span class="html-italic">n</span> = 24). (<b>C</b>) Nuclear area (<span class="html-italic">n</span> = 24). (<b>D</b>,<b>E</b>) Distribution of 3T3 nuclear shape values relative to nuclear intensity. (<b>F</b>,<b>G</b>) Distribution of 3T3 nuclear area values relative to nuclear intensity. Gray indicates percentage of nuclei &lt; 2n, blue indicates percentage of nuclei in G0/G1 phase, red indicates percentage of nuclei in S phase, green indicates percentage of nuclei in G2/M phase, and yellow indicates percentage of nuclei &gt; 4n.</p> Full article ">Figure 3
<p>Distribution of microfilament bundles of 3T3 cells. Microfilaments were stained with phalloidin (green color), and nuclei were counterstained with H33342. White arrows indicate microvilli. Scale bar = 223.64 µm.</p> Full article ">Figure 4
<p>Distribution of microtubules of 3T3 cells. Microtubules were stained with SiR-tubulin (red color). White arrows indicate perinuclear accumulations of microtubules; dashed arrows indicate distribution of microtubules surrounding nucleus. Scale bar = 223.64 µm.</p> Full article ">Figure 5
<p>Western blot analysis of major structural proteins in 3T3 cells. α-Tubulin 3 and β-actin were downregulated in 3T3 cells under SMG (<span class="html-italic">n</span> = 3). GAPDH was used as internal control.</p> Full article ">Figure 6
<p>Cell cycle progression analysis. (<b>A</b>,<b>B</b>) Cell cycle of 3T3 cells in control and SMG groups was analyzed by cell cycle app of Cytell microscope (<span class="html-italic">n</span> = 24). Gray indicates percentage of nuclei &lt; 2n, blue indicates percentage of nuclei in G0/G1 phase, red indicates percentage of nuclei in S phase, green indicates percentage of nuclei in G2/M phase, and yellow indicates percentage of nuclei &gt; 4n. (<b>C</b>) Western blot analysis of major cell cycle-related proteins in 3T3 cells (<span class="html-italic">n</span> = 3). (<b>D</b>) Number of 3T3 cells was counted by cell cycle app (<span class="html-italic">n</span> = 24).</p> Full article ">Figure 7
<p>Morphology of cell division related structures in 3T3 cells: (<b>A</b>,<b>A1</b>) contractile ring in 3T3 cells in control group; (<b>B</b>,<b>B1</b>) contractile ring in 3T3 cells in SMG group; (<b>C</b>,<b>C1</b>) polar spindle in 3T3 cells in control group; (<b>D</b>,<b>D1</b>) polar spindle in 3T3 cells in SMG group. Microfilaments were counterstained using phalloidin (green), and microtubules were stained with SiR-tubulin (red). White arrows indicate contractile rings, and dashed arrows indicate polar spindles. Scale bar = 100 µm.</p> Full article ">
17 pages, 772 KiB  
Review
In Vivo Reprogramming Using Yamanaka Factors in the CNS: A Scoping Review
by Han Eol Cho, Siwoo Lee, Jung Hwa Seo, Seong-Woong Kang, Won Ah Choi and Sung-Rae Cho
Cells 2024, 13(4), 343; https://doi.org/10.3390/cells13040343 - 15 Feb 2024
Cited by 2 | Viewed by 4051
Abstract
Central nervous system diseases, particularly neurodegenerative disorders, pose significant challenges in medicine. These conditions, characterized by progressive neuronal loss, have remained largely incurable, exacting a heavy toll on individuals and society. In recent years, in vivo reprogramming using Yamanaka factors has emerged as [...] Read more.
Central nervous system diseases, particularly neurodegenerative disorders, pose significant challenges in medicine. These conditions, characterized by progressive neuronal loss, have remained largely incurable, exacting a heavy toll on individuals and society. In recent years, in vivo reprogramming using Yamanaka factors has emerged as a promising approach for central nervous system regeneration. This technique involves introducing transcription factors, such as Oct4, Sox2, Klf4, and c-Myc, into adult cells to induce their conversion into neurons. This review summarizes the current state of in vivo reprogramming research in the central nervous system, focusing on the use of Yamanaka factors. In vivo reprogramming using Yamanaka factors has shown promising results in several animal models of central nervous system diseases. Studies have demonstrated that this approach can promote the generation of new neurons, improve functional outcomes, and reduce scar formation. However, there are still several challenges that need to be addressed before this approach can be translated into clinical practice. These challenges include optimizing the efficiency of reprogramming, understanding the cell of origin for each transcription factor, and developing methods for reprogramming in non-subventricular zone areas. Further research is needed to overcome the remaining challenges, but this approach has the potential to revolutionize the way we treat central nervous system disorders. Full article
(This article belongs to the Special Issue Genetic Regulation and Therapeutic Opportunities in Neurodegeneration and Neuroregeneration)
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<p>Flowchart of search strategy used in this study.</p> Full article ">
17 pages, 1280 KiB  
Article
A Proteomic Investigation to Discover Candidate Proteins Involved in Novel Mechanisms of 5-Fluorouracil Resistance in Colorectal Cancer
by Mario Ortega Duran, Sadr ul Shaheed, Christopher W. Sutton and Steven D. Shnyder
Cells 2024, 13(4), 342; https://doi.org/10.3390/cells13040342 - 14 Feb 2024
Cited by 3 | Viewed by 2830
Abstract
One of the main obstacles to therapeutic success in colorectal cancer (CRC) is the development of acquired resistance to treatment with drugs such as 5-fluorouracil (5-FU). Whilst some resistance mechanisms are well known, it is clear from the stasis in therapy success rate [...] Read more.
One of the main obstacles to therapeutic success in colorectal cancer (CRC) is the development of acquired resistance to treatment with drugs such as 5-fluorouracil (5-FU). Whilst some resistance mechanisms are well known, it is clear from the stasis in therapy success rate that much is still unknown. Here, a proteomics approach is taken towards identification of candidate proteins using 5-FU-resistant sublines of human CRC cell lines generated in house. Using a multiplexed stable isotope labelling with amino acids in cell culture (SILAC) strategy, 5-FU-resistant and equivalently passaged sensitive cell lines were compared to parent cell lines by growing in Heavy medium with 2D liquid chromatography and Orbitrap Fusion™ Tribrid™ Mass Spectrometry analysis. Among 3003 commonly quantified proteins, six (CD44, APP, NAGLU, CORO7, AGR2, PLSCR1) were found up-regulated, and six (VPS45, RBMS2, RIOK1, RAP1GDS1, POLR3D, CD55) down-regulated. A total of 11 of the 12 proteins have a known association with drug resistance mechanisms or role in CRC oncogenesis. Validation through immunodetection techniques confirmed high expression of CD44 and CD63, two known drug resistance mediators with elevated proteomics expression results. The information revealed by the sensitivity of this method warrants it as an important tool for elaborating the complexity of acquired drug resistance in CRC. Full article
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<p>Flowchart for the SILAC experimental approach showing (<b>A</b>) parent cell line growth in SILAC medium with Heavy amino acids that are incorporated to parent cell line during nine passages. (<b>B</b>) Parent cell line growth in drug-free RPMI medium to be used as a control during protein quantification, and (<b>C</b>) parent cell line growth in 5-FU-containing RPMI medium during the process of the establishment of CRC-resistant sublines. The strategy was applied in parallel for DLD-1 and HT-29 cell lines.</p> Full article ">Figure 2
<p>Comparative 5-FU sensitivity of the generated resistant sublines and their respective wild types (<b>A</b>,<b>B</b>), and the similarities and differences seen in terms of protein expression for the different sublines (<b>C</b>,<b>D</b>). Graphs (<b>A</b>,<b>B</b>) show cell survival profiles of parent cell lines and their respective resistant sublines to 5-FU for (<b>A</b>) DLD-1 (<b>B</b>) HT-29 CRC cell lines under exposure to (<b>A</b>) 5-FU [1–1000 µM] and (<b>B</b>) 5-FU [0.03–100 µM] doses over 96 h. MTT assays were performed in three independent experiments. The difference in IC<sub>50</sub> among parental cell line and resistant 5-FU sublines is highly significant in the three experiments (<span class="html-italic">p</span> ≤ 0.0001). A 130.2-fold change and 3.5-fold change difference in IC<sub>50</sub> was found in the DLD-1/5-FU [250 µM] and HT-29/5-FU [60 µM] resistant sublines, respectively (**** <span class="html-italic">p</span> ≤ 0.0001). The (<b>C</b>,<b>D</b>) Venn diagrams show the number of proteins commonly quantified in the two parent cell lines (<b>C</b>) DLD-1 and (<b>D</b>) HT-29, with a high and a low number of passages and in their respective resistant sublines to 5-FU. P refers to the number of cell passages carried out when the subline was assessed.</p> Full article ">Figure 3
<p>(<b>A</b>) Scatter plot figure showing dispersion of log<sub>2</sub>-fold change ratios for 3003 proteins commonly quantified in parent cell lines and 5-FU-resistant sublines. All proteins with a log<sub>2</sub>-fold change higher than ±1 were considered as altered proteins in resistant sublines. Commonly up-regulated (red) and down-regulated (green) proteins in both 5-FU-resistant sublines are highlighted. (<b>B</b>) Venn diagrams showing significantly up-regulated and down-regulated proteins in resistant sublines DLD-1/5-FU and HT-29/5-FU.</p> Full article ">Figure 4
<p>(<b>A</b>) Densitometry for CD44 expression was performed for (<b>B</b>) DLD-1 and (<b>C</b>) HT-29 parent cell lines and 5-FU-resistant sublines and analysed using a <span class="html-italic">t</span>-test. (<b>D</b>,<b>E</b>) show that relative expression of CD44 abundance in the indicated samples was divided among CD44 abundance in SILAC sample, and relative abundance was calculated as previously during the SILAC protocol to estimate SILAC ratios (L/H). SILAC ratios (L/H) for CD44 were DLD-1/5-FU (4.7), DLD-1 P = 9 (0.44), DLD-1 P = 65 (1.2), HT-29/5-FU (7.01), HT-29 P = 9 (2.8), and HT-29 P = 57 (0.42). Data are presented as mean (n = X); an asterisk represents significant differences (Student’s <span class="html-italic">t</span>-test, * <span class="html-italic">p</span> &lt; 0 0.05). MDA-MB-231 mammary adenocarcinoma cell line was used as a positive control cell line for high CD44 expression. (<b>F</b>,<b>G</b>) show immunolocalization of CD63; in (<b>F</b>) DLD-1/5-FU-resistant subline with strong labelling, and in (<b>G</b>) DLD-1 parent cell line with weak labelling.</p> Full article ">
25 pages, 3239 KiB  
Review
Wound Repair of the Cell Membrane: Lessons from Dictyostelium Cells
by Shigehiko Yumura
Cells 2024, 13(4), 341; https://doi.org/10.3390/cells13040341 - 14 Feb 2024
Viewed by 2557
Abstract
The cell membrane is frequently subjected to damage, either through physical or chemical means. The swift restoration of the cell membrane’s integrity is crucial to prevent the leakage of intracellular materials and the uncontrolled influx of extracellular ions. Consequently, wound repair plays a [...] Read more.
The cell membrane is frequently subjected to damage, either through physical or chemical means. The swift restoration of the cell membrane’s integrity is crucial to prevent the leakage of intracellular materials and the uncontrolled influx of extracellular ions. Consequently, wound repair plays a vital role in cell survival, akin to the importance of DNA repair. The mechanisms involved in wound repair encompass a series of events, including ion influx, membrane patch formation, endocytosis, exocytosis, recruitment of the actin cytoskeleton, and the elimination of damaged membrane sections. Despite the absence of a universally accepted general model, diverse molecular models have been proposed for wound repair in different organisms. Traditional wound methods not only damage the cell membrane but also impact intracellular structures, including the underlying cortical actin networks, microtubules, and organelles. In contrast, the more recent improved laserporation selectively targets the cell membrane. Studies on Dictyostelium cells utilizing this method have introduced a novel perspective on the wound repair mechanism. This review commences by detailing methods for inducing wounds and subsequently reviews recent developments in the field. Full article
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<p>Wound repair of the cell membrane. (<b>A</b>) Relative amplitudes of actin accumulation at the wound site over time following starvation (0 h). As illustrated in the lower drawings, upon initiation of vegetative cell starvation, individual cells aggregate, forming streams direct toward the aggregation center. This process leads to the creation of a multicellular structure, culminating in the development of a fruiting body. Importantly, wound repair is observed at every stage of the lifecycle in <span class="html-italic">Dictyostelium discoideum</span>. (<b>B</b>) Schematic representation of the enhanced laserporation with gold coating. The wound diameter is usually set at 0.5 μm for <span class="html-italic">Dictyostelium</span> cells. (<b>C</b>) A representative sequence of fluorescence images capturing PI influx after laserporation. (<b>D</b>) Temporal profiles of PI influx in the presence (BSS, control) and absence (EGTA) of external Ca<sup>2+</sup>. The wound laser beam was applied at 0 sec. (<b>E</b>) A typical sequence of fluorescence images illustrating FM dye influx after laserporation. (<b>F</b>) Laserporation of a cell expressing GFP-cAR1 resulted in the appearance of a black spot on the cell membrane. The black spot transiently expanded, then contracted, and finally closed. (<b>G</b>) The time course of the black spot diameter. (<b>H</b>) A sequence of fluorescence images featuring a cell expressing GCAMP6s after laserporation. (<b>I</b>) Temporal profiles of GCAMP6s fluorescence intensities in the presence (BSS) and absence (EGTA) of external Ca<sup>2+</sup>. (<b>J</b>) A typical sequence of fluorescence images illustrating PI influx after laserporation in the absence (EGTA) of external Ca<sup>2+</sup>. Scale bars, 10 µm. Figures are posted from [<a href="#B48-cells-13-00341" class="html-bibr">48</a>,<a href="#B51-cells-13-00341" class="html-bibr">51</a>,<a href="#B67-cells-13-00341" class="html-bibr">67</a>,<a href="#B68-cells-13-00341" class="html-bibr">68</a>] with proper permission.</p> Full article ">Figure 2
<p>Various models for wound repair mechanisms. (<b>A</b>) Spontaneous self-sealing. (<b>B</b>) Self-sealing by regulation of surface tension. Black arrows indicate the direction of the membrane flow. (<b>C</b>) Sealing by protein aggregation. (<b>D</b>) Sealing by membrane patch. (<b>E</b>) Endocytosis of damaged membrane. (<b>F</b>) Vesicle budding and shedding to the outside. These illustrations are simplified for a better understanding of basic concepts.</p> Full article ">Figure 3
<p>Role of actin in wound repair. (<b>A</b>) Representative sequence of fluorescence images featuring a cell expressing GFP-lifeact upon wounding. Arrows indicate the wound site. (<b>B</b>) Sequence of fluorescence images at the wound sites of cells expressing GFP-lifeact. (<b>C</b>) Temporal profiles of relative fluorescence intensity of GFP-lifeact at the wound site in the presence (LatA) and absence (BSS) of latrunculin A. (<b>D</b>) Temporal profiles of PI influx in the cytosol in the presence (LatA) and absence (BSS) of latrunculin A. (<b>E</b>) Temporal profiles of GFP-lifeact fluorescence intensities at the wound site in the presence and absence of jasplakinolide and latrunculin A (Jasp + LatA). (<b>F</b>) Temporal profiles of FM fluorescence intensities at the wound site in the presence (LatA) and absence (BSS) of latrunculin A. (<b>G</b>) Representative sequence of fluorescence images of a dividing cell expressing GFP-myosin II upon wounding. Scale bars, 10 µm. Figures are posted from [<a href="#B48-cells-13-00341" class="html-bibr">48</a>,<a href="#B51-cells-13-00341" class="html-bibr">51</a>,<a href="#B67-cells-13-00341" class="html-bibr">67</a>,<a href="#B68-cells-13-00341" class="html-bibr">68</a>] with proper permission.</p> Full article ">Figure 4
<p>Dynamics of ARPs and signal-related proteins. The graph illustrates the duration of appearance (red) and disappearance (green) of individual ARPs and signal-related proteins, including actin at wound sites. Additionally, the durations of Ca<sup>2+</sup> influx, calmodulin dynamics, ESCRT component vps4 dynamics, and annexin C1 dynamics are depicted (blue). Asterisks in the duration bars indicate peak times.</p> Full article ">Figure 5
<p>Signaling pathways for wound repair in <span class="html-italic">Dictyostelium</span>. ARPs and signal-related proteins contributing to wound repair, identified through null mutants or pharmacological inhibitors, are highlighted in red. Certain proteins (yellow) exhibit accumulation or disappearance at the wound site, though their specific contributions are yet to be fully elucidated. Data are based on [<a href="#B48-cells-13-00341" class="html-bibr">48</a>,<a href="#B51-cells-13-00341" class="html-bibr">51</a>,<a href="#B67-cells-13-00341" class="html-bibr">67</a>,<a href="#B68-cells-13-00341" class="html-bibr">68</a>].</p> Full article ">Figure 6
<p>Summary of Wound Repair in <span class="html-italic">Dictyostelium</span> Cells. This schematic diagram illustrates the wound repair mechanism in <span class="html-italic">Dictyostelium</span> cells. Upon wounding, Ca<sup>2+</sup> enters through the wound pore, initiating the de novo generation of vesicles and the mutual fusion of vesicle–vesicle and vesicle–cell membrane, forming an immediate membrane plug. Actin accumulates to finalize the plug, relying on Ca<sup>2+</sup> and calmodulin. Following the disassembly of the actin structure, the remaining damaged membrane is shed as the cell undergoes migration.</p> Full article ">
23 pages, 1693 KiB  
Systematic Review
Salivary Biomarkers for Parkinson’s Disease: A Systematic Review with Meta-Analysis
by Kacper Nijakowski, Wojciech Owecki, Jakub Jankowski and Anna Surdacka
Cells 2024, 13(4), 340; https://doi.org/10.3390/cells13040340 - 14 Feb 2024
Cited by 7 | Viewed by 2958
Abstract
Parkinson’s Disease (PD) is a common neurodegenerative disease which manifests with motor features, such as bradykinesia, resting tremor, rigidity, and postural instability. Using the non-invasive technique of saliva collection, we designed a systematic review to answer the question “Are salivary biomarkers reliable for [...] Read more.
Parkinson’s Disease (PD) is a common neurodegenerative disease which manifests with motor features, such as bradykinesia, resting tremor, rigidity, and postural instability. Using the non-invasive technique of saliva collection, we designed a systematic review to answer the question “Are salivary biomarkers reliable for the diagnosis of Parkinson’s Disease?”. Following inclusion and exclusion criteria, 30 studies were included in this systematic review (according to the PRISMA statement guidelines). Mostly proteins were reported as potential biomarkers in saliva. Based on meta-analysis, in PD patients, salivary levels of total alpha-synuclein were significantly decreased, and those of oligomeric alpha-synuclein were significantly increased. Also, according to pooled AUC, heme oxygenase-1 demonstrated significant predictive value for saliva-based PD diagnosis. In conclusion, some potential biomarkers, especially alpha-synuclein, can be altered in the saliva of PD patients, which could be reliably useful for early diagnosis of this neurodegenerative disease differentiating other synucleopathies. Full article
(This article belongs to the Special Issue Neuromodulation and Biomarkers in Neurodegenerative Diseases)
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<p>Quality assessment, including the main potential risk of bias (risk level: green—low, yellow—unspecified, and red—high; quality score: green—good, yellow—intermediate, and red—poor) [<a href="#B35-cells-13-00340" class="html-bibr">35</a>,<a href="#B36-cells-13-00340" class="html-bibr">36</a>,<a href="#B37-cells-13-00340" class="html-bibr">37</a>,<a href="#B38-cells-13-00340" class="html-bibr">38</a>,<a href="#B39-cells-13-00340" class="html-bibr">39</a>,<a href="#B40-cells-13-00340" class="html-bibr">40</a>,<a href="#B41-cells-13-00340" class="html-bibr">41</a>,<a href="#B42-cells-13-00340" class="html-bibr">42</a>,<a href="#B43-cells-13-00340" class="html-bibr">43</a>,<a href="#B44-cells-13-00340" class="html-bibr">44</a>,<a href="#B45-cells-13-00340" class="html-bibr">45</a>,<a href="#B46-cells-13-00340" class="html-bibr">46</a>,<a href="#B47-cells-13-00340" class="html-bibr">47</a>,<a href="#B48-cells-13-00340" class="html-bibr">48</a>,<a href="#B49-cells-13-00340" class="html-bibr">49</a>,<a href="#B50-cells-13-00340" class="html-bibr">50</a>,<a href="#B51-cells-13-00340" class="html-bibr">51</a>,<a href="#B52-cells-13-00340" class="html-bibr">52</a>,<a href="#B53-cells-13-00340" class="html-bibr">53</a>,<a href="#B54-cells-13-00340" class="html-bibr">54</a>,<a href="#B55-cells-13-00340" class="html-bibr">55</a>,<a href="#B56-cells-13-00340" class="html-bibr">56</a>,<a href="#B57-cells-13-00340" class="html-bibr">57</a>,<a href="#B58-cells-13-00340" class="html-bibr">58</a>,<a href="#B59-cells-13-00340" class="html-bibr">59</a>,<a href="#B60-cells-13-00340" class="html-bibr">60</a>,<a href="#B61-cells-13-00340" class="html-bibr">61</a>,<a href="#B62-cells-13-00340" class="html-bibr">62</a>,<a href="#B63-cells-13-00340" class="html-bibr">63</a>,<a href="#B64-cells-13-00340" class="html-bibr">64</a>].</p> Full article ">Figure 2
<p>PRISMA flow diagram presenting search strategy.</p> Full article ">Figure 3
<p>Standardized mean difference of total alpha-synuclein levels in saliva from patients with Parkinson’s Disease compared with healthy controls [<a href="#B35-cells-13-00340" class="html-bibr">35</a>,<a href="#B36-cells-13-00340" class="html-bibr">36</a>,<a href="#B37-cells-13-00340" class="html-bibr">37</a>,<a href="#B38-cells-13-00340" class="html-bibr">38</a>,<a href="#B40-cells-13-00340" class="html-bibr">40</a>,<a href="#B41-cells-13-00340" class="html-bibr">41</a>,<a href="#B42-cells-13-00340" class="html-bibr">42</a>,<a href="#B44-cells-13-00340" class="html-bibr">44</a>,<a href="#B45-cells-13-00340" class="html-bibr">45</a>,<a href="#B46-cells-13-00340" class="html-bibr">46</a>,<a href="#B47-cells-13-00340" class="html-bibr">47</a>,<a href="#B48-cells-13-00340" class="html-bibr">48</a>].</p> Full article ">Figure 4
<p>Standardized mean difference of oligomeric alpha-synuclein levels in saliva from patients with Parkinson’s Disease compared with healthy controls [<a href="#B36-cells-13-00340" class="html-bibr">36</a>,<a href="#B40-cells-13-00340" class="html-bibr">40</a>,<a href="#B45-cells-13-00340" class="html-bibr">45</a>,<a href="#B47-cells-13-00340" class="html-bibr">47</a>,<a href="#B48-cells-13-00340" class="html-bibr">48</a>].</p> Full article ">
23 pages, 1994 KiB  
Review
ICAMs in Immunity, Intercellular Adhesion and Communication
by Claudia Guerra-Espinosa, María Jiménez-Fernández, Francisco Sánchez-Madrid and Juan M. Serrador
Cells 2024, 13(4), 339; https://doi.org/10.3390/cells13040339 - 14 Feb 2024
Cited by 13 | Viewed by 3590
Abstract
Interactions among leukocytes and leukocytes with immune-associated auxiliary cells represent an essential feature of the immune response that requires the involvement of cell adhesion molecules (CAMs). In the immune system, CAMs include a wide range of members pertaining to different structural and functional [...] Read more.
Interactions among leukocytes and leukocytes with immune-associated auxiliary cells represent an essential feature of the immune response that requires the involvement of cell adhesion molecules (CAMs). In the immune system, CAMs include a wide range of members pertaining to different structural and functional families involved in cell development, activation, differentiation and migration. Among them, β2 integrins (LFA-1, Mac-1, p150,95 and αDβ2) are predominantly involved in homotypic and heterotypic leukocyte adhesion. β2 integrins bind to intercellular (I)CAMs, actin cytoskeleton-linked receptors belonging to immunoglobulin superfamily (IgSF)-CAMs expressed by leukocytes and vascular endothelial cells, enabling leukocyte activation and transendothelial migration. β2 integrins have long been viewed as the most important ICAMs partners, propagating intracellular signalling from β2 integrin-ICAM adhesion receptor interaction. In this review, we present previous evidence from pioneering studies and more recent findings supporting an important role for ICAMs in signal transduction. We also discuss the contribution of immune ICAMs (ICAM-1, -2, and -3) to reciprocal cell signalling and function in processes in which β2 integrins supposedly take the lead, paying particular attention to T cell activation, differentiation and migration. Full article
(This article belongs to the Special Issue Advances in Leukocyte Migration and Location in Health and Disease)
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<p>Structure, posttranslational modifications and ligands of immune ICAMs at the N-terminal (N) extracellular and C-terminal (C) intracellular domains. The binding sites of ICAMs to β2 integrins (LFA-1, Mac-1 and the putative α<sub>D</sub>β<sub>2</sub> binding site) and DC-SIGN; human rhinoviruses (HRV) and coxsackieviruses (CV) and the <span class="html-italic">Toxoplasma gondii</span> protein PfEMP1 are depicted on the corresponding Ig-like domains (D1-5) of ICAM-1, -2 and -3. Dimerization regions of ICAM-1 and -3, the N-myristoylation site (NMT1) of ICAM-1, and glycosylation sites (small triangles) for all three ICAMs are also shown. The interaction of ICAM-1 and -2 with α-actinin and the interaction of ICAM-1, -2, and -3 with ERMs (ezrin and moesin) activated by PIP2 binding and RhoGTPase (Rho-GTP)-Rho-associated protein kinase (ROCK)-mediated phosphorylation are depicted near their cytoplasmic tails and amino-acid lengths. The cytoplasmic tails of ICAM-1 and ICAM-3 show the proteolytic enzymes and recognition site (MT1-MMP/Tyr485 and human leukocyte elastase (HLE)/unknown recognition site (?)) involved in ICAM-1 cleavage/soluble (s)ICAM-1 release and the Ser motifs that regulate ERM binding, respectively.</p> Full article ">Figure 2
<p>ICAMs-mediated cell-cell interactions in immunity. (<b>A</b>) ICAM-1 and ICAM-2 differentially activate actin cytoskeleton-associated Rho GTPases (RhoA and Rac-1) and signalling during leukocyte adhesion and migration on endothelial cells. (<b>B</b>) Regulation of LFA-1 activation by ICAMs during cognate interactions in the immune system. In effector immune cells, ICAMs may regulate LFA-1 at three levels (red arrows): (i) in “cis” through unknown (?) mechanisms, during their binding to LFA-1 and DC-SIGN; (ii) in “trans” by direct binding to the ICAM-binding site of partially activated LFA-1 and; (iii) fostering F-actin rearrangements and LFA-1 clustering. (<b>C</b>) TCR-associated ICAM-1, -3 and LFA-1 costimulatory signalling in T cells during cognate interactions with dendritic (DC, magenta) or B cells (blue). Cytohesin-1-inactivated LFA-1 and DC-SIGN are represented as characteristic of DCs. Shared and non-shared ICAM-1, -3 and LFA-1 costimulatory signalling and functions are depicted. (<b>D</b>) NK cell receptor-associated LFA-1 costimulatory signalling induced by ERM-mediated ICAM-2 clustering and binding during MHC-I-mediated interactions between NK cells and target cells. LFA-1 binding to ICAM-1 and -3 are also represented as less efficient inducers of LFA-1 costimulation. (<b>E</b>) Regulatory phenotype induced in naïve T cells during ICAMs-LFA-1-mediated homotypic interactions with activated T cells. “Cis” activation and regulatory signalling of LFA-1 in naïve T cells by the binding of ICAM-2 and -3 to LFA-1 on activated effector T cells are represented.</p> Full article ">
16 pages, 1883 KiB  
Perspective
Perspective Strategies for Interventions in Parkinsonism: Remedying the Neglected Role of TPPP
by Judit Oláh, Vic Norris, Attila Lehotzky and Judit Ovádi
Cells 2024, 13(4), 338; https://doi.org/10.3390/cells13040338 - 14 Feb 2024
Cited by 1 | Viewed by 1987
Abstract
Neurological disorders such as Parkinsonism cause serious socio-economic problems as there are, at present, only therapies that treat their symptoms. The well-established hallmark alpha-synuclein (SYN) is enriched in the inclusion bodies characteristic of Parkinsonism. We discovered a prominent partner of SYN, termed Tubulin [...] Read more.
Neurological disorders such as Parkinsonism cause serious socio-economic problems as there are, at present, only therapies that treat their symptoms. The well-established hallmark alpha-synuclein (SYN) is enriched in the inclusion bodies characteristic of Parkinsonism. We discovered a prominent partner of SYN, termed Tubulin Polymerization Promoting Protein (TPPP), which has important physiological and pathological activities such as the regulation of the microtubule network and the promotion of SYN aggregation. The role of TPPP in Parkinsonism is often neglected in research, which we here attempt to remedy. In the normal brain, SYN and TPPP are expressed endogenously in neurons and oligodendrocytes, respectively, whilst, at an early stage of Parkinsonism, soluble hetero-associations of these proteins are found in both cell types. The cell-to-cell transmission of these proteins, which is central to disease progression, provides a unique situation for specific drug targeting. Different strategies for intervention and for the discovery of biomarkers include (i) interface targeting of the SYN-TPPP hetero-complex; (ii) proteolytic degradation of SYN and/or TPPP using the PROTAC technology; and (iii) depletion of the proteins by miRNA technology. We also discuss the potential roles of SYN and TPPP in the phenotype stabilization of neurons and oligodendrocytes. Full article
(This article belongs to the Collection Molecular Insights into Neurodegenerative Diseases)
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<p>The role of SYN and TPPP in the formation of Lewy bodies and glial cytoplasmic inclusions in PD and MSA.</p> Full article ">Figure 2
<p>TPPP levels in the CSF of MS and non-MS patients as quantified by Western blot [<a href="#B63-cells-13-00338" class="html-bibr">63</a>]. A representative Western blot using a specific TPPP antibody is shown for different CSF samples of patients (25 and 30, ○) and the corresponding controls (non-MS patients, ●) (14 and 26). Each box extends from the 25th to the 75th percentile with the middle line representing the median. The vertical bars indicate the full range of TPPP levels. The <span class="html-italic">p</span> values were determined by Mann–Whitney U tests. ** <span class="html-italic">p</span> &lt; 0.000005. The dashed line corresponds to 50 μg/L [<a href="#B63-cells-13-00338" class="html-bibr">63</a>].</p> Full article ">Figure 3
<p>Homo- and hetero-associations of TPPP and SYN in physiological and pathological conditions and the interface segment of the SYN-TPPP complex as a potential drug target.</p> Full article ">Figure 4
<p>Degradation of proteins of the pathological assembly by PROTAC technology.</p> Full article ">
28 pages, 1581 KiB  
Review
Extracellular Vesicles, Circulating Tumor Cells, and Immune Checkpoint Inhibitors: Hints and Promises
by Sara Bandini, Paola Ulivi and Tania Rossi
Cells 2024, 13(4), 337; https://doi.org/10.3390/cells13040337 - 13 Feb 2024
Cited by 5 | Viewed by 2517
Abstract
Immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of cancer, in particular lung cancer, while the introduction of predictive biomarkers from liquid biopsies has emerged as a promising tool to achieve an effective and personalized therapy response. Important progress has also been [...] Read more.
Immune checkpoint inhibitor (ICI) therapy has revolutionized the treatment of cancer, in particular lung cancer, while the introduction of predictive biomarkers from liquid biopsies has emerged as a promising tool to achieve an effective and personalized therapy response. Important progress has also been made in the molecular characterization of extracellular vesicles (EVs) and circulating tumor cells (CTCs), highlighting their tremendous potential in modulating the tumor microenvironment, acting on immunomodulatory pathways, and setting up the pre-metastatic niche. Surface antigens on EVs and CTCs have proved to be particularly useful in the case of the characterization of potential immune escape mechanisms through the expression of immunosuppressive ligands or the transport of cargos that may mitigate the antitumor immune function. On the other hand, novel approaches, to increase the expression of immunostimulatory molecules or cargo contents that can enhance the immune response, offer premium options in combinatorial clinical strategies for precision immunotherapy. In this review, we discuss recent advances in the identification of immune checkpoints using EVs and CTCs, their potential applications as predictive biomarkers for ICI therapy, and their prospective use as innovative clinical tools, considering that CTCs have already been approved by the Food and Drug Administration (FDA) for clinical use, but providing good reasons to intensify the research on both. Full article
(This article belongs to the Collection Extracellular Vesicles and Nucleic Acids in Health and Disease)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Representation of the influence that exosomes have on the cells in the immune system. In some cases, they inhibit the activity of the cells that try to hinder the tumor; in others, they promote cancer by favoring those cells that encourage tumor growth. Treg: regulatory T cell; Nk: natural killer; miRNA: microRNA. Created using BioRender.</p> Full article ">Figure 2
<p>The interactions between CTCs and other blood cells: platelets, macrophages, and neutrophils. CTC: circulating tumor cells; TGF-β: transforming growth factor-β; FSS: fluid shear stress; NK: natural killer; TAM: tumor-associated macrophage; CAML: cancer-associated macrophage-like cells; CHC: circulating hybrid cell; NET: neutrophil extracellular trap. Created using BioRender.</p> Full article ">
23 pages, 1545 KiB  
Review
Challenges and Promise for Glioblastoma Treatment through Extracellular Vesicle Inquiry
by Giovanna L. Liguori
Cells 2024, 13(4), 336; https://doi.org/10.3390/cells13040336 - 13 Feb 2024
Cited by 6 | Viewed by 3027
Abstract
Glioblastoma (GB) is a rare but extremely aggressive brain tumor that significantly impacts patient outcomes, affecting both duration and quality of life. The protocol established by Stupp and colleagues in 2005, based on radiotherapy and chemotherapy with Temozolomide, following maximum safe surgical resection [...] Read more.
Glioblastoma (GB) is a rare but extremely aggressive brain tumor that significantly impacts patient outcomes, affecting both duration and quality of life. The protocol established by Stupp and colleagues in 2005, based on radiotherapy and chemotherapy with Temozolomide, following maximum safe surgical resection remains the gold standard for GB treatment; however, it is evident nowadays that the extreme intratumoral and intertumoral heterogeneity, as well as the invasiveness and tendency to recur, of GB are not compatible with a routine and unfortunately ineffective treatment. This review article summarizes the main challenges in the search for new valuable therapies for GB and focuses on the impact that extracellular vesicle (EV) research and exploitation may have in the field. EVs are natural particles delimited by a lipidic bilayer and filled with functional cellular content that are released and uptaken by cells as key means of cell communication. Furthermore, EVs are stable in body fluids and well tolerated by the immune system, and are able to cross physiological, interspecies, and interkingdom barriers and to target specific cells, releasing inherent or externally loaded functionally active molecules. Therefore, EVs have the potential to be ideal allies in the fight against GB and to improve the prognosis for GB patients. The present work describes the main preclinical results obtained so far on the use of EVs for GB treatment, focusing on both the EV sources and molecular cargo used in the various functional studies, primarily in vivo. Finally, a SWOT analysis is performed, highlighting the main advantages and pitfalls of developing EV-based GB therapeutic strategies. The analysis also suggests the main directions to explore to realize the possibility of exploiting EVs for the treatment of GB. Full article
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<p>Main features of glioblastoma responsible for its high malignancy and poor prognosis.</p> Full article ">Figure 2
<p>EV exploitation strategy for the treatment of glioblastoma. Figure schematizes the identified targets that block EV release and uptake or impair specific oncogenic glioblastoma (GB) features on the left; the EV sources used in different approaches against GB in the middle; and the therapeutic molecules used in functional assays in glioblastoma models on the right (both in vitro and in vivo).</p> Full article ">Figure 3
<p>SWOT analysis of EV exploitation in GB treatment, highlighting the relative Strengths (S), Weaknesses (W), Opportunities (O), and Threats (T). BBB: blood-brain barrier; GB: glioblastoma.</p> Full article ">
22 pages, 1136 KiB  
Review
Innate Lymphoid Cells and Their Role in the Immune Response to Infections
by Marek Fol, Wojciech Karpik, Agnieszka Zablotni, Jakub Kulesza, Ewelina Kulesza, Magdalena Godkowicz and Magdalena Druszczynska
Cells 2024, 13(4), 335; https://doi.org/10.3390/cells13040335 - 13 Feb 2024
Cited by 1 | Viewed by 3139
Abstract
Over the past decade, a group of lymphocyte-like cells called innate lymphoid cells (ILCs) has gained considerable attention due to their crucial role in regulating immunity and tissue homeostasis. ILCs, lacking antigen-specific receptors, are a group of functionally differentiated effector cells that act [...] Read more.
Over the past decade, a group of lymphocyte-like cells called innate lymphoid cells (ILCs) has gained considerable attention due to their crucial role in regulating immunity and tissue homeostasis. ILCs, lacking antigen-specific receptors, are a group of functionally differentiated effector cells that act as tissue-resident sentinels against infections. Numerous studies have elucidated the characteristics of ILC subgroups, but the mechanisms controlling protective or pathological responses to pathogens still need to be better understood. This review summarizes the functions of ILCs in the immunology of infections caused by different intracellular and extracellular pathogens and discusses their possible therapeutic potential. Full article
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<p>Innate immune cells in immunity to extracellular and intracellular pathogens. Due to the wide distribution of heterogenous subtypes of ILCs across various tissues and organs in the body, these cells play a crucial role in the immune response against a range of pathogens, including viruses, bacteria, fungi, and both intracellular and extracellular parasites. Upon stimulation, ILCs secrete a variety of cytokines, with IFN-γ for ILC1, IL-5 and IL-13 for ILC2, and IL-17 and IL-22 for ILC3, serving as their signature cytokines.</p> Full article ">Figure 2
<p>Functions of innate immune cells in infections. After pathogen invasion, the interplay between innate immune cells and ILCs provides signals (e.g., cytokines) that activate ILCs, and thus they play an important role on in the immune response from the very beginning, while T cells, based on their receptor specificity, must undergo a process of selection and further multiplication, which usually takes several days. Activation of ILCs occurs <span class="html-italic">via</span> specific transcription factors which ultimately allows the cells to participate in many immune processes. Inappropriate or prolonged activation of ILCs can lead to excessive inflammation and tissue damage.</p> Full article ">
16 pages, 1284 KiB  
Review
P. falciparum Invasion and Erythrocyte Aging
by María Fernanda Alves-Rosa, Nicole M. Tayler, Doriana Dorta, Lorena M. Coronado and Carmenza Spadafora
Cells 2024, 13(4), 334; https://doi.org/10.3390/cells13040334 - 12 Feb 2024
Cited by 2 | Viewed by 3787
Abstract
Plasmodium parasites need to find red blood cells (RBCs) that, on the one hand, expose receptors for the pathogen ligands and, on the other hand, maintain the right geometry to facilitate merozoite attachment and entry into the red blood cell. Both characteristics change [...] Read more.
Plasmodium parasites need to find red blood cells (RBCs) that, on the one hand, expose receptors for the pathogen ligands and, on the other hand, maintain the right geometry to facilitate merozoite attachment and entry into the red blood cell. Both characteristics change with the maturation of erythrocytes. Some Plasmodia prefer younger vs. older erythrocytes. How does the life evolution of the RBC affect the invasion of the parasite? What happens when the RBC ages? In this review, we present what is known up until now. Full article
(This article belongs to the Section Cellular Aging)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Main receptors and ligands involved in <span class="html-italic">P. falciparum</span> invasion of human erythrocytes. Gly A: glycophorin A. Gly B: glycophorin B. Gly C: Glycophorin C. CR1: Complement Receptor 1. PMCA: plasma membrane calcium ATPase. MCT: monocarboxylate transporter. CD55: Decay-Accelerating Factor (DAF). EBA-175: Erythrocyte Binding Antigen-175. EBL-1: Erythrocyte Binding Ligand-1. EBA-140: Erythrocyte Binding Antigen-140. EBA-181: Erythrocyte Binding Antigen-181. PfRh2b: <span class="html-italic">P. falciparum</span> Rhoptry homolog 2b. PfRh4: <span class="html-italic">P. falciparum</span> Rhoptry homolog 4. PfRh5: <span class="html-italic">P. falciparum</span> Rhoptry homolog 5. SA: Sialic Acid. The illustration is not at scale. This figure is created with BioRender.com.</p> Full article ">Figure 2
<p>Cytoadherence events and main actors in the vascular system that takes place during <span class="html-italic">P. falciparum</span> infection and development in humans. ICAM-1: Adhesion Molecule-1, VCAM: Vascular cellular adhesion molecule, TSP: Thrombospondin, CD62P: P-selectin, CD62E: E-selectin, PfEMP1: <span class="html-italic">P. falciparum</span> Erythrocyte Membrane Protein 1. The illustrations are not at scale. The inset at the top of the figure represents a protein expressed in the membrane of each stage of <span class="html-italic">P. falciparum</span>: Gametocyte stages I–IV, trophozoite stage, and schizont stages. This figure is created with BioRender.com.</p> Full article ">
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