Nothing Special   »   [go: up one dir, main page]

You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (2,787)

Search Parameters:
Keywords = UCS

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
20 pages, 4082 KiB  
Article
Eisenia bicyclis Extract Ameliorates Colitis in In Vitro and In Vivo Models Through Modulation of mTOR Axis and Gut Microbiota Composition
by Qunzhe Wang, Yuri Im, Jumin Park, Hye Lim Lee, Dae Gon Ryu and Hyemee Kim
Foods 2025, 14(5), 714; https://doi.org/10.3390/foods14050714 - 20 Feb 2025
Abstract
Ulcerative colitis (UC) is a chronic inflammatory disease of the colon that is associated with dysbiosis in the gut microbiota. Eisenia bicyclis, a marine alga, is known for its anti-inflammatory, antioxidant, and gut microbiota-modulating properties. This study explored the mechanisms by which [...] Read more.
Ulcerative colitis (UC) is a chronic inflammatory disease of the colon that is associated with dysbiosis in the gut microbiota. Eisenia bicyclis, a marine alga, is known for its anti-inflammatory, antioxidant, and gut microbiota-modulating properties. This study explored the mechanisms by which a 70% ethanol extract of E. bicyclis may alleviate UC, through both in vitro and in vivo experiments. LC-MS/MS analysis revealed eckol, 7-phloroeckol, dieckol, phlorofucofuroeckol A, and fucofuroeckol as key phenolic compounds present in the extract. The administration of E. bicyclis significantly improved symptoms in a dextran sulfate sodium (DSS)-induced colitis mouse model by reducing intestinal shortening, splenomegaly, and histological scores. Both cell and animal studies demonstrated that E. bicyclis suppressed the release of inflammatory cytokines, downregulated the mRNA expression of genes related to the mTOR pathway, and reduced the p-mTOR/mTOR ratio. Microbiota analysis revealed that, while the Firmicutes/Bacteroidetes ratio was elevated in UC mice, E. bicyclis administration normalized this imbalance, with a notable increase in the abundance of beneficial probiotics such as Bifidobacterium bifidum. In conclusion, a phenolic-rich extract of E. bicyclis demonstrates significant potential as a dietary supplement to prevent and mitigate UC by modulating both the mTOR signaling pathway and gut microbiota composition. Full article
Show Figures

Figure 1

Figure 1
<p>Representative LC-MS/MS chromatograms of <span class="html-italic">E.bicyclis</span> extract. (<b>A</b>) Negative-ion TIC and (<b>B</b>) positive-ion TIC of the EB extract: 1. phloroglucinol; 2. fucodiphlorethol G; 3. dioxinodehydroeckol; 4. diphlorethol; 5. bifuhalol; 6. eckol; 7. 7-phloroeckol; 8. 2-O-(2,4,6-Trihydroxyphenyl)-6,6′-bieckol; 9. dieckol; 10. phlorofucofuroeckol A; 11. fucofuroeckol; 12. 3,4-dihydroxybenzoic acid; and 13. zingerol. EB: <span class="html-italic">E. bicyclis</span> extract.</p>
Full article ">Figure 2
<p>Inflammation-reducing effects of <span class="html-italic">E. bicyclis</span> extract (EB) in LPS-stimulated Caco-2 and RAW264.7 cells. (<b>A</b>) Cytotoxicity of EB (0–50 mg/L) against Caco-2 and RAW264.7 cells was measured using MTS assay. (<b>B</b>) IL-6 and (<b>C</b>) TNF-α levels in RAW264.7 cells treated with LPS (50 ng/mL) and EB. (<b>D</b>) Nfkb, (<b>E</b>) Inos, (<b>F</b>) Il6, and (<b>G</b>) Cox-2 mRNA expressions in RAW264.7 cells treated with LPS (50 ng/mL) and EB. (<b>H</b>) Occludin, (<b>I</b>) Zo1, and (<b>J</b>) claudin-1 mRNA expressions in Caco-2 cells treated with LPS (2 μg/mL) and EB. The data are shown as mean ± SD (n = 4), with comparisons made to the positive control (PC) group. Statistical significance was defined as * <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 **** <span class="html-italic">p</span> &lt; 0.0001. NC: negative control; PC: positive control; EB: <span class="html-italic">Ecklonia bicyclis</span> extract.</p>
Full article ">Figure 3
<p><span class="html-italic">E. bicyclis</span> extract (EB) alters cellular responses in LPS-induced Caco-2 cells. (<b>A</b>) Pi3k, (<b>B</b>) Akt, (<b>C</b>) Mtor, (<b>D</b>) S6k, (<b>E</b>) 4Ebp1, (<b>F</b>) Nfkb, and (<b>G</b>) Cox2 mRNA expressions in LPS (2 μg/mL)-stimulated Caco-2 cells with EB extracts (25 and 50 mg/L) for 4 h. β-Actin was used as the reference gene. The data are shown as mean ± SD (n = 4), with comparisons made to the positive control (PC) group. Statistical significance was defined as * <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 **** <span class="html-italic">p</span> &lt; 0.0001. (<b>H</b>) Protein expressions of p-mTOR, mTOR, p-NF-κB, NF-κB, p-S6K, S6K, and β-actin in LPS (2 μg/mL)-treated Caco-2 cells with EB extracts (25 and 50 mg/L) for 24 h. NC: negative control; PC: positive control; EB: <span class="html-italic">Ecklonia bicyclis</span> extract.</p>
Full article ">Figure 4
<p>Effects of <span class="html-italic">E. bicyclis</span> extract (EB) on sign of inflammation in UC mice. (<b>A</b>) Experimental timeline of the DSS-treated mice. (<b>B</b>) The weight changes of mice were recorded weekly. (<b>C</b>) Percentage change in body weight. (<b>D</b>) Changes in DAI scores per group after administration of DSS. (<b>E</b>) Gut length and (<b>F</b>) spleen weight were compared between the four groups. (<b>G</b>) Histological score of colon tissues stained with hematoxylin and eosin (H&amp;E) was assessed by scoring the level of inflammation and ulceration on a scale of 0–6. (<b>H</b>) Representative images of colon tissues (magnification ×400). Data are represented as mean ± SD (n = 8/group). Significance is denoted by * <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 **** <span class="html-italic">p</span> &lt; 0.0001 (in comparison to the DSS-treated group).</p>
Full article ">Figure 5
<p>Effects of <span class="html-italic">E. bicyclis</span> extract (EB) on inflammatory markers in UC mice. (<b>A</b>) Lipocalin-2 levels in serum and (<b>B</b>–<b>E</b>) myeloperoxidase (MPO), IFN-γ, TNF-α, and IL-6 levels in colon tissue were quantified using ELISA analysis. Data are represented as mean ± SD (n = 8/group). Significance is denoted by * <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 **** <span class="html-italic">p</span> &lt; 0.0001 (relative to the DSS-treated group).</p>
Full article ">Figure 6
<p><span class="html-italic">E. bicyclis</span> extract (EB) effects on tight junctions and mTOR pathway markers in UC mice. (<b>A</b>–<b>J</b>) Nfkb, Inos, Cox2, claudin-1, occludin, Zo1, Pi3k, Akt, Mtor, and S6k mRNA levels in colon tissue. β-Actin was used as the reference gene. (<b>K</b>) p-mTOR and total mTOR protein expression in mice colon tissue. (<b>L</b>) p-mTOR/mTOR ratio was calculated. Data are represented as mean ± SD (n = 8/group). Significance is denoted by * <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 **** <span class="html-italic">p</span> &lt; 0.0001 (in comparison to the DSS-treated group).</p>
Full article ">Figure 7
<p>Impact of <span class="html-italic">E. bicyclis</span> extract (EB) on the composition and distribution of gut flora in UC mice. (<b>A</b>) Shannon index and (<b>B</b>) Faith PD for evaluating alpha-diversity. (<b>C</b>) Principal coordinate analysis (PCoA) of unweighted UniFrac distances. (<b>D</b>) Taxonomic analysis of microbiota at the phylum and genus levels. (<b>E</b>) The relative abundance of <span class="html-italic">Firmicutes</span> to <span class="html-italic">Bacteroidota.</span> (<b>F</b>–<b>H</b>) Abundance differences of specific microbial groups between DSS and EB groups. Data are expressed as box and whisker plots (n = 3 or 4; fecal DNA from 2 mice was pooled into one sample for 16S sequencing). (<b>I</b>) Quantitative PCR results for <span class="html-italic">Akkermansia muciniphila</span>, (<b>J</b>) <span class="html-italic">Bifidobacterium bifidum</span>, (<b>K</b>) <span class="html-italic">Lactobacillus plantarum</span>, and (<b>L</b>) <span class="html-italic">Lactococcus lactis</span>. The relative abundance of bacterial groups was represented as the ratio of total bacteria (F341/R518). Data are expressed as mean ± SD (n = 8/group). Compared between the control and the DSS group, # <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; 0.0001. Compared between the DSS group and the EB group, * <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; 0.0001 by nonparametric Mann–Whitney U test. (<b>M</b>) Spearman correlation analysis was performed to assess the relationship between gut microbiota species and UC-related indices (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">
12 pages, 5315 KiB  
Article
Strength Model for Cement-Stabilized Marine Clay: SEM Image Analysis and Microstructural Insights
by Liyang Xu, Xipeng Wang, Yanzhi Qi, Chang Yuan, Zhi Ding and Riqing Xu
J. Mar. Sci. Eng. 2025, 13(2), 388; https://doi.org/10.3390/jmse13020388 - 19 Feb 2025
Abstract
This study investigates the strength development of cement-stabilized marine clay, which is influenced by a complex interplay of microstructural factors. To optimize its performance for coastal and offshore engineering, we explored the relationship between microstructure and unconfined compressive strength (UCS). Using Scanning Electron [...] Read more.
This study investigates the strength development of cement-stabilized marine clay, which is influenced by a complex interplay of microstructural factors. To optimize its performance for coastal and offshore engineering, we explored the relationship between microstructure and unconfined compressive strength (UCS). Using Scanning Electron Microscopy (SEM) and the Pore/Crack Analysis System (PCAS), we analyzed samples with varying cement contents (10%, 15%, and 20%) and curing times (3, 7, 14, and 28 days). Key microstructural parameters, including porosity, particle shape, size, and arrangement, were quantified and correlated with UCS results. A novel comprehensive micro-parameter was introduced to encapsulate the combined effects of these factors, revealing an exponential relationship with strength development. The findings provide a quantitative framework for predicting the performance of cement-stabilized marine clay, contributing to more efficient solutions in geotechnical engineering. Full article
(This article belongs to the Section Ocean Engineering)
Show Figures

Figure 1

Figure 1
<p>Sample preparation. (<b>a</b>) Sample for UCS test. (<b>b</b>) Sample for SEM imaging.</p>
Full article ">Figure 2
<p>Scanning electron microscope of the FEG650 type.</p>
Full article ">Figure 3
<p>SEM images of cement-treated soil with different curing ages (the magnification rate is 5000 times). (<b>a</b>) Three days curing time, 15% cement content. (<b>b</b>) Twenty eight days curing time, 15% cement content.</p>
Full article ">Figure 4
<p>The evolution of micro-parameters with increasing curing age.</p>
Full article ">Figure 5
<p>The evolution of micro-parameters with increasing cement content.</p>
Full article ">Figure 6
<p>Strength model for the cement-stabilized marine clay. (<b>a</b>) Relation between <span class="html-italic">M</span> and UCS influenced by curing age. (<b>b</b>) Relation between comprehensive micro-parameter <span class="html-italic">M</span> and UCS influenced by cement content. (<b>c</b>) Unified exponential function of all comprehensive micro-parameters <span class="html-italic">M</span> and UCS.</p>
Full article ">
17 pages, 51050 KiB  
Article
Towards Environmentally Friendly Buildings: An Assessment of the Mechanical Properties of Soil Mixtures with Graphene
by Federico Iorio Esposito, Paola Gallo Stampino, Letizia Ceccarelli, Marco Caruso, Giovanni Dotelli and Sergio Sabbadini
C 2025, 11(1), 16; https://doi.org/10.3390/c11010016 - 19 Feb 2025
Abstract
This study investigates the potential of graphene-based additives to improve the mechanical properties of compacted soil mixtures in rammed-earth construction, contributing to the development of environmentally friendly building materials. Two distinct soils were selected, combined with sand at optimized ratios, and treated with [...] Read more.
This study investigates the potential of graphene-based additives to improve the mechanical properties of compacted soil mixtures in rammed-earth construction, contributing to the development of environmentally friendly building materials. Two distinct soils were selected, combined with sand at optimized ratios, and treated with varying concentrations of a graphene liquid solution and a graphene-based paste (0.001, 0.005, 0.01, 0.05, and 0.1 wt.% relative to the soil-sand proportion). The effects of these additives were analyzed using the modified Proctor compaction and unconfined compressive strength (UCS) tests, focusing on parameters such as optimum water content (OWC), maximum dry density (MDD), maximum strength (qu), and stiffness modulus (E). The results demonstrated that graphene’s influence on compaction behavior and mechanical performance depends strongly on the soil composition, with minimal variation between additive types. In finer soil mixtures, graphene disrupted particle packing, increased water demand, and reduced strength. In silt–sandy mixtures, graphene’s hydrophobicity and limited interaction with fines decreased water absorption and preserved density but likewise led to diminished strength. Conclusions from the experiments suggest a possible interaction between graphene, soil’s finer fraction, and potentially the swelling and non-swelling clay minerals, providing insights into the complex interplay between soil properties. Full article
(This article belongs to the Topic Application of Graphene-Based Materials, 2nd Edition)
Show Figures

Figure 1

Figure 1
<p>Additive used: (<b>a</b>) GUP ADMIXTURE (GUP); (<b>b</b>) Graphene paste (GSL).</p>
Full article ">Figure 2
<p>Experimental setup for Proctor compaction test. (<b>a</b>) Proctor machine; (<b>b</b>) The mold positioned on the machine; (<b>c</b>) The rammer compacting the soil inside the mold; (<b>d</b>) The sample is leveled inside the mold; (<b>e</b>) Extraction of the sample; (<b>f</b>) The final sample extracted from the mold.</p>
Full article ">Figure 3
<p>Experimental setup for unconfined compressive strength (UCS) test. (<b>a</b>) TRITECH Load Frame for UCS test; (<b>b</b>) Sample during the test; (<b>c</b>) Sample after failure.</p>
Full article ">Figure 4
<p>Samples preparation for unconfined compressive strength (UCS) test. (<b>a</b>) Proctor cylinder on hand-driven load frame; (<b>b</b>) Coring procedure; (<b>c</b>) UCS samples in the curing chamber.</p>
Full article ">Figure 5
<p>Verified water content (%) of ABS Mix and GSL series with respect to the reference optimum water content (OWC) of the ABS Mix (7.10%). Two distinct portions of the sample were tested for water content. The name of the sample consists of the soil name, followed by the percentage and the abbreviation of the additive (e.g., ABS 0.005% GSL).</p>
Full article ">Figure 6
<p>Proctor compaction test results for ABS mixtures. (<b>a</b>) ABS Mix; (<b>b</b>) ABS 0.001% GUP; (<b>c</b>) ABS 0.005% GUP; (<b>d</b>) ABS 0.01% GUP; (<b>e</b>) ABS 0.05% GUP; (<b>f</b>) ABS 0.1% GUP. The soil saturation curves (Sr) are reported, indicating different degrees of saturation from 0.5 to 1.</p>
Full article ">Figure 7
<p>Proctor compaction test results for T2 mixtures. (<b>a</b>) T2 Mix; (<b>b</b>) T2 0.01% GUP; (<b>c</b>) T2 0.05% GUP; (<b>d</b>) T2 0.1% GUP. The soil saturation curves (Sr) are reported, indicating different degrees of saturation from 0.5 to 1.</p>
Full article ">Figure 8
<p>Unconfined compressive strength (UCS) results. (<b>a</b>) ABS mixtures with GUP additive; (<b>b</b>) ABS mixtures with GSL additive; (<b>c</b>) T2 mixtures with GUP additive. The name of the sample consists of the soil name, followed by the percentage and the abbreviation of the additive (e.g., ABS 0.001% GUP).</p>
Full article ">Figure 8 Cont.
<p>Unconfined compressive strength (UCS) results. (<b>a</b>) ABS mixtures with GUP additive; (<b>b</b>) ABS mixtures with GSL additive; (<b>c</b>) T2 mixtures with GUP additive. The name of the sample consists of the soil name, followed by the percentage and the abbreviation of the additive (e.g., ABS 0.001% GUP).</p>
Full article ">Figure 9
<p>Results from the unconfined compressive strength (UCS) test. (<b>a</b>) Maximum stress, q<sub>u</sub>, with varying graphene concentration; (<b>b</b>) Stiffness modulus, E, with varying graphene concentration.</p>
Full article ">Figure 9 Cont.
<p>Results from the unconfined compressive strength (UCS) test. (<b>a</b>) Maximum stress, q<sub>u</sub>, with varying graphene concentration; (<b>b</b>) Stiffness modulus, E, with varying graphene concentration.</p>
Full article ">Figure 10
<p>Comparison between the two graphene-based additives of unconfined compressive strength results in ABS and T2. The name of the sample consists of the soil name, followed by the percentage and the abbreviation of the additive (e.g., ABS 0.001% GUP).</p>
Full article ">
13 pages, 2563 KiB  
Article
Temporal Trends in the Use of Biological Agents in Patients with Inflammatory Bowel Disease: Real-World Data from a Tertiary Inflammatory Bowel Disease Greek Center During a 5-Year Period
by Panagiotis Markopoulos, Aikaterini Gaki, Georgios Kokkotis, Konstantina Chalakatevaki, Nikolaos Kioulos, Vasso Kitsou, Constantinos Tsitsigiannis, Michael Gizis, Paraskevi Prapa, Stamatina-Lydia Chatzinikolaou, Efrosini Laoudi, Ioannis Koutsounas and Giorgos Bamias
J. Clin. Med. 2025, 14(4), 1357; https://doi.org/10.3390/jcm14041357 - 18 Feb 2025
Abstract
Background/Objectives: Therapeutic management of inflammatory bowel diseases (IBD) is rapidly evolving in the era of novel biological therapies. However, real-world data relating to the usage trends and treatment persistence remain inconsistent. This study aimed to investigate trends in biological use, dose intensification, and [...] Read more.
Background/Objectives: Therapeutic management of inflammatory bowel diseases (IBD) is rapidly evolving in the era of novel biological therapies. However, real-world data relating to the usage trends and treatment persistence remain inconsistent. This study aimed to investigate trends in biological use, dose intensification, and treatment persistence in IBD patients, who received treatment in a large tertiary center in Greece. Methods: Patients with IBD who underwent at least one biological treatment between 2018 and 2022 were included in this retrospective study. Data on patients’ demographics, type of disease, use of biologicals, dose intensification, and treatment persistence were analyzed for time trends. Results: Data from 409 patients with IBD (mean age 39 (range 17–87), female 51%, 56.9% CD, mean duration of disease: 9.3 years) were included in the study. The number of patients on biologics was raised from 133 in 2018 to 368 in 2022 (a 28.1% yearly increase), while the percentage of patients who were treated with anti-TNF biosimilars increased to >60% of the total anti-TNF population in 2022. We observed a gradual increase in non-anti-TNF therapies in bio-naïve patients, in particular vedolizumab (46% of all biologicals in UC; 16% in CD) and ustekinumab (16.3% of all biologicals in UC, 31% in CD). The 3-year persistence rate of IFX was 64% in CD and 56% in UC, whereas it was 61% for ADA in CD. Dose intensification of anti-TNF was efficient in >50% of CD patients and >30% of UC patients; however, the majority of patients who required dose escalation within the first year eventually became unresponsive. The 3-year persistence of vedolizumab as a first-line treatment was 82% for CD and 69% for UC, respectively. The 3-year persistence of ustekinumab as first-line treatment for CD was 65%. No significant differences regarding the efficacy of anti-TNF, ustekinumab, or vedolizumab were detected when they were used as first-line treatments for Crohn’s disease; similarly, no significant differences were detected between infliximab and vedolizumab as first-line treatments for UC. Conclusions: There was a gradual increase in the use of biologicals, including biosimilars, between the years 2018–2022, reflecting adherence to current guidance with adoption of an early escalation strategy. Newer, post-anti-TNF biologics such as vedolizumab and ustekinumab have been rapidly incorporated into therapeutic approaches for both CD and UC. Full article
Show Figures

Figure 1

Figure 1
<p>Overall trend of prescribed biologics in patients with IBD from 2018 through 2022.</p>
Full article ">Figure 2
<p>The trend in novel prescriptions of each biologic as a first treatment line (<b>A</b>) or as a second treatment line (<b>B</b>) in CD, through the years 2019–2022. ADA and UST are significantly the most prescribed medications as first and second treatment lines, respectively.</p>
Full article ">Figure 3
<p>The trend in novel prescriptions of each biologic as a first treatment line (<b>A</b>) or as a second treatment line (<b>B</b>) in UC, through the years 2019–2022. VDZ is significantly the most prescribed medication as first treatment line, while UST is numerically the most frequently prescribed second-line treatment.</p>
Full article ">Figure 4
<p>“Kaplan–Meier” curves demonstrate survival free of treatment discontinuation in CD patients, when biologics are prescribed as the 1st treatment line (<b>A</b>), as the 2nd treatment line after non-response to any anti-TNF agent (<b>B</b>), or after non-response to adalimumab only (<b>C</b>). “Log-Rank” <span class="html-italic">p</span> &lt; 0.05 is considered as statistically significant.</p>
Full article ">Figure 5
<p>“Kaplan–Meier” curves demonstrate survival free of treatment discontinuation in UC patients, when biologics (IFX, VDZ) are prescribed as the 1st treatment line (<b>A</b>), when biologics (UST, VDZ) are prescribed as the 2nd treatment line after non-response to any anti-TNF agent (<b>B</b>), or when biologics (IFX, UST) are prescribed as the 2nd line treatment after non-response to vedolizumab (<b>C</b>). “Log-Rank” <span class="html-italic">p</span> &lt; 0.05 is considered as statistically significant.</p>
Full article ">
10 pages, 729 KiB  
Article
Carboxylated Osteocalcin as an Independent Predictor of Mean Arterial Pressure and the Atherogenic Index in Adults
by José Rafael Villafán-Bernal, Jorge David Rivas-Carrillo, Iris Paola Guzmán-Guzmán, Jose Luis Frias-Cabrera, Edgar Alfonso Rivera-León, Raigam Jafet Martinez-Portilla and Sergio Sánchez-Enríquez
Int. J. Mol. Sci. 2025, 26(4), 1733; https://doi.org/10.3390/ijms26041733 - 18 Feb 2025
Abstract
Bone-derived proteins, including carboxylated osteocalcin (cOC), are thought to play a role in cardiovascular and metabolic health. cOC is recognized for its strong affinity for calcium hydroxyapatite and its possible involvement in vascular calcification and lipid metabolism. Although the undercarboxylated form of osteocalcin [...] Read more.
Bone-derived proteins, including carboxylated osteocalcin (cOC), are thought to play a role in cardiovascular and metabolic health. cOC is recognized for its strong affinity for calcium hydroxyapatite and its possible involvement in vascular calcification and lipid metabolism. Although the undercarboxylated form of osteocalcin (ucOC) has been widely researched, the connections between cOC and cardiovascular risk markers, such as mean arterial pressure (MAP), pulse pressure (PP), and the atherogenic index, are still not well understood. This cross-sectional study comprised 81 adults from Western Mexico; selection was based on rigorous inclusion criteria. Participants underwent various measurements, including anthropometric, biochemical, and cardiovascular assessments, such as the body mass index (BMI), body fat percentage, serum glucose, insulin resistance (HOMA-IR), glycated hemoglobin (HbA1c), lipid profile, creatinine, blood pressure parameters, and the atherogenic index. Serum cOC levels were determined using an enzyme-linked immunosorbent assay (ELISA). The study examined the relationships between cOC and cardiovascular/metabolic markers using inferential statistics and correlation coefficients. Multivariate linear analysis was performed to identify factors independently associated with the serum levels of cOC. Multivariate analysis revealed that MAP (B coefficient: 0.138, 95% CI: 0.028–0.247, p = 0.015) and the atherogenic index (B coefficient: 0.599, 95% CI: −0.039–1.161, p = 0.037) are independent predictors of cOC levels. A positive correlation was observed between cOC, PP, the atherogenic index, and HbA1, as well as an inverse correlation between cOC and HDL-c among the participants. Additionally, PP was positively correlated with HOMA-IR. Participants with elevated cOC levels showed higher MAP and atherogenic index values, indicating a potential connection between cOC and cardiovascular risk. cOC is independently associated with MAP and the atherogenic index, suggesting it may play a role in vascular remodeling and lipid metabolism. These results emphasize the importance of the bone–vascular axis in cardiovascular health and indicate that cOC might be a useful biomarker for assessing cardiovascular risk. Additional research is necessary to confirm these findings in larger, long-term studies and to investigate the mechanisms that connect cOC with cardiovascular outcomes. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
Show Figures

Figure 1

Figure 1
<p>Median PP values by quartiles (Q1–Q4) of cOC (<span class="html-italic">p</span> = 0.013, Kruskal–Wallis test).</p>
Full article ">Figure 2
<p>Median cOC serum levels by quartiles (Q1–Q4) of PP (<span class="html-italic">p</span> = 0.015, Kruskal–Wallis test).</p>
Full article ">
22 pages, 1304 KiB  
Article
Empowerment as Prevention: How Youth-Driven Initiatives Transform Frameworks for Change
by Deborah McKoy, Ruby Kosewicz-Strickland and Pixie Popplewell
Youth 2025, 5(1), 17; https://doi.org/10.3390/youth5010017 - 17 Feb 2025
Abstract
Youth-led action research has significantly influenced local and statewide policies aimed at supporting students experiencing homelessness in California. This study employs a Youth Participatory Action Research (YPAR) methodology, summarizing five years of research conducted by high school student cohorts and UC Berkeley graduate [...] Read more.
Youth-led action research has significantly influenced local and statewide policies aimed at supporting students experiencing homelessness in California. This study employs a Youth Participatory Action Research (YPAR) methodology, summarizing five years of research conducted by high school student cohorts and UC Berkeley graduate students to examine effective strategies for preventing and addressing student homelessness. The research engaged over 240 high school students, nine graduate research fellows, 120 university student mentors, and eight civic and community organizations through data collection, policy analysis, and stakeholder collaboration. Findings indicate that youth-led research strengthens alignment mechanisms, enhances cross-sector collaboration, and improves policy coordination, leading to more effective services and positive educational experiences for students experiencing homelessness. These results underscore the transformative role of youth-driven inquiry in shaping inclusive, evidence-based policies, and demonstrate the need for sustained youth engagement in policymaking to create long-term, systemic change. Full article
(This article belongs to the Special Issue Youth Homelessness Prevention)
Show Figures

Figure 1

Figure 1
<p>Y-HEAR-US theory of change.</p>
Full article ">Figure 2
<p>Y-PLAN methodology roadmap.</p>
Full article ">Figure 3
<p>California Continuum of Care boundaries. <span class="html-italic">Note.</span> California’s 58 counties (delineated by color) are broken out into 44 Continuum of Care (CoC) regions (delineated by bold outline). Adapted from <span class="html-italic">You Count: California Youth Homelessness Data Hub, 2024</span>, by California Homeless Youth Project, (<a href="https://tinyurl.com/YouCountDataHub" target="_blank">https://tinyurl.com/YouCountDataHub</a>, accessed 1 November 2024).</p>
Full article ">
20 pages, 1398 KiB  
Article
Health Benefits of Montmorency Tart Cherry Juice Supplementation in Adults with Mild to Moderate Ulcerative Colitis; A Placebo Randomized Controlled Trial
by Jonathan Sinclair, Graham McLaughlin, Robert Allan, Johanne Brooks-Warburton, Charlotte Lawson, Shan Goh, Terun Desai and Lindsay Bottoms
Life 2025, 15(2), 306; https://doi.org/10.3390/life15020306 - 17 Feb 2025
Abstract
Aims: Ulcerative colitis (UC) significantly impacts individuals’ self-perception, body image, and overall quality of life, while also imposing considerable economic costs. These challenges highlight the necessity for complementary therapeutic strategies with reduced adverse effects to support conventional pharmacological treatments. Among natural interventions, Montmorency [...] Read more.
Aims: Ulcerative colitis (UC) significantly impacts individuals’ self-perception, body image, and overall quality of life, while also imposing considerable economic costs. These challenges highlight the necessity for complementary therapeutic strategies with reduced adverse effects to support conventional pharmacological treatments. Among natural interventions, Montmorency tart cherries, noted for their high anthocyanin content have emerged as a natural anti-inflammatory agent for UC. The current trial aimed to investigate the effects of Montmorency tart cherries compared to placebo in patients with mild to moderate UC. Materials and methods: Thirty-five patients with UC were randomly assigned to receive either placebo or Montmorency tart cherry juice, of which they drank 60 mL per day for 6 weeks. The primary outcomes and health-related quality of life, measured via the Inflammatory Bowel Disease Quality of Life Questionnaire (IBDQ), and the secondary measures, including other health-related questionnaires, blood biomarkers, and faecal samples, were measured before and after the intervention. Linear mixed-effects models were adopted to contrast the changes from baseline to 6 weeks between trial arms. Effect sizes were calculated using Cohen’s d. Results: There were significantly greater improvements in the IBDQ (22.61 (95% CI = 5.24 to 39.99) d = 0.90) and simple clinical colitis activity index (−3.98 (95% CI = −6.69 to –1.28) d = −1.01) in the tart cherry trial arm compared to placebo. In addition, reductions in faecal calprotectin levels were significantly greater in the tart cherry trial arm compared to placebo (−136.17 µg/g (95% CI = −258.06 to –4.28) d = −1.14). Loss to follow-up (N = 1) and adverse events (N = 1) were low and compliance was very high in the tart cherry (95.8%) trial arm. Conclusions: Given the profoundly negative effects of UC on health-related quality of life and its fiscal implications for global healthcare systems, this trial indicates that twice-daily tart cherry supplementation can improve IBD-related quality of life as well as the severity of symptoms and therefore may be important in the management of UC. Full article
(This article belongs to the Collection Clinical Trials)
Show Figures

Figure 1

Figure 1
<p>Consort diagram showing of participant flow throughout the study.</p>
Full article ">Figure 2
<p>Comparison of Shannon diversity index between placebo and tart cherry groups at baseline and 6 weeks.</p>
Full article ">Figure 3
<p>Beta diversity plotted using PCoA based on the Bray–Curtis dissimilarity between trial arms and study timepoints.</p>
Full article ">
28 pages, 25047 KiB  
Article
Effects of Steel Slag, Desulfurization Gypsum, and Ground Granulated Blast-Furnace Slag on the Characterization of Recycled Cement-Stabilized Macadam
by Haoyu Tan, Henggang Ji, Peilong Yuan and Xiang Fan
Materials 2025, 18(4), 874; https://doi.org/10.3390/ma18040874 - 17 Feb 2025
Abstract
Steel slag powder (SS), ground granulated blast-furnace slag (GGBS), and flue gas desulfurization gypsum (FDG) are environmentally friendly and cost-effective substitute materials for ordinary Portland cement (OPC). This study investigated the use of industrial solid wastes, including SS, GGBS, and FDG, as auxiliary [...] Read more.
Steel slag powder (SS), ground granulated blast-furnace slag (GGBS), and flue gas desulfurization gypsum (FDG) are environmentally friendly and cost-effective substitute materials for ordinary Portland cement (OPC). This study investigated the use of industrial solid wastes, including SS, GGBS, and FDG, as auxiliary materials in OPC to stabilize pretreated recycled concrete aggregate (pretreated RCA). The use of pretreated RCA, mixed cementitious materials, and water at the optimum content created a mixture designated recycled cement-stabilized macadam (RCSM). A series of mechanical tests were conducted to clarify the performance of the RCSM, and microscopic tests were performed to elucidate the microcharacteristics of the mixed cementitious materials. With a curing time from 3 days to 28 days, the unconfined compression strength (UCS) of the mixed cementitious materials (A4) composed of SS, GGBS, FDG, and OPC increased by 5.94–10.79% compared with that of the cementitious material of OPC (A0). The UCS of the mixture composed (C4) of SS, GGBS, FDG, OPC, and pretreated RCA was greater than that of the mixture composed (C0) of OPC and RCA from 7 days to 90 days, increasing by 4.26–8.35%. The total drying shrinkage coefficient of C4 was lower than that of C0, whereas the temperature shrinkage coefficient of C4 was higher than that of C0, indicating that the use of A4 can effectively reduce drying shrinkage cracking in C4. The hydration products of A4 primarily consisted of flocculent calcium silicate hydrate (C-S-H) gel, fibrous calcium aluminate hydrate gel, and needle-like ettringite crystals. The interlocked growth of C-S-H gel and ettringite crystals continued and promoted an increase in the UCS of the cementitious system. The test results provide a reference for the application of similar materials. Full article
Show Figures

Figure 1

Figure 1
<p>Appearance and micromorphology of SS, GGBS, and FDG.</p>
Full article ">Figure 1 Cont.
<p>Appearance and micromorphology of SS, GGBS, and FDG.</p>
Full article ">Figure 2
<p>Particle size distribution curves of SS, GGBS, and FDG.</p>
Full article ">Figure 3
<p>XRD analysis of OPC, SS, GGBS, and FDG.</p>
Full article ">Figure 4
<p>RCA pretreatment process and crushing value test.</p>
Full article ">Figure 5
<p>Test process.</p>
Full article ">Figure 6
<p>UCSs of mixed cementitious materials.</p>
Full article ">Figure 7
<p>pH evolution of mixed cementitious materials.</p>
Full article ">Figure 8
<p>Effects of mixed cementitious materials on the unconfined compressive strength of the mixture at 7 d.</p>
Full article ">Figure 9
<p>UCS curves of the mixtures.</p>
Full article ">Figure 10
<p>STS curves of the mixtures.</p>
Full article ">Figure 11
<p>Compressive and splitting resilient moduli of the mixture.</p>
Full article ">Figure 12
<p>Drying shrinkage test results of the mixture. (<b>a</b>) Relationship between total water loss ratio and time; (<b>b</b>) relationship between drying shrinkage strain and time; (<b>c</b>) relationship between total dry shrinkage coefficient and time.</p>
Full article ">Figure 13
<p>Temperature shrinkage test results of the mixture.</p>
Full article ">Figure 14
<p>Freeze–thaw test results of the mixture.</p>
Full article ">Figure 15
<p>XRD analysis of mixed cementitious materials.</p>
Full article ">Figure 16
<p>SEM images of (<b>a</b>) A1, (<b>b</b>) A2, (<b>c</b>) A3, and (<b>d</b>) A4.</p>
Full article ">Figure 17
<p>Mercury intrusion porosimetry test results of mixed cementitious materials.</p>
Full article ">
14 pages, 5793 KiB  
Article
Oral Microbiota and Inflammatory Bowel Diseases: Detection of Emerging Fungal Pathogens and Herpesvirus
by Manoel Marques Evangelista Oliveira, Letícia Bomfim Campos, Fernanda Brito, Flavia Martinez de Carvalho, Geraldo Oliveira Silva-Junior, Gisela Lara da Costa, Tatiane Nobre Pinto, Rafaela Moraes Pereira de Sousa, Rodrigo Miranda, Rodolfo Castro, Cyrla Zaltman and Vanessa Salete de Paula
Biomedicines 2025, 13(2), 480; https://doi.org/10.3390/biomedicines13020480 - 15 Feb 2025
Abstract
Background/Objectives: Ulcerative colitis (UC) and Crohn’s disease (CD) are the usual clinical forms of inflammatory bowel disease (IBD). Changes in the oral microbiota, especially the presence of emerging fungi and herpesviruses, have been shown to worsen the clinical aspects of IBD. The aim [...] Read more.
Background/Objectives: Ulcerative colitis (UC) and Crohn’s disease (CD) are the usual clinical forms of inflammatory bowel disease (IBD). Changes in the oral microbiota, especially the presence of emerging fungi and herpesviruses, have been shown to worsen the clinical aspects of IBD. The aim of this study was to screen for emerging pathogens in the oral yeast microbiota and the presence of herpesvirus in IBD patients. Methods: Oral swabs of seven UC or CD patients were collected. The samples were plated on Sabouraud Dextrose Agar and subcultured on CHROMagar Candida and CHROMagar Candida Plus. Polyphasic taxonomy was applied and identified using molecular tools, such as MALDI-TOF MS and ITS partial sequencing. Multiplex qPCR was used to identify the herpesvirus. Results: The mean age was 38.67 ± 14.06 years, 57.14% were female, and two had diabetes. The CD patients presented with Rhodotorula mucilaginosa, Candida orthopsilosis and Kodamaea jinghongensis, while the UC patients presented with Cutaneotrichosporon dermatis, Candida glabrata, Candida lusitanea and Candida tropicalis. Two UC individuals had at least one herpesvirus. In the first individual, a co-detection of Herpes Simplex Virus 1 (HSV-1) and C. lusitaniae was observed. The second presented with co-infections of Epstein–Barr virus (EBV), Human Herpesvirus 7 (HHV-7) and C. tropicalis. Conclusions: We identified rarely described yeasts and co-infections in IBD patients, highlighting the need to identify emerging pathogens in the oral microbiota, as they may contribute to opportunistic infections. Full article
Show Figures

Figure 1

Figure 1
<p>Growth in Sabouraud Dextrose Agar Medium (BD Difco) incubated at 35 °C for 48 h: (<b>A</b>) <span class="html-italic">Cutaneotrichosporon dermatis</span>, (<b>B</b>) <span class="html-italic">Rhodotorula mucilaginosa</span>, (<b>C</b>) <span class="html-italic">Candida glabrata</span>, (<b>D</b>) <span class="html-italic">Candida orthopsilosis</span>, (<b>E</b>) <span class="html-italic">Kodamaea jinghongensis</span>, (<b>F</b>) <span class="html-italic">Candida lusitanea</span>, (<b>G</b>) <span class="html-italic">Kodamaea jinghongensis,</span> (<b>H</b>) <span class="html-italic">Candida orthopsilosis</span> and (<b>I</b>) <span class="html-italic">Candida tropicalis</span>.</p>
Full article ">Figure 2
<p>Growth in BDTM CHROMagar<sup>TM</sup> Candida Medium (BD Difco) incubated at 35 °C for 48 h: (<b>A</b>) <span class="html-italic">Cutaneotrichosporon dermatis,</span> (<b>B</b>) <span class="html-italic">Rhodotorula mucilaginosa</span>, (<b>C</b>) <span class="html-italic">Candida glabrata</span>, (<b>D</b>) <span class="html-italic">Candida orthopsilosis</span>, (<b>E</b>) <span class="html-italic">Kodamaea jinghongensis,</span> (<b>F</b>) <span class="html-italic">Candida lusitanea</span>, (<b>G</b>) <span class="html-italic">Kodamaea jinghongensis,</span> (<b>H</b>) <span class="html-italic">Candida orthopsilosis</span> and (<b>I</b>) <span class="html-italic">Candida tropicalis</span>.</p>
Full article ">Figure 3
<p>The phylogenetic relationships between the isolates of samples with reference strains inferred from ITS sequences. (<b>A</b>) <span class="html-italic">Kodhamaea</span> sp.: this analysis involved eight nucleotide sequences, and a total of 263 positions were obtained in the final dataset. (<b>B</b>) <span class="html-italic">Rhodotorula</span> sp.: this analysis involved nine nucleotide sequences, and a total of 602 positions were obtained in the final dataset. (<b>C</b>) <span class="html-italic">Trichosporon</span> sp.: this analysis involved 16 nucleotide sequences and a total of 560 positions were obtained in the final dataset. (<b>D</b>) <span class="html-italic">Candida</span> spp.: this analysis involved 22 nucleotide sequences and a total of 92 positions were obtained in the final dataset.</p>
Full article ">
16 pages, 5675 KiB  
Article
Effects of Pilates Training Combined with Fascial Massage on Upper Cross Syndrome in Office Workers
by Liao Jiang, Yada Thadanatthaphak and Kukiat Tudpor
Healthcare 2025, 13(4), 410; https://doi.org/10.3390/healthcare13040410 - 14 Feb 2025
Abstract
Objective: Upper crossed syndrome (UCS) is an abnormal upper extremity movement pattern characterized by muscle tightness in the neck, shoulders, and upper back, coupled with weakness in opposing muscle groups. This study aimed to investigate the effectiveness of Pilates training combined with fascial [...] Read more.
Objective: Upper crossed syndrome (UCS) is an abnormal upper extremity movement pattern characterized by muscle tightness in the neck, shoulders, and upper back, coupled with weakness in opposing muscle groups. This study aimed to investigate the effectiveness of Pilates training combined with fascial massage as an intervention in office workers with UCS. Methods: 34 subjects were recruited and randomly divided into an experimental group (n = 17) and a control group (n = 17). The control group underwent 12 weeks of Pilates training, and the experimental group received 12 weeks of Pilates training combined with fascial massage. Body posture was assessed using the forward head angle (FHA) and forward shoulder angle (FSA), joint mobility was evaluated using cervical spine range of motion (ROM), muscle activity was assessed using surface electromyography (sEMG), and quality of life was evaluated using pain level (VAS) and cervical spine dysfunction index (NDI). Results: After 12 weeks of intervention, the FHA, FSA, VAS, and NDI of the experimental group were significantly lower than those of the pre-intervention group (p < 0.05) and significantly lower than those of the control group (p < 0.05); the extension and left–right rotation cervical spine ROM of the experimental group were significantly higher than those of the pre-intervention group (p < 0.05) and significantly higher than those of the control group (p < 0.05); and sEMG indexes (mean power frequency and median frequency) of the upper trapezius and the pectoralis major in the experimental group were significantly higher than those of the pre-intervention group (p < 0.05) and significantly higher than the control group (p < 0.05). Conclusion: Compared with Pilates training alone, Pilates training combined with fascial massage demonstrated a more significant effect in improving muscle activation, body posture, and pain and enhancing the quality of life for patients with UCS. Full article
(This article belongs to the Special Issue Advances in Manual Therapy: Diagnostics, Prevention and Treatment)
Show Figures

Figure 1

Figure 1
<p>The experimental flow.</p>
Full article ">Figure 2
<p>Comparison of forward head angle (FHA) and forward shoulder angle (FSA). Note: *** significant difference within groups (<span class="html-italic">p</span> &lt; 0.001); # significant difference between groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3
<p>Comparison of cervical range of motion. Note: * significant difference within groups (<span class="html-italic">p</span> &lt; 0.05); ** significant difference within groups (<span class="html-italic">p</span> &lt; 0.01); *** significant difference within groups (<span class="html-italic">p</span> &lt; 0.001); # significant difference between groups (<span class="html-italic">p</span> &lt; 0.05); ## significant difference between groups (<span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 4
<p>Comparison of frequency domain metrics mean power frequency (MPF) of surface electromyography (sEMG). Note: UT—upper trapezius; LT—lower trapezius; PM1—pectoralis major; ** significant difference within groups (<span class="html-italic">p</span> &lt; 0.01); *** significant difference within groups (<span class="html-italic">p</span> &lt; 0.001); # significant difference between groups (<span class="html-italic">p</span> &lt; 0.05); ## significant difference between groups (<span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 5
<p>Comparison of frequency domain metrics median frequency (MF) of surface electromyography (sEMG). Note: UT—upper trapezius; LT—lower trapezius; PM1—pectoralis major; ** significant difference within groups (<span class="html-italic">p</span> &lt; 0.01); *** significant difference within the group (<span class="html-italic">p</span> &lt; 0.001); # significant difference between groups (<span class="html-italic">p</span> &lt; 0.05); ## significant difference between groups (<span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 6
<p>Comparison of visual analog score (VAS) and neck disability index (NDI). Note: *** significant difference within groups (<span class="html-italic">p</span> &lt; 0.001); # significant difference between groups (<span class="html-italic">p</span> &lt; 0.05); ### significant difference between groups (<span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">
14 pages, 772 KiB  
Article
Uterine Carcinosarcoma—A Retrospective Cohort Analysis from a Tertiary Centre on Epidemiology, Management Approach, Outcomes and Survival Patterns
by Sarah Louise Smyth, Katherine Ripullone, Andreas Zouridis, Christina Pappa, Geraldine Spain, Aikaterina Gkorila, Amika McCulloch, Phoebe Tupper, Farhat Bibi, Negin Sadeghi, Alisha Sattar, Shmaila Siddiki, Susan Addley, Mostafa Abdalla, Federico Ferrari, Stephen Damato, Sean Kehoe and Hooman Soleymani majd
Cancers 2025, 17(4), 635; https://doi.org/10.3390/cancers17040635 - 14 Feb 2025
Abstract
Background/Objectives: Uterine carcinosarcoma (UCS) refers to a rare high-grade aggressive epithelial non-endometrioid endometrial carcinoma, with tumour cells demonstrating epithelial–mesenchymal metaplastic transition and composed of both carcinomatous epithelial and sarcomatous (homologous or heterologous) components. Methods: The aim of this study was to evaluate the [...] Read more.
Background/Objectives: Uterine carcinosarcoma (UCS) refers to a rare high-grade aggressive epithelial non-endometrioid endometrial carcinoma, with tumour cells demonstrating epithelial–mesenchymal metaplastic transition and composed of both carcinomatous epithelial and sarcomatous (homologous or heterologous) components. Methods: The aim of this study was to evaluate the epidemiology, management approach, outcomes and survival patterns of patients with UCS. Seventy-seven cases of UCS treated with primary surgery in a single tertiary centre underwent retrospective cohort analysis across a ten-year period. Observational data on clinicopathological variables and treatment pathways were reviewed and independent risk factors for relapse and mortality were analysed. Results: The 5-year disease-free and overall survival rates were 52.10% and 46.6%, respectively. Cervical stromal involvement was independently related to disease-free survival (HR = 6.26; 95%CI 1.82–21.59; p = 0.004) and overall survival (HR = 3.64; 95%CI 1.42–9.38; p = 0.007), whilst sarcomatous component type was independently related to recurrence only (HR = 3.62; 95%CI 1.38–9.51; p = 0.009) after adjusting for other pathological and treatment variables. No significant difference in recurrence or mortality was found when comparing the performance of pelvic lymph node dissection (p = 0.803 and p = 0.192 respectively) or the administration of adjuvant treatment (p = 0.546 and p = 0.627 respectively). Conclusions: Whilst our data suggests an encouraging similarity in overall survival rates compared with the literature, UCS continues to represent significant treatment challenges—with a paucity of guidelines available. Data regarding molecular analysis was not systemically available in our cohort, the more recent introduction of which (alongside the revision of endometrial cancer staging) will undoubtedly provide UCS patients with improved therapeutic options in the future. Full article
(This article belongs to the Special Issue Lymph Node Dissection for Gynecologic Cancers)
Show Figures

Figure 1

Figure 1
<p>Disease-free (<b>left</b>) and overall survival (<b>right</b>) for patients with uterine carcinosarcoma.</p>
Full article ">Figure 2
<p>Disease-free cervical involvement (<b>left</b>), sarcomatous component (<b>middle</b>) and overall survival cervical involvement (<b>right</b>) for patients with uterine carcinosarcoma.</p>
Full article ">
14 pages, 3276 KiB  
Article
Experimental Study on Grouting Diffusion Law of Tunnel Secondary Lining Cracks Based on Different Slurry Viscosities
by Bin Zhang, Peng Liu, Yi Wu, Liming Wu, Chen Li, Shiyang Liu and Yuanfu Zhou
Appl. Sci. 2025, 15(4), 1955; https://doi.org/10.3390/app15041955 - 13 Feb 2025
Abstract
To investigate the diffusion law of ultrafine cement slurry (UCS) with different water–cement ratios in tunnel second lining cracks during grouting, the grouting of ultrafine cement slurry with different water–cement ratios was carried out by experimental and theoretical analysis methods in this study. [...] Read more.
To investigate the diffusion law of ultrafine cement slurry (UCS) with different water–cement ratios in tunnel second lining cracks during grouting, the grouting of ultrafine cement slurry with different water–cement ratios was carried out by experimental and theoretical analysis methods in this study. Through the collection and data analysis grouting experiment of the diffusion time history, the diffusion morphological characteristics based on different slurry viscosities were obtained, which were divided into three grouting diffusion patterns: circular diffusion zone, excessive diffusion zone, and elliptical diffusion zone. Furthermore, the spatiotemporal variation rules of the diffusion radius of ultrafine cement slurry with different water–cement ratios in tunnel secondary lining cracks were obtained as well. By analyzing the diffusion radius values under different water–cement ratios in each direction of x+, x−, y+, and y−, the critical water–cement ratios ξ were found to be 0.8, which affected the diffusion radius value in the vertical upward y+ direction. Meanwhile, when the grouting was completed, the maximum diffusion radius of the ultrafine cement slurry was obtained using different water–cement ratios in each direction. Moreover, the grouting diffusion equation of tunnel secondary lining cracks based on ultrafine cement slurry with different water–cement ratios is established. The research results can accurately predict the grouting diffusion pattern and diffusion radius in tunnel second lining cracks with different water–cement ratios of ultrafine cement slurry. Full article
Show Figures

Figure 1

Figure 1
<p>Grouting materials and slurry diffusion pattern: (<b>a</b>) Four kinds of additive materials; (<b>b</b>) mixing device; (<b>c</b>) slurry morphology diagram.</p>
Full article ">Figure 2
<p>Rheological curve of slurry with different water cement ratio. (<b>a</b>) The variation curve of shear stress with shear rate; (<b>b</b>) the change curve of viscosity with shear rate.</p>
Full article ">Figure 3
<p>Secondary lining crack grouting model: (<b>a</b>) crack side view; (<b>b</b>) model crack plane front view.</p>
Full article ">Figure 4
<p>Slurry diffusion patterns in different water–cement ratios: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.5 viscosity 33.6 mPa·s; (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.6 viscosity 20.2 mPa·s; (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.7 viscosity 6.3 mPa·s; (<b>d</b>) <math display="inline"><semantics> <mrow> <mrow> <mo> </mo> <mi mathvariant="sans-serif">ξ</mi> </mrow> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.8 viscosity 3.2 mPa·s; (<b>e</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.9 viscosity 2.5 mPa·s; (<b>f</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.0 viscosity 1.8 mPa·s.</p>
Full article ">Figure 4 Cont.
<p>Slurry diffusion patterns in different water–cement ratios: (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.5 viscosity 33.6 mPa·s; (<b>b</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.6 viscosity 20.2 mPa·s; (<b>c</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.7 viscosity 6.3 mPa·s; (<b>d</b>) <math display="inline"><semantics> <mrow> <mrow> <mo> </mo> <mi mathvariant="sans-serif">ξ</mi> </mrow> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.8 viscosity 3.2 mPa·s; (<b>e</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>.9 viscosity 2.5 mPa·s; (<b>f</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">ξ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>.0 viscosity 1.8 mPa·s.</p>
Full article ">Figure 5
<p>Time history curves of diffusion radius in different water–cement ratio: (<b>a</b>) x+ direction; (<b>b</b>) x− direction; (<b>c</b>) y+ direction; (<b>d</b>) y− direction.</p>
Full article ">Figure 6
<p>Maximum diffusion radius in different water–cement ratios: (<b>a</b>) horizontal direction; (<b>b</b>) vertical direction.</p>
Full article ">Figure 7
<p>Maximum diffusion radius in different water–cement ratio: (<b>a</b>) R~t variation relation; (<b>b</b>) R~ξ variation relation.</p>
Full article ">
24 pages, 16534 KiB  
Article
The Diagnostic Significance of SLC26A2 and Its Potential Role in Ulcerative Colitis
by Lijuan Qian, Shuo Hu, Haizhou Zhao, Ye Han, Chenguang Dai, Xinquan Zan, Qiaoming Zhi and Chunfang Xu
Biomedicines 2025, 13(2), 461; https://doi.org/10.3390/biomedicines13020461 - 13 Feb 2025
Abstract
Background/Objectives: The solute carrier family 26, member 2 (SLC26A2) gene, which belongs to the family of SLC26 transporters, can be detected in multiple tissues. However, the studies of SLC26A2 in colon-related diseases are still limited and incompletely understood, especially in ulcerative colitis (UC). [...] Read more.
Background/Objectives: The solute carrier family 26, member 2 (SLC26A2) gene, which belongs to the family of SLC26 transporters, can be detected in multiple tissues. However, the studies of SLC26A2 in colon-related diseases are still limited and incompletely understood, especially in ulcerative colitis (UC). Methods: In this study, we attempted to search and identify putative UC candidate genes within a large number of known genes by multiple bioinformatics analyses. The potential cellular characteristics and biological functions of SLC26A2 in the pathogenesis of UC were also elucidated. Results: Notably, SLC26A2 was representative and down-regulated in the intestinal mucosa of patients with active UC, compared to healthy controls. Decreased levels of SLC26A2 were proved to have a more value in diagnosis of UC patients, and closely correlated with some UC characteristics, including the Mayo score and Paediatric Ulcerative Colitis Activity Index (PUCAI). Mechanistically, subsequent results from published datasets and our validated clinical data all strongly implied that SLC26A2 was negatively correlated with the IL-17 signaling pathway, and positively associated with the tight junction, which led to abnormal immune cell infiltration and inflammatory injuries. After establishing the UC mice models in vivo by orally administration of DSS in portable water, SLC26A2 was significantly down-regulated at the mRNA or protein level, when compared to that in the control groups. Furthermore, the correlation analyses confirmed that SLC26A2 was positively associated with CLDN3, and negatively correlated with IL-17A expression in colon tissues. In addition, according to the SLC26A2 expression, UC patients were divided into different subgroups. The potential target drugs for UC treatment, such as progesterone, tetradioxin, and dexamethasone, were initially predicted and exerted anti-inflammatory effects via the common molecule-SLC26A2. Conclusions: SLC26A2 might be served as a protective candidate in the UC pathogenesis as well as a potential drug target for UC treatment. Full article
Show Figures

Figure 1

Figure 1
<p>The flowchart of the analysis process.</p>
Full article ">Figure 2
<p>Screening of potential UC-related molecules. (<b>A</b>) Selection of the soft threshold for WGCNA (GSE87466 and GSE109142). (<b>B</b>) The heatmaps indicated the correlations between modules and UC. Red boxes indicate that magenta module in GSE87466 and purple module in GSE109142 exhibited the strongest correlations with UC. (<b>C</b>) The scatterplots showed the relationships between gene significance and module membership in the magenta module of GSE87466 and purple module of GSE109142. (<b>D</b>) The volcano plots displayed all the DEGs. (<b>E</b>) The Venn diagram illustrates the overlapping genes.</p>
Full article ">Figure 3
<p>Validate the clinical significance of potential UC related molecules. (<b>A</b>,<b>B</b>) The boxplots illustrated the expressing levels of 3 UC-related molecules between healthy controls and UC samples in the GSE87466 (<b>A</b>) and GSE109142 (<b>B</b>) datasets, respectively. (<b>C</b>) The ABCB1, AQP8, and SLC26A2 mRNA expressions in our collected UC samples were also determined by the RT-PCR. (<b>D</b>) ROC curves were used to evaluate the potential usages and values of tissue-derived ABCB1, AQP8, and SLC26A2 as invasive biomarkers for UC diagnosis. (<b>E</b>–<b>H</b>) The Spearman correlation analyses revealed the possible relationships between 3 UC-related genes (ABCB1, AQP8, and SLC26A2) and some significant clinical characteristics, including the Mayo and PUCAI scores in UC samples from GSE109142, GSE92415, and our collected UC samples, respectively. (**** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 4
<p>Single gene GSEA analysis was conducted on SLC26A2. (<b>A</b>) The heatmaps displayed the top 30 up-regulated and 30 down-regulated genes in the high-SLC26A2 expressed groups, compared to the low-expressed groups. (<b>B</b>) The KEGG pathway enrichment analyzed the DEGs in the GSE87466 and GSE109142 datasets. (<b>C</b>) The GSEA implied that SLC26A2 was negatively associated with the IL-17 signaling pathway. (<b>D</b>) The barplots illustrated the top 50% of enriched pathways in the GSE87466 and GSE109142 datasets.</p>
Full article ">Figure 5
<p>According to the expressing levels of SLC26A2, ssGSEA of the IL-17 signaling pathway and immune cell clusters were performed in the GSE87466 and GSE109142 datasets, respectively. (<b>A</b>) The scores of the IL-17 signaling pathway were significantly lower in the high SLC26A2 expression group, compared to the low expression group. (<b>B</b>) A strong negative correlation between the SLC26A2 expressing levels and scores of the IL-17 signaling pathway was observed by the Spearman correlation analyses. (<b>C</b>) The boxplots illustrated the differences in immune infiltration between the high and low expression groups of SLC26A2. (<b>D</b>) The correlations between immune cell infiltration and SLC26A2 were also estimated. (**** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 6
<p>Localization analysis of SLC26A2 in single-cell sequencing data. (<b>A</b>–<b>D</b>) tSNE plots visualized the cell clusters, original identities, cell annotation, and localization of SLC26A2 in healthy controls and individuals with UC, respectively. (<b>E</b>) The distribution of SLC26A2 in cells with annotation was visualized as a violin plot. (<b>F</b>) Integrated map of the different numbers of interactions detected between each cell and other cells was presented. (<b>G</b>) Intensity demonstration of cell populations in different pathways in healthy controls and individuals with ulcerative colitis. (<b>H</b>) Differential signaling pathways in epithelial cells between healthy controls and individuals with UC revealed the diverse biological functions of epithelial cells.</p>
Full article ">Figure 7
<p>hdWGCNA revealed the potential biological functions of SLC26A2 at the level of single-cell RNA-seq. (<b>A</b>) The scale-free topology model displayed the scale-free fit index and the mean connectivity for various soft-thresholding powers. (<b>B</b>) The dendrogram illustrated illustrates the different modules in which genes are clustered. (<b>C</b>) The correlations between traits and modules were are shown in the correlation heatmap. (<b>D</b>) The KEGG pathways enriched by the genes in the brown module were listed, and the tight junction pathway (marked by a red box) was enriched. (<b>E</b>) The potential correlations among modules were calculated using the Pearson method. (<b>F</b>) Gene scores of the brown module were calculated using the UCell algorithm and presented in each cell. (<b>G</b>) The correlations between the genes involved in the tight junction in the brown module and SLC26A2 (as well as the IL-17 signaling pathway), were analyzed using the Spearman method. (<b>H</b>) Similar Spearman analyses were conducted between the genes involved in the tight junction in the brown module and immune cell subtypes. (*** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 8
<p>The relationship between SLC26A2 and tight junction genes. (<b>A</b>) The PPI network demonstrated the relationships among involved proteins, including SLC26A2, tight junction proteins, the IL-17 signaling pathway, and activated molecules in epithelial cells in UC. (<b>B</b>) The mRNA expressing levels of CFTR, CLDN3, CLDN7, MYL6, SLC26A3R1, and SLC26A2 were determined by the qRT-PCR. (<b>C</b>) The potential correlations between SLC26A2 and CFTR (CLDN3, CLDN7, MYL6, SLC26A3R1 and SLC26A2, respectively) were analyzed. (<b>D</b>) According to the expressing levels of SLC26A2 in GSE87466 and GSE109142 datasets, putative drugs were predicted, and the top 10 drugs were described. Progesterone CTD 00006624, tetradioxin CTD 00006848, and dexamethasone CTD 00005779 were highly co-enriched and indicated by the red, orange and blue boxes respectively. (** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001, and ns: no significance).</p>
Full article ">Figure 9
<p>The relationships between SLC26A2 and CLDN3 (or IL-17A) at mRNA levels in vivo. (<b>A</b>) Photos of mice colon in each group. (<b>B</b>) The colon length of mice on 7th day in the control and UC groups. (<b>C</b>,<b>D</b>) The colons were stained by H&amp;E, and the corresponding histological scores were compared. (<b>E</b>,<b>F</b>) The SLC26A2 mRNA expressions in each group were detected by qRT-PCR, and correlation analysis showed the potential relationships between SLC26A2 and histological scores. (<b>G</b>–<b>J</b>) The CLDN3 and IL-17A mRNA expressions in each group were also determined by qRT-PCR, and the relationships between SLC26A2 and CLDN3 (or IL-17A) were evaluated. (**** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 10
<p>The relationships between SLC26A2 and CLDN3 (or IL-17A) at protein levels in vivo. (<b>A</b>–<b>F</b>) The protein expressions of SLC26A2, CLDN3 and IL-17A in mice colon were determined by immunofluorescence, and the fluorescence quantification was compared. (<b>G</b>,<b>H</b>) Spearman–Pearson correlation between SLC26A2 and CLDN3 (or IL-17A) fluorescence intensity in mice was analyzed. (**** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">
17 pages, 2034 KiB  
Article
Comparative Outcomes of Adalimumab and Infliximab Dose Escalation in Inflammatory Bowel Disease Patients Failing First-Line Biologic Treatment
by Ali Atay, Yavuz Cagir, Mucahit Ergul, Oguz Ozturk, Muhammed Bahaddin Durak and Ilhami Yuksel
J. Clin. Med. 2025, 14(4), 1228; https://doi.org/10.3390/jcm14041228 - 13 Feb 2025
Abstract
Background/Objectives: Dose escalation has been commonly used to achieve and maintain response. We aimed to compare the outcomes of adalimumab or infliximab dose escalation in inflammatory bowel disease (IBD) patients. Methods: Treatment persistence (TP) and predictive factors for remission-free treatment discontinuation (r-fTD) were [...] Read more.
Background/Objectives: Dose escalation has been commonly used to achieve and maintain response. We aimed to compare the outcomes of adalimumab or infliximab dose escalation in inflammatory bowel disease (IBD) patients. Methods: Treatment persistence (TP) and predictive factors for remission-free treatment discontinuation (r-fTD) were evaluated in patients treated with adalimumab or infliximab dose escalation between 2019 and 2024. Results: Dose escalation was identified in 142 patients treated with adalimumab (UC: 23.9%; CD: 76.1%) and in 126 patients treated with infliximab (UC: 23.8%; CD: 76.2%). The TP rate was significantly lower in the adalimumab group (35.2%) than the infliximab group (53.2%) (p = 0.003). The survival analysis showed that drug persistence was lower in the adalimumab group compared with the infliximab group (mean time: 74.3 vs. 99.5 months, p < 0.001). TP rates showed no significant differences between UC and CD for both adalimumab (mean time UC: 64.7 months vs. CD: 76.2 months, p = 0.403) and infliximab (mean time UC: 80.3 months and CD: 102.6 months, p = 0.151). The r-fTD rates were significantly higher in the adalimumab group (62.7%) than the infliximab group (39.7%) (p < 0.001). Primary lack of response and secondary loss of response (sLOR) rates were both higher in the adalimumab group (7.7% and 51.4%) than the infliximab group (1.6% and 28.6%). However, serious adverse events were lower in the adalimumab group (2.1%) than the infliximab group (7.9%) (p = 0.027). Conclusions: Infliximab dose escalation was more effective than adalimumab in both UC and CD patients. Regarding the side effect profile, adalimumab dose escalation was found to be safer compared with infliximab. Full article
(This article belongs to the Special Issue Current Challenges in Inflammatory Bowel Diseases)
Show Figures

Figure 1

Figure 1
<p>Kaplan–Meier survival analysis for evaluating drug persistence in patients with inflammatory bowel disease. (<b>a</b>) The blue line shows the drug persistence rates for the patients receiving adalimumab, and the green line shows the drug persistence rates for those receiving infliximab. The drug persistence rate was significantly higher in patients receiving infliximab than receiving adalimumab (<span class="html-italic">p</span> &lt; 0.001). (<b>b</b>) The blue line shows the drug persistence rates of ulcerative colitis (UC) patients and the green line shows the drug persistence rates for Crohn’s disease (CD) patients receiving adalimumab. (<b>c</b>) The blue line shows the drug persistence rates for UC patients and the green line shows the drug persistence rates for CD patients receiving infliximab. There was no statistically significant difference in the drug persistence rate between UC and CD patients, nor between those receiving adalimumab or infliximab (<span class="html-italic">p</span> = 0.403 and <span class="html-italic">p</span> = 0.151, respectively).</p>
Full article ">
15 pages, 5216 KiB  
Article
Anomalous Diffusion and Decay of Clusters of Dopants in Lanthanide-Doped Nanocrystals
by Grzegorz Pawlik and Antoni C. Mitus
Materials 2025, 18(4), 815; https://doi.org/10.3390/ma18040815 - 13 Feb 2025
Abstract
Upconversion (UC) luminescence in doped lanthanide nanocrystals is associated with the energy migration (EM) process within clusters of dopant ions. The process of the synthesis of core–shell nanocrystals occurs at elevated temperatures, promoting the diffusion of the dopants into the shell accompanied by [...] Read more.
Upconversion (UC) luminescence in doped lanthanide nanocrystals is associated with the energy migration (EM) process within clusters of dopant ions. The process of the synthesis of core–shell nanocrystals occurs at elevated temperatures, promoting the diffusion of the dopants into the shell accompanied by the decay of dopant clusters. The details of this unwanted effect are poorly understood. In this paper, we theoretically study a model of the diffusion of dopant ions in a nanocrystal using Monte Carlo (MC) simulations. We characterize the diffusion, spatial neighboring relations and clustering of dopant ions regarding the function of reduced temperature and MC time of the heating process. The dopants undergo a weak subdiffusion caused by trapping effects. The main results of this study are as follows: (i) the phase diagram of the variables reduced the temperature and MC time, which separates the enhanced and limited cluster-driven EM regimes, and (ii) a dependence of the average nearest distance between Yb ions as a function of reduced temperature, the concentration of Yb ions and MC time was found. In both cases, the requirements for an effective EM are formulated. Full article
(This article belongs to the Special Issue Development and Research on Theoretical Chemistry in Materials)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Visualization of the geometry of the core–shell nanocrystal. <math display="inline"><semantics> <mrow> <mi>D</mi> </mrow> </semantics></math> denotes the thickness of the shell. Red atoms represent ions Yb/Er in the initial state. (<b>b</b>) Potential energy diagram for the direct atom–atom exchange.</p>
Full article ">Figure 2
<p>The cell for Y atoms and possible directions of movements of a dopant atom for <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>R</mi> </mrow> <mrow> <mi>c</mi> </mrow> </msub> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> nm (<b>a</b>). Non-normalized histogram of nearest neighbors (Y atoms) of a dopant calculated for <math display="inline"><semantics> <mrow> <mi>R</mi> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math> nm (<b>b</b>). Cross-section of the nanocrystal with positions of Y atoms and 5% of dopant Yb atoms (red spheres) for the core with radius <math display="inline"><semantics> <mrow> <mi>R</mi> <mo>=</mo> <mn>2.5</mn> </mrow> </semantics></math> nm and the shell with thickness <math display="inline"><semantics> <mrow> <mi>D</mi> <mo>=</mo> <mn>2</mn> </mrow> </semantics></math> nm (<b>c</b>).</p>
Full article ">Figure 3
<p>Trajectory of a chosen dopant atom in core–shell system for 1000 MCS (<math display="inline"><semantics> <mrow> <msup> <mrow> <mi>T</mi> </mrow> <mrow> <mo>*</mo> </mrow> </msup> <mo>=</mo> <mn>0.4</mn> <mo>)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 4
<p>Exemplary trajectory of a dopant ion (red) in time interval of 1000 MCS and positions of 27,985 Y atoms (gray) (<b>a</b>). Unnormalized histogram of the first passage time for dopant atom to cross the surface of the nanocrystal (with the mean value <math display="inline"><semantics> <mrow> <mn>4.8</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math> MCS) for <math display="inline"><semantics> <mrow> <mi>R</mi> <mo>=</mo> <mn>8</mn> </mrow> </semantics></math> nm, <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>T</mi> </mrow> <mrow> <mo>*</mo> </mrow> </msup> <mo> </mo> </mrow> </semantics></math>= 0.4 (<b>b</b>).</p>
Full article ">Figure 5
<p>Temperature dependence of the exponent γ (red full circles) and linear fit (red line). The log–log plot of displacement <math display="inline"><semantics> <mrow> <msup> <mrow> <mfenced separators="|"> <mrow> <mo>∆</mo> <mi>r</mi> </mrow> </mfenced> </mrow> <mrow> <mn>2</mn> </mrow> </msup> <mfenced separators="|"> <mrow> <mi>t</mi> </mrow> </mfenced> </mrow> </semantics></math> and linear fits for the time interval <math display="inline"><semantics> <mrow> <mn>1.5</mn> <mo>&lt;</mo> <mi>l</mi> <mi>o</mi> <mi>g</mi> <mo>⁡</mo> <mfenced separators="|"> <mrow> <mi>t</mi> </mrow> </mfenced> <mo>&lt;</mo> <mn>3</mn> </mrow> </semantics></math> for <span class="html-italic">T</span>* = 0.15 (inset).</p>
Full article ">Figure 6
<p>The average number of nearest neighbors in a simple cubic lattice as a function of obstacle concentration (<b>a</b>) and the crossover from normal to anomalous diffusion (<b>b</b>,<b>c</b>).</p>
Full article ">Figure 7
<p>Plots of the upper boundary for the diffusion constant <math display="inline"><semantics> <mrow> <mover accent="true"> <mrow> <mi>D</mi> <mo> </mo> </mrow> <mo>~</mo> </mover> </mrow> </semantics></math> against temperature. Inset: time dependence of <math display="inline"><semantics> <mrow> <msup> <mrow> <mfenced separators="|"> <mrow> <mo>∆</mo> <mover accent="true"> <mrow> <mi>r</mi> </mrow> <mo stretchy="false">→</mo> </mover> </mrow> </mfenced> </mrow> <mrow> <mn>2</mn> </mrow> </msup> <mo>/</mo> <mo stretchy="false">(</mo> <mn>6</mn> <mi>t</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 8
<p>Plot of average distance <math display="inline"><semantics> <mrow> <mfenced open="&#x27E8;" close="&#x27E9;" separators="|"> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math> as a function of reduced temperature <span class="html-italic">T</span>* (<b>a</b>). Temporal dependence of <math display="inline"><semantics> <mrow> <mfenced open="&#x27E8;" close="&#x27E9;" separators="|"> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math> for a few dopant concentrations at <span class="html-italic">T</span>* = 0.4 (<b>b</b>).</p>
Full article ">Figure 9
<p>The dependence of <math display="inline"><semantics> <mrow> <mfenced open="&#x27E8;" close="&#x27E9;" separators="|"> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math> on time and temperature <span class="html-italic">T</span>* for the dopant concentration 20% (<b>a</b>) and 5% (<b>b</b>).</p>
Full article ">Figure 10
<p>The dependence of <math display="inline"><semantics> <mrow> <mfenced open="&#x27E8;" close="&#x27E9;" separators="|"> <mrow> <msub> <mrow> <mi>d</mi> </mrow> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> </mrow> </mfenced> </mrow> </semantics></math> on time and dopant concentration <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>c</mi> </mrow> <mrow> <mi>Y</mi> <mi>b</mi> </mrow> </msub> </mrow> </semantics></math> for <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>T</mi> </mrow> <mrow> <mi mathvariant="normal">*</mi> </mrow> </msup> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math> (<b>a</b>), <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>T</mi> </mrow> <mrow> <mi mathvariant="normal">*</mi> </mrow> </msup> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math> (<b>b</b>), <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>T</mi> </mrow> <mrow> <mi mathvariant="normal">*</mi> </mrow> </msup> <mo>=</mo> <mn>0.4</mn> </mrow> </semantics></math> (<b>c</b>).</p>
Full article ">Figure 11
<p>The distribution of sizes of Yb clusters for <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>c</mi> </mrow> <mrow> <mi>Y</mi> <mi>b</mi> </mrow> </msub> <mo>=</mo> <mn>10</mn> <mo>%</mo> </mrow> </semantics></math> (<b>a</b>) and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>c</mi> </mrow> <mrow> <mi>Y</mi> <mi>b</mi> </mrow> </msub> <mo>=</mo> <mn>40</mn> <mo>%</mo> </mrow> </semantics></math> (<b>b</b>). Connection/transfer probability between Yb ions. Vertical lines denote nearest distances between Yb ions (<b>c</b>). Temporal dependence of spatial distribution of Yb ions (<b>d</b>–<b>f</b>). Calculations were performed for <math display="inline"><semantics> <mrow> <msup> <mrow> <mi>T</mi> </mrow> <mrow> <mo>*</mo> </mrow> </msup> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>.</p>
Full article ">Figure 12
<p>The dependence of the threshold time <math display="inline"><semantics> <mrow> <mi mathvariant="normal">τ</mi> </mrow> </semantics></math> on reduced temperature; see text for more details.</p>
Full article ">Figure 13
<p>Total number <span class="html-italic">N</span>(<span class="html-italic">k</span>) of Er ions which have <span class="html-italic">k</span> (<span class="html-italic">k</span> = 0, …, 8) Yb ions as nearest neighbors, calculated for a few concentrations of Yb ions, and at chosen stages of dopant ion diffusion from the core into the shell. Calculations performed for <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>c</mi> </mrow> <mrow> <mi>E</mi> <mi>r</mi> </mrow> </msub> <mo>=</mo> <mn>5</mn> <mo>%</mo> </mrow> </semantics></math>.</p>
Full article ">
Back to TopTop