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Keywords = lens-free cell analyzer

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15 pages, 3100 KiB  
Article
Label-Free CD34+ Cell Identification Using Deep Learning and Lens-Free Shadow Imaging Technology
by Minyoung Baik, Sanghoon Shin, Samir Kumar, Dongmin Seo, Inha Lee, Hyun Sik Jun, Ka-Won Kang, Byung Soo Kim, Myung-Hyun Nam and Sungkyu Seo
Biosensors 2023, 13(12), 993; https://doi.org/10.3390/bios13120993 - 21 Nov 2023
Viewed by 2334
Abstract
Accurate and efficient classification and quantification of CD34+ cells are essential for the diagnosis and monitoring of leukemia. Current methods, such as flow cytometry, are complex, time-consuming, and require specialized expertise and equipment. This study proposes a novel approach for the label-free identification [...] Read more.
Accurate and efficient classification and quantification of CD34+ cells are essential for the diagnosis and monitoring of leukemia. Current methods, such as flow cytometry, are complex, time-consuming, and require specialized expertise and equipment. This study proposes a novel approach for the label-free identification of CD34+ cells using a deep learning model and lens-free shadow imaging technology (LSIT). LSIT is a portable and user-friendly technique that eliminates the need for cell staining, enhances accessibility to nonexperts, and reduces the risk of sample degradation. The study involved three phases: sample preparation, dataset generation, and data analysis. Bone marrow and peripheral blood samples were collected from leukemia patients, and mononuclear cells were isolated using Ficoll density gradient centrifugation. The samples were then injected into a cell chip and analyzed using a proprietary LSIT-based device (Cellytics). A robust dataset was generated, and a custom AlexNet deep learning model was meticulously trained to distinguish CD34+ from non-CD34+ cells using the dataset. The model achieved a high accuracy in identifying CD34+ cells from 1929 bone marrow cell images, with training and validation accuracies of 97.3% and 96.2%, respectively. The customized AlexNet model outperformed the Vgg16 and ResNet50 models. It also demonstrated a strong correlation with the standard fluorescence-activated cell sorting (FACS) technique for quantifying CD34+ cells across 13 patient samples, yielding a coefficient of determination of 0.81. Bland–Altman analysis confirmed the model’s reliability, with a mean bias of −2.29 and 95% limits of agreement between 18.49 and −23.07. This deep-learning-powered LSIT offers a groundbreaking approach to detecting CD34+ cells without the need for cell staining, facilitating rapid CD34+ cell classification, even by individuals without prior expertise. Full article
(This article belongs to the Section Biosensors and Healthcare)
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Figure 1

Figure 1
<p>(<b>a</b>) Blood samples from the bone marrow and peripheral blood were collected and separated using Ficoll density gradient centrifugation. (<b>b</b>) Mononuclear cell samples were separated from various cell types, including blasts. (<b>c</b>) Ficoll-separated samples were injected directly into a cell chip. (<b>d</b>) The cell chip was inserted into the Cellytics device, which recorded shadow images of the cells. (<b>e</b>) Cellytics rapidly classifies only cells in samples using a CD34+ marker. The identified CD34+ cells within the red circle is illustrated in the magnified yellow box.</p>
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<p>A schematic representation of the research process, divided into three main phases: sample preparation, dataset generation, and data analysis.</p>
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<p>Architecture of the customized AlexNet deep learning model for CD34+ cell classification. (<b>a</b>) Input cell images of size 30 × 30 pixels were resized to 50 × 50 pixels and (<b>b</b>) went through eight convolutional layers. (<b>c</b>) Hyperparameters used to train the modified customized AlexNet model.</p>
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<p>(<b>a</b>) Shadow image and corresponding gradient-weighted class activation mapping (Grad-CAM) heatmap of CD34+ cells. (<b>b</b>) Shadow image of a CD34+ cell with a PPD of 44.3. (<b>c</b>) Shadow image of a residual cell with a PPD of 96.3. (<b>d</b>) PPD distribution of 1929 bone marrow cells used to generate the training dataset. (<b>e</b>) Boxplot of PPD distribution of CD34+ cells.</p>
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<p>Performance of customized AlexNet model. (<b>a</b>) Training and validation accuracy, and (<b>b</b>) training and validation loss of customized AlexNet model with optimized hyperparameters. (<b>c</b>) Confusion matrix of the model for a test set of 2000 images. (<b>d</b>) Comparison of the customized AlexNet model with the VGG16 and ResNet50 models.</p>
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<p>(<b>a</b>) Correlation between the percentage of CD34+ cells measured by standard flow cytometry (FACS) and the customized AlexNet model using samples from 13 patients. (<b>b</b>) Bland−Altman for FACS and the customized AlexNet model.</p>
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16 pages, 1649 KiB  
Article
In Vitro Cytopathogenic Activities of Acanthamoeba T3 and T4 Genotypes on HeLa Cell Monolayer
by Rosnani Hanim Mohd Hussain, Mohamed Kamel Abdul Ghani, Naveed Ahmed Khan, Ruqaiyyah Siddiqui, Shafiq Aazmi, Hasseri Halim and Tengku Shahrul Anuar
Pathogens 2022, 11(12), 1474; https://doi.org/10.3390/pathogens11121474 - 5 Dec 2022
Cited by 1 | Viewed by 2000
Abstract
Amoebic keratitis and encephalitis are mainly caused by free-living amoebae of the genus Acanthamoeba, which consists of both pathogenic and nonpathogenic species. The global distribution, amphizoic properties and the severity of the disease caused by Acanthamoeba species have inspired the scientific community [...] Read more.
Amoebic keratitis and encephalitis are mainly caused by free-living amoebae of the genus Acanthamoeba, which consists of both pathogenic and nonpathogenic species. The global distribution, amphizoic properties and the severity of the disease caused by Acanthamoeba species have inspired the scientific community to put more effort into the isolation of Acanthamoeba, besides exploring the direct and indirect parameters that could signify a pathogenic potential. Therefore, this study was performed to characterize the pathogenic potential of Acanthamoeba isolated from contact lens paraphernalia and water sources in Malaysia. Various methodologies were utilized to analyze the thermotolerance and osmotolerance, the secretion level of proteases and the cytopathic effect of trophozoites on the cell monolayer. In addition, the in vitro cytopathogenicity of these isolates was assessed using the LDH-release assay. A total of 14 Acanthamoeba isolates were classified as thermo- and osmotolerant and had presence of serine proteases with a molecular weight of 45–230 kDa. Four T4 genotypes isolated from contact lens paraphernalia recorded the presence of serine-type proteases of 107 kDa and 133 kDa. In contrast, all T3 genotypes isolated from environmental samples showed the presence of a 56 kDa proteolytic enzyme. Remarkably, eight T4 and a single T3 genotype isolates demonstrated a high adhesion percentage of greater than 90%. Moreover, the use of the HeLa cell monolayer showed that four T4 isolates and one T3 isolate achieved a cytopathic effect in the range of 44.9–59.4%, indicating an intermediate-to-high cytotoxicity level. Apart from that, the LDH-release assay revealed that three T4 isolates (CL5, CL54 and CL149) and one T3 isolate (SKA5-SK35) measured an exceptional toxicity level of higher than 40% compared to other isolates. In short, the presence of Acanthamoeba T3 and T4 genotypes with significant pathogenic potential in this study reiterates the essential need to reassess the functionality of other genotypes that were previously classified as nonpathogenic isolates in past research. Full article
(This article belongs to the Special Issue Genomics and Epidemiology of Protozoan Parasites)
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Figure 1
<p>Zymography analysis of <span class="html-italic">Acanthamoeba</span> trophozoite lysate from contact lens paraphernalia and environmental isolates without protease inhibitor (lane 1) and pretreated with 1 mM PMSF (serine protease inhibitor) (lane 2). The molecular weight in kDa is indicated on the edge of each gel. Contact lens paraphernalia isolates: CL5, CL54, CL126, CL149 and CL176. Environmental isolate: SKA5-SK35.</p>
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<p>Inverted-light microscope image analysis of the interaction between HeLa cell line and <span class="html-italic">Acanthamoeba</span> trophozoites from the contact lens paraphernalia and environmental isolates. Images: The arrow shown in the images indicates: (<b>a</b>) The confluent monolayer appearance of the HeLa (ATCC CCL-2) cell line incubated for 24 h; (<b>b</b>) <span class="html-italic">Acanthamoeba</span> trophozoites adapting and attaching to the culture flask; (<b>c</b>,<b>d</b>) the coincubation between HeLa cell monolayer and trophozoites during the adhesion assays. Trophozoites were discovered in close proximity to the surface of epithelial cells as well as beneath the cell layer. Magnification in (<b>a</b>–<b>d</b>) was made at 20×.</p>
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<p>Crystal-violet stain that shows cytopathic effects (CPEs) of <span class="html-italic">Acanthamoeba</span> isolates over HeLa cell monolayer. Amoebae were incubated with HeLa cell line in 24-well plates for 24 h at 37 °C and their CPE was observed using the crystal-violet stain. Images: (<b>a</b>) HeLa cell control; (<b>b</b>,<b>c</b>) showing CPEs with up to 10% monolayer destruction; (<b>d</b>–<b>f</b>) represent CPEs with 10–50% monolayer destruction; (<b>g</b>,<b>h</b>) CPEs with 50–100% monolayer destruction; and (<b>i</b>) HeLa cells incubated with <span class="html-italic">Acanthamoeba castellanii</span> (ATCC 50492) (control strain of CPE). Images are representative of experiments performed in triplicate.</p>
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15 pages, 9166 KiB  
Article
Kaempferol and Its Glycoside Derivatives as Modulators of Etoposide Activity in HL-60 Cells
by Magdalena Kluska, Michał Juszczak, Jerzy Żuchowski, Anna Stochmal and Katarzyna Woźniak
Int. J. Mol. Sci. 2021, 22(7), 3520; https://doi.org/10.3390/ijms22073520 - 29 Mar 2021
Cited by 20 | Viewed by 2948
Abstract
Kaempferol is a polyphenol found in a variety of plants. Kaempferol exerts antitumor properties by affecting proliferation and apoptosis of cancer cells. We investigated whether kaempferol and its glycoside derivatives—kaempferol 3-O-[(6-O-E-caffeoyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P2), kaempferol 3-O-[(6-O-E-p-coumaroyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P5) and kaempferol 3-O-[(6-O-E-feruloyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P7), isolated from aerial parts [...] Read more.
Kaempferol is a polyphenol found in a variety of plants. Kaempferol exerts antitumor properties by affecting proliferation and apoptosis of cancer cells. We investigated whether kaempferol and its glycoside derivatives—kaempferol 3-O-[(6-O-E-caffeoyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P2), kaempferol 3-O-[(6-O-E-p-coumaroyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P5) and kaempferol 3-O-[(6-O-E-feruloyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P7), isolated from aerial parts of Lens culinaris Medik.—affect the antitumor activity of etoposide in human promyelocytic leukemia (HL-60) cells. We analyzed the effect of kaempferol and its derivatives on cytotoxicity, DNA damage, apoptosis, cell cycle progression and free radicals induced by etoposide. We demonstrated that kaempferol increases the sensitivity of HL-60 cells to etoposide but does not affect apoptosis induced by this drug. Kaempferol also reduces the level of free radicals generated by etoposide. Unlike kaempferol, some of its derivatives reduce the apoptosis of HL-60 cells (P2 and P7) and increase the level of free radicals (P2 and P5) induced by etoposide. Our results indicate that kaempferol and its glycoside derivatives can modulate the activity of etoposide in HL-60 cells and affect its antitumor efficacy in this way. Kaempferol derivatives may have the opposite effect on the action of etoposide in HL-60 cells compared to kaempferol. Full article
(This article belongs to the Section Molecular Toxicology)
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<p>Chemical structures of kaempferol and its derivatives isolated from <span class="html-italic">Lens culinaris</span> Medik. (<b>A</b>) Kaempferol; (<b>B</b>) kaempferol 3-O-[(6-O-E-caffeoyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P2); (<b>C</b>) kaempferol 3-O-[(6-O-E-p-coumaroyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P5); (<b>D</b>) kaempferol 3-O-[(6-O-E-feruloyl)-β-D-glucopyranosyl-(1→2)]-β-D-galactopyranoside-7-O-β-D-glucuropyranoside (P7).</p>
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<p>Viability of HL-60 cells determined by resazurin reduction assay after 24 h treatment with 1–10 µM etoposide (E) and 10-50 µg/mL kaempferol (K) (<b>A</b>), P2 (<b>B</b>), P5 (<b>C</b>) and P7 (<b>D</b>) derivatives. The figure shows mean results ± SD, <span class="html-italic">n</span> = 6; * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Morphological changes of human promyelocytic leukemia (HL-60) cells as examined by phase-contrast microscopy (magnification, ×200) after incubation with kaempferol and etoposide (<b>A</b>), kaempferol derivatives (<b>B</b>) or kaempferol derivatives and etoposide (<b>C</b>). Cells with fragmented nuclei (I) and enlarged cells (II).</p>
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<p>DNA damage, measured as the comet tail DNA (%) of HL-60 cells incubated for 2 h at 37 °C with P2 (<b>A</b>) and P5 (<b>B</b>) derivative (10–50 µg/mL) and 1 µM etoposide (E), analyzed by the alkaline comet assay. The figure shows mean results ± standard error of the mean (SEM), <span class="html-italic">n</span> = 100; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Representative pictures of comets obtained in the alkaline version of the comet assay after incubation of HL-60 cells with 10, 25 or 50 µg/mL P2 and P5 kaempferol derivatives and 1 µM etoposide (E). The figure also contains pictures of comets from negative control (Ctrl) and positive control (cells incubated with H<sub>2</sub>O<sub>2</sub> at 20 µM for 15 min on ice).</p>
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<p>Apoptosis measured by flow cytometry using a double staining of FITC Annexin V and propidium iodide in HL-60 cells incubated for 24 h at 37 °C with 5 µM etoposide (E) and 10 or 50 µg/mL kaempferol (K) (<b>A</b>), P2 (<b>B</b>), P5 (<b>C</b>) and P7 (<b>D</b>) derivatives. The cells incubated with 20 µM camptothecin (CAM) for 24 h at 37 °C were positive control. The figure shows mean results ± SD, <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05, 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Reactive oxygen species (ROS) level in HL-60 cells incubated for 24 h at 37 °C with 5 µM etoposide (E) and 10 µg/mL or 50 µg/mL kaempferol (K) (<b>A</b>), P2 (<b>B</b>), P5 (<b>C</b>) and P7 (<b>D</b>) derivatives. The cells incubated with 5 mM H<sub>2</sub>O<sub>2</sub> for 15 min at 37 °C were positive control. The figure shows mean results ± SD, <span class="html-italic">n</span> = 6; ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Representative photos of cells with 20 the fluorescence probe H<sub>2</sub>DCFH-DA after 24 h incubation at 37 °C with 5 µM etoposide (E) and 10 µg/mL or 50 µg/mL kaempferol (K). The figure also contains pictures of comets from negative control (Ctrl).</p>
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3400 KiB  
Article
A Field-Portable Cell Analyzer without a Microscope and Reagents
by Dongmin Seo, Sangwoo Oh, Moonjin Lee, Yongha Hwang and Sungkyu Seo
Sensors 2018, 18(1), 85; https://doi.org/10.3390/s18010085 - 29 Dec 2017
Cited by 17 | Viewed by 6184
Abstract
This paper demonstrates a commercial-level field-portable lens-free cell analyzer called the NaviCell (No-stain and Automated Versatile Innovative cell analyzer) capable of automatically analyzing cell count and viability without employing an optical microscope and reagents. Based on the lens-free shadow imaging technique, the NaviCell [...] Read more.
This paper demonstrates a commercial-level field-portable lens-free cell analyzer called the NaviCell (No-stain and Automated Versatile Innovative cell analyzer) capable of automatically analyzing cell count and viability without employing an optical microscope and reagents. Based on the lens-free shadow imaging technique, the NaviCell (162 × 135 × 138 mm3 and 1.02 kg) has the advantage of providing analysis results with improved standard deviation between measurement results, owing to its large field of view. Importantly, the cell counting and viability testing can be analyzed without the use of any reagent, thereby simplifying the measurement procedure and reducing potential errors during sample preparation. In this study, the performance of the NaviCell for cell counting and viability testing was demonstrated using 13 and six cell lines, respectively. Based on the results of the hemocytometer (de facto standard), the error rate (ER) and coefficient of variation (CV) of the NaviCell are approximately 3.27 and 2.16 times better than the commercial cell counter, respectively. The cell viability testing of the NaviCell also showed an ER and CV performance improvement of 5.09 and 1.8 times, respectively, demonstrating sufficient potential in the field of cell analysis. Full article
(This article belongs to the Special Issue Point of Care Sensors)
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Graphical abstract

Graphical abstract
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<p>Lens-free cell analyzer, NaviCell. (<b>a</b>) The optical part consists of a blue LED, a 300 μm pinhole for coherent illumination to a sample chip and a CMOS image sensor for acquiring images from the sample; (<b>b</b>) For convenient usability, a 5-in. touch display is mounted at the top of the device, which allows for the reporting of quantitative results and for viewing images of the samples without additional equipment. The NaviCell is operated by a proprietary program based on an Android system. Samples for analysis are prepared on a disposable chip which was developed to increase the shadow intensity of the cell.</p>
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<p>Concise workflow of the algorithm for the processing of the lens-free shadow image. The algorithm consists of binarized image, clustering, counting and viability analysis. Bottom pictures show how the original image is transformed at critical steps.</p>
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<p>Advantages of the NaviCell platform. (<b>a</b>) FOVs of the three different measurement methods used in the experiment are superimposed for easy comparison. Blue box shows the FOV of a hemocytometer, red box shows the FOV of the commercial cell counter and green box shows the FOV of the NaviCell; (<b>b</b>) To measure 10 μm beads with various concentrations, the average standard deviation of the hemocytometer (blue line), the commercial cell counter (red line) and the NaviCell (green line) are 2.3 × 10<sup>4</sup>, 2.1 × 10<sup>4</sup> and 1.1 × 10<sup>4</sup> beads/mL, respectively.</p>
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<p>Comparison of cell counting performance using 13 cell lines. (<b>a</b>) Cell counting results of the NaviCell and the conventional methods are analyzed for the A549, BT474, CHO, COS7, HELA, HL60, HT29, L929, MDA-MB-231, PC3, SK-BR-3, SWRC-GRO and U87 cell lines. Improved counting precision of the NaviCell is demonstrated in terms of (<b>b</b>) average ER values and (<b>c</b>) average CV values.</p>
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<p>Principle of viability analysis without reagent. (<b>a</b>) Lens-free shadow image of stained Raji cells; (<b>b</b>) Corresponding microscope image of (<b>a</b>); (<b>c</b>) Live and dead cell shadow images of six cell lines (BT474, L929, MDA-MB-231, THP-1, SWRC-G-R-O and U87) without staining; (<b>d</b>) The PPD is defined as a difference between the highest and lowest intensity of all pixels in a specific square area, enabling the analysis of cell viability without reagent. Note that the analysis with the NaviCell does not require any staining procedure intrinsically; however, <a href="#sensors-18-00085-f005" class="html-fig">Figure 5</a>a was inevitably acquired after the staining procedure in order to analyze the identical sample both with a microscope and the Navicell.</p>
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<p>Comparison of cell viability performance using six cell lines. (<b>a</b>–<b>f</b>) Concentrations of BT474, L929, MDA-MB-231, THP-1, SWRC-G-R-O and U87 cell lines, respectively, by dividing into total number of cells, number of dead cells and number of live cells; (<b>g</b>) Average ER of the total cell count, dead cell count and live cell count; (<b>h</b>) Average CV of the total cell count, dead cell count and live cell count.</p>
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2012 KiB  
Article
Plumbagin Suppresses α-MSH-Induced Melanogenesis in B16F10 Mouse Melanoma Cells by Inhibiting Tyrosinase Activity
by Taek-In Oh, Jeong-Mi Yun, Eun-Ji Park, Young-Seon Kim, Yoon-Mi Lee and Ji-Hong Lim
Int. J. Mol. Sci. 2017, 18(2), 320; https://doi.org/10.3390/ijms18020320 - 3 Feb 2017
Cited by 41 | Viewed by 12748
Abstract
Recent studies have shown that plumbagin has anti-inflammatory, anti-allergic, antibacterial, and anti-cancer activities; however, it has not yet been shown whether plumbagin suppresses alpha-melanocyte stimulating hormone (α-MSH)-induced melanin synthesis to prevent hyperpigmentation. In this study, we demonstrated that plumbagin significantly suppresses α-MSH-stimulated melanin [...] Read more.
Recent studies have shown that plumbagin has anti-inflammatory, anti-allergic, antibacterial, and anti-cancer activities; however, it has not yet been shown whether plumbagin suppresses alpha-melanocyte stimulating hormone (α-MSH)-induced melanin synthesis to prevent hyperpigmentation. In this study, we demonstrated that plumbagin significantly suppresses α-MSH-stimulated melanin synthesis in B16F10 mouse melanoma cells. To understand the inhibitory mechanism of plumbagin on melanin synthesis, we performed cellular or cell-free tyrosinase activity assays and analyzed melanogenesis-related gene expression. We demonstrated that plumbagin directly suppresses tyrosinase activity independent of the transcriptional machinery associated with melanogenesis, which includes micropthalmia-associated transcription factor (MITF), tyrosinase (TYR), and tyrosinase-related protein 1 (TYRP1). We also investigated whether plumbagin was toxic to normal human keratinocytes (HaCaT) and lens epithelial cells (B3) that may be injured by using skin-care cosmetics. Surprisingly, lower plumbagin concentrations (0.5–1 μM) effectively inhibited melanin synthesis and tyrosinase activity but do not cause toxicity in keratinocytes, lens epithelial cells, and B16F10 mouse melanoma cells, suggesting that plumbagin is safe for dermal application. Taken together, these results suggest that the inhibitory effect of plumbagin to pigmentation may make it an acceptable and safe component for use in skin-care cosmetic formulations used for skin whitening. Full article
(This article belongs to the Special Issue Nutrients and Phytochemicals for Skin Health)
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<p>Chemical structure and cytotoxicity of plumbagin. (<b>A</b>) Chemical structure of plumbagin; (<b>B</b>) toxicity of plumbagin in B16F10 mouse melanoma cells. Cells were incubated with 1, 2, 5, 10, 20 μM of plumbagin for 48 or 72 h. Values (left panel) represent mean ± SD of three independent experiments performed in duplicate; * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01. Crystal violet staining images are shown in the right panel.</p>
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<p>Effects of plumbagin on melanin production in B16F10 mouse melanoma cells. (<b>A</b>) Plumbagin suppressed α-MSH-induced melanin production. Cells were pre-incubated in the absence or presence of plumbagin for 1 h, following which α-MSH (0.2 mM) was added and the cells were incubated for 3 or 4 days. Color changes in the cultured medium are shown; (<b>B</b>) extracellular and (<b>C</b>) intracellular melanin content increased by α-MSH treatment alone and decreased when plumbagin treatment was also given. Cells were pre-incubated with arbutin (1 mM), kojic acid (0.2 mM), or plumbagin (0.5, 1 μM) for 1 h, and then further incubated with α-MSH (0.2 mM) for 3 or 4 days as indicated. Values represent means ± SD of three independent experiments performed in duplicate; # <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; 0.01.</p>
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<p>Plumbagin does not affect the transcriptional machinery and signal transduction cascade associated with melanogenesis. (<b>A</b>) Determination of time to mRNA expression associated with melanogenesis. Cells were incubated with 0.2 mM of α-MSH for indicated time periods, following which melanogenesis-related gene-specific mRNA expression level was measured. Values represent means ± SD of two independent experiments performed in triplicate; * <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>B</b>) effects of plumbagin on MITF and tyrosinase protein expression levels. B16F10 cells pre-incubated with plumbagin (0.25, 0.5, 1, 2 μM) were further incubated with 0.2 mM α-MSH. MITF and tyrosinase protein expression levels were measured via immunoblotting as described in the materials and methods section; (<b>C</b>) effect of plumbagin on MITF, TYR, and TYRP1 mRNA expression. B16F10 cells were incubated in the absence or presence of α-MSH and plumbagin (1, 2 μM) for 4 h (MITF mRNA) or 48 h (TYR and TYRP1 mRNA). MITF, TYR, and TYRP1 mRNA expression levels were measured using quantitative RT-PCR. Values represent means ± SD of three independent experiments performed in triplicate; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and NS (not significant); (<b>D</b>) regulatory effects of plumbagin on signal transduction proteins that participate in melanogenesis. Cells were pre-incubated with plumbagin for 1 h, and cells were then further incubated with α-MSH (0.2 mM) for 3 h. Indicated protein levels were measured via immunoblotting.</p>
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<p>Inhibitory effects of plumbagin on (<b>A</b>) cellular tyrosinase activity and (<b>B</b>) cell-free tyrosinase activity. Tyrosinase activity was determined by measuring <span class="html-small-caps">l</span>-DOPA oxidation to dopachrome, and this oxidation of <span class="html-small-caps">l</span>-DOPA was read using an absorbance reader at 475 nm; (<b>C</b>) antioxidants activity of plumbagin. DPPH scavenging activity was examined at indicated concentrations using plumbagin or vitamin C as a positive control. Values represent means ± SD of three independent experiments performed in triplicate; * <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; 0.05.</p>
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<p>Cytotoxic effects of plumbagin in B3 and HaCaT cells. (<b>A</b>) Cytotoxicity of plumbagin in B3 and HaCaT cells. Cells were incubated with various concentrations (1, 2, 5, 10, 20 μM) of plumbagin for 3 days. Values (left panel) represent means ± SD of three independent experiments performed in duplicate; ** <span class="html-italic">p</span> &lt; 0.01. Crystal violet staining images were shown (right panel); (<b>B</b>) plumbagin does not cause DNA damage and apoptosis in B3 and HaCaT cells. Cells were incubated with or without 2 μM of plumbagin for 3 days, and protein levels were then measured via immunoblotting.</p>
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<p>Proposed regulatory mechanism of plumbagin on suppression of melanin synthesis in melanocytes. The dotted line and white arrows indicate stimulating signals. The black T bar indicates inhibitory effect. α-MSH: alpha-melanocyte stimulating hormone; MC1R: melanocortin 1 receptor; PKA: protein kinase A; CREB: cAMP response element binding protein; MITF: micropthalmia-associated transcription factor; TYR: tyrosinase; TYRP1: tyrosinase-related protein 1; <span class="html-small-caps">l</span>-DOPA: <span class="html-small-caps">l</span>-3,4-dihydroxyphenylalanine.</p>
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