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12 pages, 1577 KiB  
Article
Understanding the Interaction of Röntgen Radiation Employed in Computed Tomography/Cone Beam Computed Tomography Investigations of the Oral Cavity by Means of Surface-Enhanced Raman Spectroscopy Analysis of Saliva
by Rareș-Mario Borșa, Valentin Toma, Melania-Teodora Nășcuțiu, Anca Onaciu, Ioana-Maria Colceriu-Șimon, Grigore Băciuț, Simion Bran, Cristian-Mihail Dinu, Florin Onișor, Gabriel Armencea, Carina Culic, Mihaela-Carmen Hedeșiu, Rareș-Ionuț Știufiuc and Mihaela-Felicia Băciuț
Sensors 2024, 24(24), 8021; https://doi.org/10.3390/s24248021 (registering DOI) - 16 Dec 2024
Viewed by 93
Abstract
The use of Raman spectroscopy, particularly surface-enhanced Raman spectroscopy (SERS), offers a powerful tool for analyzing biochemical changes in biofluids. This study aims to assess the modifications occurring in saliva collected from patients before and after exposure to cone beam computed tomography (CBCT) [...] Read more.
The use of Raman spectroscopy, particularly surface-enhanced Raman spectroscopy (SERS), offers a powerful tool for analyzing biochemical changes in biofluids. This study aims to assess the modifications occurring in saliva collected from patients before and after exposure to cone beam computed tomography (CBCT) and computed tomography (CT) imaging. SERS analysis revealed significantly amplified spectra in post-imaging samples compared to pre-imaging samples, with pronounced intensification of thiocyanate and opiorphin bands, which, together with proteins, dominated the spectra. The changes were more pronounced in the case of CT as compared to CBCT, probably due to the use of a high radiation dose in the case of the first-mentioned technique. These findings underscore the impact of CBCT and CT on salivary composition, highlighting the relevance of SERS as a sensitive method for detecting subtle molecular changes in biofluids post-radiation exposure. This study’s results emphasize the importance of monitoring biochemical markers in patients undergoing diagnostic imaging to better understand the systemic effects of ionizing radiation. Full article
(This article belongs to the Section Sensing and Imaging)
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<p>Mean SERS spectra of the CT batch before and after irradiation (green and red spectra represent the average of the analysis of the 12 samples), measured at a laser wavelength of 785 nm. The spectra represent the average of the 12 samples that were previously incubated with the substrate. NR- non-radiation and R- radiation. The magenta-colored peaks represent the most relevant ones that have been amplified after radiation. Refer to <a href="#app1-sensors-24-08021" class="html-app">Table S1</a> for details of tentative band assignment.</p>
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<p>Mean SERS spectra of the CBCT batch before and after irradiation (green and orange spectra represent the average of the analysis of the 14 samples), measured at a laser wavelength of 785 nm. The spectra represent the average of the 14 samples that were previously deposited on the substrate. The magenta-colored peaks represent the most relevant ones that have been amplified after radiation. Refer to <a href="#app1-sensors-24-08021" class="html-app">Table S1</a> for details of tentative band assignment.</p>
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19 pages, 5749 KiB  
Article
NEK2 Phosphorylates RhoGDI1 to Promote Cell Proliferation, Migration and Invasion Through the Activation of RhoA and Rac1 in Colon Cancer Cells
by Jeewon Lim, Yo-Sep Hwang, Jong-Tae Kim, Hyang-Ran Yoon, Hyo-Min Park, Jahyeong Han, Taeho Kwon, Kyung-Ho Lee, Hee-Jun Cho and Hee-Gu Lee
Cells 2024, 13(24), 2072; https://doi.org/10.3390/cells13242072 - 16 Dec 2024
Viewed by 136
Abstract
Rho guanine nucleotide dissociation inhibitor 1 (RhoGDI1) plays a critical role in regulating the activity of Rho guanosine triphosphatases (GTPases). Phosphorylation of RhoGDI1 dynamically modulates the activation of Rho GTPases, influencing cell proliferation and migration. This study explored the involvement of Never In [...] Read more.
Rho guanine nucleotide dissociation inhibitor 1 (RhoGDI1) plays a critical role in regulating the activity of Rho guanosine triphosphatases (GTPases). Phosphorylation of RhoGDI1 dynamically modulates the activation of Rho GTPases, influencing cell proliferation and migration. This study explored the involvement of Never In Mitosis A (NIMA)-related serine/threonine protein kinase 2 (NEK2) in phosphorylating RhoGDI1 and its implications in cancer cell behavior associated with tumor progression. We employed GST pull-down assays and immunoprecipitation to investigate the interaction between NEK2 and RhoGDI1. Truncation fragments identified the region of RhoGDI1 responsible for binding with NEK2. Phosphorylation assays determined the site of NEK2-mediated phosphorylation on RhoGDI1. Functional assays were conducted using overexpression of the RhoGDI1 substitution mutant to assess their impact on cancer cell behavior. NEK2 directly bound to RhoGDI1 and phosphorylated it at Ser174. This phosphorylation event facilitated cancer cell proliferation and motility by activating RhoA and Rac1. The RhoGDI1 aa 112–134 region was critical for the binding to NEK2. Disruption of the NEK2–RhoGDI1 interaction through overexpression of a RhoGDI1 truncated fragment (aa 112–134) led to diminished RhoGDI1 phosphorylation and RhoA/Rac1 activation induced by NEK2, resulting in reduced cancer cell proliferation and migration. Moreover, in vivo studies showed reduced tumor growth and lung metastasis when the NEK2–RhoGDI1 interaction was disrupted. This study indicates that NEK2 promotes the metastatic behaviors of cancer cells by activating RhoA and Rac1 by phosphorylating RhoGDI1. Full article
(This article belongs to the Collection Rho GTPases in Health and Disease)
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<p>NEK2 interacts with RhoGDI1 but not RhoGDI2. (<b>A</b>) HeLa cells were co-transfected with HA-tagged NEK2 and Flag-tagged RhoGDI1 or RhoGDI2. Cell lysates were subjected to immunoprecipitation using HA antibody, followed by Western blotting with HA and Flag antibodies. (<b>B</b>) GST pull-down assay was conducted using recombinant His-tagged NEK2 and GST-tagged RhoGDI1 or RhoGDI2. (<b>C</b>) Western blot analysis was performed to assess NEK2 and RhoGDI1 expression in human colon cancer cell lines. (<b>D</b>) Cell lysates from HT-29 and HCT116 were immunoprecipitated with either IgG or RhoGDI1 antibodies, followed by Western blot analysis using indicated antibodies.</p>
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<p>The requirement of the RhoGDI1 aa 112–134 region for its interaction with NEK2. (<b>A</b>) Schematic diagram of RhoGDI1 WT and 6 truncated fragments. (<b>B</b>,<b>C</b>) Purified GST-tagged RhoGDI1 WT or truncation fragments along with recombinant His-NEK2 were subjected to His pull-down assay. His pull-down samples were analyzed by WB using NEK2 and GST antibodies. (<b>D</b>) HCT116 cells were transfected with the mock vector or GFP-tagged RhoGDI1 aa 112–134 fragment. Cell lysates were immunoprecipitated with either IgG or RhoGDI1 antibodies, followed by Western blot analysis using indicated antibodies (left). Relative band intensities (NEK2/RhoGDI1) were quantified using Image J and shown as a graph (right). Quantitative data represent the mean ± S.D. (<span class="html-italic">n</span> = 3). ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>NEK2 phosphorylates RhoGDI1 at Ser174. (<b>A</b>) Purified His-RhoGDI1 were subjected to in vitro kinase assay with recombinant active NEK2 (+) or without NEK2 (−). Samples were then analyzed by WB using indicated antibodies. (<b>B</b>) Purified His-RhoGDI1 WT and substituted mutants (S34A, S96A, S101A, S174A and T7/91A) were subjected to in vitro kinase assay with recombinant active NEK2 (+) or without NEK2 (−), followed by WB analysis using indicated antibodies. The arrow indicates phosphorylated RhoGDI1. (<b>C</b>) DLD-1 cells were stably transfected with HA-NEK2. (<b>C</b>,<b>D</b>) DLD-1 and HCT116 cells were incubated with 50 nM of NCL 00017509 (NEK2 inhibitor) in serum-free media for 24 h, followed by WB analysis using indicated antibodies (left). Relative band intensities (p-RhoGDI1/RhoGDI1) were quantified using Image J and shown as a graph (right). (<b>E</b>) HCT116 cells stably expressing control shRNA or two NEK2 shRNAs were incubated in serum-free media for 24 h. Cell lysates were subjected to WB analysis using indicated antibodies (upper). Relative band intensities (p-RhoGDI1/RhoGDI1) (lower). (<b>F</b>) DLD-1 cells stably expressing mock or HA-NEK2 were transiently transfected with mock or GFP-RhoGDI1 aa 112–134 expressing vector. Cells were incubated in serum-free media for 24 h. Cell lysates were analyzed by WB using indicated antibodies (upper). Relative band intensities (p-RhoGDI1/RhoGDI1) (lower). (<b>G</b>) DLD-1 cells stably expressing mock or HA-NEK2 were incubated in serum-free media for 24 h. IP analysis was performed with DLD-1 cell lysates and a RhoGDI1 antibody, followed by WB analysis using indicated antibodies (upper). Relative band intensities (14-3-3 tau/RhoGDI1) (lower). Quantitative data represent the mean ± S.D. (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>NEK2 facilitates the activation of RhoA and Rac1 by interaction with RhoGDI1. (<b>A</b>) DLD-1 cells stably expressing mock or HA-NEK2 were incubated in serum-free media for 24 h. A pull-down assay was performed to assess the levels of active RhoA and Rac1/Cdc42, as described in the Materials and Methods Section (left). (<b>B</b>) DLD-1 cells stably expressing mock or HA-NEK2 were treated with 50 nM of NCL 00017509 in serum-free media for 24 h, followed by pull-down assay and WB analysis (left). (<b>C</b>) HCT116 cells stably expressing control shRNA or two NEK2 shRNAs were incubated in serum-free media for 24 h and subjected to pull-down assay and WB analysis (left). (<b>D</b>) HA-NEK2 expressing DLD-1 cells were stably transfected with mock or mCherry-RhoGDI1 aa 112–134 expressing vector. Cells were incubated in serum-free media for 24 h, followed by pull-down assay and WB analysis (left). Relative band intensities (GTP-RhoA/total RhoA) were measured by Image J and shown as a graph (right). Quantitative data represent the mean ± S.D. (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>NEK2 promotes migration and invasion of colon cancer cells by phosphorylating RhoGDI1. (<b>A</b>–<b>C</b>) HCT116 cells were incubated with 50 nM of NCL 00017509, NEK2 inhibitor. (<b>A</b>) The viability of treated cells was assessed using a WST-8 assay. The graph represents the relative percentages of proliferating cells compared to untreated control. (<b>B</b>) Cell migration was evaluated using wound-healing assay at indicated time point. Representative images of migrating cells obtained at 48 h after wound formation (left). Scale bar = 200 μm. The migration was quantified by calculating the cell-covered area using Image J (right). (<b>C</b>) Cells were incubated in serum-free media for 24 h and subjected to transwell invasion assay. Representative images (100×) of invading cells are shown on the left, and the relative percentages of invasion are presented on the right. (<b>D</b>,<b>E</b>) DLD-1 cells stably expressing mock or HA-NEK2 were transiently transfected with Flag-RhoGDI1 WT or Flag-RhoGDI1 S174A. (<b>D</b>) Cell migration was evaluated using wound-healing assay at indicated time point. Representative images of migrating cells are shown on the left, and the percentage of wound closure is depicted on the right. Scale bar = 200 μm. (<b>E</b>) Cells were incubated in serum-free media for 24 h and subjected to transwell invasion assay. Migrating or invading cells were shown in representative images (left) or the relative percentages of invasion (right). Quantitative data represent the mean ± S.D. (<span class="html-italic">n</span> = 3). ** <span class="html-italic">p</span> &lt; 0.01; NS, non-significant.</p>
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<p>Interaction of NEK2 with aa 112–134 on RhoGDI1 is crucial for promoting proliferation, migration and invasion of colon cancer cells. DLD-1 cells expressing mock or HA-NEK2 were stably transfected with mCherry or mCherry-RhoGDI1 aa 112–134. (<b>A</b>) Cells were subjected to WST-8 assay. The graph represents the relative percentages of proliferating cells. (<b>B</b>) Migration of indicated cells was evaluated by wound-healing assay at each time point. Representative images of migrating cells obtained at 24 h after wound formation (left). Scale bar = 200 μm. The migration was quantified by calculating the cell-covered area using Image J (right). (<b>C</b>) Cells were incubated in serum-free media for 24 h and then subjected to transwell invasion assay. Representative images (100×) of invading cells are displayed on the left, and the relative percentages of invasion are quantified on the right. Quantitative data represent the mean ± S.D. (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>NEK2 promotes tumor growth and metastasis of colon cancer through its association with RhoGDI1. (<b>A</b>–<b>D</b>) DLD-1 cells expressing either mCherry or mCherry-RhoGDI1 aa 112–134 with or without HA-NEK2 were subcutaneously inoculated into the mice (5 × 10<sup>6</sup>/mouse). (<b>A</b>) Representative image of the tumors from each group of mice. (<b>B</b>) Measurement of tumor weights. (<b>C</b>) Measurement of tumor volumes, following procedures described in the Materials and Methods Section. (<b>D</b>) Tumor sections of each mouse were stained with anti-Ki67 or anti-CD31 antibody to assess proliferation and angiogenesis, respectively. Scale bar = 500 μm. Insets display accumulation of Ki-67 or CD31. Scale bar = 100 µm. (<b>E</b>,<b>F</b>) Indicated DLD-1 were intravenously inoculated into the mice (2 × 10<sup>6</sup>/mouse). (<b>E</b>) Representative images of H&amp;E-stained lung tissues of the mice injecting DLD-1 cell lines. Scale bar = 500 μm. (<b>F</b>) The number of metastatic nodules was counted per lung tissue and represented in the scatter plots. Quantitative data represent the mean ± S.D. (<span class="html-italic">n</span> = 8). ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>The schematic diagram shows that NEK2 induces proliferation and metastatic behaviors of cells. The red arrows indicate increase.</p>
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11 pages, 3147 KiB  
Communication
Active Surface-Enhanced Raman Scattering Platform Based on a 2D Material–Flexible Nanotip Array
by Yong Bin Kim, Satyabrat Behera, Dukhyung Lee, Seon Namgung, Kyoung-Duck Park, Dai-Sik Kim and Bamadev Das
Biosensors 2024, 14(12), 619; https://doi.org/10.3390/bios14120619 (registering DOI) - 15 Dec 2024
Viewed by 420
Abstract
Two-dimensional materials with a nanostructure have been introduced as promising candidates for SERS platforms for sensing application. However, the dynamic control and tuning of SERS remains a long-standing problem. Here, we demonstrated active tuning of the enhancement factor of the first- and second-order [...] Read more.
Two-dimensional materials with a nanostructure have been introduced as promising candidates for SERS platforms for sensing application. However, the dynamic control and tuning of SERS remains a long-standing problem. Here, we demonstrated active tuning of the enhancement factor of the first- and second-order Raman mode of monolayer (1L) MoS2 transferred onto a flexible metallic nanotip array. Using mechanical strain, the enhancement factor of 1L MoS2/nanotip is modulated from 1.23 to 8.72 for 2LA mode. For the same mode, the SERS intensity is enhanced by ~31 times when silver nanoparticles of ~13 nm diameter are deposited on 1L MoS2/nanotip, which is tuned up to ~34 times by compressive strain. The change in SERS enhancement factor is due to the decrease (increase) in gap width as the sample is bent inwardly (outwardly). This is corroborated by FEM structural and electromagnetic simulation. We also observed significant control over mode peak and linewidth, which may have applications in biosensing, chemical detection, and optoelectronics. Full article
(This article belongs to the Special Issue Micro-nano Optic-Based Biosensing Technology and Strategy)
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<p><b>Flexible nanotip array.</b> (<b>a</b>) Schematic diagram of fabrication process of flexible nanotip array. SEM images of (<b>b</b>) low and (<b>c</b>) high aspect ratio Ag nanotip array fabricated by direct and angle deposition, respectively (scale bar: 100 nm). (<b>d</b>) Distribution of diameter and inter-tip gap of nanotip array sample.</p>
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<p><b>Surface-enhanced Raman scattering of 1L MoS<sub>2</sub> enabled by nanotip array.</b> (<b>a</b>) Optical microscope image of monolayer, bilayer (2L), and few-layer MoS<sub>2</sub> on nanotip array. Scale bar: 10 um. (<b>b</b>) Top view FESEM images of nanotip covered with 1L MoS<sub>2</sub>. Scale bar: 500 nm. (<b>c</b>) FEM simulation of field confinement in between nanotips of low (left) and high (right) aspect ratio. (<b>d</b>) Raman spectra of 1L MoS<sub>2</sub> on PET (left), low aspect ratio (middle), and high aspect ratio nanotips (right).</p>
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<p><b>Tunable SERS platform based on 1L MoS<sub>2</sub>/Nanotip.</b> (<b>a</b>) Schematic diagram describing tuning methodology of SERS of 1L MoS<sub>2</sub>/nanotip (top), strain-dependent Raman spectra of 1L MoS<sub>2</sub>/PET (middle), and 1L MoS<sub>2</sub>/nanotip (bottom). (<b>b</b>) Extracted strain-dependent Raman mode peak position, FWHM, intensity of 1L MoS<sub>2</sub>/PET, and 1L MoS<sub>2</sub>/nanotip. (<b>c</b>) FEM simulation of nanotip array showing stress concentration in between tips under inward bending. (<b>d</b>) Digital images of sample (left) and FEM simulation (right) of field confinement in between tips under inward bent (top), flat (middle), and outward bent (bottom) conditions (scale bar: 20 mm).</p>
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<p><b>Tunable SERS platform based on nanoparticles/1L MoS<sub>2</sub>/nanotip.</b> (<b>a</b>) Schematic diagram describing the tunable SERS platform based on nanoparticles/1L MoS<sub>2</sub>/nanotip. (<b>b</b>) SEM image of nanoparticle on nanotip sample (scale bar: 100 nm). (<b>c</b>) Compressive strain-induced Raman spectra of nanoparticles/1L MoS<sub>2</sub>/nanotip. (<b>d</b>) Extracted strain-dependent Raman mode peak position, FWHM, and intensity of nanoparticles/1L MoS<sub>2</sub>/nanotip.</p>
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<p><b>Active control of enhancement factors.</b> (<b>a</b>) Strain dependent enhancement factors of nanoparticle/1L MoS<sub>2</sub>/nanotip and 1L MoS<sub>2</sub>/nanotip. (<b>b</b>) Depth of modulation of enhancement factor. (<b>c</b>) Finite element simulation of 1L MoS<sub>2</sub>/nanotip for various inter-dot gap sizes. (<b>d</b>) Literature survey of enhancement factor of 1L MoS<sub>2</sub> and comparison with this work.</p>
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31 pages, 2779 KiB  
Review
Emerging Sensing Technologies for Liquid Biopsy Applications: Steps Closer to Personalized Medicine
by Panagiota M. Kalligosfyri, Eleni Lamprou and Despina P. Kalogianni
Sensors 2024, 24(24), 7902; https://doi.org/10.3390/s24247902 - 11 Dec 2024
Viewed by 312
Abstract
Liquid biopsy is an efficient diagnostic/prognostic tool for tumor-derived component detection in peripheral circulation and other body fluids. The rapid assessment of liquid biopsy techniques facilitates early cancer diagnosis and prognosis. Early and precise detection of tumor biomarkers provides crucial information about the [...] Read more.
Liquid biopsy is an efficient diagnostic/prognostic tool for tumor-derived component detection in peripheral circulation and other body fluids. The rapid assessment of liquid biopsy techniques facilitates early cancer diagnosis and prognosis. Early and precise detection of tumor biomarkers provides crucial information about the tumor that guides clinicians towards effective personalized medicine. Point-of-care-testing remains still a great challenge in cancer diagnostics. Liquid biopsy is a promising alternative to tissue biopsy with the great advantages of less invasion and real-time monitoring of the disease, also providing information about tumor heterogeneity. The field is continuously and rapidly expanding. Numerous sophisticated biosensors have been developed targeting several biomarkers to achieve low detection limits, increased specificity and robustness. Current biosensors include mainly optical sensors, such as colorimetric, fluorescent, SPR, SERS and lateral flow assays. Electrochemical sensors have also been developed, providing very low detection limits. Colorimetric sensors exhibited simplicity in signal interpretation, while fluorescent sensors contributed to low analysis times, and SPR/SERS enabled label-free and rapid analysis. Novel target amplification and signal enhancement techniques have been exploited to increase the detectability of the sensors. In this context, this review is focused on the recent advances in biosensing technology for cutting-edge liquid biopsy applications towards point-of-care testing. Full article
(This article belongs to the Special Issue Feature Review Papers in Biosensors Section 2024)
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<p>Overview of sensors for cutting-edge liquid biopsy applications.</p>
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<p>A colorimetric sensor for the detection of exosomes based on AuNP aggregation after aptamer-based capturing of exosomes, TdT elongation of the aptamers and NaCl addition [<a href="#B16-sensors-24-07902" class="html-bibr">16</a>].</p>
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<p>An SPR sensor based on polystyrene beads with a Ag/Au layer for signal enhancement coupled to antibodies for specific detection of neuron-specific enolase [<a href="#B38-sensors-24-07902" class="html-bibr">38</a>].</p>
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<p>A CRISPR/Cas12a system based on AuNPs and dark-field microscopy (DFM) for detecting BRCA-1 mutations related to breast cancer. Meanshift and partial least-square algorithms were used for signal interpretation [<a href="#B45-sensors-24-07902" class="html-bibr">45</a>].</p>
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<p>Detection of exosomes through RCA using an aptamer specific for exosomes and dimer-G4/thioflavin-based fluorescence output [<a href="#B49-sensors-24-07902" class="html-bibr">49</a>].</p>
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<p>An overview of the sensors and biomarkers of interest that have emerged for cutting-edge liquid biopsy towards point-of-care testing.</p>
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13 pages, 2198 KiB  
Article
Study of Variation of ACOX1 Gene Among Different Horse Breeds Maintained in Iran
by Shayan Boozarjomehri Amnieh, Ali Hassanpour, Sina Moghaddam, Fatemeh Sakhaee and Katarzyna Ropka-Molik
Animals 2024, 14(24), 3566; https://doi.org/10.3390/ani14243566 - 10 Dec 2024
Viewed by 384
Abstract
The ACOX1 gene is vital for fatty acid metabolism and is linked to environmental stress and physical exertion adaptation. The p.Asp237Ser variant (rs782885985) in ACOX1 is associated with increased enzyme activity and reactive oxygen species (ROS) levels. This study examined the ACOX1 polymorphism [...] Read more.
The ACOX1 gene is vital for fatty acid metabolism and is linked to environmental stress and physical exertion adaptation. The p.Asp237Ser variant (rs782885985) in ACOX1 is associated with increased enzyme activity and reactive oxygen species (ROS) levels. This study examined the ACOX1 polymorphism across six horse breeds in Iran: Arabian, Thoroughbred, KWPN, Caspian, Kurdish, and Turkmen. The goal was to identify differences in ACOX1 genotype distribution, potentially serving as genetic markers under selection pressure related to breed-specific traits. In a sample of 324 horses, genomic DNA was analyzed using PCR-RFLP, revealing three genotypes (TT, TG, GG). The GG genotype was most common in Kurdish and Arabian horses (86% and 70%, respectively), while the TT genotype was prevalent in Turkmen (24%) and Thoroughbred horses (23%). The T allele’s frequency in Thoroughbred and Turkmen horses suggests that ACOX1 may be under selection pressure for phenotypic traits. Differences in genotype distribution were confirmed among breeds, with no sex-based association. The study concludes that ACOX1 is a potential genetic marker for horse performance and adaptability, emphasizing the importance of genetic diversity in breeding programs. Full article
(This article belongs to the Section Animal Genetics and Genomics)
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<p>(<b>a</b>) Arabian horse in Tabriz, Iran. This photograph was taken by the author Shayan Boozarjomehri Amnieh. (<b>b</b>) Kurdish horse in Marand, Iran. This photograph was taken by the author Sina Moghaddam. (<b>c</b>) Caspian horse in Anzali, Iran. This photograph was taken by the author Sina Moghaddam. (<b>d</b>) KWPN horse in Tehran, Iran. This photograph was taken by the author Shayan Boozarjomehri Amnieh. (<b>e</b>) Turkmen horse in Gonbad-e-Kavoos, Iran. This photograph was taken by the author Shayan Boozarjomehri Amnieh.</p>
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<p>The banding pattern observed on the 3% agarose gel after digestion with DdeI endonuclease confirms the genotypes as follows: GG genotype: A single band is visible at 342 bp, representing the undigested fragment. TG genotype: Three bands are visible at 342 bp, 197 bp, and 145 bp, indicating the presence of both alleles. TT genotype: Two bands are visible at 197 bp and 145 bp, as the 342 bp fragment is absent due to complete digestion.</p>
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<p>Distribution of ACOX1 genotypes by breed.</p>
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<p>Distribution of genotypes for mares vs. stallions in Turkmen horses. The <span class="html-italic">Y</span>-axis represents percentages related to genotype.</p>
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<p>Localization of SNP- Acyl-coenzyme A oxidase, N-terminal domain. The phylogenetic analysis of ENSECAP00000020757.3:p.Ser80Ala (rs782885985) polymorphisms across different species: the exact localization of mutation site in the gene, transcript ((<b>A</b>), Ensembl database) and protein chain ((<b>C</b>), UniProtKB database); F6TRZ0 Equus Caballus reference); the conservation analysis of rs782885985 SNP across species ((<b>B</b>), Ensembl database).</p>
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15 pages, 6275 KiB  
Article
O-GlcNAcylation of Focal Adhesion Kinase Regulates Cell Adhesion, Migration, and Proliferation via the FAK/AKT Pathway
by Zhiwei Zhang, Tomoya Isaji, Yoshiyuki Oyama, Jianwei Liu, Zhiwei Xu, Yuhan Sun, Tomohiko Fukuda, Haojie Lu and Jianguo Gu
Biomolecules 2024, 14(12), 1577; https://doi.org/10.3390/biom14121577 - 10 Dec 2024
Viewed by 517
Abstract
Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase pivotal in cellular signal transduction, regulating cell adhesion, migration, growth, and survival. However, the regulatory mechanisms of FAK during tumorigenesis and progression still need to be fully understood. Our previous study demonstrated that O [...] Read more.
Focal Adhesion Kinase (FAK) is a non-receptor tyrosine kinase pivotal in cellular signal transduction, regulating cell adhesion, migration, growth, and survival. However, the regulatory mechanisms of FAK during tumorigenesis and progression still need to be fully understood. Our previous study demonstrated that O-GlcNAcylation regulates integrin-mediated cell adhesion. To further elucidate the underlying molecular mechanism, we focused on FAK in this study and purified it from 293T cells. Using liquid chromatography–mass spectrometry (LC-MS/MS), we identified the O-GlcNAcylation of FAK at Ser708, Thr739, and Ser886. Compared with wild-type FAK expressed in FAK-knockout 293T cells, the FAK mutant, in which Ser708, Thr739, and Ser886 were replaced with Ala, exhibited lower phosphorylation levels of Tyr397 and AKT. Cell proliferation and migration, assessed through MTT and wound healing assays, were significantly suppressed in the FAK mutant cells compared to the wild-type FAK cells. Additionally, the interaction among FAK, paxillin, and talin was enhanced, and cell adhesion was increased in the mutant cells. These data indicate that specific O-GlcNAcylation of FAK plays a critical regulatory role in integrin-mediated cell adhesion and migration. This further supports the idea that O-GlcNAcylation is essential for tumorigenesis and progression and that targeting the O-GlcNAcylation of FAK could offer a promising therapeutic strategy for cancer treatment. Full article
(This article belongs to the Section Biomacromolecules: Carbohydrates)
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<p>Established <span class="html-italic">O</span>-GlcNAcylation KD 293T cell model and confirmed FAK modification by <span class="html-italic">O</span>-GlcNAc. (<b>A</b>) A schematic diagram illustrating the catalytic reaction of <span class="html-italic">O</span>-GlcNAcylation. (<b>B</b>) <span class="html-italic">OGT</span> KD 293T cells described in the Materials and Methods were treated with 5 μg/mL of DOX for 72 h, with an untreated group as the control. OGT levels were detected through immunoblot. Tubulin was a loading control. Western blot original images can be found in <a href="#app1-biomolecules-14-01577" class="html-app">Figure S1</a>. (<b>C</b>) The <span class="html-italic">O</span>-GlcNAcylation levels in cell lysates of DOX-dependent <span class="html-italic">OGT</span> KD 293T cells were validated by the anti-<span class="html-italic">O</span>-GlcNAcylation antibody. CBB staining was performed as a loading control. (<b>D</b>) VSV-G-tagged FAK was transfected into both control and KD cells. Further immunoprecipitation of cell lysates was performed using a VSV-G antibody, followed by immunoblotting to detect the <span class="html-italic">O</span>-GlcNAcylation levels of VSV-G-tagged FAK.</p>
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<p>Identification of <span class="html-italic">O</span>-GlcNAcylation sites on FAK through LC-MS/MS. (<b>A</b>) VSV-G-tagged mouse FAK was transfected into 293T cells, and cell lysates were subjected to immunoprecipitation and separated using 7.5% SDS-PAGE gel. The FAK-VSV-G band (red dashed line) was cut off for LC-MS analysis. (<b>B</b>) The sites for determining FAK <span class="html-italic">O</span>-GlcNAcylation were mapped using MS to detect <span class="html-italic">O</span>-GlcNAcylation sites on FAK. <span class="html-italic">O</span>-GlcNAcylation peptides were analyzed through LC-MS/MS. Analysis with the Byonic software identified <span class="html-italic">O</span>-GlcNAcylation on three peptides, as indicated. The Ser708, Thr739, and Ser886 sites were marked in red. The phosphorylation site at Ser722 was also detected and shown in red. (<b>C</b>) Sequence alignments of FAK at Ser708, Thr739, and Ser886, along with adjacent sequences from different species with conserved serine/threonine residues, were highlighted in red. (<b>D</b>) Schematic representation of the wild-type and mutant plasmids utilized in this study. From the N-terminus to the C-terminus are the FERM domain, the kinase domain, the FAT domain, and the GFP tag, where the three black bars represent three proline-rich regions (PRR1, PRR2, PRR3). The MUT indicates that the Ser or Thr at Ser708, Thr739, and Ser886 sites were replaced with Ala through site-directed mutagenesis.</p>
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<p>Influences of <span class="html-italic">O</span>-GlcNAcylation on FAK in the mutant. Cell lysates were extracted from 293T and 293T FAK-KO cells and analyzed through Western blotting with anti-FAK or anti-<span class="html-italic">O</span>-GlcNAc antibodies to detect FAK (<b>A</b>) and <span class="html-italic">O</span>-GlcNAc modification levels (<b>B</b>). α-Tubulin or CBB staining was used as the loading control. (<b>C</b>,<b>D</b>) Wild-type (WT) and mutant (MUT) FAK plasmids were transfected into the 293T FAK-KO cells, and the expression levels of FAK and <span class="html-italic">O</span>-GlcNAcylation were Western blotted with anti-FAK (<b>C</b>) or anti-<span class="html-italic">O</span>-GlcNAc antibodies (<b>D</b>). α-Tubulin or CBB staining as the loading control. (<b>E</b>) Cell lysates were immunoprecipitated using anti-GFP magnetic beads, followed by Western blotting with anti-<span class="html-italic">O</span>-GlcNAc and anti-GFP antibodies. The relative ratio of <span class="html-italic">O</span>-GlcNAcylated FAK to total FAK was normalized to 1.0. Experiments were independently repeated at least three times. Values represent mean ± SD. *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effects of FAK <span class="html-italic">O</span>-GlcNAcylation on cell adhesion, migration and proliferation. (<b>A</b>) Equal numbers of WT and MUT cells were seeded into FN-coated 96-well plates for 30 min. Non-adherent cells were washed using PBS. The adhered cells were then fixed with 4% paraformaldehyde and stained with DAPI for nuclear visualization. Representative fields were captured using a fluorescence microscope, and cells were counted. Scale bar, 200 μm. Values represent the mean ± SD (<span class="html-italic">n</span> = 5). *** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) Transfected cells were seeded into six-well plates. When the cells reached over 90% confluence, a 200 μL pipette tip was used to scratch each well to create a wound. Images were taken at 0 and 48 h using a phase-contrast microscope. Migration distances were evaluated using ImageJ. Experiments were independently repeated three times. Scale bar, 200 μm. Values represent the mean ± SD (<span class="html-italic">n</span> = 3). *** <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>) Transfected WT and MUT cells were cultured in DMEM with 5% FBS and seeded into 96-well plates. At designated time points (24, 48, 72 h), cell numbers were measured using the MTT assay. Experiments were independently repeated three times. Values represent the mean ± SD (<span class="html-italic">n</span> = 05); * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effects of FAK <span class="html-italic">O</span>-GlcNAcylation on cellular signaling and complex formation in FAs. (<b>A</b>) Cell lysates were subjected to Western blot analysis using the indicated antibodies to detect phosphorylated Tyr397-FAK, total FAK, p-ERK, total ERK, p-JNK, total JNK, and phosphorylated Akt and total Akt expression levels. The relative expression level of each phosphorylated form vs. the total form was calculated using ImageJ software 1.51o based on the intensity of the phosphorylated form relative to the total form. Values represent mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) Western blot analysis used the indicated antibodies to detect paxillin and talin expression levels in cell lysates. α-tubulin was used as the loading control. (<b>C</b>) Cell lysates were immunoprecipitated using anti-GFP magnetic beads. The immunoprecipitates were Western blotted with the indicated antibodies to detect paxillin and talin levels. Experiments were independently repeated at least three times. The ratio of paxillin or talin intensity vs. the total GFP-FAK in 293T FAK-KO cells expressing WT FAK was 1.0. Experiments were independently repeated at least three times. Values represent mean ± SD. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01. ns, no significance.</p>
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<p>Schematic working model for regulating FAK-mediated cellular signaling and cell behaviors by <span class="html-italic">O</span>-GlcNAcylation. In normal conditions, integrin-mediated cell adhesion upregulates Tyr397 phosphorylation of FAK and downstream signaling, which induces appropriate cell adhesion to promote cell migration and proliferation. Ablation of <span class="html-italic">O</span>-GlcNAcylation on the three sites of FAK decreases its Tyr397 phosphorylation. It enhances FA formation through the upregulation of FAK, talin, and paxillin complex formation, which in turn suppresses cell migration and proliferation.</p>
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14 pages, 769 KiB  
Article
Speech Emotion Recognition Using Multi-Scale Global–Local Representation Learning with Feature Pyramid Network
by Yuhua Wang, Jianxing Huang, Zhengdao Zhao, Haiyan Lan and Xinjia Zhang
Appl. Sci. 2024, 14(24), 11494; https://doi.org/10.3390/app142411494 - 10 Dec 2024
Viewed by 377
Abstract
Speech emotion recognition (SER) is important in facilitating natural human–computer interactions. In speech sequence modeling, a vital challenge is to learn context-aware sentence expression and temporal dynamics of paralinguistic features to achieve unambiguous emotional semantic understanding. In previous studies, the SER method based [...] Read more.
Speech emotion recognition (SER) is important in facilitating natural human–computer interactions. In speech sequence modeling, a vital challenge is to learn context-aware sentence expression and temporal dynamics of paralinguistic features to achieve unambiguous emotional semantic understanding. In previous studies, the SER method based on the single-scale cascade feature extraction module could not effectively preserve the temporal structure of speech signals in the deep layer, downgrading the sequence modeling performance. To address these challenges, this paper proposes a novel multi-scale feature pyramid network. The enhanced multi-scale convolutional neural networks (MSCNNs) significantly improve the ability to extract multi-granular emotional features. Experimental results on the IEMOCAP corpus demonstrate the effectiveness of the proposed approach, achieving a weighted accuracy (WA) of 71.79% and an unweighted accuracy (UA) of 73.39%. Furthermore, on the RAVDESS dataset, the model achieves an unweighted accuracy (UA) of 86.5%. These results validate the system’s performance and highlight its competitive advantage. Full article
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<p>Functional diagram of SER system.</p>
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<p>The overview of proposed multi-scale feature pyramid network.</p>
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<p>Bottom-up pathway, where <math display="inline"><semantics> <mrow> <mi>k</mi> <mi>w</mi> </mrow> </semantics></math> denotes different kernel widths, and <math display="inline"><semantics> <mrow> <mi>C</mi> <mi>S</mi> <mi>A</mi> </mrow> </semantics></math> denotes convolutional self-attention.</p>
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<p>Backward fusion structure, where <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math> represents the attention score calculation function as shown in Equation (<a href="#FD1-applsci-14-11494" class="html-disp-formula">1</a>), and <math display="inline"><semantics> <msub> <mi>F</mi> <mi>i</mi> </msub> </semantics></math> denotes the feature of the <span class="html-italic">i</span>-th layer.</p>
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<p>Convolutional self-attention (CSA) framework. (<b>a</b>) vanilla CSA; (<b>b</b>) improved CSA.</p>
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<p>The number of audio samples corresponding to each emotional label in IEMOCAP.</p>
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<p>The number of audio samples corresponding to each emotional label in RAVDESS.</p>
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<p>The t-SNE visualization of the proposed framework. (<b>a</b>) MSFPN; (<b>b</b>) DRN.</p>
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10 pages, 2264 KiB  
Case Report
Expanding the Clinical Spectrum of CEP290 Variants: A Case Report on Non-Syndromic Retinal Dystrophy with a Mild Phenotype
by Anna Esteve-Garcia, Cristina Sau, Ariadna Padró-Miquel, Jaume Català-Mora, Cinthia Aguilera and Estefania Cobos
Genes 2024, 15(12), 1584; https://doi.org/10.3390/genes15121584 - 9 Dec 2024
Viewed by 455
Abstract
Background/Objectives: Biallelic pathogenic variants in the CEP290 gene are typically associated with severe, early-onset inherited retinal dystrophies (IRDs) in both syndromic and non-syndromic forms. This study explores the phenotypic variability of non-syndromic IRDs associated with CEP290 variants, focusing on two siblings with [...] Read more.
Background/Objectives: Biallelic pathogenic variants in the CEP290 gene are typically associated with severe, early-onset inherited retinal dystrophies (IRDs) in both syndromic and non-syndromic forms. This study explores the phenotypic variability of non-syndromic IRDs associated with CEP290 variants, focusing on two siblings with biallelic variants, one of whom exhibits a remarkably mild phenotype, thereby expanding the clinical spectrum. Methods: Whole-exome sequencing (WES) and mRNA analysis were performed to identify and characterize CEP290 variants in the siblings. Comprehensive ophthalmologic evaluations assessed retinal function and disease progression. Results: Two CEP290 variants, a frameshift (c.955del, p.(Ser319LeufsTer16)) and a missense (c.5777G>C, p.(Arg1926Pro)), were identified in trans in both siblings. Despite sharing the same genetic variants, the sister exhibited significantly preserved retinal function, while the brother presented with a more severe, progressive retinal dystrophy. Conclusions: This study broadens the phenotypic spectrum of non-syndromic CEP290-related IRDs, demonstrating variability in disease severity ranging from mild to severe. These findings highlight the importance of personalized monitoring and tailored management strategies based on individual clinical presentations of CEP290-related IRDs. Full article
(This article belongs to the Section Genetic Diagnosis)
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<p>Family pedigree. Proband 1 is indicated by an arrow, and individuals with a clinical diagnosis of cone-rod dystrophy are shaded in black. Proband 2 has a 22-year-old asymptomatic daughter, and the affected siblings share a third sister who underwent a normal ophthalmological examination and remained unaffected. The family is of Spanish origin, with no other reported cases of ophthalmological diseases and no known consanguinity among relatives.</p>
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<p>Ultra-widefield autofluorescence (FAF) and optical coherence tomography (OCT) of both eyes in each sibling. (<b>A</b>) FAF image of proband 1, with blinking artifact in OD. (<b>B</b>) OCT of proband 1. (<b>C</b>) FAF image of proband 2. (<b>D</b>) OCT of proband 2 showing discontinuities in external retinal layers. OD, right eye; OS, left eye.</p>
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19 pages, 3637 KiB  
Article
Valorization of Hom Thong Banana Peel (Musa sp., AAA Group) as an Anti-Melanogenic Agent Through Inhibition of Pigmentary Genes and Molecular Docking Study
by Pichchapa Linsaenkart, Wipawadee Yooin, Supat Jiranusornkul, Korawan Sringarm, Chaiwat Arjin, Pornchai Rachtanapun, Kittisak Jantanasakulwong, Juan M. Castagnini and Warintorn Ruksiriwanich
Int. J. Mol. Sci. 2024, 25(23), 13202; https://doi.org/10.3390/ijms252313202 - 8 Dec 2024
Viewed by 601
Abstract
Prolonged and unprotected exposure to the environment explicitly influences the development of hyperpigmented lesions. The enzyme tyrosinase (TYR) is a key target for regulating melanin synthesis. Several bioactive compounds derived from plant extracts have been found to possess potent anti-melanogenesis properties against TYR. [...] Read more.
Prolonged and unprotected exposure to the environment explicitly influences the development of hyperpigmented lesions. The enzyme tyrosinase (TYR) is a key target for regulating melanin synthesis. Several bioactive compounds derived from plant extracts have been found to possess potent anti-melanogenesis properties against TYR. In particular, the potential of banana peels from various varieties has garnered interest due to their application in skin hyperpigmentation treatment. A molecular docking study demonstrated interactions between rosmarinic acid, which is predominantly found in all Hom Thong peel extracts, and the active site of TYR (PDB ID: 2Y9X) at residues HIS263, VAL283, SER282, and MET280, with the lowest binding energy of −5.05 kcal/mol, showing the strongest interaction. Additionally, Hom Thong banana peels are rich in phenolic compounds that could inhibit melanin content and tyrosinase activity in both human and mouse melanoma cells. These effects may be attributed to the suppression of gene expression related to melanogenesis, including the regulator gene MITF and pigmentary genes TYR, TRP-1, and DCT, indicating effects comparable to those of the standard treatment groups with arbutin and kojic acid. Our findings indicated the potential of Hom Thong peel extracts as anti-melanogenic agents. Full article
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<p>The molecular interaction profile of mushroom tyrosinase (PDB ID: 2Y9X) and the ligands after molecular docking studies binding poses of (<b>a</b>) L-tyrosine; (<b>b</b>) L-DOPA; (<b>c</b>) β-arbutin; and (<b>d</b>) kojic acid visualized by the BIOVIA Discovery Studio Visualizer.</p>
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<p>The molecular interaction profile of (<b>a</b>) 2D and (<b>b</b>) 3D structures of <span class="html-italic">(R)</span>-rosmarinic acid towards mushroom tyrosinase (PDB ID: 2Y9X) visualized by the BIOVIA Discovery Studio Visualizer and PyMOL, respectively.</p>
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<p>Effects of Hom Thong banana peel extracts on cell viability in (<b>a</b>) G361 human melanoma cells at 48 h; (<b>b</b>) B16 mouse melanoma cells at 48 h; (<b>c</b>) G361 human melanoma cells at 72 h; and (<b>d</b>) B16 mouse melanoma cells at 72 h. Data are expressed as the mean ± SD. Significant differences between samples are indicated by different letters (a, b, c, d, e, and f) with <span class="html-italic">p</span> &lt; 0.05. Ct: control, Water: aqueous extract of Hom Thong banana peel, 50EtOH: 50% ethanolic extract of Hom Thong banana peel, 95EtOH: 95% ethanolic extract of Hom Thong banana peel.</p>
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<p>Effects of Hom Thong banana peel extracts on cell viability in (<b>a</b>) G361 human melanoma cells at 48 h; (<b>b</b>) B16 mouse melanoma cells at 48 h; (<b>c</b>) G361 human melanoma cells at 72 h; and (<b>d</b>) B16 mouse melanoma cells at 72 h. Data are expressed as the mean ± SD. Significant differences between samples are indicated by different letters (a, b, c, d, e, and f) with <span class="html-italic">p</span> &lt; 0.05. Ct: control, Water: aqueous extract of Hom Thong banana peel, 50EtOH: 50% ethanolic extract of Hom Thong banana peel, 95EtOH: 95% ethanolic extract of Hom Thong banana peel.</p>
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<p>Effects of Hom Thong banana peel extracts and their bioactive compounds on (<b>a</b>) melanin content in G361 human melanoma cells; (<b>b</b>) melanin content in B16 mouse melanoma cells; (<b>c</b>) tyrosinase activity in G361 human melanoma cells; and (<b>d</b>) tyrosinase activity in B16 mouse melanoma cells. Figures of L-dopachrome formation in (<b>e</b>) G361 human melanoma cells and (<b>f</b>) B16 mouse melanoma cells. Data are expressed as the mean ± SD. Significant differences between samples are indicated by different letters (a, b, c, and d) with <span class="html-italic">p</span> &lt; 0.05. Water: aqueous extract of Hom Thong banana peel, 50EtOH: 50% ethanolic extract of Hom Thong banana peel, 95EtOH: 95% ethanolic extract of Hom Thong banana peel.</p>
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<p>Effects of Hom Thong banana peel extracts and their bioactive compounds on (<b>a</b>) melanin content in G361 human melanoma cells; (<b>b</b>) melanin content in B16 mouse melanoma cells; (<b>c</b>) tyrosinase activity in G361 human melanoma cells; and (<b>d</b>) tyrosinase activity in B16 mouse melanoma cells. Figures of L-dopachrome formation in (<b>e</b>) G361 human melanoma cells and (<b>f</b>) B16 mouse melanoma cells. Data are expressed as the mean ± SD. Significant differences between samples are indicated by different letters (a, b, c, and d) with <span class="html-italic">p</span> &lt; 0.05. Water: aqueous extract of Hom Thong banana peel, 50EtOH: 50% ethanolic extract of Hom Thong banana peel, 95EtOH: 95% ethanolic extract of Hom Thong banana peel.</p>
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<p>Effects of Hom Thong banana peel extracts and their bioactive compounds on relative gene expression of (<b>a</b>) <span class="html-italic">MITF</span> in G361 human melanoma cells; (<b>b</b>) <span class="html-italic">MITF</span> in B16 mouse melanoma cells; (<b>c</b>) <span class="html-italic">TYR</span> in G361 human melanoma cells; (<b>d</b>) <span class="html-italic">TYR</span> in B16 mouse melanoma cells; (<b>e</b>) <span class="html-italic">TRP-1</span> in G361 human melanoma cells; (<b>f</b>) <span class="html-italic">TRP-1</span> in B16 mouse melanoma cells; (<b>g</b>) <span class="html-italic">DCT</span> in G361 human melanoma cells; and (<b>h</b>) <span class="html-italic">DCT</span> in B16 mouse melanoma cells. Data are expressed as the mean ± SD. Significant differences between samples are indicated by different letters (a, b, and c) with <span class="html-italic">p</span> &lt; 0.05. Water: aqueous extract of Hom Thong banana peel, 50EtOH: 50% ethanolic extract of Hom Thong banana peel, 95EtOH: 95% ethanolic extract of Hom Thong banana peel.</p>
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<p>Effects of Hom Thong banana peel extracts and their bioactive compounds on relative gene expression of (<b>a</b>) <span class="html-italic">MITF</span> in G361 human melanoma cells; (<b>b</b>) <span class="html-italic">MITF</span> in B16 mouse melanoma cells; (<b>c</b>) <span class="html-italic">TYR</span> in G361 human melanoma cells; (<b>d</b>) <span class="html-italic">TYR</span> in B16 mouse melanoma cells; (<b>e</b>) <span class="html-italic">TRP-1</span> in G361 human melanoma cells; (<b>f</b>) <span class="html-italic">TRP-1</span> in B16 mouse melanoma cells; (<b>g</b>) <span class="html-italic">DCT</span> in G361 human melanoma cells; and (<b>h</b>) <span class="html-italic">DCT</span> in B16 mouse melanoma cells. Data are expressed as the mean ± SD. Significant differences between samples are indicated by different letters (a, b, and c) with <span class="html-italic">p</span> &lt; 0.05. Water: aqueous extract of Hom Thong banana peel, 50EtOH: 50% ethanolic extract of Hom Thong banana peel, 95EtOH: 95% ethanolic extract of Hom Thong banana peel.</p>
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<p>The scheme summarizes melanin biosynthesis.</p>
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18 pages, 2264 KiB  
Review
Advancements in Detection Methods for Salmonella in Food: A Comprehensive Review
by Aayushi Patel, Andrew Wolfram and Taseen S. Desin
Pathogens 2024, 13(12), 1075; https://doi.org/10.3390/pathogens13121075 - 7 Dec 2024
Viewed by 1016
Abstract
Non-typhoidal Salmonella species are one of the leading causes of gastrointestinal disease in North America, leading to a significant burden on the healthcare system resulting in a huge economic impact. Consequently, early detection of Salmonella species in the food supply, in accordance with [...] Read more.
Non-typhoidal Salmonella species are one of the leading causes of gastrointestinal disease in North America, leading to a significant burden on the healthcare system resulting in a huge economic impact. Consequently, early detection of Salmonella species in the food supply, in accordance with food safety regulations, is crucial for protecting public health, preventing outbreaks, and avoiding serious economic losses. A variety of techniques have been employed to detect the presence of this pathogen in the food supply, including culture-based, immunological, and molecular methods. The present review summarizes these methods and highlights recent updates on promising emerging technologies, including aptasensors, Surface Plasmon Resonance (SPR), and Surface Enhanced Raman Spectroscopy (SERS). Full article
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<p>Schematic illustration of aptamer-based electrochemical biosensor construction used for detection of <span class="html-italic">Salmonella</span>. GCE was modified with GO and GNPs for biocompatibility and high electron transfer properties. Then, thiolated aptamer ssDNA was attached to the surface, capable of capturing <span class="html-italic">Salmonella</span>. Created in BioRender. Wolfram, A. (2024) <a href="https://BioRender.com/r18r866" target="_blank">https://BioRender.com/r18r866</a> (accessed on 23 November 2024).</p>
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<p>Schematic representation of the detection of bacteria using the gold nanoparticle-aptamer-based localized surface plasmon resonance (SPR) sensing chip. Created in BioRender. Wolfram, A. (2024) <a href="https://BioRender.com/c38m504" target="_blank">https://BioRender.com/c38m504</a> (accessed on 5 December 2024).</p>
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<p>Schematic illustration of the CRISPR-SERS biosensor. DNA was extracted from <span class="html-italic">S.</span> Typhimurium and used to trigger the CRISPR system after binding with Cas12a-crRNA duplex for cleavage. The Raman signal reporter consists of ssDNA and Rox molecular which will be cleaved to decrease Raman intensity following wash out from SERS substrate. Without <span class="html-italic">S.</span> Typhimurium present, Cas12a/ccRNA would not initiate the cleavage activity of the probe, resulting in no detectable change in the Raman signal. Created in BioRender. Wolfram, A. (2024) <a href="https://BioRender.com/k99l567" target="_blank">https://BioRender.com/k99l567</a> (accessed on 23 November 2024).</p>
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<p>Schematic illustration of a bacteriophage detecting, infecting, and lysing bacteria like <span class="html-italic">Salmonella</span>. Created in BioRender. Wolfram, A. (2024) <a href="https://BioRender.com/g33l156" target="_blank">https://BioRender.com/g33l156</a> (accessed on 23 November 2024).</p>
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<p>A comparison of the Limits of Detection (LoD) across various technologies used for the Detection of <span class="html-italic">Salmonella</span> species. All LoDs were converted to CFU/mL from CFU/g using 1g to 1 mL conversion based on the density of water.</p>
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<p>A comparison of the total time required across various technologies used for the detection of <span class="html-italic">Salmonella</span> species. The average reported detection time for each method (including any enrichment time) was used to create this chart.</p>
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<p>Factoring both Limits of Detection (LoD) and total detection time (including enrichment) for comparison of the various detection methods of <span class="html-italic">Salmonella</span> species. Lower total values have lower LoDs and total detection times. All LoDs were converted to CFU/mL from CFU/g using 1 g to 1 mL conversion based on the density of water.</p>
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15 pages, 14402 KiB  
Article
Pheromone-Binding Protein 1 Performs a Dual Function for Intra- and Intersexual Signaling in a Moth
by Yidi Zhan, Jiahui Zhang, Mengxian Xu, Frederic Francis and Yong Liu
Int. J. Mol. Sci. 2024, 25(23), 13125; https://doi.org/10.3390/ijms252313125 - 6 Dec 2024
Viewed by 310
Abstract
Moths use pheromones to ensure intraspecific communication. Nevertheless, few studies are focused on both intra- and intersexual communication based on pheromone recognition. Pheromone-binding proteins (PBPs) are generally believed pivotal for male moths in recognizing female pheromones. Our research revealed that PBP1 of Agriphila [...] Read more.
Moths use pheromones to ensure intraspecific communication. Nevertheless, few studies are focused on both intra- and intersexual communication based on pheromone recognition. Pheromone-binding proteins (PBPs) are generally believed pivotal for male moths in recognizing female pheromones. Our research revealed that PBP1 of Agriphila aeneociliella (AaenPBP1) serves a dual function in both intra- and intersexual pheromone recognition. Here, a total of 20 odorant-binding protein (OBP) family genes from A. aeneociliella were identified and subjected to transcriptional analysis. Among these, AaenPBP1 was primarily highly expressed in the antennae. Competitive fluorescence binding assays and molecular docking analyses demonstrated that AaenPBP1 exhibits a strong binding affinity for the female sex pheromone (Z)-9-Hexadecenyl acetate and the male pheromone 1-Nonanal. Notably, hydrogen bonds were observed between Ser56 and the ligands. The analysis of pheromone components and PBPs in lepidopteran lineage suggested that their strong and precise interactions, shaped by coevolution, may play a crucial role in facilitating reproductive isolation in moths. Our findings provide valuable insight into the functional significance of PBPs in invertebrates and support the development of behavioral regulation tools as part of an integrated pest management strategy targeting crambid pests. Full article
(This article belongs to the Special Issue Molecular Signalling in Multitrophic Systems Involving Arthropods)
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<p>Multiple sequence alignment of <span class="html-italic">Agriphila aeneociliella</span> odorant-binding proteins (OBPs). Conserved amino acid residues are highlighted in black (highly conserved) and grayscale (moderately conserved). The asterisks indicate the count of amino acids.</p>
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<p>Phylogenetic analysis of odorant-binding proteins (OBPs) from <span class="html-italic">Agriphila aeneociliella</span> and other lepidopteran species. OBPs are categorized into subfamilies: typical OBPs (blue), Minus-C OBPs (green), Plus-C OBPs (red), and PBP/GOBP (yellow). Species abbreviations: Bmor (<span class="html-italic">Bombyx mori</span>), Slit (<span class="html-italic">Spodoptera littoralis</span>), Hvir (<span class="html-italic">Heliothis virescens</span>), Harm (<span class="html-italic">Helicoverpa armigera</span>), and Msex (<span class="html-italic">Manduca sexta</span>).</p>
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<p>MEME motif pattern analysis of <span class="html-italic">Agriphila aeneociliella</span> odorant-binding proteins (OBPs). The upper section illustrated the six motifs identified in lepidopteran OBPs, with each motif represented by a numbered box. The lower section displays the most commonly occurring motif patterns, with the numbers in the boxes corresponding to the motifs shown in the upper section.</p>
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<p>Transcript levels of odorant-binding protein (OBP) genes in various tissues of <span class="html-italic">Agriphila aeneociliella</span>. A: antennae; L: legs; Ab: abdomens. Data are presented as mean ± SE. Asterisks indicate statistically significant differences (*, <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).</p>
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<p>Competitive binding assays of AaenPBP1 to <span class="html-italic">Agriphila aeneociliella</span> male and female pheromones. (<b>a</b>) Binding curves and Scatchard plots of the probe 1-NPN to AaenPBP1 at pH 7.4 and 5.0. (<b>b</b>) Competitive binding properties of AaenPBP1 with female and male pheromones at pH 7.4 and 5.0. (<b>c</b>–<b>e</b>) Competitive binding curves of AaenPBP1 with six host-plant volatiles at pH 7.4 and 5.0: terpenoids (<b>c</b>), aldehyde (<b>d</b>), alcohols (<b>e</b>). (<b>f</b>) Comparison of the binding ability (1/Ki) of AaenPBP1 with three pheromones and six host-plant volatiles at pH 7.4 and 5.0.</p>
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<p>Sequence alignment of AaenPBP1 and AtraPBP1 pheromone-binding proteins. Conserved residues are highlighted, with the three disulfide bridges denoted by green numbers. The alignment highlights structural similarities between AaenPBP1 and the AtraPBP1 template (PDB ID: 4INW).</p>
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<p>Molecular interactions of AaenPBP1 with two female components and one male pheromone component. The 2D and 3D interaction diagrams illustrate the binding of AaenPBP1 with (Z)-9-Hexadecenyl acetate (<b>a</b>), (Z,Z,Z)-9,12,15-Octadecatrienal (<b>b</b>), and 1-Nonanal (<b>c</b>). Hydrogen bonds and hydrophobic interactions with specific amino acid residues are labeled. The distances of the hydrogen bonds are indicated in (<b>a</b>) and (<b>c</b>).</p>
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<p>Distribution of pheromones and phylogenetic analysis of PBPs in moths and butterflies. (<b>a</b>) The presence and utilization of three pheromones—(Z,Z,Z)-9,12,15-Octadecatrienal, (Z)-9-Hexadecenyl acetate, and 1-Nonanal—across moths and butterflies. “F” represents female sex pheromones, and “M” represents male sex pheromones. The tree topology follows Mitter et al. [<a href="#B21-ijms-25-13125" class="html-bibr">21</a>]. (<b>b</b>) Phylogenetic tree depicting the relationships of PBPs from various moths and butterflies, including <span class="html-italic">Agriphila aeneociliella</span>. Detailed information about the PBPs and pheromones for each species is provided in <a href="#app1-ijms-25-13125" class="html-app">Table S5</a>.</p>
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11 pages, 3743 KiB  
Article
Au Ordered Array Substrate for Rapid Detection and Precise Identification of Etomidate in E-Liquid Through Surface-Enhanced Raman Spectroscopy
by Yan Mo, Xiaoping Zhang, Ke Zou, Wen Xing, Xiayang Hou, Yu Zeng, Yugang Cai, Ruixiang Xu, Hongwen Zhang and Weiping Cai
Nanomaterials 2024, 14(23), 1958; https://doi.org/10.3390/nano14231958 - 6 Dec 2024
Viewed by 400
Abstract
Etomidate (ET), a medical anesthetic, is increasingly being incorporated into e-liquids for consumption and abuse as a new psychoactive substance (NPS), leading to significant social issues. In this work, large-area Au micro- and nano-structured ordered arrays were engineered as surface-enhanced Raman spectroscopy (SERS) [...] Read more.
Etomidate (ET), a medical anesthetic, is increasingly being incorporated into e-liquids for consumption and abuse as a new psychoactive substance (NPS), leading to significant social issues. In this work, large-area Au micro- and nano-structured ordered arrays were engineered as surface-enhanced Raman spectroscopy (SERS) substrates for fast detection and precise identification of ET and its metabolites. This ordered array, characterized by abundant electromagnetic enhancement hotspots and structural uniformity, imparts unique properties to the SERS substrate, including ultra-sensitivity, spectral signal reproducibility, and precise quantitative capabilities. Furthermore, it effectively mitigates interference from the complex matrix of e-liquids, facilitating the rapid detection of trace amounts of ET molecules. This SERS rapid detection technology can act as a preliminary screening method for gold-standard spectroscopic analysis, facilitating the on-site rapid screening of suspicious samples and thereby enabling efficient detection and precise verification. Full article
(This article belongs to the Special Issue Functional Nanomaterials for Sensing and Detection (2nd Edition))
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<p>Schematic diagram of template-based fabrication of Au micro- and nano-structured ordered arrays as sensitive SERS substrate for fast E-liquid detection and drug identification.</p>
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<p>(<b>A</b>) SEM image of the SERS substrate composed of Au ordered array. (<b>B</b>,<b>C</b>) The EDS analysis of the Au and Si elemental distribution in the SERS substrate. (<b>D</b>) The SEM cross-sectional observation of the substrate, along with the elemental distribution. (<b>E</b>) The theoretical simulation of the spatial electric field distribution of the structural unit of the array (sphere size 100 nm, gap distance 15 nm). (<b>F</b>) SERS spectra of 10<sup>−7</sup> M 4-MBA probe molecule and its spectral reproducibility. Each color curve corresponds to a spectrum acquisition point.</p>
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<p>(<b>A</b>) SERS spectrum of ET at a concentration of 10 ppm acquired from the Au nano-structured ordered array substrate. The comparison sample is Au nanoparticle (NP) film obtained by sputter deposition with identical parameters. (<b>B</b>) Theoretically simulated Raman spectrum of ET molecules, used to assign the characteristic vibrational peaks in the SERS spectrum.</p>
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<p>(<b>A</b>) Reproducibility of SERS spectra for 10 ppm ET molecules acquired from one substrate. (<b>B</b>) The intensity and relative standard deviation (RSD) of the vibrational peak at 1003 cm<sup>−1</sup> within and between SERS substrates. (<b>C</b>) SERS spectra of ET molecules with concentrations ranging from 1 to 50 ppm. (<b>D</b>) The linear relationship between the peak intensities at 618, 1003, and 1351 cm<sup>−1</sup> and the concentration.</p>
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<p>(<b>A</b>) SERS spectra of e-liquid oil and ET-containing sample with a concentration of 10 ppm. The dotted circle marks the most significant characteristic vibrational peaks that are exclusive to the ET molecule. (<b>B</b>) Spectral comparison of the SERS spectra of ET and its metabolite etomidate acid (ETA). The dotted cycles highlight the differences in the characteristic vibrational peaks of the two molecules.</p>
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4 pages, 1092 KiB  
Comment
Comment on Borșa et al. Developing New Diagnostic Tools Based on SERS Analysis of Filtered Salivary Samples for Oral Cancer Detection. Int. J. Mol. Sci. 2023, 24, 12125
by Ivan Bratchenko and Lyudmila Bratchenko
Int. J. Mol. Sci. 2024, 25(23), 13030; https://doi.org/10.3390/ijms252313030 - 4 Dec 2024
Viewed by 344
Abstract
This comment discusses a recent research paper on the classification of saliva samples with SERS by Borsa et al. The authors suggested utilizing PCA-LDA to detect oral cancer and claimed to achieve an accuracy of up to 77%. Despite the high prediction capability [...] Read more.
This comment discusses a recent research paper on the classification of saliva samples with SERS by Borsa et al. The authors suggested utilizing PCA-LDA to detect oral cancer and claimed to achieve an accuracy of up to 77%. Despite the high prediction capability of the proposed approach, the demonstrated findings could be treated as unclear due to possible overestimation of the proposed classification models. Data should be provided for both the training and the validation sets to make sure that there were no repeated data from the same sample in either set. Moreover, the authors proposed to measure opiorphin in saliva with SERS as a potential biomarker of oral cancer. However, opiorphin in saliva is contained in ng/mL concentrations, and the proposed technique is most likely not capable of recording the real concentration of opiorphin. Full article
(This article belongs to the Special Issue Pathogenesis and Therapy of Oral Carcinogenesis, 2nd Edition)
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<p>Example of utilizing RMSE for determining the number of PCs in the PLS-DA model for discriminating between a group of patients with kidney failure and a group of healthy volunteers in the analysis of human skin spectra (obtained with permission from the authors [<a href="#B17-ijms-25-13030" class="html-bibr">17</a>]).</p>
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<p>SERS spectrum of opiorphin, uric acid, hypoxanthine, and salivary control probes using the excitation wavelength of 785 nm (from Figure S5 in the commented paper [<a href="#B13-ijms-25-13030" class="html-bibr">13</a>]).</p>
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33 pages, 3010 KiB  
Review
Towards Point-of-Care Single Biomolecule Detection Using Next Generation Portable Nanoplasmonic Biosensors: A Review
by Saeed Takaloo, Alexander H. Xu, Liena Zaidan, Mehrdad Irannejad and Mustafa Yavuz
Biosensors 2024, 14(12), 593; https://doi.org/10.3390/bios14120593 - 4 Dec 2024
Viewed by 629
Abstract
Over the past few years, nanoplasmonic biosensors have gained widespread interest for early diagnosis of diseases thanks to their simple design, low detection limit down to the biomolecule level, high sensitivity to even small molecules, cost-effectiveness, and potential for miniaturization, to name but [...] Read more.
Over the past few years, nanoplasmonic biosensors have gained widespread interest for early diagnosis of diseases thanks to their simple design, low detection limit down to the biomolecule level, high sensitivity to even small molecules, cost-effectiveness, and potential for miniaturization, to name but a few benefits. These intrinsic natures of the technology make it the perfect solution for compact and portable designs that combine sampling, analysis, and measurement into a miniaturized chip. This review summarizes applications, theoretical modeling, and research on portable nanoplasmonic biosensor designs. In order to develop portable designs, three basic components have been miniaturized: light sources, plasmonic chips, and photodetectors. There are five types of portable designs: portable SPR, miniaturized components, flexible, wearable SERS-based, and microfluidic. The latter design also reduces diffusion times and allows small amounts of samples to be delivered near plasmonic chips. The properties of nanomaterials and nanostructures are also discussed, which have improved biosensor performance metrics. Researchers have also made progress in improving the reproducibility of these biosensors, which is a major obstacle to their commercialization. Furthermore, future trends will focus on enhancing performance metrics, optimizing biorecognition, addressing practical constraints, considering surface chemistry, and employing emerging technologies. In the foreseeable future, these trends will be merged to result in portable nanoplasmonic biosensors offering detection of even a single biomolecule. Full article
(This article belongs to the Special Issue Micro-nano Optic-Based Biosensing Technology and Strategy)
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<p>The schematic of SPR and evanescent waves. Evanescent waves occur at the metal-prism interface.</p>
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<p>Comparison between SPR and LSPR biosensors (<b>a</b>) SPR biosensors (<b>b</b>) LSPR biosensors.</p>
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<p>Portable NPBs, including portable SPR, miniaturization SPR components, flexible NPBs, wearable SERS-based designs, and microfluidic NPBs. (<b>A</b>) Spreeta 2000 plasmonic sensor, reproduced with permission. Ref. [<a href="#B76-biosensors-14-00593" class="html-bibr">76</a>], copyright 2003, Elsevier. (<b>B</b>) Gold-coated diffraction grating sensor chip integrated with microfluidics, reproduced with permission. Ref. [<a href="#B77-biosensors-14-00593" class="html-bibr">77</a>], copyright 2010, Elsevier. (<b>C</b>) Integrated quantum dot LED with plasmonic nanograting, reproduced with permission. Ref. [<a href="#B78-biosensors-14-00593" class="html-bibr">78</a>], copyright 2015, IOP Publishing Ltd. (<b>D</b>) Integration of array of gold nanodiscs to CMOS chip, reproduced with permission. Ref. [<a href="#B79-biosensors-14-00593" class="html-bibr">79</a>], copyright 2016, American Chemical Society. (<b>E</b>) Polymer integrated biosensing system, reproduced with permission. Ref. [<a href="#B83-biosensors-14-00593" class="html-bibr">83</a>], copyright 2010, John Wiley &amp; Sons. (<b>F</b>) Flexible LSPR biosensor based on AuNP/APTES/PDMS. reproduced with permission. Ref. [<a href="#B80-biosensors-14-00593" class="html-bibr">80</a>], under the CC-BY 4.0 license. (<b>G</b>) Wearable SERS biosensors based on gold nanostars for sweat monitoring. reproduced with permission. Ref. [<a href="#B81-biosensors-14-00593" class="html-bibr">81</a>], under the CC-BY 4.0 license. (<b>H</b>) Wearable SERS Sensor Based on Omnidirectional Plasmonic Nanovoids Array, reproduced with permission. Ref. [<a href="#B84-biosensors-14-00593" class="html-bibr">84</a>], copyright 2022, John Wiley &amp; Sons. (<b>I</b>) Wearable diaper sensor and handheld Raman spectrometer for urinalysis, reproduced with permission. Ref. [<a href="#B85-biosensors-14-00593" class="html-bibr">85</a>], copyright 2003, Elsevier. (<b>J</b>) Ultrathin wearable 3D particle-in-cavity SF-AAO-Au SERS biosensors for glucose and pesticide detection, reproduced with permission. Ref. [<a href="#B86-biosensors-14-00593" class="html-bibr">86</a>], copyright 2022, Elsevier. (<b>K</b>) Wearable microfluidic nanoplasmonic biosensor based on a miniature, thin plasmonic metasurface with homogeneous mushroom-shaped hot spots and high SERS activity, reproduced with permission. Ref. [<a href="#B87-biosensors-14-00593" class="html-bibr">87</a>], under the CC-BY 4.0 license. (<b>L</b>) Wearable SERS–based microfluidic system for sweat rate and sweat lose quantification, reproduced with permission. Ref. [<a href="#B88-biosensors-14-00593" class="html-bibr">88</a>], under the CC-BY 4.0 license. (<b>M</b>) Wearable and Flexible plasmonic biosensor based on SERS fingerprint analysis of chemical biomarkers, reproduced with permission. Ref. [<a href="#B89-biosensors-14-00593" class="html-bibr">89</a>], copyright 2022, Science Advances. (<b>N</b>) Wearable flexible SERS biosensors based on Au/TPU nanofibers, reprinted with permission from [<a href="#B90-biosensors-14-00593" class="html-bibr">90</a>]. Copyright 2021 American Chemical Society. (<b>O</b>) Flexible wearable plasmonic paper-based microfluidic SERS biosensor based on, reprinted with permission from [<a href="#B91-biosensors-14-00593" class="html-bibr">91</a>]. Copyright 2024 American Chemical Society. (<b>P</b>) wearable Janus fabric/grapefruit optical fiber embedded with Ag nanoparticles, reprinted with permission from [<a href="#B92-biosensors-14-00593" class="html-bibr">92</a>]. Copyright 2024 American Chemical Society.</p>
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<p>Miniaturized plasmonic nano-ring resonator sensor device with a fluid flow channel. Reprinted with permission from [<a href="#B105-biosensors-14-00593" class="html-bibr">105</a>]. Copyright 2017 American Chemical Society.</p>
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<p>The schematic of strategies to enhance reproducibility of NPBs.</p>
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<p>Potential applications of nanoplasmonic biosensors.</p>
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13 pages, 2989 KiB  
Article
Self-Assembled Lubricin (PRG-4)-Based Biomimetic Surface-Enhanced Raman Scattering Sensor for Direct Droplet Detection of Melamine in Undiluted Milk
by Mingyu Han, Mya Myintzu. Hlaing, Paul R. Stoddart and George W. Greene
Biosensors 2024, 14(12), 591; https://doi.org/10.3390/bios14120591 - 3 Dec 2024
Viewed by 513
Abstract
Surface-enhanced Raman scattering (SERS) is a powerful optical sensing platform that amplifies the target signals by Raman scattering. Despite SERS enabling a meager detection limit, even at the single-molecule level, SERS also tends to equally enhance unwanted molecules due to the non-specific binding [...] Read more.
Surface-enhanced Raman scattering (SERS) is a powerful optical sensing platform that amplifies the target signals by Raman scattering. Despite SERS enabling a meager detection limit, even at the single-molecule level, SERS also tends to equally enhance unwanted molecules due to the non-specific binding of noise molecules in clinical samples, which complicates its use in complex samples such as bodily fluids, environmental water, or food matrices. To address this, we developed a novel non-fouling biomimetic SERS sensor by self-assembling an anti-adhesive, anti-fouling, and size-selective Lubricin (LUB) coating on gold nanoparticle (AuNP) functionalized glass slide surfaces via a simple drop-casting method. Compared to a conventional AuNPs-SERS substrate, the biomimetic SERS meets the requirements of simple preparation and enables direct droplet detection without any sample pre-treatment. Atomic force microscopy was used to confirm the self-assembled Lubricin coating on the AuNP surface, acting as an anti-fouling and size-selective protection layer. A series of Raman spectra were collected using melamine as the target analyte, which was spiked into 150 mM NaCl solution or undiluted milk. It was demonstrated that the LUB coating effectively prevents the detrimental fouling generated by the proteins and fats in milk, ensuring the clear detection of melamine. Our sensor showed high selectivity and could detect melamine in milk at concentrations as low as 1 ppm. Given that the EU/US legal limit for melamine in food is 2.5 ppm, this sensor offers a promising, cost-effective solution for routine screening and has potential applications for detecting food adulteration in the food safety, environmental monitoring, aquaculture, and biomedical fields. Full article
(This article belongs to the Special Issue SERS-Based Biosensors: Design and Biomedical Applications)
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<p>(<b>A</b>) Representative AFM images of bare SERS. (<b>B</b>) Corresponding 3D image of <a href="#biosensors-14-00591-f001" class="html-fig">Figure 1</a>A. (<b>C</b>) Representative AFM images of biomimetic SERS. (<b>D</b>) Corresponding 3D image of <a href="#biosensors-14-00591-f001" class="html-fig">Figure 1</a>C. The AFM images were collected using contact mode and the Ra values listed on the images are averages of the RMS data for each. The average roughness shown was calculated from ten total traces of an individual image.</p>
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<p>Representative AFM normal–force distance curves of (<b>A</b>) bare SERS and (<b>B</b>) biomimetic DNA sensor.</p>
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<p>(<b>A</b>) SERS measurement of melamine in buffer made with bare SERS. (<b>B</b>) SERS measurements of pure milk and melamine–spiked undiluted milk made with the bare SERS sensor or biomimetic SERS, respectively.</p>
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<p>(<b>A</b>) SERS spectra of melamine–spiked buffer collected with biomimetic SERS and bare SERS. (<b>B</b>) SERS spectra of melamine–spiked undiluted milk or buffer with the same biomimetic SERS sensors and background spectra of bare SERS and biomimetic SERS without melamine.</p>
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<p>(<b>A</b>) SERS spectra under different concentrations of melamine in undiluted milk, ranging from 1 ppm to 500 ppm, were collected with biomimetic SERS. (<b>B</b>) Calibration curve of melamine peak intensity at 680 cm<sup>–1</sup> as a function of melamine concentration in undiluted milk.</p>
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<p>(<b>A</b>–<b>D</b>) Schematic illustration of the fabrication of the biomimetic SERS sensor. (<b>E</b>,<b>F</b>) SERS measurements of melamine-spiked undiluted milk with the bare SERS sensor and the biomimetic sensor, respectively.</p>
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