Pub Date : 2026-01-01Epub Date: 2025-10-13DOI: 10.1016/j.ymeth.2025.09.006
Xinfu Liu , Yirui Wu , Yuting Zhou
With the continuous advancement of medical enterprise, intelligent medical technologies supported by natural language processing and knowledge representation have made significant progress. However, with the continuous generation of vast amounts of medical data, the current methods still perform poorly in handling specialized medical data, particularly unlabeled medical diagnostic data. Inspired by the outstanding performance of large language models in various downstream expert tasks in recent years, this article leverages large language models to handle the massive unlabelled medical data, aiming to provide more accurate technical solutions for medical image classification tasks. Specifically, we propose a novel Cross-Modal Knowledge Representation framework (CMKR) to handle vast unlabeled medical data, which utilizes large language models to extract implicit knowledge from medical images, while also extracting explicit textual knowledge with the aid of knowledge graphs. To better utilize the associative information between medical images and textual records, we have designed a cross-modal alignment strategy that enhances knowledge representation capabilities both intra- and inter-modal. We conducted extensive experiments on public datasets, demonstrating that our method outperforms most mainstream approaches.
{"title":"Zero-shot medical image classification via large multimodal models and knowledge graphs-driven processing","authors":"Xinfu Liu , Yirui Wu , Yuting Zhou","doi":"10.1016/j.ymeth.2025.09.006","DOIUrl":"10.1016/j.ymeth.2025.09.006","url":null,"abstract":"<div><div>With the continuous advancement of medical enterprise, intelligent medical technologies supported by natural language processing and knowledge representation have made significant progress. However, with the continuous generation of vast amounts of medical data, the current methods still perform poorly in handling specialized medical data, particularly unlabeled medical diagnostic data. Inspired by the outstanding performance of large language models in various downstream expert tasks in recent years, this article leverages large language models to handle the massive unlabelled medical data, aiming to provide more accurate technical solutions for medical image classification tasks. Specifically, we propose a novel Cross-Modal Knowledge Representation framework (CMKR) to handle vast unlabeled medical data, which utilizes large language models to extract implicit knowledge from medical images, while also extracting explicit textual knowledge with the aid of knowledge graphs. To better utilize the associative information between medical images and textual records, we have designed a cross-modal alignment strategy that enhances knowledge representation capabilities both intra- and inter-modal. We conducted extensive experiments on public datasets, demonstrating that our method outperforms most mainstream approaches.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"245 ","pages":"Pages 25-34"},"PeriodicalIF":4.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145297807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01Epub Date: 2025-10-30DOI: 10.1016/j.ymeth.2025.10.008
Donghyeok Gang, Yeonju Song, Yeonjin Ko
Approximately 80% of drugs developed to date are small molecule compounds. While these compounds can effectively inhibit intracellular targets by crossing cell membranes, their efficacy often depends on stringent conditions, such as the presence of a deep hydrophobic pocket for strong binding. Biologics—including peptides, antibodies, and genetic materials—have fewer binding requirements but cannot penetrate cell membranes, limiting their activity to extracellular targets. Notably, the number of intracellular protein and nucleic acid targets is more than four times that of extracellular targets. Given their potential to treat fundamental disease mechanisms, the intracellular delivery of biologics is of critical importance. In this review, we discuss the generation and application of membrane-based carriers, including cell-derived vesicles and artificial membrane-based carriers, with examples categorized by modality to enhance the therapeutic utility of biologics.
{"title":"Membrane-mediated strategies for efficient intracellular delivery of biologics","authors":"Donghyeok Gang, Yeonju Song, Yeonjin Ko","doi":"10.1016/j.ymeth.2025.10.008","DOIUrl":"10.1016/j.ymeth.2025.10.008","url":null,"abstract":"<div><div>Approximately 80% of drugs developed to date are small molecule compounds. While these compounds can effectively inhibit intracellular targets by crossing cell membranes, their efficacy often depends on stringent conditions, such as the presence of a deep hydrophobic pocket for strong binding. Biologics—including peptides, antibodies, and genetic materials—have fewer binding requirements but cannot penetrate cell membranes, limiting their activity to extracellular targets. Notably, the number of intracellular protein and nucleic acid targets is more than four times that of extracellular targets. Given their potential to treat fundamental disease mechanisms, the intracellular delivery of biologics is of critical importance. In this review, we discuss the generation and application of membrane-based carriers, including cell-derived vesicles and artificial membrane-based carriers, with examples categorized by modality to enhance the therapeutic utility of biologics.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"245 ","pages":"Pages 13-24"},"PeriodicalIF":4.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-03DOI: 10.1016/j.ymeth.2025.10.001
Yugyeong Sim , Eunbeom Lee , Jinyoung Jeong
Zebrafish imaging is a powerful tool for observing physiological responses in real time, from the whole organism to the organ, tissue, and cellular levels. It enables researchers to derive biological meaning by observing morphological and histological changes, cell migration, and more. To analyze such dynamic phenomena, the acquisition of high-quality and consistent images is essential. However, it remains challenging to acquire standardized images at specific regions of interest in zebrafish. In this study, we developed a customized imaging platform, the zebrafish embedding mold (ZEM), designed to facilitate imaging of zebrafish embryos and larvae. Three types of molds were fabricated to accommodate different developmental stages and imaging orientations. The ZEM provided stable positioning of embryos (0–2 days post-fertilization, dpf) and larvae (3–7 dpf), enabling improved imaging of developmental stages, morphological changes, and fluorescence signals. Using this platform, we successfully analyzed the biodistribution and accumulation patterns of fluorescent polystyrene nanoplastics, as well as morphological alteration induced by exposure to the environmental pollutant benzo[a]pyrene. The ZEM ensured consistent specimen orientation in lateral, dorsal and ventral view, enabling quantitative image-based analysis and reliable toxicological assessment. This platform has the potential to be utilized for image-based screening and mechanistic studies, supporting multi-time point observations, reproducible image acquisition, and statistical analysis using the zebrafish model.
{"title":"ZEMs: Zebrafish embedding molds for high-throughput imaging of zebrafish embryos and larvae","authors":"Yugyeong Sim , Eunbeom Lee , Jinyoung Jeong","doi":"10.1016/j.ymeth.2025.10.001","DOIUrl":"10.1016/j.ymeth.2025.10.001","url":null,"abstract":"<div><div>Zebrafish imaging is a powerful tool for observing physiological responses in real time, from the whole organism to the organ, tissue, and cellular levels. It enables researchers to derive biological meaning by observing morphological and histological changes, cell migration, and more. To analyze such dynamic phenomena, the acquisition of high-quality and consistent images is essential. However, it remains challenging to acquire standardized images at specific regions of interest in zebrafish. In this study, we developed a customized imaging platform, the zebrafish embedding mold (ZEM), designed to facilitate imaging of zebrafish embryos and larvae. Three types of molds were fabricated to accommodate different developmental stages and imaging orientations. The ZEM provided stable positioning of embryos (0–2 days post-fertilization, dpf) and larvae (3–7 dpf), enabling improved imaging of developmental stages, morphological changes, and fluorescence signals. Using this platform, we successfully analyzed the biodistribution and accumulation patterns of fluorescent polystyrene nanoplastics, as well as morphological alteration induced by exposure to the environmental pollutant benzo[a]pyrene. The ZEM ensured consistent specimen orientation in lateral, dorsal and ventral view, enabling quantitative image-based analysis and reliable toxicological assessment. This platform has the potential to be utilized for image-based screening and mechanistic studies, supporting multi-time point observations, reproducible image acquisition, and statistical analysis using the zebrafish model.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 157-167"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145231032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-03DOI: 10.1016/j.ymeth.2025.09.011
Dong-Gyu Jeon , Chung-Young Lee , Chang-Hee Cho , Gang Ho Lee , Yongmin Chang , Sung-Wook Nam
We report a comparative study of macroscopic and microscopic optical absorbance in hemagglutination (HA) assay. Red blood cells (RBCs) exhibit unique optical absorbance properties with characteristic peaks including Soret, Qv, and Qo. In addition, RBCs absorb light and appear as dark contrast in bright-field microscopy images, indicating an increase in local optical density (OD). By systematic analysis of macroscopic and microscopic OD measurements and UV–Visible (UV–Vis) spectroscopy, we developed a phenomenological model of RBC agglutination and non-agglutination. The antigen–antibody reaction in RBC agglutination behaves as a catastrophic event such that networking of RBC clumps is initiated at a critical RBC concentration. We analyzed the dependence of OD on RBC concentration. At the critical RBC concentration, OD values are dropped or saturated for RBC agglutination, on the other hand, ODs keep increasing as the increase of RBC concentration for RBC non-agglutination. By the analysis of UV–Vis spectroscopy for HA assay, we provide an optimal wavelength range as 480-520 nm, away from RBC characteristic absorption peaks. For further validation, we demonstrated the OD-based HA assay for the detection of H1N1 influenza A virus. Our investigation provides insights into how to utilize the physical properties of RBCs for novel HA assay platforms.
{"title":"Comparative analysis of macroscopic and microscopic optical absorbance in hemagglutination assay","authors":"Dong-Gyu Jeon , Chung-Young Lee , Chang-Hee Cho , Gang Ho Lee , Yongmin Chang , Sung-Wook Nam","doi":"10.1016/j.ymeth.2025.09.011","DOIUrl":"10.1016/j.ymeth.2025.09.011","url":null,"abstract":"<div><div>We report a comparative study of macroscopic and microscopic optical absorbance in hemagglutination (HA) assay. Red blood cells (RBCs) exhibit unique optical absorbance properties with characteristic peaks including Soret, Qv, and Qo. In addition, RBCs absorb light and appear as dark contrast in bright-field microscopy images, indicating an increase in local optical density (OD). By systematic analysis of macroscopic and microscopic OD measurements and UV–Visible (UV–Vis) spectroscopy, we developed a phenomenological model of RBC agglutination and non-agglutination. The antigen–antibody reaction in RBC agglutination behaves as a catastrophic event such that networking of RBC clumps is initiated at a critical RBC concentration. We analyzed the dependence of OD on RBC concentration. At the critical RBC concentration, OD values are dropped or saturated for RBC agglutination, on the other hand, ODs keep increasing as the increase of RBC concentration for RBC non-agglutination. By the analysis of UV–Vis spectroscopy for HA assay, we provide an optimal wavelength range as 480-520 nm, away from RBC characteristic absorption peaks. For further validation, we demonstrated the OD-based HA assay for the detection of H1N1 influenza A virus. Our investigation provides insights into how to utilize the physical properties of RBCs for novel HA assay platforms.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 195-209"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145231083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-09DOI: 10.1016/j.ymeth.2025.10.002
Yogita Jethmalani , Matthew S. Sutton , Robin Carroll , Rachel Kazmierski , Kwang Low , Madeeha Mughal , Jimmie Bullock , Cecilia S. Lindestam Arlehamn , David M. Lewinsohn , Deborah A. Lewinsohn , Chelsea C. Lehman , Courtney Green , James Moshi , Allen Mueller , Patricia A. Darrah , Robert A. Seder , Bob C. Lin , Richard A. Koup , Leonid A. Serebryannyy , Mario Roederer
Immunospot assays are known for high sensitivity and low material requirement. ELISpot and FluoroSpot assays have been frequently used in immune cell monitoring and profiling, specifically with T-cells and B-cells. FluoroSpot enables multiplexing, similar to flow cytometry, but has the added benefit of requiring fewer cells, higher throughput at screening immunogens, and a faster assay readout. Immunospot assays are generally performed manually and are prone to operator errors in plate handling, leading to overlapping spots with low resolution and high variability. Here, we describe the development of a High-throughput Immune Cell FluoroSpot (HI-CeFSpot) assay that has been adapted on the Biomek i7 liquid handler with labware storage, in conjunction with an automated plate washer with stacker, and the IRIS 2 plate reader from Mabtech attached to the Orbitor robotic arm. To develop the HI-CeFSpot assay, we used immune cells from non-human primates (NHPs) and screened them against various stimuli to test the release of interferon gamma (IFN-γ). We tested parameters such as precision, robustness, reproducibility, and compared two different cell types across various cell densities. We found that the HI-CeFSpot assay had intra- and inter-plate precision of <10 %, and inter-assay precision of <15 %. The assay showed high reproducibility and was robust across multiple samples. The HI-CeFSpot assay described here is a platform solution that can be used in clinical trial endpoint testing for drug development, immune cell monitoring, testing the efficacy of immunotherapy, and in vaccine research with high-throughput, high precision, reproducibility, and multiplexing.
{"title":"HI-CeFSpot: High-throughput Immune Cell FluoroSpot assay","authors":"Yogita Jethmalani , Matthew S. Sutton , Robin Carroll , Rachel Kazmierski , Kwang Low , Madeeha Mughal , Jimmie Bullock , Cecilia S. Lindestam Arlehamn , David M. Lewinsohn , Deborah A. Lewinsohn , Chelsea C. Lehman , Courtney Green , James Moshi , Allen Mueller , Patricia A. Darrah , Robert A. Seder , Bob C. Lin , Richard A. Koup , Leonid A. Serebryannyy , Mario Roederer","doi":"10.1016/j.ymeth.2025.10.002","DOIUrl":"10.1016/j.ymeth.2025.10.002","url":null,"abstract":"<div><div>Immunospot assays are known for high sensitivity and low material requirement. ELISpot and FluoroSpot assays have been frequently used in immune cell monitoring and profiling, specifically with T-cells and B-cells. FluoroSpot enables multiplexing, similar to flow cytometry, but has the added benefit of requiring fewer cells, higher throughput at screening immunogens, and a faster assay readout. Immunospot assays are generally performed manually and are prone to operator errors in plate handling, leading to overlapping spots with low resolution and high variability. Here, we describe the development of a <u>H</u>igh-throughput <u>I</u>mmune <u>Ce</u>ll <u>F</u>luoro<u>Spot</u> (HI-CeFSpot) assay that has been adapted on the Biomek i7 liquid handler with labware storage, in conjunction with an automated plate washer with stacker, and the IRIS 2 plate reader from Mabtech attached to the Orbitor robotic arm. To develop the HI-CeFSpot assay, we used immune cells from non-human primates (NHPs) and screened them against various stimuli to test the release of interferon gamma (IFN-γ). We tested parameters such as precision, robustness, reproducibility, and compared two different cell types across various cell densities. We found that the HI-CeFSpot assay had intra- and inter-plate precision of <10 %, and inter-assay precision of <15 %. The assay showed high reproducibility and was robust across multiple samples. The HI-CeFSpot assay described here is a platform solution that can be used in clinical trial endpoint testing for drug development, immune cell monitoring, testing the efficacy of immunotherapy, and in vaccine research with high-throughput, high precision, reproducibility, and multiplexing.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 210-218"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145257070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-09-04DOI: 10.1016/j.ymeth.2025.08.014
Hafeez Ur Rehman , Dawood Ahmad Warraich , Abdur Rehman , Israr Fatima , Yuxuan Meng , Mohamed Aldaw , Yanheng Ding , Ruiqi Zhang , Yu Ni , Zhijie He , Hao Zhang , Zhibo Wang , Lijun Feng , Yingcui Yu , Mingzhi Liao
Parkinson’s disease is a prevalent neurodegenerative disease, in which genetic mutations in many genes play an important role in its pathogenesis. Among these, a mutation in the PINK1 gene, a mitochondrial-targeted serine/threonine putative kinase 1 that protects cells from stress-induced mitochondrial dysfunction, is implicated in autosomal recessive Parkinsonism. However, the exact etiology is not well understood. Therefore, this study aimed to identify the most damaging non-synonymous single-nucleotide polymorphisms (nsSNPs) distributed in the kinase domain of the PINK1 gene and their structural and functional alterations using a range of bioinformatics and deep learning tools. Next, to find the possible impact of these mutations on PINK1 interactions and binding affinities, a protein–protein interaction and molecular docking analysis were conducted. Finally, molecular dynamics (MD) simulations were performed to observe the stability and dynamic behaviour of the pathogenic SNPs on the PINK1 protein over time. Our integrated bioinformatics and deep learning approaches predicted 5 SNPs (C166R, E240K, D362N, D362Y, and C388R) as high-risk candidates for disrupting PINK1 structure and function. In conclusion, we propose that the pathogenicity of these variants may provide an important clue to understanding the mechanism by which pathogenic nsSNPs contribute to PD, thereby enhancing future diagnostic value for the disease and serving as potential targets for new drugs.
{"title":"AI-augmented prediction of high-risk PINK1 variants associated with Parkinson’s disease: integrating multilayered bioinformatics, MD simulation, and deep learning","authors":"Hafeez Ur Rehman , Dawood Ahmad Warraich , Abdur Rehman , Israr Fatima , Yuxuan Meng , Mohamed Aldaw , Yanheng Ding , Ruiqi Zhang , Yu Ni , Zhijie He , Hao Zhang , Zhibo Wang , Lijun Feng , Yingcui Yu , Mingzhi Liao","doi":"10.1016/j.ymeth.2025.08.014","DOIUrl":"10.1016/j.ymeth.2025.08.014","url":null,"abstract":"<div><div>Parkinson’s disease is a prevalent neurodegenerative disease, in which genetic mutations in many genes play an important role in its pathogenesis. Among these, a mutation in the PINK1 gene, a mitochondrial-targeted serine/threonine putative kinase 1 that protects cells from stress-induced mitochondrial dysfunction, is implicated in autosomal recessive Parkinsonism. However, the exact etiology is not well understood. Therefore, this study aimed to identify the most damaging non-synonymous single-nucleotide polymorphisms (nsSNPs) distributed in the kinase domain of the PINK1 gene and their structural and functional alterations using a range of bioinformatics and deep learning tools. Next, to find the possible impact of these mutations on PINK1 interactions and binding affinities, a protein–protein interaction and molecular docking analysis were conducted. Finally, molecular dynamics (MD) simulations were performed to observe the stability and dynamic behaviour of the pathogenic SNPs on the PINK1 protein over time. Our integrated bioinformatics and deep learning approaches predicted 5 SNPs (C166R, E240K, D362N, D362Y, and C388R) as high-risk candidates for disrupting PINK1 structure and function. In conclusion, we propose that the pathogenicity of these variants may provide an important clue to understanding the mechanism by which pathogenic nsSNPs contribute to PD, thereby enhancing future diagnostic value for the disease and serving as potential targets for new drugs.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 30-45"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145008071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-10-14DOI: 10.1016/j.ymeth.2025.10.005
Xiaodong Zhang , Caixia Li , Yongzhen Wang , Yue Cao , Xiaona He , Fugang Xiao , Deguo Wang
Panax notoginseng, a cornerstone of traditional Chinese medicine, is frequently subject to adulteration in commercial markets, compromising its therapeutic efficacy and safety. This study introduces a novel application of Proofman-LMTIA technology to authenticate P. notoginseng with high precision and efficiency. By targeting unique sequence variations in the ITS2 rDNA region, we developed species-specific primers and probe to distinguish P. notoginseng from common adulterants. The method achieves a detection sensitivity of 10 pg/µL and identifies adulteration at levels as low as 1 % (v/v), validated across diverse commercial products, including powders and capsules. With a detection time of under 30 min and no reliance on specialized equipment, this approach offers a streamlined, cost-efficient solution for quality assurance in the herbal industry. Our results demonstrate 100 % accuracy in market sample testing, addressing critical challenges in P. notoginseng authentication and supporting regulatory compliance.
{"title":"Authentication of Panax notoginseng with high-efficiency Proofman-LMTIA technology","authors":"Xiaodong Zhang , Caixia Li , Yongzhen Wang , Yue Cao , Xiaona He , Fugang Xiao , Deguo Wang","doi":"10.1016/j.ymeth.2025.10.005","DOIUrl":"10.1016/j.ymeth.2025.10.005","url":null,"abstract":"<div><div><em>Panax notoginseng</em>, a cornerstone of traditional Chinese medicine, is frequently subject to adulteration in commercial markets, compromising its therapeutic efficacy and safety. This study introduces a novel application of Proofman-LMTIA technology to authenticate <em>P. notoginseng</em> with high precision and efficiency. By targeting unique sequence variations in the ITS2 rDNA region, we developed species-specific primers and probe to distinguish <em>P. notoginseng</em> from common adulterants. The method achieves a detection sensitivity of 10 pg/µL and identifies adulteration at levels as low as 1 % (v/v), validated across diverse commercial products, including powders and capsules. With a detection time of under 30 min and no reliance on specialized equipment, this approach offers a streamlined, cost-efficient solution for quality assurance in the herbal industry. Our results demonstrate 100 % accuracy in market sample testing, addressing critical challenges in <em>P</em>. <em>notoginseng</em> authentication and supporting regulatory compliance.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 219-226"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145306601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Single-cell surface-enhanced Raman scattering (SERS) has emerged as a powerful tool for precision medicine owing to its label-free detection, ultrasensitivity, and unique molecular fingerprinting. Unlike conventional bulk analysis, it enables detailed characterization of cellular heterogeneity, with particular promise in circulating tumor cell (CTC) identification, tumor microenvironment (TME) metabolic profiling, subcellular imaging, and drug sensitivity assessment. Coupled with microfluidic droplet systems, SERS supports high-throughput single-cell analysis and multiparametric screening, while integration with complementary modalities such as fluorescence microscopy and mass spectrometry enhances temporal and spatial resolution for monitoring live cells. Despite hurdles in nanoprobe safety, complex spectral interpretation, and clinical translation, advances in AI-driven data processing (e.g., convolutional neural networks) and miniaturized devices are accelerating progress toward intraoperative guidance, improved liquid biopsy, and primary healthcare adoption. Looking ahead, its applications in single-cell metabolomics, exosome studies, and microbial detection hold promise for uncovering disease mechanisms and fostering personalized diagnostics and therapeutics.
{"title":"Deciphering cellular heterogeneity: Breakthroughs and prospects of single-cell-level SERS analysis in precision medicine","authors":"Biqing Chen, Jiayin Gao, Haizhu Sun, Yan Liu, Yinghan Zhao, Xiaohong Qiu","doi":"10.1016/j.ymeth.2025.09.002","DOIUrl":"10.1016/j.ymeth.2025.09.002","url":null,"abstract":"<div><div>Single-cell surface-enhanced Raman scattering (SERS) has emerged as a powerful tool for precision medicine owing to its label-free detection, ultrasensitivity, and unique molecular fingerprinting. Unlike conventional bulk analysis, it enables detailed characterization of cellular heterogeneity, with particular promise in circulating tumor cell (CTC) identification, tumor microenvironment (TME) metabolic profiling, subcellular imaging, and drug sensitivity assessment. Coupled with microfluidic droplet systems, SERS supports high-throughput single-cell analysis and multiparametric screening, while integration with complementary modalities such as fluorescence microscopy and mass spectrometry enhances temporal and spatial resolution for monitoring live cells. Despite hurdles in nanoprobe safety, complex spectral interpretation, and clinical translation, advances in AI-driven data processing (e.g., convolutional neural networks) and miniaturized devices are accelerating progress toward intraoperative guidance, improved liquid biopsy, and primary healthcare adoption. Looking ahead, its applications in single-cell metabolomics, exosome studies, and microbial detection hold promise for uncovering disease mechanisms and fostering personalized diagnostics and therapeutics.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 7-29"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01Epub Date: 2025-09-25DOI: 10.1016/j.ymeth.2025.09.008
Junmo Hwang , Eunbi Kim , Jina Kim , Sujin Shin , Hyun-Ho Lim
The complementarity-determining regions (CDRs) of monoclonal antibodies are essential for antigen recognition and antibody engineering. Accurate determination of CDR sequences typically requires cDNA synthesis from hybridoma-derived mRNA followed by sequencing of the variable regions. However, murine monoclonal antibodies are composed of diverse heavy and light chain isotypes, necessitating prior isotype determination to select appropriate primers for cDNA synthesis. Conventional workflows rely on immunoassays for isotype identification, which adds time and complexity. Here, we developed a streamlined, isotype-independent workflow for the molecular characterization of mouse monoclonal antibodies. A multiplex set of reverse transcription primers (Multiplex-RT) incorporating a universal adaptor sequence was designed to enable cDNA synthesis across major murine isotypes without prior isotype knowledge. Variable regions were subsequently amplified by isotype-specific PCR (Iso-PCR), allowing identification of antibody isotypes, IgG subclasses, and CDR sequences in a single workflow. We applied this method to characterize a murine antibody targeting the astrocytic membrane protein MLC1 and engineered a human-mouse chimeric antibody by grafting murine CDRs onto a human IgG1 backbone. The chimeric antibody retained antigen-binding activity, as demonstrated by immunoprecipitation and immunoblotting. This workflow provides a rapid and reliable strategy for sequencing and isotyping mouse monoclonal antibodies and facilitates downstream applications in antibody discovery, recombinant production, and engineering.
{"title":"Integrated isotyping and CDR identification of mouse monoclonal antibodies using multiplex RT-PCR","authors":"Junmo Hwang , Eunbi Kim , Jina Kim , Sujin Shin , Hyun-Ho Lim","doi":"10.1016/j.ymeth.2025.09.008","DOIUrl":"10.1016/j.ymeth.2025.09.008","url":null,"abstract":"<div><div>The complementarity-determining regions (CDRs) of monoclonal antibodies are essential for antigen recognition and antibody engineering. Accurate determination of CDR sequences typically requires cDNA synthesis from hybridoma-derived mRNA followed by sequencing of the variable regions. However, murine monoclonal antibodies are composed of diverse heavy and light chain isotypes, necessitating prior isotype determination to select appropriate primers for cDNA synthesis. Conventional workflows rely on immunoassays for isotype identification, which adds time and complexity. Here, we developed a streamlined, isotype-independent workflow for the molecular characterization of mouse monoclonal antibodies. A multiplex set of reverse transcription primers (Multiplex-RT) incorporating a universal adaptor sequence was designed to enable cDNA synthesis across major murine isotypes without prior isotype knowledge. Variable regions were subsequently amplified by isotype-specific PCR (Iso-PCR), allowing identification of antibody isotypes, IgG subclasses, and CDR sequences in a single workflow. We applied this method to characterize a murine antibody targeting the astrocytic membrane protein MLC1 and engineered a human-mouse chimeric antibody by grafting murine CDRs onto a human IgG1 backbone. The chimeric antibody retained antigen-binding activity, as demonstrated by immunoprecipitation and immunoblotting. This workflow provides a rapid and reliable strategy for sequencing and isotyping mouse monoclonal antibodies and facilitates downstream applications in antibody discovery, recombinant production, and engineering.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"244 ","pages":"Pages 134-142"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145155811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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