Methods (San Diego, Calif.)[JOURNAL]
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200 papers
Comprehensive account of exosome isolation from rat substantia nigra for mass spectrometry-based proteomics study.
Ghosh S, Ghosh S, Jana A … +2 more , Roy R, Ghosh S
Methods · 2025 Sep · PMID 40482943 · Publisher ↗
Exosomes, small extracellular vesicles originating from endocytic processes, have garnered increasing attention due to their roles in both physiological functions and pathological conditions. Initially identified in the...
Exosomes, small extracellular vesicles originating from endocytic processes, have garnered increasing attention due to their roles in both physiological functions and pathological conditions. Initially identified in the 1980 s, exosomes are formed within multivesicular bodies (MVBs) through the invagination of the endosomal membrane, leading to the creation of intraluminal vesicles (ILVs). These ILVs can either be degraded by lysosomes or released into the extracellular space as exosomes, facilitating intercellular communication. In the nervous system, exosomes are implicated in various functions, including neural development and the progression of neurodegenerative diseases such as Alzheimer's and Parkinson's disease. This study presents a novel protocol for the isolation and proteomic analysis of exosomes derived from the substantia nigra (SN) of rat brains. By employing a combination of differential centrifugation and immunocapture techniques, we achieved a purer exosome fraction and higher exosome yield compared to traditional ultracentrifugation methods. Our proteomics analysis identified 51, 48, and 70 proteins from three distinct exosome samples (SN-EV-1, SN-EV-2, and SN-EV-4), with Gene Ontology annotation revealing their involvement in diverse biological functions. This research not only establishes a reliable method for isolating brain-derived exosomes but also sets the stage for comparative studies between healthy and neurodegenerative conditions. Ultimately, our findings aim to enhance the understanding of exosomal roles in disease mechanisms and contribute to the identification of potential biomarkers and therapeutic targets for neurodegenerative disorders.
cfDNAFE: Comprehensively extracting multi-omics features of cell-free DNA for noninvasive diagnosis.
Cui W, You J, Jie W … +2 more , Li Z, Peng X
Methods · 2025 Sep · PMID 40472984 · Publisher ↗
The tissues-of-origin of circulating cell-free DNA (cfDNA) holds great promise for non-invasive diagnosing cancers, monitoring allograft rejection, and prenatal testing. Many features for inferring the tissues-of-origin...
The tissues-of-origin of circulating cell-free DNA (cfDNA) holds great promise for non-invasive diagnosing cancers, monitoring allograft rejection, and prenatal testing. Many features for inferring the tissues-of-origin of cfDNAs are being revealed from different angles, including genetics, epigenetics, and fragmentomics, with whole-genome sequencing (WGS) and whole-genome bisulfite sequencing (WGBS) data of cfDNA. However, it lacks integrative toolkits for automatically extracting the revealed features from the WGS and WGBS data of cfDNA samples. Here, we propose cfDNAFE, a comprehensive and easy-to-use python package for extracting multi-omics features from the aligned cfDNA sequencing data. It covers three aspects: cfDNA genetic features, cfDNA methylation features, and cfDNA fragmentation features, including 13 types of feature profiles. The genetic features include substitution mutations, mutation signatures and copy number variations. The methylation features are the proportions of methylated fragments, unmethylated fragments, and mixed methylated fragments on cell-type-specific markers. The fragmentation features related to the fragment sizes, end/breakpoint motifs, and nucleosome positions are also integrated. To verify the functions of cfDNAFE, we perform analysis on the WGS/WGBS data of cfDNA samples based on the feature profiles extracted by cfDNAFE. The comparison between the cfDNA samples of hepatocellular carcinoma (HCC) patients and normal controls suggests HCC cfDNA samples exhibit significant difference in fragment size related features and breakpoint/end motif patterns, and obtain significant higher OCF values in the liver-specific open regions than the health controls. Conclusively, cfDNAFE is a most comprehensive toolkit which covers the most features for inferring the tissues-of-origin of cfDNAs in existing studies up to date. It will facilitate researchers to build machine learning models for auxiliary diagnosis based on these features. Availability and implementation: https://github.com/Cuiwanxin1998/cfDNAFE.
Label-free spectral confocal reflectance microscopy for ex vivo neuroimaging and neural structure visualization.
Pimentel-Domínguez R, Ordaz RP, Cisneros-Mejorado AJ … +2 more , Arellano RO, Avila R
Methods · 2025 Sep · PMID 40466964 · Publisher ↗
Confocal microscopy is an essential technique in the field of life sciences, commonly used to study molecules in a variety of preparations, ranging from cells and tissues to entire organisms. In the field of neuroscience...
Confocal microscopy is an essential technique in the field of life sciences, commonly used to study molecules in a variety of preparations, ranging from cells and tissues to entire organisms. In the field of neuroscience, it is a widely utilized tool for both anatomical-structural and functional studies. However, a lesser-known application of this microscopy method is confocal reflectance microscopy, which involves image acquisition based on reflected light from the sample. In this study, we present the use of spectral confocal reflectance microscopy (SCoRe) to explore multiple structures in the rat brain, without the use of any dyes or immunolabeling. Our results demonstrate that this technique allows for the distinction between different brain structures with high spatial resolution, enabling the observation of fibers in the cerebral cortex, corpus callosum, hippocampus, cerebellum, and other regions. These findings highlight the ability of SCoRe to provide detailed anatomical insights that are comparable to those obtained through conventional methods. Additionally, we have shown that SCoRe is compatible with samples prepared using traditional techniques, such as histochemical staining and immunofluorescence. This research emphasizes the value of SCoRe as a cost-effective and label-free method for high-resolution brain imaging, which can improve neuroscience studies and reduce long-term expenses.
Development and interpretation of a pathomics-based model for the prediction of immune therapy response in colorectal cancer.
Luo Y, Tian Q, Xu L … +6 more , Zeng D, Zhang H, Zeng T, Tang H, Wang C, Chen Y
Methods · 2025 Sep · PMID 40456461 · Publisher ↗
Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related deaths worldwide, with a 5-year survival rate below 20 %. Immunotherapy, particularly immune checkpoint blockade...
Colorectal cancer (CRC) is the third most common malignancy and the second leading cause of cancer-related deaths worldwide, with a 5-year survival rate below 20 %. Immunotherapy, particularly immune checkpoint blockade (ICB)-based therapies, has become an important approach for CRC treatment. However, only specific patient subsets demonstrate significant clinical benefits. Although the TIDE algorithm can predict immunotherapy responses, the reliance on transcriptome sequencing data limits its clinical applicability. Recent advances in artificial intelligence and computational pathology provide new avenues for medical image analysis. In this study, we classified TCGA-CRC samples into immunotherapy responder and non-responder groups using the TIDE algorithm. Further, a pathomics model based on convolutional neural networks was constructed to directly predict immunotherapy responses from histopathological images. Single-cell analysis revealed that fibroblasts may induce immunotherapy resistance in CRC through collagen-CD44 and ITGA1 + ITGB1 signaling axes. The developed pathomics model demonstrated excellent classification performance in the test set, with an AUC of 0.88 at the patch level and 0.85 at the patient level. Moreover, key pathomics features were identified through SHAP analysis. This innovative predictive tool provides a novel method for clinical decision-making in CRC immunotherapy, with potential to optimize treatment strategies and advance precision medicine.
Metabolic impacts of long-chain fatty acids on cardiomyocyte maturation in neonatal mammalian hearts.
Cha SE, Lee MN, Kim ES
Methods · 2025 Sep · PMID 40449856 · Publisher ↗
Cardiomyocytes are essential models for cardiac disease modeling, drug development, and regenerative therapies. Specifically, human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as widely...
Cardiomyocytes are essential models for cardiac disease modeling, drug development, and regenerative therapies. Specifically, human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have emerged as widely used cellular models with high reproducibility. However, cardiomyocytes generated in vitro tend to remain immature and insufficient in replicating the electrophysiological and mechanical functions of adult cardiomyocytes, limiting the clinical and experimental applications of these models. Thus, various biochemical and biophysical strategies have been explored to promote the maturation of cardiomyocytes, to address these limitations, and more accurately mimic the characteristics of mature cardiomyocytes. This review summarizes recent studies on multiple methodologies employed to induce cardiomyocyte maturation, with a particular emphasis on the role of long-chain fatty acids (LCFAs). The evidence summarized in this review is derived from studies utilizing cardiomyocytes from neonatal mice or rats and hiPSC-CMs. Meanwhile, immature cardiomyocytes have been demonstrated to predominantly rely on glycolysis, transitioning to oxidative phosphorylation through maturation, which enhances electrical stability, contractility, and structural organization. LCFAs play a key role in the cardiomyocyte maturation process by serving as key metabolic factors that generate ATP through mitochondrial β-oxidation, thereby improving metabolic efficiency. Additionally, LCFAs are involved in activating cytoskeletal components and signaling pathways integral to cardiomyocyte contractility. Importantly, studies suggest that when multiple biochemical and biophysical stimuli are simultaneously applied, various aspects of cardiomyocyte maturation are synergistically accelerated. Therefore, future studies focusing on the coordinated application of these regulatory factors are expected to enhance the maturation process, ultimately contributing to the generation of mature cardiomyocytes suitable for regenerative medicine and other advanced applications.
Development and validation of the Azu-Eos as a fluorescence-free staining method for enhanced bright-field microscopy in the comet assay.
Ivanov P, Staneva D, Georgieva M … +1 more , Miloshev G
Methods · 2025 Sep · PMID 40441464 · Publisher ↗
The comet assay is a valuable technique for assessing cellular DNA damage due to intrinsic and environmental factors, particularly in studies of genotoxicity and mutagenesis. However, its broader application is limited b...
The comet assay is a valuable technique for assessing cellular DNA damage due to intrinsic and environmental factors, particularly in studies of genotoxicity and mutagenesis. However, its broader application is limited by the need for fluorescent staining, the requirement for expensive fluorescent microscopes, and the inability to preserve and re-examine slides over time. We developed the Azure B-Eosin Y (Azu-Eos) staining method to visualise the comets under a standard bright-field microscope to overcome these limitations. The newly developed DNA-staining technique eliminates the need for fluorescence and allows unlimited slide storage and re-examination without quality deterioration. We optimised various factors to ensure the reliability and quality of bright-field stained comets, achieving results comparable to and even better than those obtained with traditional fluorescent dyes. This cost-effective, sensitive, and fluorescence-free method has broad potential applications in medicine, ecology, and environmental monitoring, enabling fast and on-site genotoxicity testing.
Surface-enhanced Raman scattering (SERS) technology: Emerging applications in cancer imaging and precision medicine.
Chen B, Gao J, Sun H … +2 more , Chen Z, Qiu X
Methods · 2025 Sep · PMID 40409483 · Publisher ↗
Recent advancements in Surface-enhanced Raman Scattering (SERS) bioprobes have substantially enhanced their bioimaging capabilities for disease theranostics. This review systematically analyzes three categories of engine...
Recent advancements in Surface-enhanced Raman Scattering (SERS) bioprobes have substantially enhanced their bioimaging capabilities for disease theranostics. This review systematically analyzes three categories of engineered SERS probes: noble metal nanostructures, metal oxide hybrids, and multifunctional composite materials, emphasizing their optimized designs for targeted tumor detection and image-guided surgery. Key developments include improved in vitro biosensing platforms for rapid tumor screening and advanced in vivo probes enabling real-time intraoperative imaging with molecular specificity. The integration of SERS with complementary modalities (fluorescence, photoacoustic, MRI) is critically examined as a strategy to overcome individual technical limitations and achieve multiscale tissue characterization. Technical progress in spatial resolution enhancement, multiplex biomarker detection, and biocompatibility optimization is quantitatively highlighted. Current challenges in signal consistency across biological systems and scalable probe manufacturing are discussed, proposing standardized evaluation frameworks as essential for clinical translation. This work establishes SERS as a multimodal imaging cornerstone for precision oncology, particularly in tumor margin delineation and metastatic lesion identification.
Enhancing RNA Delivery: Practical insights into NeoLNP transfection reagent.
Chen X, Wu Y, Liu L … +1 more , Wang W
Methods · 2025 Sep · PMID 40409482 · Publisher ↗
The rapid advancement of RNA-based therapeutics, particularly in the wake of COVID-19 vaccine success, has prompted significant research into optimizing RNA delivery mechanisms. This study evaluates the NeoLNP RNA Transf...
The rapid advancement of RNA-based therapeutics, particularly in the wake of COVID-19 vaccine success, has prompted significant research into optimizing RNA delivery mechanisms. This study evaluates the NeoLNP RNA Transfection Kit developed by Scindy Pharmaceutical, which utilizes lipid nanoparticles (LNPs) for efficient RNA encapsulation and delivery. We systematically investigate various parameters affecting transfection efficiency, including RNA concentration, RNA/LNP volume ratios, mixing techniques, LNP stability, and culture media. Our results demonstrate that the optimal RNA concentration for transfection efficiency is around 40-60 ng/µL, with a 1:0.75-1:1 RNA-to-LNP ratio yielding the highest protein expression. Additionally, we find that gentle mixing techniques outperform harsher methods, and the stability of LNP-RNA complexes significantly influences transfection outcomes. This research provides practical guidelines for enhancing RNA transfection efficiency, paving the way for more effective RNA therapeutics.
Quorum sensing: An essential factor in culturing the human promyelocytic leukemia cell line HL-60 and its neutrophil-related functions.
Li D, Yang T, Ma S … +5 more , Lyu X, Hu C, Yan J, Guo L, Tan J
Methods · 2025 Sep · PMID 40403782 · Publisher ↗
HL-60 cells are frequently employed as a standard in vitro model for neutrophil research and extensively utilized. However, the cultivation of HL-60 cells presents a recurring challenge. Historically, cell culture densit...
HL-60 cells are frequently employed as a standard in vitro model for neutrophil research and extensively utilized. However, the cultivation of HL-60 cells presents a recurring challenge. Historically, cell culture density has been ignored in the consistency of culture conditions. Here, we optimized the culture protocol and explored the impact of culture density on HL-60 cells. Additionally, we investigated the differentiated rate and antibacterial potential of differentiated HL-60 (dHL-60) neutrophils across varying cell density cultures. The findings revealed a positive correlation between cell proliferation activity and cell density, suggesting that increased density facilitates enhanced cell proliferation. Furthermore, as the density of the cell culture increased, there was a concomitant rise in the differentiation rate of HL-60 cells into neutrophils upon stimulation. Importantly, this elevated density also led to significantly higher levels of mitochondrial reactive oxygen species (ROS) production and bacterial phagocytosis. Further investigation revealed that small extracellular vesicles (sEVs) are crucial communicator in quorum sensing within HL-60 cells. Supplementation of HL60-derived sEVs (hEVs) in low-density cell populations resulted in a restoration of cell proliferation, in dose-dependent tendency. Conversely, the inhibition of EV-secretion in HL-60 cells restrains cell growth and proliferation. Overall, our study not only optimized the HL-60 cell culture protocol but also elucidated the critical role of culture density in enhancing HL-60 cell proliferation and antibacterial activity. This finding offers a noteworthy consideration for in vitro experiments of HL-60 cells and suggests the involvement of a quorum sensing mechanism within the neutrophil microenvironment.
The influence of structured light scanning probe configuration on the 3D scanning accuracy of the maxillofacial region in a smiling state: An in vitro study.
Guan M, Wang X, Li X … +6 more , Wang Y, Yan K, Huo R, Song T, Liu L, Li H
Methods · 2025 Sep · PMID 40383285 · Publisher ↗
Currently, single-unit, dual-unit, and triple-unit structured light 3D scanning technologies have become the predominant facial scanning methods. However, the impact of different unit strategies on facial scanning accura...
Currently, single-unit, dual-unit, and triple-unit structured light 3D scanning technologies have become the predominant facial scanning methods. However, the impact of different unit strategies on facial scanning accuracy remains unclear. A standardized 3D facial model in a smiling state was established. Key point reference coordinates and 3D data were obtained using a coordinate measurement instrument and an industrial-grade laser 3D scanner. Three structured light scanning techniques (single-, dual-, triple-unit) were utilized to capture the 3D information of the model. Linear distance deviations and 3D surface deviations (trueness and precision) of the three scanning strategies were compared. The triple-unit scanning strategy exhibited the lowest deviation among 20 trueness indicators and 22 precision indicators for linear distance measurements (P < 0.05). Furthermore, the accuracy of the triple-unit strategy (trueness: 0.1607 ± 0.0201 mm, precision: 0.0161 ± 0.0112 mm) for overall facial scanning was significantly lower than that of the single-unit and dual-unit strategies, particularly in critical regions for oral and maxillofacial aesthetic analysis, such as the orbital, nasal, and perioral regions. The triple-unit structured light scanning strategy significantly enhances the accuracy of facial 3D scanning, particularly when acquiring 3D facial information from the midline and perioral regions. This in vitro study demonstrates that the triple-unit structured light 3D scanning strategy effectively improves the accuracy of facial scanning, especially in the oral-maxillofacial aesthetic regions. This approach provides a foundation and support for both preoperative planning and postoperative evaluation of aesthetic restoration.
Multi-filter based signed heterogeneous graph convolutional networks for predicting activating/inhibiting drug-target interactions.
Chen M, Li H, Pan Y … +3 more , Dai Y, Lei X, Pan Y
Methods · 2025 Sep · PMID 40381927 · Publisher ↗
The prediction of mechanisms within drug-target interactions (DTIs) can boost the drug discovery process, which has traditionally relied on time-consuming and expensive laboratory experiments. Despite much more attention...
The prediction of mechanisms within drug-target interactions (DTIs) can boost the drug discovery process, which has traditionally relied on time-consuming and expensive laboratory experiments. Despite much more attention has been paid to predicting DTIs, but few studies focused on their activating/inhibiting mechanisms. In this work, we model DTIs on signed heterogeneous networks, through categorizing activating/inhibiting DTIs into signed links, and accordingly introducing the coherence/incoherence between drugs on a common target to construct signed drug-drug links. We propose a multi-filter based signed heterogeneous graph convolutional network (MFSHGCN) for drugs and targets embedding, via employing dual filters on both the signed drug-drug sub-graph and the signed DTI sub-graph to converge the spectral information from positive and negative edges. We further put forward an end-to-end framework to predict activation and inhibition within DTIs. The comparison results demonstrate the introduction of coherence/incoherence of drug pairs and the design of our multi-filter system can effectively improve the prediction metrics, even without relying on rich node information and interactions from drug pairs or target pairs. Case studies on breast cancer and lung cancer confirm the model's feasibility.
An NGS-based approach for precise and footprint-free CRISPR-based gene editing in human stem cells.
Vandendriessche B, Huyghebaert J, Rossem KV … +12 more , Cremers TC, Man K, Sieliwonczyk E, Boen H, Akdeniz D, Rabaut L, Schippers J, Ponsaerts P, Kooy RF, Loeys B, Schepers D, Alaerts M
Methods · 2025 Sep · PMID 40373837 · Publisher ↗
Precise gene editing with conventional CRISPR/Cas9 is often constrained by low knock-in (KI) efficiencies (≈ 2-20 %) in human induced pluripotent stem cells (hiPSCs) and human embryonic stem cells (hESCs). This limitatio...
Precise gene editing with conventional CRISPR/Cas9 is often constrained by low knock-in (KI) efficiencies (≈ 2-20 %) in human induced pluripotent stem cells (hiPSCs) and human embryonic stem cells (hESCs). This limitation typically necessitates labour-intensive manual isolation and genotyping of hundreds of colonies to identify correctly edited cells. Fluorescence- or antibiotic-based enrichment methods facilitate the identification process but can compromise cell viability and genomic integrity. Here, we present a footprint-free editing strategy that combines low-density seeding with next-generation sequencing (NGS) to rapidly identify cell populations containing precisely modified clones. By optimising the transfection workflow and adhering to CRISPR/Cas9 KI design principles, we achieved high average editing efficiencies of 64 % in hiPSCs (introducing a Brugada syndrome-associated variant) and 51 % in hESCs (introducing a neurodevelopmental disorder (NDD)-associated variant). Furthermore, under suboptimal CRISPR design conditions, this approach successfully identified hESC clones carrying a second NDD-associated variant, despite average KI efficiencies below 1 %. Importantly, genomic integrity was preserved throughout subcloning rounds, as confirmed by Sanger sequencing and single nucleotide polymorphism (SNP) array analysis. Hence, this NGS-based enrichment strategy reliably identifies desired KI clones under both optimal and challenging conditions, reducing the need for extensive colony screening and offering an effective alternative to fluorescence- and antibiotic-based selection methods.
Robust temporal knowledge inference via pathway snapshots with liquid neural network.
Han P, Wang J, Liu D … +2 more , Liu L, Song T
Methods · 2025 Sep · PMID 40349883 · Publisher ↗
Static graphs play a pivotal role in modeling and analyzing biological and biomedical data. However, many real-world scenarios-such as disease progression and drug pharmacokinetic processes-exhibit dynamic behaviors. Con...
Static graphs play a pivotal role in modeling and analyzing biological and biomedical data. However, many real-world scenarios-such as disease progression and drug pharmacokinetic processes-exhibit dynamic behaviors. Consequently, static graph methods often struggle to robustly address new environments characterized by complex and previously unseen relationship changes. Here, we propose a method for constructing temporal knowledge inference agents tailored to disease pathways, enabling effective relation reasoning beyond their training environment under complex shifts. To achieve this, we developed an imitation learning framework using liquid neural networks, a class of continuous-time neural models inspired by the brain function that are causal and adaptable to changing conditions. Our findings indicate that liquid agents can distill the essential tasks from knowledge graph inputs while accounting temporal evolution, thereby enabling the transfer of temporal skills to novel time nodes. Compared to state-of-the-art deep reinforcement learning agents, experiments demonstrate that temporal robustness in decision-making emerges uniquely in liquid networks.
Electrochemical assay for the quantification of anticancer drugs and their inhibition mechanism.
Branco Leote RJ, Sanz CG, Diculescu VC … +1 more , Barsan MM
Methods · 2025 Sep · PMID 40345605 · Publisher ↗
Overexpression of pyruvate kinase (PyK) is linked to many kinds of malignant tumors, representing therefore one of the most promising therapeutic targets for cancer treatment. Inhibition of PyK slows down tumor growth or...
Overexpression of pyruvate kinase (PyK) is linked to many kinds of malignant tumors, representing therefore one of the most promising therapeutic targets for cancer treatment. Inhibition of PyK slows down tumor growth or causes tumor cell death, minimizing cancer cell proliferation, and understanding inhibitor mechanism of action can significantly improve cancer therapy. The present work describes the use of an amperometric bienzymatic biosensor, based on PyK and pyruvate oxidase (PyOx), in enzyme inhibition studies of four kinase inhibitors, CPG77675, Nilotinib, Ruxolitinib, Cerdulatinib. Their inhibition mechanism is studied and discussed in detail, with a thorough evaluation of their enzyme-inhibitor complex binding constants (K) and the inhibitor concentration required for 50% inhibition (IC), employing standard inhibition procedure graphical methods. The biosensor is successfully applied for the quantification of the inhibitors by fixed potential amperometry, with excellent detection limit values in the pM range. It is the first detection method reported for the anticancer drugs CPG77675 and Cerdulatinib. The electrochemical assay based on the biosensor brings several advantages over the available assay kits for high-throughput screening (HTS) of kinase inhibitors, namely: low cost, easy operability and robustness demonstrated by biosensor high reproducibility and both operational and storage stability, offering an opportunity to discover new inhibitors and optimize their therapeutic index.
Optical pooled screening for the discovery of regulators of the alternative lengthening of telomeres pathway.
Quintanilla I, Azeroglu B, Sagar MAK … +3 more , Stracker TH, Denchi EL, Pegoraro G
Methods · 2025 Sep · PMID 40324704 · Full text
Telomere elongation is essential for the proliferation of cancer cells. Telomere length control is achieved either by the activation of the telomerase enzyme, or by the recombination-based Alternative Lengthening of Telo...
Telomere elongation is essential for the proliferation of cancer cells. Telomere length control is achieved either by the activation of the telomerase enzyme, or by the recombination-based Alternative Lengthening of Telomeres (ALT) pathway. ALT is active in about 10-15% of human cancers, but its molecular underpinnings remain poorly understood, preventing the discovery of potential novel therapeutic targets. Pooled CRISPR-based functional genomic screens enable the unbiased discovery of molecular factors involved in cancer biology. Recently, Optical Pooled Screens (OPS) have significantly extended the capabilities of pooled functional genomics screens to enable sensitive imaging-based readouts at the single cell level and large scale. To gain a better understanding of the ALT pathway, we developed a novel OPS assay that employs telomeric native DNA FISH (nFISH) as an optical quantitative readout to measure ALT activity. The assay uses standard OPS protocols for library preparation and sequencing. As a critical element, an optimized nFISH protocol is performed before in situ sequencing to maximize the assay performance. We show that the modified nFISH protocol faithfully detects changes in ALT activity upon CRISPR knock-out (KO) of the FANCM and BLM genes, which were previously implicated in ALT. Overall, the OPS-nFISH assay is a reliable method that can provide deep insights into the ALT pathway in a high-throughput format.
CRISPR revolution: Unleashing precision pathogen detection to safeguard public health and food safety.
Liberty JT, Bromage S, Peter E … +3 more , Ihedioha OC, Alsalman FB, Odogwu TS
Methods · 2025 Aug · PMID 40311721 · Publisher ↗
Foodborne pathogens represent a significant challenge to global food safety, causing widespread illnesses and economic losses. The growing complexity of food supply chains and the emergence of antimicrobial resistance ne...
Foodborne pathogens represent a significant challenge to global food safety, causing widespread illnesses and economic losses. The growing complexity of food supply chains and the emergence of antimicrobial resistance necessitate rapid, sensitive, and portable diagnostic tools. CRISPR technology has emerged as a transformative solution, offering unparalleled precision and adaptability in pathogen detection. This review explores CRISPR's role in addressing critical gaps in traditional and modern diagnostic methods, emphasizing its advantages in sensitivity, specificity, and scalability. CRISPR-based diagnostics, such as Cas12 and Cas13 systems, enable rapid detection of bacterial and viral pathogens, as well as toxins and chemical hazards, directly in food matrices. Their integration with isothermal amplification techniques and portable biosensors enhances field applicability, making them ideal for decentralized and real-time testing. Additionally, CRISPR's potential extends beyond food safety, contributing to public health efforts by monitoring antimicrobial resistance and supporting One Health frameworks. Despite these advancements, challenges remain, including issues with performance in complex food matrices, scalability, and regulatory barriers. This review highlights future directions, including AI integration for assay optimization, the development of universal CRISPR platforms, and the adoption of sustainable diagnostic solutions. By tackling these challenges, CRISPR has the potential to redefine global food safety standards and create a more resilient food system. Collaborative research and innovation will be critical to fully unlocking its transformative potential in food safety and public health.
Challenges, optimization strategies, and future horizons of advanced deep learning approaches for brain lesion segmentation.
Zaman A, Yassin MM, Mehmud I … +4 more , Cao A, Lu J, Hassan H, Kang Y
Methods · 2025 Jul · PMID 40306473 · Publisher ↗
Brain lesion segmentation is challenging in medical image analysis, aiming to delineate lesion regions precisely. Deep learning (DL) techniques have recently demonstrated promising results across various computer vision...
Brain lesion segmentation is challenging in medical image analysis, aiming to delineate lesion regions precisely. Deep learning (DL) techniques have recently demonstrated promising results across various computer vision tasks, including semantic segmentation, object detection, and image classification. This paper offers an overview of recent DL algorithms for brain tumor and stroke segmentation, drawing on literature from 2021 to 2024. It highlights the strengths, limitations, current research challenges, and unexplored areas in imaging-based brain lesion classification based on insights from over 250 recent review papers. Techniques addressing difficulties like class imbalance and multi-modalities are presented. Optimization methods for improving performance regarding computational and structural complexity and processing speed are discussed. These include lightweight neural networks, multilayer architectures, and computationally efficient, highly accurate network designs. The paper also reviews generic and latest frameworks of different brain lesion detection techniques and highlights publicly available benchmark datasets and their issues. Furthermore, open research areas, application prospects, and future directions for DL-based brain lesion classification are discussed. Future directions include integrating neural architecture search methods with domain knowledge, predicting patient survival levels, and learning to separate brain lesions using patient statistics. To ensure patient privacy, future research is anticipated to explore privacy-preserving learning frameworks. Overall, the presented suggestions serve as a guideline for researchers and system designers involved in brain lesion detection and stroke segmentation tasks.
Breaking barrier of binding buffer in colorimetric aptasensing of tetracycline in food fish using peroxidase mimic gold NanoZyme.
Sarkar DJ, Raja R, Santhana Kumar V … +4 more , Bhattacharyya S, Pal S, Mukherjee S, Das BK
Methods · 2025 Aug · PMID 40306472 · Publisher ↗
Tetracycline is extensively used in aquaculture as a therapeutic agent that needs to be monitored due to food safety concerns. Aptasensing has been revealed as a suitable diagnostic platform for tetracycline sensing in f...
Tetracycline is extensively used in aquaculture as a therapeutic agent that needs to be monitored due to food safety concerns. Aptasensing has been revealed as a suitable diagnostic platform for tetracycline sensing in food matrix due to its quick, low cost and robust nature. But, the colorimetric aptasensing of tetracycline employing the peroxidase activity of gold nanoparticles (AuNPs) to 3,3,5,5-tetramethylbenzidine (TMB) was unsuitable until now owing to the aptamer-specific alkaline binding buffer. The present study developed a method with an optimized reaction protocol diminishing the inhibitory effect of binding buffer on the sensor probe (AuNPs-aptamer + TMB + HO). The overall peroxidase activity of the sensor probe was only inhibited by tetracycline through selective adsorption on the AuNPs-aptamer complex. The peroxidase inhibition percentage in the test range of 0.01 to 0.5 mg L tetracycline gave a logarithmic response (R, 0.99) with a detection limit of 0.017 mg L which is less than the prescribed limit (0.1 mg L) set by EU and FSSAI. The developed sensing system in fish muscle showed high recovery (111-115 %) with great potential for rapid detection of tetracycline in fish muscle.
Drug-target interaction prediction based on metapaths and simplified neighbor aggregation.
Yu D, Yang X, Shang Y … +3 more , Yuan S, Liu Y, Liu Y
Methods · 2025 Aug · PMID 40288620 · Publisher ↗
Drug-target interaction (DTI) prediction is critical in drug repositioning and discovery. In current metapath-based prediction methods, attention mechanisms are often used to differentiate the importance of various neigh...
Drug-target interaction (DTI) prediction is critical in drug repositioning and discovery. In current metapath-based prediction methods, attention mechanisms are often used to differentiate the importance of various neighbors, enhancing the model's expressiveness. However, in biological networks with small-scale imbalanced data, attention mechanisms are prone to interference from noise and missing data, leading to instability in weight learning, reduced efficiency, and an increased risk of overfitting. To address these issues, we propose the use of average aggregation to mitigate noise, simplify model complexity, and improve stability. Specifically, we introduce a simplified mean aggregation method for DTI prediction. This approach uses average aggregation, effectively reducing noise interference, lowering model complexity, and preventing overfitting, making it especially suitable for current biological networks. Extensive testing on three heterogeneous biological datasets shows that SNADTI outperforms 12 leading methods across two evaluation metrics, significantly reducing training time and validating its effectiveness in DTI prediction. Complexity analysis reveals that our method offers a substantial computational speed advantage over other methods on the same dataset, highlighting its enhanced efficiency. Experimental results demonstrate that SNADTI excels in prediction accuracy, stability, and reproducibility, confirming its practicality and effectiveness in DTI prediction.
Enabling high-resolution diagnostic oral confocal laser endomicroscopy in mice.
Celentano A, Rickard JA, Low J … +10 more , Silke N, Mohammed AI, Moslemi E, Ramani RS, De Souza Franca PD, Reiner T, McCullough MJ, Yap T, Silke J, O'Reilly LA
Methods · 2025 Jul · PMID 40287077 · Publisher ↗
Therapeutic prevention of oral squamous cell carcinoma (OSCC) will avoid significant morbidity and mortality. To observe and measure the in vivo efficacy of therapeutic challenges, microscopic-level diagnosis without ani...
Therapeutic prevention of oral squamous cell carcinoma (OSCC) will avoid significant morbidity and mortality. To observe and measure the in vivo efficacy of therapeutic challenges, microscopic-level diagnosis without animal sacrifice is required. This study introduces a refined diagnostic methodology for non-invasive cellular-level imaging for diagnosis of micro-lesions by utilizing high-resolution scanning-fibre confocal laser endomicroscopy (ViewnVivo) with topical fluorescence imaging agents. We detail the development and standardization of imaging protocols using a fluorescent, cell-permeable cancer-targeting agent (PARPi-FL) as a cancer-targeting agent and a pan-cytoarchitectural (acriflavine) agent in a pre-clinical murine 4-NQO induced OSCC model. We provide comprehensive methodology for the in vivo identification of the progressive stages of oral carcinogenesis from microscopic lesions, supported by an annotated signature guide correlating with conventional histopathology. Our findings demonstrate that in vivo CLE imaging with both PARPi-FL and acriflavine clearly distinguishes between histologically normal and pathological oral tissue. Tissues with histologic dysplasia and carcinoma demonstrated PARPi-FL positivity and an aberrant nuclear staining pattern with acriflavine, compared to the regularly spaced nuclear staining of normal nuclei. Crucially, this methodology detects microscopic changes not visible to the naked eye, but histologically abnormal. Our observation model of progressive oral carcinogenesis has the potential to accelerate standardised interrogation of early molecular diagnostic applications and novel therapeutic efficacy, whilst reducing the need for animal sacrifice. This will result in faster validated translation to human applications, advancing effective early oral cancer detection and prevention.
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