Methods (San Diego, Calif.)[JOURNAL]
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200 papers
From sample to clinical insight: a review of exome sequencing in disease diagnostics.
Manjunath GK, Verma RK, Berua A … +3 more , Mahalingam S, Dakal TC, Kumar A
Methods · 2026 Feb · PMID 41271122 · Publisher ↗
Exome sequencing (ES) has transformed genomic research and clinical diagnostics by enabling precise identification of disease-associated variants within protein-coding regions, which, while representing a minority of the...
Exome sequencing (ES) has transformed genomic research and clinical diagnostics by enabling precise identification of disease-associated variants within protein-coding regions, which, while representing a minority of the genome, include many well-characterized pathogenic mutations. This review provides a comprehensive overview of ES methodology, data analysis pipelines, clinical relevance, and ethical considerations. We describe the ES workflow from DNA extraction and library preparation to target enrichment, sequencing to ES data analysis. We have also evaluated major capture technologies and sequencing platforms, including short-read and emerging long-read systems. Furthermore, we discuss computational analysis tools such as GATK, FreeBayes, DeepVariant, and Platypus, and strategies to improve accuracy through rigorous quality control, coverage optimization, and orthogonal validation. Beyond rare disease and cancer genomics, ES has expanded into pharmacogenomics, population-scale studies, and integrative multi-omics frameworks that combine transcriptomic and proteomic data to enhance functional interpretation. We highlight actionable examples such as CYP2C19 variants influencing clopidogrel metabolism, illustrating ES's growing role in personalized medicine. Challenges (including variant interpretation complexity, false positives, and data standardization) are critically discussed. The review also addresses ethical, legal, and social dimensions of ES, including informed consent, data privacy, incidental findings, and adherence to ACMG, HIPAA, and GDPR. Finally, we outline future directions emphasizing machine learning-based variant prioritization, single-cell sequencing integration, and scalable bioinformatics infrastructures to enhance accuracy and clinical translation. Collectively, these developments position ES as a pivotal tool bridging genomic discovery, disease diagnostics, and precision healthcare in the era of personalized medicine.
Toward accurate breast cancer classification: A review of multi-modal machine learning approaches.
Mathur A, Dudhiyawala AM, Dey SR … +1 more , Saha S
Methods · 2026 Feb · PMID 41265505 · Publisher ↗
The innovations in classifying breast cancer into malignant and benign categories and further categorizing it into molecular subtypes have reshaped healthcare services, enabling accurate diagnosis of these complex condit...
The innovations in classifying breast cancer into malignant and benign categories and further categorizing it into molecular subtypes have reshaped healthcare services, enabling accurate diagnosis of these complex conditions. Identification of molecular subtypes of breast cancer is one of the most important treatment challenges, as these subtypes can have an enormous effect on the prognosis and treatment approaches. Data integration from various modalities, such as transcriptomics, imaging, and genomics, has been crucial in leveraging new opportunities to increase classification accuracy and improve individualized treatment plans. These heterogeneous data sources are examined by applying deep learning algorithms, which provide further insights into the complex patterns that traditional approaches often overlook. In this paper, we explore the various modalities researchers use to investigate breast cancer and the intriguing fusion techniques employed to combine these modalities. We also review the most recent models (traditional, machine learning, and deep learning), emphasizing their improvements over traditional classification methods and the molecular subtype categorization of breast cancer. Furthermore, the emphasis of this review is to examine techniques to process the entire image of the breast tissue slide, which is challenging, particularly due to its size. We explore recent advances in multiple instance learning tasks and the use of attention-based transformers and similar architectures for annotating the WSI slides before using them for cancer classification. We additionally discuss the interpretability tools-attention maps, saliency maps and model explainability- in the context of transformers. In a nutshell, we aim to provide an in-depth look at the revolutionary capabilities of deep learning models in precision oncology and guide future research paths in this crucial field by synthesizing existing studies.
Unravelling cell heterogeneity and gene regulation mechanisms in multiple myeloma through single-cell RNA-seq.
Jiang J, Xu J, Wang P … +2 more , Liu Y, Liu Y
Methods · 2026 Feb · PMID 41253222 · Publisher ↗
Multiple myeloma (MM) is the second most common blood cancer in the world, yet its genetic pathology is not fully understood and MM cells have highly heterogeneous regulatory mechanisms. Single-cell RNA-Sequencing (scRNA...
Multiple myeloma (MM) is the second most common blood cancer in the world, yet its genetic pathology is not fully understood and MM cells have highly heterogeneous regulatory mechanisms. Single-cell RNA-Sequencing (scRNA-Seq) technologies provide an unprecedented opportunity to investigate cell heterogeneity and understand regulatory mechanisms at the single-cell level. Four MM scRNA-Seq datasets were retrieved from the public domain containing 597, 172, 477, and 51,840 cells, respectively. First, they were integrated and jointly analyzed to accurately identify 24 MM cell clusters, using a normal hematopoiesis cells atlas as a control. Then we predicted 651 regulons within the 24 MM cell clusters. The identified regulons can substantially improve the elucidation of heterogeneous gene regulation mechanisms across various cell clusters, and hence can serve as a reference for diagnosis in MM.
Natural language processing.
Le NQK, Chua MCH
Methods · 2026 Jan · PMID 41238069 · Publisher ↗
Abstract loading — click title to view on PubMed.
Scale-adjusted distance transform and its applications to segmentation of multimodal images.
Das N, Basu S, Saha PK
Methods · 2026 Jan · PMID 41207402 · Publisher ↗
Distance transform (DT) is widely used for structural analysis of multi-dimensional (mainly 2-D and 3-D) objects. Association of DT values with local structure scale, often, adds challenges and limits the scope of applic...
Distance transform (DT) is widely used for structural analysis of multi-dimensional (mainly 2-D and 3-D) objects. Association of DT values with local structure scale, often, adds challenges and limits the scope of applications of DT in relative structural analysis among multiple objects with varying scales. In this paper, we introduce a new notion of scale-adjusted distance transform (SADT), conceptually different from traditional DT, which is independent of object scale and offers DT values of scale varying objects on a uniform scale with the value of '1' at ridges. It has been shown that scale-adjusted distance is a metric function in a continuous Euclidean space, and SADT generates a normalized field that is invariant under translation, rotation, and isotropic scaling. The computational method for digital objects traces gradient flow paths on a conventional DT field and uses the change in velocity along a digital path to detect local ridges, which are then used to generate a scale-adjusted density (SAD) field. Finally, SADT is computed using the SAD value. The results of applying the method on 2-D and 3-D multimodal image datasets are presented. Two real-life applications of SADT are shown: 1) segmentation of conjoined nuclei from 2-D microscopic images, and 2) multi-scale separation of conjoined artery-vein in 3-D pulmonary CT image of a pig lung phantom. SADT outperforms the traditional marker-controlled watershed algorithm in conjoined nuclei segmentation from 2-D images and achieves highly accurate multi-scale artery-vein separation in the pig lung phantom experiment. The performance of SADT is invariant to image dimension and imaging modality. Unlike modern deep learning methods, the proposed fuzzy method is transparent and data modality independent. The source code and sample data are freely available at: https://github.com/CMATERJU-BIOINFO/Scale-Adjusted-Distance-Transform.
Disease-related omics data analysis.
Peng W, Cai Z
Methods · 2026 Feb · PMID 41192634 · Publisher ↗
Abstract loading — click title to view on PubMed.
Carboxyl-PEG modified FeO nanoparticles as an ultrasensitive SERS substrate for multiplex detection of exogenous hormones related to endometrial cancer.
Chen B, Gao J, Sun H … +3 more , Zhao Y, Liu Y, Qiu X
Methods · 2026 Jan · PMID 41192633 · Publisher ↗
Traditional surface-enhanced Raman scattering (SERS) technology often struggles to achieve high-precision discrimination in the simultaneous detection of multiple exogenous hormones due to complex spectral overlap and ma...
Traditional surface-enhanced Raman scattering (SERS) technology often struggles to achieve high-precision discrimination in the simultaneous detection of multiple exogenous hormones due to complex spectral overlap and matrix interference, limiting its application in trace analyte analysis within complex matrices (e.g., biological samples). This study developed a SERS substrate based on carboxyl-terminal polyethylene glycol (PEG)-modified iron oxide (FeO) nanoparticles (FeO@PEG), integrated with artificial intelligence (AI)-driven high-throughput spectral analysis algorithms. This approach successfully enabled ultrasensitive detection and precise discrimination of multiple typical exogenous hormonal drugs, including tamoxifen, drospirenone, cyproterone acetate, medroxyprogesterone acetate, estradiol ester derivatives, and dydrogesterone. By optimizing the surface enhancement effect of FeO@PEG nanocomposites and employing machine learning models (e.g., convolutional neural networks, CNN) for collaborative analysis, the weak Raman fingerprint features of target hormones in complex mixtures were effectively extracted and classified, achieving a detection limit at the corresponding to 10-10 mg/mL level. In matrix-spiked serum and urine samples, which mimic complex biological matrices validations, the AI-SERS platform demonstrated exceptional performance in the identification and quantitative analysis of target exogenous hormones. This research provides an intelligent analytical strategy for rapid and highly sensitive detection of multiple trace exogenous hormones in complex matrices.
Membrane-mediated strategies for efficient intracellular delivery of biologics.
Gang D, Song Y, Ko Y
Methods · 2026 Jan · PMID 41173234 · Publisher ↗
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 conditi...
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.
Materials-Based spatiotemporal analysis of microbial responses to glyphosate in Winogradsky columns.
Itani A, Velaz Martín M, Meisch L … +5 more , Lemke P, Scharnweber T, Khattab IM, Rabe KS, Niemeyer CM
Methods · 2026 Jan · PMID 41167541 · Publisher ↗
Glyphosate, the active ingredient in many broad-spectrum herbicides, is extensively used in agriculture but has come under increasing scrutiny due to its potential impacts on non-target microbial communities. To investig...
Glyphosate, the active ingredient in many broad-spectrum herbicides, is extensively used in agriculture but has come under increasing scrutiny due to its potential impacts on non-target microbial communities. To investigate these effects within a controlled yet ecologically relevant framework, Winogradsky columns, self-contained sediment-based ecosystems, were employed as a model system. A novel, non-destructive sampling approach was introduced using macroporous elastomeric silicone foam (MESIF) integrated in stainless-steel frames to enable spatiotemporal monitoring of benthic microbial communities. These MESIF-loaded frames were vertically embedded in columns filled with lake sediment and subjected to varying experimental conditions, including light exposure and glyphosate treatment. Microbial colonization of the MESIF was assessed via amplicon sequencing at defined time points. Glyphosate-treated columns exhibited delayed microbial stratification and diminished development of characteristic pigmentation associated with functional groups such as iron-oxidizing and sulfate-reducing bacteria. Although within-column alpha diversity remained relatively constant, glyphosate exposure led to distinct shifts in community composition, including an increased abundance of taxa potentially involved in glyphosate degradation. These findings demonstrate the effectiveness of combining Winogradsky columns with MESIF-based sampling for studying environmental stressors and underscore glyphosate's influence on microbial succession and functional diversity in sediment ecosystems.
Comprehensive analysis of the inhibition of aldehyde dehydrogenase from Flavobacterium PL002 and its coupling with SERS as a path for the selective detection of thiram.
Ftodiev AI, Petrareanu GN, Puiu M … +15 more , Proteasa G, Munteanu CVA, Banciu RM, Chauhan R, Visinescu D, Purcarea C, Fanjul-Bolado P, Ibañez D, Fogel R, Limson J, Potara M, Bonciu AF, Astilean S, Bala C, Vasilescu A
Methods · 2026 Jan · PMID 41109437 · Publisher ↗
The selective detection of dithiocarbamate fungicides in food and agricultural products presents significant analytical challenges. While Surface-enhanced Raman spectroscopy (SERS) has been extensively investigated to ad...
The selective detection of dithiocarbamate fungicides in food and agricultural products presents significant analytical challenges. While Surface-enhanced Raman spectroscopy (SERS) has been extensively investigated to address this, detection systems based on enzymatic inhibition remain underexplored. Using thiram as a model dithiocarbamate, the present work explores the potential application of a cold-active aldehyde dehydrogenase from Flavobacterium PL002 for the development of specific, inhibition-based analytical methods. A molecular modelling and docking study confirmed that thiram fits into the binding pocket of the enzyme. An irreversible inhibition mechanism was inferred for thiram based on enzymatic kinetics studies. The mechanism was supported by SERS, mass spectrometry measurements and tests with reducing agents. A simple assay for the detection of the fungicide was developed and compared to a SERS-based procedure. The advantages and the practical limitations of the two methods were revealed by studying the detection of thiram from the surface of fungicide-spiked tomatoes. By coupling enzymatic inhibition with SERS, the selectivity for the detection of individual fungicides can be increased, as illustrated by comparing thiram with ziram, a structurally related compound. The study serves as basis for the development of analytical methods for the selective detection of thiram.
Novel primer-less amplification method for detection of RNA molecules.
Prado AD, Martínez-Jiménez MI, Blanco L … +1 more , de Vega M
Methods · 2025 Dec · PMID 41109436 · Publisher ↗
As shown here, isothermal and primer-less amplification of specific padlock probes allows direct detection of SARS-CoV2 RNA without needing for a reverse transcription step. This simplified method of Hyperbranched Rollin...
As shown here, isothermal and primer-less amplification of specific padlock probes allows direct detection of SARS-CoV2 RNA without needing for a reverse transcription step. This simplified method of Hyperbranched Rolling Circle Amplification (HRCA) only requires three enzymes: SplintR (to ligate a specific padlock probe to its circular form, only when viral RNA is present), the unique DNA primase TthPrimPol (to generate de novo DNA primers), and an engineered and thermostabilized variant of bacteriophage phi29 DNA polymerase (phi29 DNApol), named Qx5. Qx5 is significantly more efficient than wild-type phi29 DNApol and shows an unexpectedly strong 3'-5' exoribonucleolytic activity capable of trimming the 3' polyA tail of the RNA target, thus enabling it as a primer for Qx5 to start Rolling Circle Amplification (RCA) of a nearby circularized padlock. The RCA step, that yields a long ssDNA concatemeric product (RCA product, RCP) is coupled to a second isothermal amplification step, assisted by TthPrimPol by synthesizing DNA primers on the RCP, that triggers exponential HRCA of the padlock sequence, catalyzed by Qx5. As a proof of concept, the application of this method for detection of SARS-CoV2 RNA rendered a significant amount of DNA in just 2 h at 37 °C, that can be easily evidenced by colorimetry, or even quantitated with a pocket fluorometer, and served for a quick diagnosis of SARS-CoV2 RNA infected versus non-infected samples.
Authentication of Panax notoginseng with high-efficiency Proofman-LMTIA technology.
Zhang X, Li C, Wang Y … +4 more , Cao Y, He X, Xiao F, Wang D
Methods · 2025 Dec · PMID 41101611 · Publisher ↗
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 o...
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.
Zero-shot medical image classification via large multimodal models and knowledge graphs-driven processing.
Liu X, Wu Y, Zhou Y
Methods · 2026 Jan · PMID 41093082 · Publisher ↗
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 g...
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.
LabImageXpert: imaging platform for mechanism-resolved detection of antimicrobial activity via β-galactosidase assay.
Kharga K, Kumar D, Kumar L
Methods · 2025 Dec · PMID 41086936 · Publisher ↗
Antimicrobial resistance (AMR) has emerged as a global crisis, responsible for millions of deaths annually. Traditionally used antimicrobial susceptibility testing (AST) methods, such as disk diffusion and broth dilution...
Antimicrobial resistance (AMR) has emerged as a global crisis, responsible for millions of deaths annually. Traditionally used antimicrobial susceptibility testing (AST) methods, such as disk diffusion and broth dilution, suffer from limitations including prolonged incubation time, inconsistent results, and high instrumentation cost. To address these challenges, we present in this study our novel, cost-effective antimicrobial detection assay equipped with a highly sensitive quantification system, LabImageXpert. Our antimicrobial detection system leverages the ability of β-galactosidase to convert colorless X-gal to an intense insoluble blue colored product. Unlike traditional MIC assays, LabImageXpert enables image-based, mechanism-specific growth assessment. During our investigation, we tested compounds already known to possess antimicrobial properties against our antimicrobial assay and found that it could not only detect the antimicrobial activity but also reveal the mechanism of action behind their antimicrobial activity, i.e., bacteriostatic and bacteriolytic. Further, this system contains a high-resolution DSLR camera to image samples in a microtiter plate placed inside a special box. The captured images are processed using the open-source software. We performed an experiment exclusively to test its ability to quantify minute variations in bacterial growth over time. The results showed that it could detect minute deviations in average pixel intensity over time. LabImageXpert detected bacteriolytic activity of compounds within 3 h. Our findings suggest that the LabImageXpert provides a reproducible, scalable, and cost-effective alternative platform for antimicrobial research in teaching, research and clinical diagnostic labs.
Gelatin methacryloyl - thiolated graphene oxide composites for soft tissue engineering.
Shiravandi A, Zarkesh I, Ghasemian M … +6 more , Kazemi Ashtiani M, Bayazian G, Asghari A, Alizadeh R, Bagher Z, Davachi SM
Methods · 2025 Dec · PMID 41082953 · Publisher ↗
Soft tissue engineering represents a transformative solution for regenerating damaged tissues, with the development of advanced hydrogels playing a crucial role in this process. Gelatin methacryloyl (GelMA) has emerged a...
Soft tissue engineering represents a transformative solution for regenerating damaged tissues, with the development of advanced hydrogels playing a crucial role in this process. Gelatin methacryloyl (GelMA) has emerged as a promising material due to its biocompatibility and ability to support cell growth; however, its mechanical limitations have driven the exploration of composite hydrogels, with thiolated graphene oxide (tGONS) standing out as a key additive. In this study, we present a novel strategy involving thiolated graphene oxide nanosheets (tGONS) as covalent crosslinkers within the GelMA hydrogel matrix, wherein thiol groups on tGONS react with GelMA's acrylate groups, enhancing crosslinking and strengthening the hydrogel network. The results demonstrate that incorporation of tGONS at optimized concentrations (≤0.5 mg/mL) leads to a substantial increase in Young's modulus and gel fraction, along with a marked enhancement in antioxidant activity, evidenced by up to 40 % DPPH and 60 % HO scavenging in G1GTII formulations. Despite the increased stiffness, acceptable elongation and high cytocompatibility (>85 % cell viability) were maintained. Additionally, the composite hydrogels showed improved resistance to enzymatic degradation and reduced swelling, offering more precise control over physicochemical properties.These findings highlight the multifunctional advantages of GelMA-tGONS composite hydrogels, positioning them as adaptable and robust scaffolds suitable for applications in soft tissue engineering, including cartilage, dermal, and neural regeneration.
HI-CeFSpot: High-throughput Immune Cell FluoroSpot assay.
Jethmalani Y, Sutton MS, Carroll R … +17 more , Kazmierski R, Low K, Mughal M, Bullock J, Lindestam Arlehamn CS, Lewinsohn DM, Lewinsohn DA, Lehman CC, Green C, Moshi J, Mueller A, Darrah PA, Seder RA, Lin BC, Koup RA, Serebryannyy LA, Roederer M
Methods · 2025 Dec · PMID 41067553 · Publisher ↗
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. Fluor...
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.
ZEMs: Zebrafish embedding molds for high-throughput imaging of zebrafish embryos and larvae.
Sim Y, Lee E, Jeong J
Methods · 2025 Dec · PMID 41046991 · Publisher ↗
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...
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.
Comparative analysis of macroscopic and microscopic optical absorbance in hemagglutination assay.
Jeon DG, Lee CY, Cho CH … +3 more , Lee GH, Chang Y, Nam SW
Methods · 2025 Dec · PMID 41046990 · Publisher ↗
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 Sore...
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.
UHPLC-Orbitrap-MS/MS metabolite profiling combined with HPLC-PDA targeted chemical fingerprint reveals the geographic-environment (G × E) effect on chemical constituents of Bilvamula (Aegle marmelos root).
Ramdas, Singh M, Singh AP … +2 more , Tiwari N, Shanker K
Methods · 2025 Dec · PMID 41046004 · Publisher ↗
Aegle marmelos (AM) (Rutaceae family) holds significant economic value due to its uses in food, traditional medicines, and timber. Studies have confirmed that its extracts and phytochemicals possess various pharmacologic...
Aegle marmelos (AM) (Rutaceae family) holds significant economic value due to its uses in food, traditional medicines, and timber. Studies have confirmed that its extracts and phytochemicals possess various pharmacological actions, including anti-obesity, diuretic, anti-inflammatory, and chemopreventive. However, challenges remain due to the limited information on its secondary metabolites and the lack of validated methodologies. Natural variability in the raw material further complicates the assessment of therapeutic efficacy. Hence, we have conducted the untargeted metabolite profiling of A. marmelos root (AMR) using UHPLC-Orbitrap-MS/MS analysis, identifying 69 phytochemicals of diverse classes. Additionally, we have isolated and characterised 09 key phytochemicals to evaluate the chemical variability in AMR from 15 geographical locations. HPLC-PDA method, compliant with ICH Q2 (R2) guidelines, was developed and validated to quantitate 02 alkaloids (skimmianine, O-Methyl tembamide) and 07 coumarins [umbelliferone, xanthotoxol, marmin, and 7-(6-Hydroxy-7-methoxy-3,7-dimethyl-(2E)-2-octenyloxy) coumarin, 7-(3,7-Dimethyl-6-oxo-(2E)-2-octenyloxy) coumarin, marmelosin, and auraptene]. Chemometric analysis has distinguished 15 AMR ecotypes, and hierarchical cluster analysis resulted in AM-S4 as a distinctive ecotype, which was verified by principal component analysis with 96 % data variance. Partial least square-discriminate analysis predicted a relationship between targeted metabolites and ecotypes. The metabolites associated with a discriminatory pattern of AMR ecotypes were identified by variable importance for projection (VIP) score. Unlike previous reports, the present method fulfils the ISO: 17025-2017 requirement by evaluating the measurement of uncertainty (MU) to ensure the accuracy and traceability of the results. Overall, present study summarises comprehensive metabolite profiling, multi-components classification of AMR to define genetic-environment (G × E) effect, and quality evaluation of AMR derived medicinal product.
Modern membrane biophysics approaches.
Barrera FN
Methods · 2025 Dec · PMID 41016459 · Publisher ↗
Abstract loading — click title to view on PubMed.
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