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شواهد علوم پایه پزشکی
PubMed2027
A Standardized Protocol for Generating iPSC-Derived Human Microglia for Functional Genomic Assays.
Human induced pluripotent stem cell (iPSC)-derived microglia (iMG) provide an in vitro experimental system for studying human microglial biology, neuroinflammation, and genetic risk mechanisms associated with neurological disease. This chapter describes a standardized, scalable, and reproducible protocol for the differentiation of human iPSCs into functional microglia-like cells, with particular emphasis on applications in transcriptional and epigenomic network analysis. The protocol supports high-viability floating iMG production, compatibility with pooled CRISPR perturbation approaches, and downstream multiomic profiling, including single-cell RNA sequencing, chromatin accessibility assays, and proteomics. Detailed procedures are provided for iPSC maintenance, hematopoietic progenitor cell generation, microglial maturation, functional genomics integration, and quality control.
PubMed2027
Chikungunya Virus Infection in Paraffin-Embedded Tissue: Analysis of Histological Alterations and Viral Detection by Immunohistochemistry.
Histopathological analysis of tissues infected with Chikungunya virus (CHIKV), including biopsy and autopsy specimens, can provide valuable insights into the pathogenesis of atypical and fatal cases. By examining tissue architecture and cellular alterations under the microscope, it is possible to identify patterns of injury, inflammation, and cellular degeneration. These morphological findings provide evidence of how the pathogen interacts with host cells and tissues. Moreover, immunohistochemistry may be performed in tissue sections for the detection of viral antigens. Importantly, this technique allows the characterization of diverse biologically relevant targets in tissue samples, such as distinct immune cell subsets, cytokines, and additional molecular markers. This is accomplished by the use of antibodies selected for their specificity toward the antigen of interest. In this chapter, we present a concise overview of how histological analysis and immunohistochemical approaches can enhance the understanding of CHIKV-associated pathological mechanisms.
PubMed2027
Combined Lipidomic and Metabolomic Analyses on Cardiac Organoids.
Cardiac organoids are increasingly used to model human cardiac development and disease, but their small size often limits molecular characterization, especially if different approaches and protocols are necessary to extract and quantify metabolites and lipids. Here, we present a multistep workflow for combined targeted free amino-acid (FAA) based metabolomic and lipidomic profiling from a single pooled cardiac organoid sample. The protocol covers organoid harvesting, detergent-assisted lysis, and a modified Folch extraction that generates an organic phase for lipid analysis and an aqueous phase for FAA metabolite analysis. Lipids are quantified by Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS) in Multiple Reaction Monitoring (MRM) mode using class-matched external standards and an internal standard to support calibration and reduce technical variability. Free amino acids and derivatives are analyzed from the same sample after filtration, drying, and AccQ-Tag derivatization, with norvaline as an internal standard. Together, this approach maximizes information yield from limited material and enables integrated analysis of metabolic and lipid pathways within the same biological specimen, facilitating organoid-based studies of cardiac maturation, disease modeling, and pharmacological responses.
PubMed2027
CRISPR/Cas Systems: Biological Basis and Genome Editing Applications.
Clustered regularly interspaced short palindromic repeats (CRISPR) and associated (Cas) systems have revolutionized the field of genome engineering by providing versatile, efficient, and programmable tools for precise genetic manipulation. Originally identified as an adaptive immune mechanism in prokaryotes, CRISPR/Cas systems have been extensively repurposed for a wide range of applications across molecular biology, biotechnology, and medicine. This chapter provides a comprehensive overview of the molecular mechanisms underlying CRISPR/Cas immunity. Furthermore, the classification of CRISPR/Cas systems into distinct types and subtypes is discussed, highlighting their structural and functional diversity. Advances in genome editing technologies, including CRISPR-mediated knockout, base editing, and prime editing, are explored with an emphasis on their mechanisms and applications. The chapter also examines emerging CRISPR-based platforms for transcriptional regulation, epigenome editing, and RNA targeting, which enable precise and reversible modulation of gene expression without altering genomic DNA. In addition, the transformative impact of CRISPR technologies on functional genomics is addressed, particularly through high-throughput screening approaches that facilitate the identification of gene function and genetic vulnerabilities. CRISPR-based diagnostic tools and therapeutic strategies are also reviewed, underscoring their potential in disease detection and treatment. Despite significant progress, challenges such as off-target effects, delivery limitations, and safety concerns remain critical considerations. Overall, this chapter highlights the expanding capabilities of CRISPR/Cas systems and their growing importance in both fundamental research and clinical applications.
PubMed2027
Enrichment of Arabidopsis Plasma Membrane Proteins by Sequential Differential Centrifugation.
The plasma membrane (PM) is the primary interface between plant cells and their environment, and its resident proteins mediate key processes such as extracellular signal perception and downstream cellular reprogramming. Yet, PM proteins are typically underrepresented in total protein extracts, and existing enrichment strategies are often laborious and require extensive optimization. Here, a simple and robust workflow is described for enriching PM proteins from Arabidopsis thaliana seedlings using total microsomal membranes obtained by differential centrifugation as starting material. Sequential low- and high-speed spins are used to isolate total microsomal membranes and progressively deplete contaminating organelles, thereby increasing the relative abundance of PM proteins. Coupled with the rich genetic toolkit available in Arabidopsis, this protocol provides an accessible platform for systematic characterization of the PM proteome.
PubMed2027
Epitope Tagging and Coimmunoprecipitation to Identify Viral Protein Interactors.
Affinity purification-mass spectrometry (AP-MS) is a powerful proteomic approach for dissecting the interaction network between virus and host. Traditional AP-MS employs overexpression of viral proteins as baits to enrich host interactors. However, overexpressed viral proteins may mislocalize to inappropriate cellular compartments and trigger endoplasmic reticulum stress by overwhelming the protein-folding machinery, which leads to false identification of host factors. To overcome these limitations, we introduce an AP-MS strategy based on direct infection with an epitope-tagged chikungunya virus (CHIKV/myc-E2), which we used to successfully uncover two new antiviral factors in CHIKV cellular reservoirs-macrophages. In this protocol, we will describe this technique step by step: (1) design and construction of myc-tagged virus by advanced multi-fragment assembly, (2) in vitro transcription and preparation of infectious myc-tagged virus stocks, and (3) immunoprecipitation of myc-tagged viral protein and its interactome for mass spectrometry analysis. This strategy enables accurate identification of viral interactors in a physiologically relevant context, providing a framework for future proteomic studies using tagged viruses.
PubMed2027
Genome Assembly and Annotation of a Plant Pathogen Using the Example of Botrytis cinerea.
The availability of a high-quality genome assembly facilitates the analysis of fungal genomes. This chapter outlines the tools and steps involved in genome sequence assembly and annotation of a plant pathogen, Botrytis cinerea. We describe the use of Illumina short-read and Oxford Nanopore long-read sequencing data to assemble the B. cinerea genome. The steps include the pre-processing of sequencing data, genome assembly using Flye, scaffolding with NtLink, and polishing with Racon, Medaka, and NextPolish. The quality of the final assembly is evaluated using BUSCO, which serves as a benchmark for the completeness of a genome. We also provide details on the identification and masking of repetitive elements using the EarlGrey pipeline, as well as the gene prediction and annotation process with Funannotate. The methodologies and insights described can be applied to genome research in other fungal species.
PubMed2027
Genomic Profiling of Chromatin State Using CUT&Tag.
Alterations in chromatin state, mediated through histone modifications and the incorporation of histone variants, are fundamental to establishing transcriptional networks and cell identity. Recent advances in low-input epigenome profiling methods, such as CUT&Tag and CUT&RUN, have enabled the study of chromatin states from very limited starting materials. In this chapter, we describe procedures for generating CUT&Tag libraries to profile histone modifications and histone variants in early-developing zebrafish embryos.
PubMed2027
Global Genomic Surveillance.
Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.
PubMed2027
High-Throughput Sample Preparation for Plant (Phospho) Proteomics.
Mass spectrometry-based proteomics allows the unbiased identification and quantification of proteins and phosphopeptides in biological materials. The nature of walled plant cells requires specific protocols for effective and efficient protein isolation, and, in general, the plant sciences can benefit from more accessible, optimized proteomics workflows. Advances in MS instrumentation now allow the measurement of large numbers of samples, shifting constraints in proteomics toward the accurate, high-throughput preparation of samples. Here, we describe a high-throughput (phospho)proteomics protocol that enables processing of samples using different filter types in a 96-well format.
PubMed2027
Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.
Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.
PubMed2027
Identification of Mycoviral Infections.
High-throughput sequencing of total RNA has permitted the detection of novel mycoviruses in fungi with different types of genomes, including mycoviruses with double-stranded RNA, single-stranded positive- or negative-stranded RNA, or single-stranded DNA genomes. However, in silico detection of mycoviruses is not always sufficient to guarantee their presence in sequenced samples, especially in the case of the discovery of unique mycoviruses, and additional analyses are required to validate in vivo the data obtained by bioinformatics analysis. This chapter provides comprehensive protocols for the extraction of total RNA from the plant pathogenic fungus Botrytis cinerea for next-generation sequencing (NGS), outlines the bioinformatics pipeline designed and followed to detect mycoviruses in the sequenced samples, and details the detection in vivo and the complete molecular characterization of the mycoviruses identified in silico.
PubMed2027
Immunophenotyping by Single-Cell CITE-Seq.
Single-cell transcriptomics has revolutionized our understanding of cellular heterogeneity by enabling high-resolution gene expression profiling at the individual cell level. However, traditional single-cell RNA sequencing (scRNA-seq) lacks direct protein quantification, limiting comprehensive immunophenotyping. Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq) overcomes this limitation by integrating antibody-derived tag (ADT) quantification with scRNA-seq, allowing simultaneous measurement of surface protein and gene expression from the same cell. This multimodal approach enhances immune cell characterization, revealing new functional states and rare subpopulations in complex biological systems. Here, we provide a detailed protocol for performing CITE-seq, from sample preparation to sequencing and data analysis. We highlight key experimental considerations, discuss challenges related to antibody selection and batch effects, and provide troubleshooting strategies to ensure robust and reproducible results. The integration of transcriptomic and proteomic data through CITE-seq provides unparalleled insights into cellular function, with broad applications in immunology, oncology, and systems biology.
PubMed2027
Immunophenotyping by Spatial Biology.
Studying the transcriptome and the proteome of cells is essential for gaining a detailed understanding of cellular behavior, development, drug action, and disease progression. Spatial biology emerges to advance our ability to study the expression of molecules within tissues while preserving their natural spatial context. These cutting-edge technologies enable the mapping of thousands of individual cells in their original environment by detecting the location and biological quantity of cellular contents, such as RNAs and proteins. Here, we present a protocol to combine spatial transcriptomics (Xenium) and spatial proteomics (PhenoCycler-Fusion) within 8 days on the same tissue section to successfully study the expression of hundreds of RNAs and tens of proteins simultaneously. The combination of these two technologies and consequent integration of the two data layers together with high-resolution H&E images allows for the extraction of a maximum of information from a single tissue section. Application of this protocol and the resulting integrated data will help researchers to understand complex biological processes and disease mechanisms, supporting more nuanced research in molecular biology and pathology.
PubMed2027
Mass Spectrometry-Based Proteomics of Intestinal Organoids.
Proteomics, the large-scale study of proteins, enables the identification, quantification, and functional characterization of proteins, revealing post-translational modifications and protein interactions that are not apparent from transcriptomic data. Human organoids, which recapitulate the structural and functional complexity of native epithelial tissues, provide powerful tools to study disease mechanisms and personalize therapies. However, their culture poses challenges for efficient protein extraction and reproducible analysis. Here, we present a proteomics workflow optimized to maximize protein recovery from Matrigel-encased organoids. Samples were processed using S-Trap microcolumns to minimize losses, followed by liquid chromatography-mass spectrometry (LC-MS) in data-independent acquisition (DIA/SWATH-MS) mode for comprehensive, untargeted quantification. Library-free computational analysis using DIA-NN, combined with differential expression analysis, enabled sensitive detection of key proteins in intestinal organoids.
PubMed2027
Methods for Processing Stem Cell-Derived Organoids for Histological and Immunofluorescence Staining.
Intestinal stem cell (ISC)-derived organoids provide a physiologically relevant 3D culture system to model intestinal biology, regeneration, and disease mechanisms. Their complex architecture, recapitulating crypt structures, poses challenges for downstream histological and immunohistochemical analyses, necessitating optimized processing, and staining protocols. Here, we describe robust workflows for the fixation, embedding, sectioning, and staining of ISC-derived organoids. Each method is detailed stepwise, with emphasis on preserving morphology and antigenicity. We discuss reagent choices, critical technical considerations, and troubleshooting tips to maximize data reproducibility and quality. We have integrated recent advances and best practices, serving as a comprehensive guide for researchers working with intestinal organoids.
PubMed2027
Nanopore Sequencing for Chikungunya Virus: Principles and Application.
Nanopore sequencing is transforming viral genomics through real-time, portable, long-read analysis of RNA and DNA. Unlike traditional short-read platforms, it detects nucleotide sequences by measuring ionic current changes as nucleic acids pass through nanoscale pores, enabling direct single-molecule sequencing and base modification detection. Its simplicity, flexibility, and capacity for ultra-long reads make it ideal for resolving complex genomic regions, structural variants, and full viral genomes. These advantages have accelerated its use in pathogen surveillance and outbreak response, especially in resource-limited settings. For chikungunya virus (CHIKV), nanopore sequencing allows rapid, culture-independent recovery of complete genomes from clinical and vector samples, enabling real-time tracking of viral diversity, evolution, and spread. Experiences from Ebola, Zika, and COVID-19 have demonstrated the power of portable sequencing, now applied to CHIKV monitoring. Advances in tools such as Guppy, Dorado, Minimap2, and Medaka enhance read quality, consensus accuracy, and downstream analyses. Despite challenges in basecalling and error correction, robust quality control pipelines ensure reliable results. Ongoing improvements in chemistry, flow cell design, and machine learning will further enhance fidelity and throughput, establishing nanopore sequencing as a cornerstone of CHIKV genomic surveillance and epidemic preparedness.
PubMed2027
Procedures for the Study of Botrytis cinerea Proteome.
Proteomics has been revealed as a key set of technologies that provide a detailed description of the molecular processes involved in the development of a specific phenotype. "Omics" technologies can collect an incredible amount of information. Among them, proteomics is an invaluable tool for defining specific biological information by studying the complete set of proteins under specific conditions, the proteome; or specific subsets of proteins, the subproteome. It is a crucial instrument for describing protein post-translational modifications, the functional annotation of the genome, and the detection of orphan genes. Protein extraction procedures are necessary to obtain B. cinerea protein extracts of sufficient quality to be analyzed by LC-MS/MS, avoiding contaminants that interfere with the identification process. After experimental design, collect the samples and replicates as defined in each experimental approach; we will describe protocols and procedures for the next steps of proteome and subproteome extraction and LC-MS analysis.
PubMed2027
Systematic Analysis of Tumor Microenvironment Using IOBR.
The Immuno-Oncology Biological Research (IOBR) package is an R-based analysis tool for exploring the tumor microenvironment (TME) and its influence on anti-tumor immunity. Built for high-throughput data-spanning both transcriptomic and genomic profiles-IOBR integrates six analytical modules, including transcriptomic data preprocessing, TME profiling, TME pattern identification, ligand-receptor interaction analysis, genome-TME interaction assessment, and visualization. In this chapter, we walk through a multi-omics workflow using example datasets, illustrating data preparation, distribution analyses, result interpretation, and graphical output. IOBR is open source and is available at https://github.com/IOBR/IOBR and a detailed GitBook ( https://iobr.github.io/book/ ) offers a complete manual and analysis guide for each function.
PubMed2027
Teratoma Formation and Genomic Profiling Using Multi-Omics Approaches.
Teratoma formation is the gold standard assay for evaluating the developmental pluripotency of human and mouse embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). Following subcutaneous injection into immunodeficient mice, pluripotent stem cells spontaneously differentiate into derivatives representing all three embryonic germ layers-ectoderm, mesoderm, and endoderm. Beyond serving as a functional assay for pluripotency, teratomas provide a unique three-dimensional model system for studying early human development and lineage specification in vivo. This chapter describes comprehensive protocols for teratoma formation in immunodeficient mice, tissue processing for multiple downstream genomic applications, and multi-omics profiling approaches. We detail methods for embryonic stem cell culture, teratoma generation via subcutaneous injection, tissue dissection and processing for chromatin immunoprecipitation followed by sequencing (ChIP-Seq), RNA sequencing (RNA-Seq), single-cell multiome profiling combining chromatin accessibility (ATAC-Seq) and gene expression (scRNA-Seq), and histological analysis using hematoxylin and eosin (H&E) staining. Additionally, we provide bioinformatics workflows for analyzing the resulting genomic datasets to characterize the epigenetic and transcriptional landscapes of teratoma-derived tissues. These methods enable comprehensive molecular characterization of developmental processes and provide valuable resources for stem cell biologists studying pluripotency, differentiation, and early embryonic development.
PubMed2027
Whole-Mount Immunostaining of Human Intestinal Organoids.
Human intestinal organoids (HIOs) recapitulate the architecture and cell diversity of intestinal epithelium, hence providing a system for modeling processes like regeneration and tumorigenesis. Here, we describe a detailed whole-mount immunostaining protocol for HIOs to visualize proliferative cell population. Briefly, this protocol includes preparation of HIOs, fixation and permeabilization of tissue, blocking of non-specific binding, antibody crosslinking, and visualization using a confocal microscope. Additionally, the protocol is broadly adaptable for investigating different antibodies, enabling the exploration of other cell signaling processes in HIO models. By eliminating embedding and sectioning steps, this method is both time-efficient and preserves spatial tissue architecture.
PubMed2026
Implementation of Nano Flow Chromatography Coupled to Mass Spectrometry as a Reliable and Sensitive Discovery Lipidomics Platform.
RATIONALE: Untargeted lipidomics is commonly performed at analytical flow rates, which consume more solvent and may require higher on-column sample loads when sensitivity is limited by analyte abundance. Nano flow separations use lower flow rates and sample loads, reducing solvent consumption and facilitating improved electrospray ionization. We present here practical considerations for implementing a routine nano flow lipidomics workflow. METHODS: Bovine liver total lipid extract was spiked with SPLASH Lipidomix internal standards and analyzed by nano flow and high flow liquid chromatography coupled to a high-resolution accurate mass Orbitrap-based mass spectrometer. Full-scan polarity switching was used for untargeted profiling, and the AcquireX Deep Scan workflow was applied to support data-dependent MS/MS acquisition in the complex matrix. A SPLASH dilution series was analyzed in triplicate injections to compare analytical response across on-column loads between the two workflows. RESULTS: At 25 ng on-column, nano flow yielded 1266 total lipid annotations and 835 high-quality annotations, compared with 919 total and 518 high-quality annotations for high flow at 100 ng. Unintentional fragmentation decreased under nano flow conditions by 21%-31% across the representative lipid species evaluated. The use of nano flow allowed for the detection of lower on-column loads across several standards, extending the lower end of the response range by up to 40-fold compared with high flow analyses. CONCLUSIONS: Nano flow lipidomics improved sensitivity for untargeted analysis by increasing the number of lipid annotations, reducing unintentional fragmentation, and extending the analytical response to lower on-column loads. Together with practical guidance around sample preparation, injection volume, washing, and equilibration, these results support nano flow chromatography as a sensitive and reliable approach for sample-limited untargeted lipidomics.
PubMed2026
Improving grain yield prediction in Southern US oat germplasm using genomics information and environmental covariates.
Genetic gains of oat (Avena sativa L.) grain yield have been historically low compared to other major cereal crops. The use of machine learning models to capture complex interactions and leveraging data types other than genomic information in prediction models has great potential for improving complex traits in oat breeding programs. This study assessed the performance of deep learning model for genomic prediction compared to other statistical models, examined the optimal training set size for grain yield prediction, and investigated the potential of incorporating environmental covariates for enhancing oat grain yield prediction. A total of 463 oat lines were evaluated in five environments in Southern United States, and genotyping of the lines gave 12,657 single-nucleotide polymorphism markers. Our results showed that training set sizes 200-350 could be the optimal size for our panel, indicating the possibility of reducing phenotyping costs by reducing the size of the oat panel tested. The deep learning model was less superior to genomic best linear unbiased prediction and other models for grain yield, test weight, and heading days in the different environments. Incorporating interaction effects (G × E or G × W) into the multikernel prediction models across environments improved predictive abilities for grain yield by up to 0.21 compared to the baseline models. This reveals the potential of incorporating weather data to enhance predictive abilities in genomic prediction models. Our findings provide important information for improving genetic gains in oat breeding programs by integrating genomics and environmental information.
PubMed2026
Near-Peer Anatomy-Anchored Teaching.
BACKGROUND: The transition from pre-clinical to clinical medicine is challenging, particularly in applying anatomical knowledge to patient care. Reductions in dedicated anatomy teaching time have compounded this. Near-peer teaching may help address this gap by reducing hierarchy and enhancing psychological safety, though few programmes have explicitly targeted the pre-clinical to clinical transition through the integration of anatomy with clinical cases. APPROACH: A prospective educational evaluation examined a near-peer, case-based orthopaedic anatomy programme delivered to Year 4 medical students by Year 5 facilitators across four sessions. Knowledge acquisition was assessed using parallel pre- and post-session multiple-choice question (MCQ) sets compared using Wilcoxon signed-rank test and Cohen's dz. Student experience was evaluated using purpose-designed questionnaires. EVALUATION: Thirty-two matched pairs were available for analysis. Baseline anatomical confidence (mean 2.76/5) and ratings of placement-based anatomy teaching (mean 2.26/5) indicated clear unmet need. MCQ scores improved significantly from 5.0 to 7.0 out of 8 (mean 5.00 vs. 6.69, p < 0.001, Cohen's dz = 1.12). Post-session confidence improved to 4.03/5, facilitators were rated highly (mean 4.59/5), and 97% of students felt comfortable engaging with peer facilitators. IMPLICATIONS: This programme provides preliminary support for near-peer, case-based anatomy teaching as a promising approach to supporting the pre-clinical to clinical transition, demonstrating short-term improvements in MCQ performance, confidence and student satisfaction.
PubMed2026
PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.
BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.
PubMed2026
Refining Genetic Instruments for Dietary Intake Mendelian Randomization Using Phenome-Wide Association Studies.
Most Mendelian randomization (MR) of dietary intake use the full set of genome-wide significant (GWS) variants in the instrumental variable (IV), likely biasing causal estimates due to pleiotropy. To characterize the common methods to handle pleiotropy in dietary intake MR, we conducted a scoping review of the literature on dietary intake MR studies. We extracted information on IV construction, assessment of pleiotropy, and sensitivity analyzes revealing that only 20% of studies used an IV with functional plausibility. In the absence of functionally-informed IVs, we tested if two-sample MR using GWS variants filtered for pleiotropic associations through phenome-wide association studies (PheWAS) could identify diet-health relationships supported by existing nutrition science, focusing on oily fish and alcohol intake, the latter of which has a functionally-informed IV for comparison (rs1229984 in the ADH1B gene). To further explore this question, we performed multivariable MR and employed MR-CAUSE. The numerous models consistently supported that oily fish reduced triglycerides. In contrast, GWS and PheWAS-filtered IVs suggested that alcohol decreased alanine aminotransferase levels, whereas the functional IV (rs1229984) found the opposite expected relationship. Isolating the direct effect of dietary intake from GWS IV remains challenging. Future work should focus on identifying functional variants impacting dietary behavior.
PubMed2026
Chemical Profiling by UHPLC-MS/MS and In Vitro Antioxidant, Antimicrobial, and Cytotoxic Properties of Lepidoceras peruvianum Kuijt Leaves and Fruits.
RATIONALE: Lepidoceras peruvianum Kuijt is an understudied hemiparasitic species endemic to the Peruvian Andes that lacks comprehensive phytochemical characterization. Investigating its metabolome is important for understanding its chemotaxonomic relevance and potential as a source of bioactive compounds. METHODS: Leaves and fruits of L. peruvianum were subjected to untargeted metabolomic profiling using high-resolution UHPLC-ESI-Orbitrap-MS/MS in positive and negative ionization modes. Metabolites were annotated based on accurate mass measurements, isotopic patterns, collision-induced dissociation (CID) fragmentation data, and spectral matching with the Global Natural Products Social Molecular Networking (GNPS), METLIN, and MassBank databases. Structural elucidation employed diagnostic fragmentation pathways, including retro-Diels-Alder (RDA), heterocyclic ring fission (HRF), quinone methide (QM), and benzofuran-forming (BFF) cleavages. Antioxidant activity was evaluated using DPPH●, ABTS●+, and FRAP assays, while antimicrobial activity and toxicity were assessed through antibacterial testing and the Artemia salina lethality assay. RESULTS: Leaves contained 34 metabolites, mainly flavan-3-ols, proanthocyanidins, flavonols, lignans, and isoquinoline alkaloids, whereas fruits were characterized by anthocyanins, organic acids, and polar lipids. Total phenolic content was higher in leaves (292.4 mg GAE/g) than in fruits (216.8 mg GAE/g), corresponding to stronger antioxidant activity. Leaves extracts exhibited greater antibacterial activity against Staphylococcus aureus, while fruit extracts showed stronger effects against Gram-negative bacteria. LC50 values in the A. salina assay were 181.8 μg/mL for leaves and 475.9 μg/mL for fruits. CONCLUSIONS: This study provides the first comprehensive metabolomic characterization of L. peruvianum, revealing organ-specific chemical diversity and notable bioactive properties. The findings demonstrate the utility of HRMS/MS fragmentation analysis for metabolite annotation and identify this endemic species as a promising source of bioactive natural products.
PubMed2026
Integrated Metabolomic and Gut Microbiome Analyses Reveal the Therapeutic Effects of Xuanfei Heji in Rats With Chronic Obstructive Pulmonary Disease.
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a leading cause of death, underscoring the need for improved therapies. Xuanfei Heji (XFHJ), a hospital-prepared herbal formula, has been used clinically in the treatment of COPD. However, its mechanisms remain unclear. METHODS: XFHJ constituents were profiled using UHPLC-HRMS. COPD was induced in rats by intratracheal lipopolysaccharide instillation and cigarette smoke exposure. Treatment effects were assessed using pulmonary function, lung histopathology, and proinflammatory cytokines. Untargeted serum metabolomics and fecal 16S rRNA gene sequencing were performed; associations among differential metabolites, microbial taxa, and inflammatory markers were evaluated using Spearman's rank correlation analysis. RESULTS: Chemical profiling tentatively identified 374 constituents. XFHJ improved pulmonary function and attenuated lung histopathological injury and inflammation. Tryptophan and glycerophospholipid metabolism were the principal treatment-associated pathways. XFHJ also altered gut microbial diversity and composition, with enrichment of potentially beneficial taxa such as Bifidobacterium, Roseburia, and several Clostridia-related taxa. Treatment-responsive taxa correlated positively with indole-related metabolites, which correlated inversely with pulmonary inflammatory markers. CONCLUSIONS: XFHJ exhibited significant therapeutic effects on COPD rats, and its mechanism may be correlated with regulating the intestinal microbiota structure and metabolic profiles of COPD rats, thereby attenuating lung histopathological injury and pulmonary inflammation.
PubMed2026
All You Need to Know to Better Implement Quality Improvement into Your Practice.
This article uses a hypothetical quality improvement project to discuss the process of the Model for Improvement and ways to incorporate this into allergy practice.
PubMed2026
Beyond Bactericidal: Plasma Surface Engineering to Defeat Food Matrix-Conditioning Layers.
The persistence of foodborne pathogens on industrial food contact surfaces continues to challenge global food safety despite advances in sanitation technologies. A central limitation of current antimicrobial strategies lies in their validation under simplified laboratory conditions that overlook the physicochemically driven formation of food matrix conditioning films. Upon contact with food residues, organic macromolecules reorganize at the solid‒liquid interface, forming conditioning layers that mask engineered surface functionalities and facilitate microbial attachment. This review examines how such interfacial transformations constrain conventional bactericidal approaches and contribute to sanitization failures in industrial environments. Plasma surface engineering is evaluated as a matrix-aware strategy capable of tailoring surface energy, hydration behavior, and nanoscale architecture through plasma-enhanced chemical vapor deposition and magnetron sputtering. These approaches may mitigate organic fouling and modulate bacterial surface sensing under controlled conditions. Particular attention is given to mechanotransduction pathways implicated in early biofilm formation, highlighting how nanoscale surface cues influence c-di-GMP signaling and biofilm commitment in both Gram-negative and Gram-positive foodborne pathogens, including Salmonella spp. and Listeria monocytogenes. Significant translational gaps remain, including long-term durability under repeated cleaning-in-place cycles, antimicrobial transport through complex conditioning films, and adaptive tolerance under chronic exposure. This review situates plasma surface engineering within a preventive interfacial design framework, offering an evidence-based rationale for the development of food contact materials capable of meeting the durability, safety, and regulatory demands of modern processing environments.