Nature Protocols

The binding of transmembrane (TM) ligands to their cognate TM receptors on neighboring cells governs intercellular adhesion and direct cell-cell communication. However, these interactions are difficult to study in vitro because they depend on membrane presentation, ligand orientation, receptor clustering, and avidity, features often not captured by soluble recombinant ligands or cell-free assays. Here, we describe a flow cytometry-based assay using fluorescent, lentiviral-derived virus-like particles (VLPs) displaying TM ligands to quantify binding to their receptors on target cells. Fluorescent VLPs are generated in-house by plasmid transfection in HEK293T cells and enable direct fluorescent detection without fluorochrome-conjugated secondary antibodies. The system is modular and readily accommodates engineered ligand constructs, including patient-derived variants. We applied this platform to generate ICAM-1-displaying fluorescent VLPs and to study human LFA-1 function in patient-derived leukocytes. This protocol provides a detailed workflow for VLP production and in vitro binding assays, offering a simple, quantitative, and cost-effective approach for studying TM ligand-receptor interactions in a membrane context. The system is well suited for mechanistic studies, functional assessment of patient-derived variants, and direct binding assays using patient-derived cells. Integrating the assay into multicolor flow cytometry panels enables simultaneous immunophenotyping and quantification of up to four ligand-receptor interactions at single-cell resolution. Key featuresO_LIQuantifies TM ligand-receptor binding in a membrane context using fluorescent VLPs and flow cytometry. C_LIO_LIFully in-house, modular system based on plasmid transfection in HEK293T cells, without reliance on recombinant ligands or fluorochrome-conjugated secondary antibodies. C_LIO_LISupports testing of engineered ligand variants, including patient-derived alleles, and direct functional studies on patient-derived cells. C_LIO_LICompatible with multicolor flow cytometry panels, enabling simultaneous immunophenotyping and quantification of up to four ligand-receptor interactions at single-cell resolution. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/725198v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@a43069org.highwire.dtl.DTLVardef@166491borg.highwire.dtl.DTLVardef@49c7d4org.highwire.dtl.DTLVardef@1de36a0_HPS_FORMAT_FIGEXP M_FIG C_FIG

Stroboscopic light stimulation (SLS) is a candidate non-pharmacological intervention that induces transient visual and affective experiences, with potential application in depression. Before efficacy testing, clinical development requires safety, tolerability and feasibility data. We report a staged, single-site programme in adults reporting depressive symptoms. Work Package (WP) 1 tested 11 SLS parameter sets for safety and tolerability. An interim bridge study assessed whether a low-phenomenology SLS control reduced subjective visual effects while preserving session context. WP2 randomised 84 participants to four weekly supervised 31-minute sessions of the intervention or a low-phenomenology control. In WP1, 31 participants were analysed; no severe adverse reactions occurred, mean discomfort was low (0.49/10), and the highest session-level upper 80% confidence limit was 1.13/10, well below the prespecified threshold. The interim study supported experiential separation between intervention and control. In WP2, endpoint data were available for 70/84 participants (83.3%): 39/42 in the intervention arm and 31/42 in the control arm. Overall retention met the criterion, but lower control-arm retention remains a design issue; protocol adherence was high, discomfort remained low, and no serious SLS-attributable adverse events occurred. Exploratory depressive-symptom changes suggested a possible BDI-II signal, but do not establish efficacy. Supervised SLS met key safety, tolerability, and feasibility criteria, and a lower visual-phenomenology active control can be carried forward, while masking and comparator credibility remain to be established. The next step is a diagnostically defined, CTU-governed Phase 2a feasibility trial that pre-registers a locked protocol and tests masking, credibility, retention and endpoint precision.

Drug-induced liver injury (DILI) remains a major cause of clinical attrition and postmarketing withdrawal, but structure only DILI predictors are difficult to compare because public benchmarks are vulnerable to compound overlap, scaffold similarity and shared label provenance. We present OakuloidTM, an open DILI prediction framework that pairs a leakage audited structure based model with an optional iBAC 3D primary human hepatocyte IC50/Cmax confirmation signal. The structural model integrates gradient boosted descriptor backbones, fingerprint random forests and LivTox proxy-DILI features through a logistic meta learner. Its evaluation is designed as part of the contribution: internal DILIrank, strict external TDC, scaffold disjoint TDC and independent Geci provenance checks are reported with released per compound predictions. Oakuloid reaches AUROC 0.811 on the strict external TDC benchmark and remains competitive under scaffold and fully clean TDC filtering. A channel attribution ablation shows that the external benchmark lead is driven by descriptor based gradient boosted trees rather than by DILIPredictor derived proxy features, reducing a potential circularity concern. The wet lab IC50/Cmax signal is largely orthogonal to structure and supports a confirmation mode that shifts the internal operating point toward higher specificity without claiming a universal AUROC gain. Oakuloid is released with code, model artifacts, calibration analysis, a 122 compound wet lab benchmark and a model card under the Apache License 2.0, supporting reproducible DILI screening and benchmark auditing.

This protocol describes the workflow for the preparation of tissue samples for proteome and phosphoproteome analyses using mass spectrometry. The tissue samples are cryogenically pulverized and homogenized in a sucrose-based buffer to ensure proper tissue disruption. For depletion of lipid contaminants, proteins are purified using chloroform-methanol precipitation, followed by a resuspension in a urea-based buffer for enzymatic digestion. Peptides are desalted and enriched for phosphopeptides prior LC-MS/MS analysis. The workflow was developed for skin biopsies but is compatible with a broad range of tissue types. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=51 SRC="FIGDIR/small/732915v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@6a44aforg.highwire.dtl.DTLVardef@c34dc9org.highwire.dtl.DTLVardef@27d7ecorg.highwire.dtl.DTLVardef@1d1038e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

SummaryBiological growth curves are widely used but inconsistently analyzed due to fragmented workflows and limited quality control. We present growthcurves, a Python package for extracting growth parameters, and two open-source web applications, MicroGrowth and AutoGrowth, that combine automated fitting with interactive, human-in-the-loop inspection, selective refitting and traceable export for microplate reader and mini-bioreactor datasets in batch or turbidostat cultivation mode. Availability and Implementationgrowthcurves is implemented in Python and is freely available to non-commercial users at [https://github.com/biosustain/growthcurves.git] and through PyPI at [https://pypi.org/project/growthcurves/]. MicroGrowth and AutoGrowth are available at [https://biosustain.github.io/growthcurves_app/], and their source code is available at [https://github.com/biosustain/growthcurves_app.git]. Documentation, installation instructions, example datasets and tutorials are available at [https://growthcurves.readthedocs.io/en/latest/]. Contactstefdon@dtu.dk; cargac@dtu.dk Supplementary InformationSupplementary information and Supplementary Methods are available online.

The structural and functional diversity of RNAs is expanded by the post-transcriptional incorporation of nucleoside variants. Emblematic of this, tRNAs contain extensive modifications that ensure their function during protein synthesis. Mass spectrometry has long been the field standard for identifying specific sites of chemical modifications on RNA. Nonetheless, mass spectrometry-based mapping approaches are not widely implemented. This is partially due to technical challenges associated with current methodologies including the limited diversity of available RNases, complexity of RNA mixtures, and conventional use ion-pairing reagents that require dedicated instrumentation. Here, we present a bottom-up liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflow employing hydrophilic interaction liquid chromatography (HILIC) without ion-pairing reagents to globally map E. coli tRNA modifications. We implement orthogonal digestions using RNase 4 and a folded digestion scheme with RNase T1 to generate uniquely mappable oligonucleotides compatible with HILIC-MS/MS analysis and achieve 75-100% sequence coverage for most tRNA isoacceptors. HILIC-MS/MS matches the performance of traditional ion-pairing reverse-phased LC-MS/MS. This level of coverage allowed us to discover a new site of methylation (Gm17) in tRNAGly, and confirm the presence of an s4U8 modification predicted in tRNAArg. Furthermore, by applying this method to E. coli lacking the m5U54 methyltransferase (trmA) we confirmed the established dependence of acp3U47 insertion on m5U54 in tRNAPhe. Our findings show that RNase 4 improves bottom-up tRNA sequencing, enabling high-quality E. coli tRNA analysis without ion-pairing reagents. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/727428v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@1f483a3org.highwire.dtl.DTLVardef@1ee5e01org.highwire.dtl.DTLVardef@5db88borg.highwire.dtl.DTLVardef@fee855_HPS_FORMAT_FIGEXP M_FIG C_FIG

Transcriptional bursts regulate gene expression by altering burst size or burst frequency. Here, we present a protocol that integrates fixed-cell smFISH and live-cell single-molecule imaging to analyze estrogen-responsive transcriptional bursting of the TFF1 gene in human breast cancer cell lines. This workflow enables measurement of burst size, burst initiation, and active allele frequency to determine how endocrine disruptor chemicals modulate transcriptional bursting dynamics. For complete details on the use and execution of this protocol, please refer to Day, Yasar et al.1

This step-by-step protocol provides a cross-species, non-surgical approach that enables prenatal gene delivery to the developing nervous system in rats and marmosets. Under transabdominal ultrasound guidance, intracerebroventricular injection of recombinant adeno-associated virus vectors into the fetal brain achieves robust and long-term transduction from prenatal stages into adulthood. This approach can be adapted to other species and target sites outside nervous system, enabling safe and selective intrauterine manipulation and the generation of diverse experimental models for basic and preclinical research. For complete details on the use and execution of this protocol, please refer to Ribeiro Gomes et al (2026)1. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/737050v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@696364org.highwire.dtl.DTLVardef@fc3c7forg.highwire.dtl.DTLVardef@1e7c7caorg.highwire.dtl.DTLVardef@1edcef0_HPS_FORMAT_FIGEXP M_FIG C_FIG Before you beginExperimental procedures during gestation allow researchers to study developmental processes, including how manipulations of the fetus and its intrauterine environment influence biological outcomes. Ultrasound imaging guidance greatly facilitates such interventions by providing safe and targeted access to fetal compartments, including for prenatal gene delivery to developing neural cell populations. Critically, delivery of recombinant adeno-associated viruses (rAAVs) into the cerebrospinal fluid (CSF) of developing animals enables widespread gene transfer across the brain. The efficiency and distribution of transduction are strongly influenced by developmental stage, making the timing of delivery an important experimental variable. In altricial species such as mice, major developmental processes, including cortical lamination and the establishment of long-range connections, begin prenatally but continue throughout early postnatal life. In primates, however, development is more advanced at birth, and many equivalent developmental events are shifted to the prenatal period. Consequently, developmental stages that can be targeted postnatally in mice require prenatal access in primates. Here, we present a step-by-step protocol for ultrasound-guided fetal intracerebroventricular viral injection (FIVI) of rAAV in marmosets (Callithrix jacchus) and rats (Rattus norvegicus). The procedure was initially developed and optimized in rats before being translated to marmosets, small New World primates that share key developmental, anatomical, and functional characteristics with humans. Together, these models illustrate the cross-species applicability of the approach, while providing gene delivery strategies for both a genetically tractable rodent model and a translationally relevant nonhuman primate. FIVI enables broad gene transfer and stable, long-term transgene expression in wild type animals, facilitating the generation of complementary quasi-transgenic models for research and translational applications from prenatal development through adulthood.

RNA modifications contribute to the regulatory and structural complexity of RNA molecules, influencing key biological processes. Nanopore direct RNA sequencing (DRS) enables the detection of these modifications at single-molecule resolution without chemical conversion. Oxford Nanopore Technologies recently introduced RNA004 sequencing chemistry and the Dorado basecaller, which improves accuracy and enables the identification of eight RNA modifications. However, the reliability of these predictions requires careful validation using orthogonal approaches. Here, we profiled RNA modifications in the MS2 bacteriophage genome using both LC-MS/MS and Nanopore DRS. LC-MS/MS analysis revealed that {Psi} is the predominant modification, present at approximately one site per RNA molecule, while all other modifications were found at low levels (< 0.04 modifications per RNA). In contrast, Dorado-based modification calling not only confirmed {Psi} but also predicted multiple m6A, m5C, 2OMe, and inosine sites not supported by LC-MS/MS data. To refine modification calling, we used in vitro transcribed (IVT) RNA as a negative control and subtracted IVT-derived false positive rates from native RNA predictions. This adjustment reduced overcalling and improved confidence in site-specific predictions. These data demonstrate that while Dorado can detect RNA modifications de novo, its predictions require careful filtering and validation. Our studies of provide a rare benchmark dataset for assessing the ability of transcriptome-wide methods to accurately identify RNA modifications and estimate modification stoichiometry. These findings support the use of orthogonal approaches, including LC-MS/MS and IVT controls, alongside Nanopore sequencing to provide a more reliable and interpretable strategy for studying RNA modification patterns. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/729303v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@637a55org.highwire.dtl.DTLVardef@f48272org.highwire.dtl.DTLVardef@a0465aorg.highwire.dtl.DTLVardef@6af045_HPS_FORMAT_FIGEXP M_FIG C_FIG

Double-stranded RNA (dsRNA) is recognized by cellular receptors as a sign of viral infection, triggering the innate immune response. Increasing evidence shows that cellular dysregulation, for example in immune disorders and neurodegenerative diseases, can also lead to accumulation of endogenously produced dsRNA that stimulates a viral-like immune response. Additionally, dsRNA contamination in RNA therapeutics can lead to harmful side effects via a similar pathway. Despite the clinical relevance of dsRNA, reliable tools for its detection remain limited. At present, dsRNA detection relies almost exclusively on the monoclonal antibodies J2 and K1, which suffer from sequence bias and low sensitivity, limiting their reliability. To address this challenge, we aimed to repurpose naturally occurring dsRNA-binding domains (dsRBDs) to produce reliable, pan-specific affinity reagents for dsRNA. We first systematically screened the dsRBDs of the three human adenosine deaminases acting on RNA (ADARs). This analysis identified ADAR3 dsRBDs as promising candidates due to their reduced sequence dependence compared to the dsRBDs of ADAR1 and ADAR2. We then engineered ADAR3-derived dsRBD constructs having varying linker lengths and domain combinations, allowing us to specifically vary the length cutoff of dsRNA detected, thus creating dsRNA accumulation detected by ADAR3 RBDs (dsRADAR) affinity reagents. Finally, we demonstrate the superior performance of dsRADAR over currently available dsRNA antibodies in a cell model of viral infection and a tissue model of gastric inflammation. Together, dsRADAR provides a sensitive and reliable approach for imaging and quantifying diverse dsRNA structures in a variety of biological contexts. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/724404v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1d89c30org.highwire.dtl.DTLVardef@1f64fc1org.highwire.dtl.DTLVardef@1ee391forg.highwire.dtl.DTLVardef@e834a6_HPS_FORMAT_FIGEXP M_FIG C_FIG

Genome mining now yields tens of thousands of putative biosynthetic gene clusters (BGCs) per project, yet, separating genuinely novel candidates from rediscoveries of known compounds remains the rate-limiting step before experimental validation. Single-axis prioritisation tools, antiSMASH similarity, BiG-FAM GCF distance, and self-resistance-enzyme (SRE) filters such as ARTS, each surface a different facet of evidence, yet their isolated use systematically over-ranks rediscovery-prone BGCs and overlooks genuinely orphan clusters. We present novelBGC, a web-hosted framework that converts these disparate outputs into two deliberately non-inverse continuous metrics per BGC, a Novelty (N) and a Reference Similarity (RS) score which together define a 2D decision plane that resolves rediscoveries, divergent family members, contig-edge artefacts, and uncharted chemistry with interactive visualisations, with all component weights user-tuneable at submission. Retrospective validation across three independent experimental datasets demonstrates the utility of the framework for candidate prioritization. Within the first 186-BGC SRE-guided cloning study, every confirmed bioactive product fell within the low-to-mid N band whereas 55 high-N (N [&ge;] 0.50) BGCs were never selected. Moreover, in the other two studies, it correctly prioritised the fully orphan lariocidin BGC of Paenibacillus sp. M2 and the divergent within-family indanopyrrole-A idp BGC of Streptomyces sp. CNX-425. Together, these case studies demonstrate that the joint (N, RS) space facilitates prioritization decisions that are difficult to achieve using any single criterion alone. from identical input data. novelBGC requires no command-line expertise, no local tool installation, and no manual integration of intermediate output formats, addressing a well-documented accessibility barrier for wet-laboratory researchers engaging with genome-mining workflows. novelBGC is freely available at https://project.iith.ac.in/sharmaglab/novelbgc/.

Connectomic reconstruction from large image volumes produces segmentation and synaptic-assignment errors that must be resolved to support downstream analyses. As datasets have grown larger and teams more distributed, proofreading has become a critical operational bottleneck. Workflows for proofreading and error correction have not scaled commensurately with connectomic data production and may not accommodate heterogeneous proofreader expertise and machine-generated candidate edits. New tools are therefore needed to organize, prioritize, and coordinate proofreading at volume scale. Here we present NeuVue, a task-management and prioritization framework that operationalizes proofreading through atomic, auditable tasks for individual and team review, multistage routing across proofreader cohorts, performance and volume-state tracking, and integration with community annotation, visualization, and analysis services. We report the use of NeuVue across two volumetric datasets, supporting scalable proofreading by over forty proofreaders and producing over fifty thousand edits. NeuVue provides a reproducible human-in-the-loop framework for generating, validating, and maintaining large connectomic datasets.

Different omics types such as genomics and proteomics all contribute to deciphering biology. Applying these omics approaches in a spatial context helps reveal biology in situ at a single cell level. Here we present a protocol for the combined multiplexed detection of targeted genes using DNA FISH, and proteins using multiplexed immunofluorescence. The protocol is integrated on the commercial PhenoCycler platform and generates one single dataset with gene and protein readout at a single cell level in large tissue sections, allowing for a throughput of thousands to millions of cells. The workflow can be used for characterising malignant cells in large tumor areas based on genetic aberrations, while deciphering the cellular landscape and microenvironment from multiplexed protein detection using immunofluorescence.

Structured AbstractO_ST_ABSBackgroundC_ST_ABSPost-Traumatic Stress Disorder (PTSD) is a mental health condition affecting people who experience traumatic events. Trauma-exposed occupational groups report higher rates of PTSD than the general population. Current treatments, and access, often take months and may cause distress when people are required to talk about the trauma. ObjectiveTo determine the proof of concept of FIRST, a brief, non-trauma focussed therapy, in two separate populations with employment-associated PTSD. MethodTwo independent, single-arm, experimental therapy pilot trials were conducted. Trial one recruited 20 military veterans who received FIRST therapy via trained third-sector therapists. Trial two recruited 16 health and social care workers with FIRST therapy delivered by healthcare provider therapists. All participants were adults with PTSD (confirmed via CAPS-5 in trial one, and symptom score of [&ge;]33 on the PCL5 in trial two). Primary outcomes were recruitment feasibility, retention, data quality and reduction in PTSD symptoms. Secondary outcomes were anxiety and depression symptoms, daily life functioning and perceived health status. Veterans were followed up at 12 weeks post-enrolment and healthcare workers at 8 weeks. ResultsThe veteran trial progression criteria to main trial were met. Seventy-nine people screened eligible, 43 attended a CAPS-5 assessment; 20 had confirmed PTSD and were enrolled. Seventeen completed therapy and 12-week outcome measures. Mean PCL-5 scores decreased from 48.7 (SD = 13.02, n=20) at baseline to 23.5 (SD = 15.30, n=17) at 12-weeks. The healthcare worker trial obtained informed consent from 16 participants, 10 commenced therapy and were included in analysis with eight completing therapy. Mean PCL-5 scores decreased from 42.60 (12.23, (n=10) at baseline to 22.00 (19.92, n=8) at 8-weeks. ConclusionsProof of concept of FIRST was established. PTSD symptom reductions exceeded the PCL-5 minimal clinically important difference. Undertaking a fully powered randomised controlled trial of FIRST therapy is feasible within both healthcare and third sectors. HighlightsO_LIPost-traumatic stress disorder (PTSD) is more common in military veterans and health workers than the general population C_LIO_LITherapy can be challenging to commence and complete when it requires a focus on the trauma incident C_LIO_LIFIRST offers a promising, brief, non-trauma focused therapy for the treatment of PTSD C_LI

Reconstructing dynamic immune cell state transitions from single-cell transcriptomic data requires coordinated analytical strategies that capture both phenotypic progression and underlying regulatory programs. This protocol describes a step-by-step computational workflow for analyzing human tumor-infiltrating T cells using the sequential application of dimensionality reduction, pseudotime trajectory inference, regulon activity analysis, and transcription factor-transcription factor network reconstruction. The workflow outlines data preprocessing and quality control, trajectory rooting and parameter selection, branch-specific differential analysis, and the integration of regulon inference to contextualize transcriptional programs along inferred trajectories. Regulon-based TF-TF network reconstruction is used as a downstream interpretive layer to identify regulatory modules associated with distinct cell-state transitions. Publicly available at GitHub repository https://github.com/rogercasalsfr/immuno-trajectory-grn-integrative-workflow, this protocol emphasizes practical considerations including parameter sensitivity, trajectory robustness, and consistency between phenotypic and regulatory outputs. The protocol supports reproducible analysis and interpretation of immune cell dynamics in human tumor microenvironment studies using single-cell RNA sequencing data.

Whole-genome sequencing identifies focal DNA amplifications with base-pair resolution but cannot determine whether amplified sequences reside on extrachromosomal DNA (ecDNA, also known as double minutes) or within chromosomally integrated homogeneously staining regions (HSRs). DNA fluorescence in situ hybridization (DNA-FISH) metaphase spreads remain the gold standard for distinguishing these amplification states at single-cell resolution. Here, we present a detailed protocol for DNA-FISH metaphase spreads using human cancer cell lines, encompassing cell culture, metaphase arrest, hypotonic treatment, fixation, chromosome spreading, fluorescent probe hybridization, and fluorescence imaging. The protocol incorporates intermediate quality-control steps to verify successful chromosome dispersion and optimize metaphase spread quality, making the workflow accessible to laboratories without specialized cytogenetics expertise. Results demonstrate clear visualization of ecDNA and HSR amplification states using locus-specific probes and illustrate common technical artifacts that can affect interpretation. This protocol provides a robust and reproducible approach for studying the structural organization of oncogene amplification in cancer cells.

Biosynthetic gene clusters (BGCs) encode enzymatic pathways for natural products with pharmaceutical potential, yet prioritizing candidates from fragmented environmental DNA (eDNA) assemblies remains computationally challenging. We present BGC-QDR (Biosynthetic Gene Cluster Quantum Discovery and Ranking), an open-source pipeline that integrates input quality control, Prodigal ORF prediction, Pfam HMM domain annotation, rule-based BGC classification, MiBIG 4.0 novelty assessment, and variational quantum classifier (VQC) ranking via PennyLane. BGC-QDR is designed as a quantum-assisted ranking framework for biologically informed BGC prioritization, not as a claim of quantum computational advantage over classical machine learning. We evaluate the pipeline on MiBIG 4.0 (2,636 annotated BGCs) using a 20-dimensional biosynthetic feature vector and stratified 10-fold cross-validation. The integrated VQC (6 qubits x 3 layers, 54 parameters) achieves accuracy of 0.789 {+/-} 0.076 and ROC-AUC of 0.835 {+/-} 0.057. Random Forest achieves the highest ROC-AUC (0.898 {+/-} 0.032), followed by Logistic Regression (0.874 {+/-} 0.020) and MLP (0.872 {+/-} 0.024). Wilcoxon signed-rank tests on per-fold AUC scores show that VQC ROC-AUC is significantly lower than Random Forest (p = 0.0098) and Logistic Regression (p = 0.037) at = 0.05, with no significant difference versus MLP (p = 0.064). Architecture ablation identifies 4 qubits x 3 layers as the best VQC configuration on hold-out validation (AUC = 0.737). Feature importance analysis highlights peptidyl carrier protein domains, cluster length, and module count as dominant predictors. BGC-QDR provides a reproducible, end-to-end workflow for eDNA-derived BGC discovery with integrated novelty scoring and quantum-assisted candidate ranking. The complete BGC-QDR source code, benchmark datasets, and reproduction instructions are publicly available at: Abhishekmishra2808/BGC-PIPELINE

Animal cell-cultured ingredients are entering the EU and UK pet food markets under frameworks that do not require pre-market, ingredient-level safety assessments, creating an ethical need for transparent safety disclosure. We present the first public safety dossier for this sector, describing the proprietary mouse embryonic stem cell line PE25 and its derived, non-viable cellular and conditioned media ingredient produced in food and feed-grade media. PE25 characterization confirmed Mus musculus identity, sterility, absence of mycoplasma and replication-competent retroviruses, and stable growth. Doxorubicin-induced p53 stress testing, CD44/BMI1 profiling, and soft agar assays showed no cancer-like traits and a non-tumorigenic profile; the final ingredient contains no viable cells. Independent OECD TG 471 and 487 assays confirmed non-genotoxicity. Heavy metals, biogenic amines, solvents, and chemical residues were below regulatory limits. Given process variability, we recommend case-by-case safety evaluation and propose this dossier as a model for responsible commercialization.

MotivationThe ToxCast database is a valuable resource for computational toxicology and new approach methodologies (NAMs), but the approximately 100 GB MySQL distribution is difficult to use for portable local analysis and cross-domain evidence mining. Many practical questions concern chemicals, in vitro bioactivity, in vivo toxicological evidence, and exposure-relevant product-use context rather than raw database keys. ResultsWe present ToxCastLite, a portable semantic evidence-access system that combines assay-scoped SQLite databases with a compact RDF layer for GraphDB-based querying. The system streams large ToxCast/invitrodb MySQL dumps into curated SQLite profiles, reducing the footprint to approximately 3 GB for focused use cases such as developmental neurotoxicity. Dense numerical evidence, including concentration-response rows, remains in SQLite, while the RDF projection exposes linked semantic entities such as chemicals, assays, endpoints, model results, potency parameters (AC50), and MC6 quality flags. We further extend the graph with CPDat v4.0 product-use and functional-use evidence and ToxRefDB v3.0 in vivo toxicity evidence, including processed studies, point-of-departure records, effect summaries, and observation summaries. These layers are linked through DSSTox Substance Identifiers, enabling integrated queries across NAM bioactivity, curated animal-study evidence, and exposure/use context. A Streamlit prototype supports exploration through a locally deployed LLM that translates natural-language questions into SPARQL, grounded by a versioned RDF schema to reduce hallucination risk. Case studies in developmental neurotoxicity demonstrate how ToxCastLite identifies concordance between high-confidence in vitro DNT activity and positive in vivo apical evidence, detects in vitro DNT activity beyond available DNT-specific in vivo evidence, and prioritizes chemicals where NAM signals, ToxRefDB evidence, and CPDat product-use context intersect. For selected results, users can drill down from the semantic graph to the underlying SQLite records and retrieve concentration-response curves for expert inspection without manually writing SQL or SPARQL. AvailabilityProject website at toxcast-lite.github.io/. Contactarif.doenmez@iuf-duesseldorf.de

This protocol details the extraction of high-molecular-weight genomic DNA from grapevine tissues (wild and cultivated Vitis spp., including pathogen-infected samples) and the subsequent preparation of Illumina(R) whole-genome sequencing libraries using bead-bound Tn5 transposase. It is designed to overcome challenges from polyphenolic compounds and secondary metabolites in wild plants, providing a cost-effective workflow for large-scale population genomics. It includes recipes for buffers, incubation times, critical notes, and troubleshooting tips to maximize yield and library quality. Although designed for the grapevine DNA, this protocol is potentially applicable to other similar wild plant species HighlightsO_LIOptimized CTAB-PTB DNA extraction protocol for field-collected wild plant tissues. C_LIO_LIEffective removal of polyphenols and secondary metabolites associated with DNA using PTB. C_LIO_LICost-effective Illumina DNA Prep library preparation using bead-bound Tn5 transposase (Tagmentation). C_LIO_LIScalable workflow suitable for large-scale population genomics in Vitis species. C_LIO_LIValidated method for high-molecular-weight DNA and high-quality sequencing data. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC="FIGDIR/small/713680v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@b637d4org.highwire.dtl.DTLVardef@10b563aorg.highwire.dtl.DTLVardef@14a32caorg.highwire.dtl.DTLVardef@4c9577_HPS_FORMAT_FIGEXP M_FIG C_FIG