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At least 127 records · Page 7Linked to original sources

Generation of Fibrin-Based Three-Dimensional Engineered Vascular Tissues from Human Aortic Smooth Muscle Cells for Proteomic Analysis.

Vascular smooth muscle cells (SMCs) reside within the medial layer of blood vessels, where they interact with an extracellular matrix (ECM) composed of collagen, elastin, and proteoglycans to maintain vascular structure and function. Aberrant ECM remodeling contributes to multiple vascular diseases; however, conventional two-dimensional culture systems do not adequately recapitulate the three-dimensional (3D) cellular and matrix environment required to study SMC-ECM interactions and matrix remodeling. This protocol describes the generation of engineered vascular tissues (EVTs) from primary human aortic SMCs cultured within fibrin-based 3D hydrogels. Following casting between flexible polydimethylsiloxane posts, EVTs undergo cellular alignment, contraction, and deposit de novo ECM, providing a physiologically relevant platform for studying vascular matrix biology. The protocol details tissue fabrication, culture, harvesting, and downstream analysis of newly deposited ECM by immunofluorescence staining. In addition, a workflow is presented for qualitative and quantitative characterization of EVT-derived proteins using Western blotting and mass spectrometry-based proteomics. Sequential protein extraction enables assessment of soluble and ECM-enriched protein fractions, facilitating in-depth evaluation of ECM composition. This platform provides a reproducible approach for investigating ECM production and remodeling by human SMCs in a 3D environment.

Humans↗

OmnibusX: A unified platform for accessible multi-omics analysis.

OmnibusX is an integrated, privacy-centric platform that enables code-free multi-omics data analysis by bridging computational methodologies with user-friendly interfaces. Designed to overcome challenges posed by fragmented analytical tools and high computational barriers, OmnibusX consolidates workflows for diverse technologies - including bulk RNA-seq, single-cell RNA-seq, single-cell ATAC-seq, and spatial transcriptomics - into a single, cohesive application. The application integrates established open-source tools such as Scanpy, DESeq2, SciPy, and scikit-learn into transparent, reproducible pipelines, offering users control over analytical parameters. Additionally, OmnibusX features proprietary modules, including a highly accurate cell-type prediction engine and an interactive plotting editor for generating publication-quality visualizations. Available as a standalone desktop application and an enterprise edition for centralized server deployment, OmnibusX ensures all data processing is conducted locally, eliminating external data transfer and usage tracking. By lowering technical barriers and enhancing reproducibility, OmnibusX aims to accelerate biological discovery and foster robust, data-driven collaborations. A fully documented trial version is accessible at: https://omnibusx.com/apps.

Computational Biology↗

Generation of Aneuploid Human Induced Pluripotent Stem Cells from Primary Amniotic Fluid Cells via Episomal Plasmid Electroporation.

The generation of patient-specific induced pluripotent stem cells (iPSCs) from amniotic fluid cells (AFCs) carrying defined chromosomal aneuploidies provides a powerful platform for modeling genetic disorders. However, establishing a reliable and reproducible reprogramming pipeline for aneuploid AFCs remains technically challenging due to the intrinsic genomic instability and variable proliferative capacity of these cells. Here, we present a comprehensive, non-integrating method for generating aneuploid human iPSCs from primary AFCs using episomal plasmid electroporation. This protocol details the complete workflow, encompassing cell thawing and expansion with a gradual media adaptation strategy, optimized plasmid delivery via electroporation system, sequential post-electroporation culture with mesenchymal-to-epithelial transition (MET)-directed media changes, and mechanical colony picking based on defined morphological criteria. We further describe validation procedures, including immunofluorescence staining for core pluripotency markers, G-banding karyotype analysis to confirm aneuploid karyotype maintenance, and PCR-based episomal vector clearance verification. This feeder-free, integration-free protocol yields aneuploid iPSC lines suitable for disease modeling, drug screening, and studies of chromosome biology.

Humans↗

ClarID: A Human-Readable and Compact Identifier Specification for Biomedical Metadata Integration.

BACKGROUND: In biomedical research, subjects and biospecimens are commonly tracked using simple IDs or UUIDs, which guarantee uniqueness but convey no embedded semantic information. Contextual metadata (such as tissue type, diagnosis, or assay) is often stored separately, making integration, cohort selection, and downstream analysis cumbersome. While structured barcoding systems exist in large consortia (e.g., TCGA, GTEx) or domain-specific contexts (e.g., SPREC, GOLD), no unified, extensible framework currently spans both subjects and biosamples in a human- and machine-readable way. METHODS: We developed ClarID, a domain-agnostic specification that supports two identifier formats: (i) a human-readable form (e.g., 'CNAG_Test-HomSap-00001-LIV-TUM-RNA-C22.0-TRT-P1W' that encodes key metadata such as project, species, subject_id, tissue, assay, disease, timepoint and duration (from that event); and (ii) a compact version named 'stub' (e.g., 'CT01001LTR0N401T1W') optimized for filenames, pipelines, and labeling.ClarID is implemented through an open-source command-line tool, ClarID-Tools, which processes tabular metadata files (CSV/TSV) and uses a YAML-based codebook to generate, decode, and validate identifiers, as well as to create and read QR codes. The tool supports bulk and single-sample processing and allows easy integration with institutional workflows. RESULTS: To demonstrate ClarID's utility, we applied it to datasets from the Genomic Data Commons (GDC), generating interpretable identifiers for more than 113,000 clinical records (subjects) and 4,255 biospecimen records. All materials, including pre-processing scripts, input and encoded data, are publicly available and fully reproducible via the accompanying GitHub repository and Google Colab. CONCLUSIONS: ClarID fills a critical gap between opaque accession numbers and rich metadata schemas by embedding key context directly into structured identifiers. It enhances traceability, facilitates downstream analysis, and remains adaptable to project-specific needs through a configurable codebook. The accompanying ClarID-Tools software is freely available, together with full documentation and reproducible pipelines, at https://github.com/CNAG-Biomedical-Informatics/clarid-tools.

Biosample identifiers↗

ECHO: a nanopore sequencing-based workflow for (epi)genetic profiling of the human repeatome.

SUMMARY: The human genome is dominated by repetitive DNA, whose genetic and epigenetic variation plays a key role in gene regulation, genome stability, and disease. Recent advances in long-read sequencing now enable large-scale, haplotype-resolved, and DNA methylation-informative analysis of the human genome, including on previously inaccessible complex and repetitive regions. However, the comprehensive, simultaneous characterisation of the "human repeatome" remains challenging, largely due to the lack of comprehensive tools integrated in a single pipeline that can capture the full spectrum of variation across diverse types of DNA repeats. Here, we present ECHO, a user-friendly, Snakemake-based pipeline for the "(Epi)genomic Characterisation of Human Repetitive Elements using Oxford Nanopore Sequencing." ECHO provides a reproducible and scalable framework for end-to-end analysis of whole-genome nanopore sequencing data, enabling integrative but also tailored (epi)genetic analyses of the human repeatome. AVAILABILITY AND IMPLEMENTATION: ECHO is freely available at Github: https://github.com/leenput/ECHO-pipeline, with the archived version at Zenodo: https://zenodo.org/records/19068468.

Humans↗

SynchroSep-MS: Parallel LC Separations for Multiplexed Proteomics.

Achieving high throughput remains a challenge in MS-based proteomics for large-scale applications. We introduce SynchroSep-MS, a novel method for parallelized, label-free proteome analysis that leverages the rapid acquisition speed of modern mass spectrometers. This approach employs multiple liquid chromatography columns, each with an independent sample, simultaneously introduced into a single mass spectrometer inlet. A precisely controlled retention time offset between sample injections creates distinct elution profiles, facilitating unambiguous analyte assignment. We modified the DIA-NN workflow to effectively process these unique parallelized data, accounting for retention time offsets. Using a dual-column setup with mouse brain peptides, SynchroSep-MS detected approximately 16,700 unique protein groups, nearly doubling the peptide information obtained from a conventional single proteome analysis. The method demonstrated excellent precision and reproducibility (median protein %RSDs less than 4%) and high quantitative linearity (median R2 greater than 0.96) with minimal matrix interference. SynchroSep-MS represents a new paradigm for data collection and the first example of label-free multiplexed proteome analysis via parallel LC separations, offering a direct strategy to accelerate throughput for demanding applications such as large-scale clinical cohorts and single-cell analyses without compromising peak capacity or causing ionization suppression.

Proteomics↗

Reimagining research papers as interactive and reliable AI agents.

Here we introduce Paper2Agent, an automated framework that converts research papers into artificial intelligence (AI) agents. Paper2Agent transforms research output from passive artefacts into active systems that accelerate use and discovery. Conventional research papers require readers to understand and adapt the paper's code, data and methods to their work, creating barriers to dissemination and reuse. Paper2Agent addresses this challenge by converting a paper into an AI agent that functions as a virtual corresponding author, exposing its manuscript, supplementary materials, datasets, code and workflows as active, agent-native knowledge rather than static text. It analyses the paper and codebase using multiple agents to construct a model context protocol (MCP) server, then generates and runs tests to refine and increase robustness of the MCP. These paper MCPs can be connected to a chat agent (such as Claude Code) to carry out complex scientific queries through natural language while invoking tools and workflows from the paper. We demonstrate Paper2Agent's effectiveness through case studies. Paper2Agent created an agent that leveraged AlphaGenome1 to interpret genomic variants and agents based on Scanpy2 and TISSUE (transcript imputation with spatial single-cell uncertainty estimation)3 to conduct single-cell and spatial transcriptomics analyses. We validate that these agents reproduce the results of the original papers and carry out novel user queries. Paper2Agent created multiple agents that collaborate to prioritize a causal gene for psoriasis. By turning static papers into interactive AI agents, Paper2Agent introduces a paradigm for knowledge dissemination and a collaborative ecosystem of AI co-scientists.

Journal Article↗

OctopuSV and TentacleSV: a one-stop toolkit for multi-sample, cross-platform structural variant comparison and analysis.

MOTIVATION: Structural variants (SVs) influence gene regulation, disease progression, and diagnostics, yet integrating SV calls across platforms remains difficult due to inconsistent annotations, limited merging flexibility, and fragmented workflows. Ambiguous breakend (BND) annotations, which comprise many variant calls, are often discarded or misclassified, hindering variant characterization. Existing tools lack advanced merging operations essential for precise identification of disease-specific or somatic variants across samples or patient groups. Additionally, current SV analysis pipelines require extensive manual intervention and complex parameter tuning, compromising reproducibility and scalability. Addressing these gaps is crucial for improving the accuracy, interpretability, and clinical utility of SV analyses. RESULTS: We developed OctopuSV and TentacleSV to address these long-standing challenges in SV analysis. OctopuSV features a specialized BND correction module that converts ambiguous BND annotations into canonical SV types, recovering important variants that are often overlooked by existing tools. Additionally, it provides advanced set operations (difference, complement, custom-defined) that enable sophisticated variant filtering without programming expertise, critical for identifying tumor-specific SVs or variants unique to specific sample groups. TentacleSV completes our solution by automating the entire SV analysis process from raw sequencing data to high-confidence callsets, ensuring consistency and reproducibility across projects. Benchmarking across short-read and long-read platforms showed superior F1 score, complete SV type consistency compared to existing tools. Our framework enables experimental biologists and clinical researchers to perform sophisticated analyses ranging from cancer subtype-specific SV identification to multi-sample comparative studies without requiring specialized programming skills. AVAILABILITY AND IMPLEMENTATION: All codes are available at https://github.com/ylab-hi/OctopuSV; https://github.com/ylab-hi/TentacleSV.

Software↗

Challenges for reproducibility in species delimitation.

Species richness is a foundational metric for comparing biodiversity among clades and regions in ecology, evolution, and conservation. As the biodiversity crisis accelerates, taxonomists face increasing pressure to delimit and name species rapidly, often relying on automated or semi-automated methods that prioritize speed over thoroughness. Yet the reproducibility of species delimitation (the degree to which independent experts reach consistent conclusions given the same evidence) remains largely unquantified, and its consequences for estimates of species richness have never been assessed at the scale of an entire fauna. This gap is consequential: if species delimitation is highly variable among practitioners, then published species counts may reflect the idiosyncrasies of individual taxonomists as much as the true biological structure of diversity within and among clades. Here we evaluate the precision, or reproducibility, of species delimitation in Neotropical freshwater fishes, the most species-rich continental vertebrate assemblage. We provided identical morphological and molecular datasets for species representing four genera to 40 taxonomic experts (10 per genus), who were asked to delimit species using (1) their preferred analytical approaches and (2) standardized analytical outputs. Total variance in species delimitation was partitioned into variance attributable to data analysis and interpretation of results. Total discordance was high (35.0%), and although standardization of analytical methods reduced discordance, substantial variance remained (23.5%) due to interpretative differences. Deviations from modal species estimates were not explained by any of seven expert attributes assessed, including taxonomic experience, publication record, geographic location, taxonomic concepts, or analytical methods. These results demonstrate that species delimitation can be subject to considerable subjectivity, even among experienced taxonomists working with identical data. Improving the precision of species delimitation will require coordinated advances across the full taxonomic workflow, including greater standardization of data acquisition and analysis, and clearer interpretative frameworks that explicitly define the evidentiary thresholds required to recognize species boundaries. Community-wide adoption of transparent reporting standards, analogous to those developed in genomics and clinical research, would help expose the sources of interpretative disagreement and facilitate more consistent application of species concepts across taxa and research groups. Developing benchmark datasets and shared reference taxonomies, against which new delimitation hypotheses can be evaluated, represents a tractable near-term goal for the systematic community. Ultimately, however, reproducible taxonomy cannot be achieved through procedural standardization alone. High-quality revisionary taxonomy must be grounded in experienced character evaluation and homology assessment, concept delimitation, and contingent analytical judgment, skills that are developed over years of immersive engagement with natural history collections, primary literature, and fieldwork. The decline of training opportunities in classical systematics therefore poses a direct threat not only to taxonomic productivity but to taxonomic consistency. Continued investment in a well-trained community of systematists, supported by institutions, collections, and funding agencies, remains the most reliable foundation for consistent and accurate species delimitation. Our results underscore that biodiversity metrics widely used in ecology, conservation planning, and macroevolutionary research are sensitive to practitioner variation in ways that have not previously been quantified, and that addressing this variation requires both methodological reform and sustained commitment to systematic expertise.

biodiversity↗

ModiCal: A Targeted Calibration Workflow for Site-Specific m5C Validation by Nanopore Direct RNA Sequencing.

Accurate identification of RNA 5-methylcytidine (m5C) at the single-nucleotide resolution remains a central challenge in nanopore direct RNA sequencing (DRS). Current global scanning and modification-aware basecalling methods enable transcriptome-wide profiling but often yield high false-positive rates and lack site-specific accuracy. To address this, we repurposed ModiDeC, originally a de novo multimodification classifier, into a targeted, high-precision validation tool for RNA modification sites with prior biochemical knowledge. This was implemented through a three-step calibration workflow that alternates between biochemical and computational modules using the well-characterized m5C2278 site in 25S rRNA as a starting point. Baseline training uses short synthetic RNAs carrying either a methylated or unmodified C2278 as ground truth, followed by IVT-derived calibration and validation in methyltransferase knockout yeast. The baseline model accurately detected the bona fide m5C2278 site but initially produced off-target predictions. Iterative retraining with unmodified IVT signals progressively reduced and ultimately eliminated false positives while maintaining a strong signal at the bona fide site. The final model retained enzyme-dependent detection in wild-type versus knockout yeast and, when explicitly targeted, was also able to detect the second rRNA site, C2870, which remained invisible in the initial analysis. Application to native human prerRNA processing intermediates further resolved two distinct m5C deposition regimes on 28S rRNA, while generalization to dengue virus genomic RNA confirmed that the same calibration logic transfers across diverse RNA contexts. Together, this study establishes a reproducible and transferable framework that integrates biochemical validation with iterative neural network refinement, providing a route toward reliable site-specific m5C confirmation by nanopore direct RNA sequencing.

RNA Methylation↗

Multicentre performance evaluation of the E170 module for modular analytics.

The E170 module was evaluated at 13 sites in an international multicentre study. The objective of the study was to assess the analytical performance of 49 analytes, and to collect feedback on the system's reliability and practicability. The typical, within-run coefficients of variation (CVs) for most of the quantitative assays ranged between 1 and 2% while a range of 2-4% was achieved with the infectious disease methods. Total precision CVs were found to be within the manufacturer's expected performance ranges, demonstrating good concordance of the system's measuring channels and a high reproducibility during the 2-4-week trial period. The functional sensitivity of 11 selected assays met the clinical requirements (e.g., thyreotroponin (TSH) 0.008 mU/l, troponin T 0.02 microg/l, total prostate-specific antigen (PSA) 0.03 microg/l). The E170 showed no drift during an 8-hour period and no relevant reagent carryover. Accuracy was confirmed by ring trial experiments and method comparisons vs. Elecsys 2010. The reliability and practicability of the system's hardware and software met with, or even exceeded, the evaluator's requirements. Workflow studies showed that E170 can cover the combined workload of various routine analysers in a variety of laboratory environment. Throughput and sample processing time requirements were achieved while personnel 'hands-on-time' could be reduced.

Calibration↗

The MEPUC concept adapts the C-arm fluoroscope to image-guided surgery.

Image-guided surgery requires surgeons to be able to manipulate the imaging modality themselves and without delay. Intraoperative fluoroscopic imaging does not meet this requirement as the C-arm fluoroscope cannot be operated or positioned by the surgeons themselves. The Motorized Exact Positioning Unit for C-arm (MEPUC) concept aims to optimize the workflow of positioning the C-arm fluoroscope. The hardware component of the MEPUC equips the fluoroscope with electric stepping motors. The software component allows the surgeon to control the fluoroscope's movements. The study presented here showed that translational movements within the x-y plane are most frequently performed when positioning the C-arm fluoroscope. Furthermore, reproducing a former projection was found to be a frequent task during image-guided procedures. In our opinion, the MEPUC concept adapts the fluoroscope to image-guided surgery. The most important improvement being definition of a bidirectional data exchange between the surgeon and the C-arm fluoroscope: positioning data from the surgeon to the C-arm fluoroscope and-subsequently-image information from C-arm fluoroscope to the surgeon.

Femoral Fractures↗

SynFlow: an interactive online genome structural variant viewer.

MOTIVATION: Structural variations (SVs), including inversions, translocations (TRAs), duplications, and large insertions or deletions, are key drivers of genome evolution and phenotypic diversity. With the increasing number of high-quality, chromosome-scale genome assemblies, the ability to detect and interpret SVs has become a crucial aspect of modern genomics. While SV detection has advanced, most visualization methods produce static plots that fall short when researchers, particularly in comparative genomics, need to interactively explore large datasets, zoom into specific genomic regions, or dynamically filter structural events in real time. RESULTS: To address this gap, we introduce SynFlow, a lightweight, web-based interactive application specifically designed for exploring and visualizing SVs identified by SyRI. We demonstrate that SynFlow can reproduce complex static synteny plots published in literature, but transforms them into dynamic, shareable visualizations that support real-time filtering, reordering, and deep exploration of specific SVs, including TRAs. SynFlow is available as a web server and offers multiple entry points: browsing precomputed datasets (e.g. banana and grapevine genomes), uploading user-provided SyRI outputs, or running an integrated workflow to produce and visualize SVs on the fly. AVAILABILITY AND IMPLEMENTATION: https://synflow.southgreen.fr; source code https://github.com/SouthGreenPlatform/synflow; preprocessing Snakemake workflow https://gitlab.cirad.fr/agap/cluster/snakemake/synflow.

Software↗

Proteomics: the next revolution in laboratory medicine?

BACKGROUND: The identification of specific genetic alterations and protein profiles associated with disease offers a unique opportunity to develop proteomics-based assays for early diagnosis. By identifying proteins in serum/plasma, a minimally invasive tool is used to assess the presence of disease and to monitor response to treatment and/or disease progression. The potential clinical applications of this tool are broad-based, including the diagnosis not only of cancer but also cardiovascular and neuromuscular diseases, organ transplantation associated conditions, and infertility. METHODS: A number of competing chromatographic techniques have been proposed for overcoming the complexity and labor-intensive manipulations associated with the traditional technique for proteomic analysis, which is based on two-dimensional gel electrophoretic techniques. However, mass spectrometry has now assumed a central role in most proteomic workflows, and several combinations of ionization sources, analyzers and fragmentations devices have been described and developed. RESULTS: Thanks to proteomic applications in the diagnosis of cancer, several research groups have identified proteomic patterns associated with ovarian, prostatic, colorectal and other cancers. While the sensitivity and specificity of these patterns are highly satisfactory, there are still some open questions concerning the standardization, reproducibility, and inter-laboratory agreement of these data. CONCLUSIONS: Proteomics, and, in particular, serum mass spectroscopic proteomic pattern diagnostics, is a rapid expanding field of research. The plasma proteoma has an important position at the intersection between genes and diseases, and clinical laboratories must adapt to a new era of tests based on proteomics and genomics. In the future, mass spectrometry will become an essential tool in the clinical laboratory.

Biomarkers, Tumor↗

Power matters in closing the phenotyping gap.

Much of our understanding of physiology and metabolism is derived from investigating mouse mutants and transgenic mice, and open-access platforms for standardized mouse phenotyping such as the German Mouse Clinic (GMC) are currently viewed as one powerful tool for identifying novel gene-function relationships. Phenotyping or phenotypic screening involves the comparison of wild-type control mice with their mutant or transgenic littermates. In our study, we explored the extent to which standardized phenotyping will succeed in detecting biologically relevant phenotypic differences in mice generated and provided by different collaborators. We analyzed quantitative metabolic data (body mass, energy intake, and energy metabolized) collected at the GMC under the current workflow, and used them for statistical power considerations. Our results demonstrate that there is substantial variability in these parameters among lines of wild-type C57BL/6 (B6) mice from different sources. Given this variable background noise in mice that serve as controls, subtle phenotypes in mutant or transgenic littermates may be overlooked. Furthermore, a phenotype observed in one cohort of a mutant line may not be reproducible (to the same extent) in mice coming from a different environment or supplier. In the light of these constraints, we encourage researchers to incorporate information on intrastrain variability into future study planning, or to perform advanced hierarchical analyses. Both will ultimately improve the detectability of novel phenotypes by phenotypic screening.

Animals↗

An efficient woody plant protoplast platform enables transgene-free multiplex genome editing and rapid trait validation in pear.

Multiplex editing is crucial for analysing complex multiple-gene traits in woody plants, yet its application remains limited because of low transformation efficiency and lengthy regeneration cycles. To overcome these barriers, in this study we establish an efficient protoplast isolation protocol for pear (Pyrus) that employs 1.0% cellulase R10 and 0.4% macerozyme R10 with an 8.5 h digestion. Its broad applicability using different digestion times across seven other economically important woody plants is demonstrated. Coupling a 40% PEG-4000-mediated transfection regimen with DNA-free CRISPR/Cas9 ribonucleoprotein (RNP) delivery enables multiplex genome editing in isolated protoplasts. Using this platform, we simultaneously disrupted the key components of the chloroplast division apparatus ARC3, PARC6, and FtsZ2-1a in Pyrus bretschneideri and found that it consistently reproduced macro-chloroplast abnormalities, confirming effective multigene perturbation within a single cellular context. Notably, failure of chloroplast division activated chloroplast-to-nucleus retrograde signaling, as evidenced by the induction of the nuclear stress-response genes RBOHD and ZAT12, a concomitant surge in reactive oxygen species, and progression to severe cellular deformation. Thus, our study establishes a rapid, cross-genus protoplast-RNP workflow that enables DNA-free multiplex editing and accelerates genotype-to-phenotype analyses in woody perennials. The approach provides a practical foundation for functional genomics and supports advances in non-transgenic precision breeding of tree crops.

Protoplasts↗

metaExpertPro: A Computational Workflow for Metaproteomics Spectral Library Construction and Data-Independent Acquisition Mass Spectrometry Data Analysis.

Analysis of large-scale data-independent acquisition mass spectrometry metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS, protein identification and quantification using data-independent acquisition mass spectrometry, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-min diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67-0.90) in genus diversity and showed a high correlation (rSpearman = 0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.

Proteomics↗

Filmless cardiac imaging: motion or commotion?

At present times the medical cardiology imaging is still arguing about the usefulness of X-Ray Cine film in comparison with digital and filmless imaging. It is clear that both techniques have their advantages. X-Ray Cine film is a well established technique of which the possibilities are well known. At a first glance filmless imaging offers nothing but advantages. However the whole picture becomes clear when trying to implement these systems in a clinical environment, because at that time aspects of investments, technological continuity and risks, needed skills and effects on the workflow appear. This article has the purpose to clarify some of these aspects and give guidance in the difficult process of making the right decision.

Cineangiography↗