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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 307 records · Page 17Linked to original sources

Early mitophagy defects and impaired mitochondrial energy metabolism drive target organ damage progression: lessons from the Fabry heart

Increased literature support the pathogenetic role of dysfunctional energetic metabolism in the setup and progression of organ damage and failure. Genetic diseases often offer the possibility to investigate pathogenetic mechanisms. In particular, excessive cardiac damage is the most frequent cause of mortality in Fabry disease (FD), a genetic condition caused by deficient -galactosidase A (GLA) activity, leading to globotriaosylceramide (Gb3) accumulation. Beyond Gb3 storage, metabolic alterations and mitochondrial dysfunction, supported by in vitro evidence or studies in other tissues, may contribute to FD cardiomyopathy. This study investigated, for the first time, the mechanisms of mitochondrial involvement in FD, its role in determining cardiac manifestations, and its potential as a therapeutic target. We used a humanized FD mouse model (R301Q-Tg/GLA knockout), along with derived embryonic fibroblasts and neonatal and adult cardiomyocytes, to assess mitochondrial function across the lifespan. FD cells showed impaired mitophagy, reduced mitochondrial respiration, and increased reactive oxygen species production. Importantly, this mitochondrial dysfunction exacerbated the lysosomal deficit in FD cells, forming a vicious cycle. In cardiomyocytes, these alterations progressed with age, leading to the accumulation of dysfunctional mitochondria, energetic failure, and, in adult hearts, terminal mitochondrial damage and apoptosis. These events ultimately result in cardiac remodeling and dysfunction, including hypertrophy and diastolic impairment. Indeed, L-arginine supplementation, which promotes NO/PGC-1-dependent mitochondrial rescue, prevented the development of cardiac abnormalities in FD mice. Our findings identify early mitochondrial dysfunction as a key driver of FD cardiomyopathy and support mitochondrial targeting, including L-arginine supplementation, as a promising adjuvant therapeutic strategy. The mechanistic link between lysosomal dysfunction, altered mitochondrial turnover, and energetic collapse emerges as a key targetable pathway in organ damage, extending beyond FD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/718770v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@3353deorg.highwire.dtl.DTLVardef@1c7234forg.highwire.dtl.DTLVardef@df3632org.highwire.dtl.DTLVardef@5f143e_HPS_FORMAT_FIGEXP M_FIG C_FIG Cardiac manifestations vs mitochondrial alterations in Fabry disease: the visible tip and the hidden base of the icebergCardiac manifestations in hR301Q Tg/KO mice become evident from 9 months of age. However, mitochondrial homeostasis is perturbed much earlier (neonatal to young stages), with impaired mitophagy, reduced mitochondrial respiration and membrane potential, increased ROS production and PGC-1 downregulation. At later stages, from 6 months of age, mitochondrial dysfunction progresses and begins to impact cellular energetics, as indicated by reduced ETC expression and the onset of energetic deficit (ATP reduction). The resulting energetic collapse, together with progressive mitochondrial leakage, leads to cardiomyocyte hypertrophy, apoptosis, and dysfunction, which become detectable from 9 months of age, when clinical signs emerge. These findings support a mechanistic model in which 1) lysosomal incompetence due to GLA deficit is the initiating event inducing impairment of mitophagy; 2) Unsuccessful mitophagy, induces downregulation of PGC-1a-dependent mitogenesis; 3) exhausted mitochondria accumulate, inducing energetic collapse (able to exacerbate lysosomal dysfunction and further perturb mitophagy in a vitious cycle); 4) ultimate mitochondrial leakage induces Cytochrome C release and apoptosis activation. This cascade of molecular events is responsible for clinical manifestations, and mitochondrial targeting prevents cardiac organ damage. Significance statementFabry disease is a rare genetic disorder in which cardiac complications are a major cause of death, yet underlying mechanisms remain unclear. Here, we identify mitochondrial dysfunction as an early pathogenic event associated with impaired mitophagy, whereby defective mitochondrial quality control both results from and exacerbates lysosomal dysfunction, creating a self-reinforcing cycle that drives disease progression. Using a humanized model, we demonstrate that mitochondrial dysfunction is a key determinant of cardiac phenotype in vivo, driving energetic failure, oxidative stress, and cardiac damage. Importantly, L-arginine treatment restores mitochondrial function and prevents cardiac abnormalities. Our findings define a broadly relevant pathogenic axis linking lysosomal dysfunction, mitophagy failure, and mitochondrial impairment, that lead to impaired energetic metabolism and consequent cardiac hypertrophy, independently from GB3 accumulation. The implications of our study go beyond Fabry disease and support the therapeutic targeting of cellular energy homeostasis to prevent and treat organ damage and failure in chronic diseases. IMPORTANTO_LIManuscripts submitted to Review Commons are peer reviewed in a journal-agnostic way. C_LIO_LIUpon transfer of the peer reviewed preprint to a journal, the referee reports will be available in full to the handling editor. C_LIO_LIThe identity of the referees will NOT be communicated to the authors unless the reviewers choose to sign their report. C_LIO_LIThe identity of the referee will be confidentially disclosed to any affiliate journals to which the manuscript is transferred. C_LI GUIDELINESO_LIFor reviewers: https://www.reviewcommons.org/reviewers C_LIO_LIFor authors: https://www.reviewcommons.org/authors C_LI CONTACTThe Review Commons office can be contacted directly at: office@reviewcommons.org

pathology↗

Functionalization and Antimicrobial Evaluation of Azadirachta indica Leaf-Synthesized Silver Nanoparticles with Amoxicillin

The authors have withdrawn this manuscript on administrative grounds to ensure full compliance with institutional requirements regarding the dissemination of thesis-derived research prior to completion of the degree evaluation process. This withdrawal does not reflect any concern about the validity, integrity, accuracy, or reproducibility of the data, methods, or conclusions presented in the manuscript, which stand as reported. The work is intended to be made available again, either as a revised preprint or through peer-reviewed publication, once the relevant institutional requirements have been completed. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

microbiology↗

Synthesis of Biogenic Silver Nanoparticles with Aqueous Extract of Azadirachta indica Seed and Its Antimicrobial Activity on MDR and ESBL-Producing Escherichia coli.

The authors have withdrawn this manuscript on administrative grounds to ensure full compliance with institutional requirements regarding the dissemination of thesis-derived research prior to completion of the degree evaluation process. This withdrawal does not reflect any concern about the validity, integrity, accuracy, or reproducibility of the data, methods, or conclusions presented in the manuscript, which stand as reported. The work is intended to be made available again, either as a revised preprint or through peer-reviewed publication, once the relevant institutional requirements have been completed.. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

microbiology↗

First record of the subfamily Eucerotinae (Hymenoptera: Ichneumonidae) from the mainland Afrotropics, with a description of a new species

The ichneumonid subfamily Eucerotinae has been thought to be almost absent from the tropics, with the only known Afrotropical species found in Madagascar. We report the subfamily to be present in the mainland Afrotropics, and describe a new species, Euceros species 1 from Uganda and Cameroon (name not yet shown in preprint). The subfamily had likely not been observed in the mainland Afrotropics before due to low abundances and insufficient sampling. More Eucerotinae likely remain to be discovered in tropical Africa and Asia, although tropical America may genuinely have few eucerotine species. Much more extensive sampling will be needed before it is possible to make confident estimates of how eucerotine diversity is distributed globally.

zoology↗

Compartment-dependent selection regimes maintain the G-quadruplex paradox across the eukaryotic kingdoms

G-quadruplex (G4) DNA structures are depleted from coding sequences (CDS) and enriched in regulatory regions across diverse genomes (the "G4 paradox"), but the selection regime maintaining this architecture across eukaryotes remains unclear. Analysing 198 reference genomes balanced across the four kingdoms (Animalia 86, Fungi 49, Plantae 33, Protozoa 30), we pro-pose a two-regime architecture in which the dominant selective force depends on the genomic compartment. In CDS, codon-adaptation selection takes priority: naive Nei-Gojobori comparison shows 5-16% synonymous-rate (dS) suppression at G4 codons in six of seven unsaturated species pairs, but the signal is absorbed by per-gene codon-adaptation-index (CAI) adjustment (0/7 pairs retain a G4 odds ratio below 1; five reverse to OR > 1). In introns and promoters, where no codons exist, selection acts directly on G4 structure: phylogenetic generalised least-squares (PGLS) yields five Benjamini-Hochberg-significant kingdom-specific helicase associations (q < 0.10), all at intronic or promoter G4s, including context-dependent FANCJ/BRIP1 ({beta} = +1.60, q = 0.057 for intron G4 in Plantae; {beta} = -2.49, q = 0.004 for promoter G4 in Proto-zoa); three of five remain significant on an independent Open Tree of Life backbone. Intronic G4 are concentrated in deeply conserved orthologue groups ([&ge;] 87% in every kingdom), consistent with maintenance of regulatory G4 host-gene context since early eukaryotic evolution. Interim-correction notice (bioRxiv v3, 2026-08-03)This preprint version corrects a set of documentation-level errors identified in a coauthor audit of the analysis pipeline (available as AUDIT_REPORT.md in the Zenodo deposit). Several central analytical claims of this manuscript -- the definition of the log2 IRR (density-vs. fraction-ratio), the downstream use of consensus-stable versus candidate G4 motifs, the CAI-controlled dS adjustment model, the filter chain in the stable-G4 classifier, and the reconciliation of PGLS output across main, alternative-tree, robustness, and Supplementary Information files -- are currently under clean-environment re-verification. The outcome of that re-verification may change specific numerical values, the direction of some regional sign summaries, and the framing of downstream conclusions in a subsequent version. Readers should treat the present version as an interim documentation correction, not as a fully verified revision. Users planning to build on the deposited results should consult CORRECTION_NOTES.md and AUDIT_REPORT.md in the Zenodo deposit for the current list of open methodology-level issues.

genomics↗

A response-geometry framework separates microbiome movement magnitude from directional coherence in intervention studies

Dietary and lifestyle microbiome interventions often produce mild but heterogeneous remodeling rather than uniform community shifts. In this setting, scalar diversity or group-level summaries can appear weak or inconclusive even when participants move in organized but magnitude-limited directions, or move substantially in divergent directions. We developed a response-geometry framework that jointly describes baseline-referenced response magnitude and cross-participant directional coherence within a compositional feature space. The framework complements diversity, ordination, trajectory, PERMANOVA, PERMDISP, and beta-diversity analyses by asking whether paired responses differ in size, shared direction, or both. MethodsA response vector for each participant was defined as the follow-up minus baseline profile after adding a 0.5 pseudocount and applying centered log-ratio transformation in Aitchison-based response space. Response magnitude was the Euclidean length of this vector. Directional coherence was quantified as cosine alignment between participant-level response vectors and the mean group response vector, with sign-flip permutations as a paired-structure-preserving diagnostic null. We evaluated the framework using workflow-sensitive diversity comparisons, 198,000 logistic-normal compositional simulations with 100 or 500 features and small-to-large shared-direction effects, public-data-derived implementation stress tests, a synbiotic and dietary-intervention cohort, and a fiber/fermented-food application in 16S rRNA gene amplicon and shotgun-derived CAZyme gene-family feature spaces. A beta research-preview repository accompanying the preprint is available at https://github.com/carolyyszeto/microbiome-response-interpreter-beta as v6.5-beta, including documented scripts, a toy dataset, environment notes, output-interpretation guidance, and exploratory implementation utilities. ResultsWorkflow comparisons showed that richness-sensitive differences were concentrated in rare-tail and low-abundance structure, informing the analytical feature-space context for response interpretation. In simulations, null and magnitude-only random-direction scenarios showed near-null detection rates of 0.061 and 0.062, close to nominal alpha = 0.05, whereas shared-direction scenarios showed increasing coherence with stronger effects and larger sample sizes. Mixed-responder and opposing-subgroup scenarios attenuated or cancelled pooled coherence, supporting separation between response magnitude and directional organization. The synbiotic and dietary-intervention cohort showed modest, heterogeneous displacement with limited within-arm coherence, with permutation p values from 0.575 to 0.653. In the fiber/fermented-food application, fermented-food exposure showed stronger 16S response organization than the baseline-period reference, while CAZyme estimates used non-identical sampling endpoints and remained feature-space-specific. ConclusionsThis response-geometry framework helps distinguish paired microbiome movement size from shared response orientation. It is intended as an interpretively cautious response-organization descriptor for mild, heterogeneous intervention settings, not as a replacement for existing multivariate methods. Its interpretation depends on sample size, effect structure, endpoint alignment, zero handling, group-direction stability, and feature-space definition. The framework does not convert weak, null, endpoint-limited, or sensitivity-dependent findings into efficacy, predictive, or mechanistic claims.

microbiology↗

Ultra-Fast Implementation of Multivariate GWAS in Genomic SEM Using Flexible Analytic Estimation

Many medical, physiological, and psychiatric traits and disorders are highly polygenic and exhibit complex patterns of genetic sharing and differentiation. In 2018, we introduced Genomic Structural Equation Modelling (Genomic SEM) as a formal framework and free, open source, R-based software for modelling the multivariate genetic architecture of both continuous and binary Genome-Wide Association Study (GWAS) phenotypes, interrogating their joint and distinct functional genomic pathways, and leveraging empirical models of the genetic relations among phenotypes to guide multivariate GWAS discovery. Here we introduce a closed-form analytic solution for estimating SNP effects within multivariate GWAS in Genomic SEM. This estimator is over 800 times faster than the existing iterative estimator, drastically decreasing reliance on high performance computing (HPC). On a MacBook pro laptop with M4 Max chip, a multivariate GWAS ([~]1M SNPs) of 5 common factors underlying 13 phenotypes takes approximately 2 minutes. Concurrent with the release of this preprint, we are adding an analytic estimation option to the userGWAS function in the GenomicSEM package for alpha testing along with a tutorial on our GitHub wiki.

genetics↗

Controlled microtrauma opens a regenerative window for appendage-bearing skin repair

Adult skin normally resolves injury through rapid closure and fibrotic matrix deposition, often at the cost of permanent appendage loss. We tested whether spatially controlled microtrauma could instead serve as a regenerative entry point when paired with temporally coordinated molecular cues. We engineered a hierarchical extracellular-matrix-based microneedle patch that combines rapid local availability of verteporfin, an inhibitor of YAP-associated mechanotransduction, with sustained retinoic-acid delivery to support follicle-regenerative signalling. The microneedle interface was evaluated in full-thickness rabbit ear wounds, which are prone to hypertrophic scarring, and in Bama miniature-pig wounds, whose skin architecture more closely resembles human skin. Across both models, staged dual-cue treatment accelerated wound closure, reduced collagen-dense scar formation and promoted the appearance of hair-bearing tissue and histologically identifiable follicular structures. These findings support a trauma-guided regeneration framework in which controlled microinjury is used not only for delivery but also to open a transient repair niche that can be molecularly redirected toward appendage-bearing skin restoration. ImportanceMicroneedles are generally treated as minimally invasive delivery devices. Here, the microinjury itself is incorporated into the therapeutic design. The study provides cross-species proof of concept that a patterned injury interface, combined with staged anti-fibrotic and pro-regenerative signalling, can shift wound repair away from fibrotic closure and toward hair-follicle-containing skin. This concise preprint reports the central concept and the rabbit and porcine evidence supporting it; expanded mechanistic and source datasets will be reported separately.

bioengineering↗

SentryPath: a mechanistic protocol-ranking simulator with leave-one-trial-out cross-validation across 13 phase-III oncology randomised controlled trials and a pre-registered prospective forecast

BackgroundPivotal oncology trials cost a median of {approx}$19 million each (oncology often $45 million or more) and contribute to a capitalised cost of {approx}$2.6 billion per approved drug, yet most candidate protocols never reach trial. Existing in-silico screening tools either rely on closed proprietary PK/PD modelling or require patient-level data; a transparent, cohort-level, cross-validated mechanistic alternative is missing. MethodsSentryPath is a physics-based stochastic differential equation simulator built on a Gompertzian tumour-growth term with Emax pharmacodynamic kill and Bliss-independence combination modelling, scored at the cohort level. Validation against 13 published phase-3 randomised controlled trials covering six cancer types uses the 2-year overall-survival (OS) rate ratio as the primary endpoint, cross-checked against ClinicalTrials.gov posted results. For cancer types with [&ge;]2 trials we apply leave-one-trial-out crossvalidation: two shared efficacy scalars per cancer type are fit on training trials and used to predict the heldout trial cold. ResultsWith the per-drug efficacy proxies held fixed from the literature, two shared cancer-type scalars fit on the training trials transfer to the held-out trial with a mean held-out error of 3.7 % (range 0.7-7.3 %) on 2-year OS rate ratios across three NSCLC trials; extending the same method to RCC, HCC, and ESCC yields a 5.4 % aggregate across nine folds (per-fold range 0.2-11.2 %), reported with per-cancer stratification. We are explicit that only the two scalars are held out -- the per-protocol efficacy proxies underneath are literature-anchored to drug classes that include the benchmark trials, so this is a test of scalar transfer, not of the whole engine cold. Cross-validation improves on the same engine without it (16.4 % with production cancer priors; 21.9 % with no efficacy modifiers); a matched in-sample fit of the same two-scalar model gives 4.4 %, slightly below the 5.4 % held-out, the expected direction. Two prospective forecasts are preregistered on the Open Science Framework with falsification envelopes and pre-readout bias disclosure. The first forecast (NCT04770896) reaches its primary data cutoff on 2026-06-30; the observed outcome and its mapping to the pre-committed interpretation will be reported in a versioned update to this preprint. ConclusionA transparent mechanistic simulator, with a literature-anchored efficacy library and only two cross-validated scalars per cancer type, transfers those scalars across held-out NSCLC trials at 3.7 % mean error (range 0.7-7.3 %) and extends to other cancers with documented per-cancer stratification. The validation is pilot-scale (3-9 folds) and the scalars sit on a fixed, trial-informed substrate; its distinguishing contribution is less the error magnitude than the public predict-verify-disclose cycle that goes beyond retrospective fit.

bioinformatics↗

Formation, persistence, and breakdown of carrier-set topology in linkage disequilibrium: empirical structure in 1000 Genomes and a two locus Wright Fisher model

Linkage disequilibrium between two biallelic loci is usually summarized by scalar association measures such as r2 and D'. These measures quantify how visible an allelic association is to a symmetric LD scan, but they do not directly represent the topology of carrier sets: whether the carriers of one variant are contained within, partially overlap with, or are disjoint from the carriers of the other. This distinction is structural. On the haplotype-frequency simplex, carrier-set inclusion corresponds to a boundary face where one haplotype class is absent. In the rare-common regime, a nested rare variant is further constrained by the ceiling r2 [&le;] pA/pB, so that complete carrier-set inclusion can remain nearly invisible to r2. Here, as a companion to the Fisher-geometry preprint 1, we examine the empirical and dynamic behavior of this carrier-set topology. In 1000 Genomes Phase 3, across 156,604,320 SNP pairs from the MHC and NEGR1 regions, pairs on the | D' |= 1 boundary span a wide range of r2 and | C |. Within fixed r2 strata, r2 poorly distinguishes nested from non-nested carrier-set configurations, with AUROC values of approximately 0.54-0.62, whereas the boundary-sensitive normalization | D' | separates them much more effectively, with AUROC values of approximately 0.90-0.92. The empirical data also obey the predicted r2 [&le;] pA/pB ceiling. We then introduce a temporal axis using a two-locus Wright-Fisher model on the same simplex. Carrier-set topology evolves through three motions relative to the | D' |= 1 boundary: formation or persistence, in which recombination suppression establishes and maintains inclusion without requiring selection; visibility change, in which selection or drift moves r2 along the boundary while preserving the inclusion relation; and breaking, in which a recombination pulse introduces the previously absent haplotype and dissolves inclusion. A fourth mode, specificity erosion, expands the partner carrier set while preserving inclusion, thereby lowering P(A | B) while keeping P(B | A) and | D' | equal to one. This mode shows that asymmetric conditional probabilities are best understood as diagnostic coordinates for carrier-set topology, not as the primary object itself. Together, these results show that topology and visibility are separable axes of LD structure. Conventional r2-based scans and carrier-set topology scans therefore answer complementary, not interchangeable, questions.

genetics↗

Negligible participation in the scientific literature of AI unicorn startups

Artificial intelligence (AI) development is concentrated within private firms, yet their participation in scientific publishing remains poorly understood. We conducted a bibliometric analysis of all 317 AI unicorn startups (1998-2025). Only 1,389 eligible peer-reviewed publications and 688 preprints involving some leading startup contributions were identified. More than half of startups (52.4%) produced no qualifying scientific output, and only 24 firms (7.6%) produced any highly cited papers ([&ge;]200 citations). Scientific influence was highly concentrated: the top 10% of firms accounted for 96.8% of citations, while three startups accounted for 92 of 134 firm-attributed highly cited papers. Firm valuation was not associated with publication productivity or highly cited output, whereas funding raised showed weak associations. Overall, participation in formal scientific communication among AI unicorn startups is negligible, comprising only 0.1% of the overall AI literature in 2025. Most leading developers of AI technology do not engage with the scientific literature, raising concerns for the transparency, reproducibility, and accountability of this rapidly moving innovation frontier.

scientific communication and education↗

OmicsLake: Versioned, Agent-Aware Data Lineage for R/Bioconductor Workflows

OmicsLake is an R package for version-aware, dataset-level lineage in R/Bioconductor exploratory workflows. It associates stored versions with dependencies captured within tracked ref()-dplyr-save_as() pipelines or supplied explicitly, and can attach caller-supplied human or software-agent identifiers. Controlled tests recovered all ground-truth edges within the supported path and enabled explicit recovery of an overwritten tagged intermediate. OmicsLake 0.99.3 is MIT-licensed software available at https://github.com/matsui-lab/OmicsLake (tag v0.99.3); source, tests, and evaluation files are archived at https://doi.org/10.5281/zenodo.21391428. Supplementary Material accompanies this preprint.

bioinformatics↗

A high throughput system reveals distinct segmentation clock phase responses in hiPSC-derived organoids

During somitogenesis, the vertebrate body axis segments into transient periodic structures known as somites. Somite formation is regulated by a multicellular molecular oscillator known as the segmentation clock. Recent advances in human induced pluripotent stem cell (hiPSC) culture have shown that hiPSC-derived somitogenesis organoids (somitoids) exhibit segmentation clock oscillations and can be produced at scale, making them an excellent model system for high throughput investigation of the mechanisms underpinning the segmentation clock. However, somitoids interact both biochemically and mechanically, and accurate high-throughput sampling of segmentation clock phases is required to exploit this system effectively. Here we address these challenges using an image-based, high-content screening workflow. Individual hiPSC-derived somitoids carrying a segmentation clock reporter are cultured in 384-well plates, and a programmable feeding schedule is used to initiate oscillations that are monitored using fluorescence microscopy. We develop an automated pipeline for image segmentation and data analysis, represent oscillations using a compact set of parameters, and construct predictive mathematical models to interpret data. We find that: (i) a staggered feeding schedule that sequentially initiates oscillations yields large numbers of somitoids at defined stages of the segmentation clock cycle; (ii) media exchange in established oscillations induces a Type 0-like phase response, resetting the segmentation clock to a state characterised by low NOTCH pathway transcription; and (iii) control wells in media exchange experiments exhibit a Type 1 phase response in which the segmentation clock is delayed non-uniformly across the cycle. Using a mathematical model of segmentation clock dynamics along the anterior-posterior axis, we show that periodic activation of a Type 1 phase response could segment a continuous phase gradient -- an insight with potential implications for the determination of somite boundaries in vivo. IMPORTANTO_LIManuscripts submitted to Review Commons are peer reviewed in a journal-agnostic way. C_LIO_LIUpon transfer of the peer reviewed preprint to a journal, the referee reports will be available in full to the handling editor. C_LIO_LIThe identity of the referees will NOT be communicated to the authors unless the reviewers choose to sign their report. C_LIO_LIThe identity of the referee will be confidentially disclosed to any affiliate journals to which the manuscript is transferred. C_LI GUIDELINESO_LIFor reviewers: https://www.reviewcommons.org/reviewers C_LIO_LIFor authors: https://www.reviewcommons.org/authors C_LI CONTACTThe Review Commons office can be contacted directly at: office@reviewcommons.org

developmental biology↗

ChemoCalib: multiblock PLS calibration of genome-scale metabolic models improves flux prediction over expression-only integration

MotivationConstraint-based metabolic modeling faces a calibration gap: genome-scale metabolic models (GEMs) integrated with transcriptomics alone rely on expression-to-flux heuristics (E-Flux, GIMME, iMAT, MOMENT) that ignore cross-omics co-variance structure and lack statistical mechanisms for propagating omics uncertainty into reaction bounds, yielding flux predictions with limited agreement to 13C metabolic flux analysis (MFA) measurements. ResultsWe present Chemo-Calib, a multiblock PLS (MB-PLS) framework that calibrates GEM reaction bounds from the shared latent structure of metabolomics, transcriptomics, and proteomics data. On 11 E. coli 13C-MFA reference conditions spanning the Keio fluxome and Holm 2010 datasets, ChemoCalib constrained FBA on iJO1366 achieves a Spearman{rho} = 0.461 overall (up to 0.523 in PPP) and Pearson r of 0.49-0.58 across central carbon pathways, with statistically significant improvement over expression-only baselines including E-Flux2 and SPOT (p < 0.05, Holm-corrected). The latent-to-constraint mapping employs GPR-aware VIP aggregation (Algorithm 1) to project multi-omics latent scores onto genome-scale reaction bounds without heuristic thresholding. An optional in-silico active learning loop (relegated to Supplementary Material) further tightens calibration through virtual experiment selection. AvailabilityChemoCalib is open-source (MIT) at https://github.com/chemocalib/chemocalib with Docker support, a 5-minute tutorial, and pre-computed iJO1366 benchmarks. Preprint available at bioRxiv; code archived at Zenodo DOI: 10.5281/zenodo.21645890.

bioinformatics↗

A generative model for dimensionality reduction with millions of features and few samples

MotivationIn this paper, we demonstrate that it is feasible to train a deep generative model for dimensionality reduction with millions of features using few samples, which makes this type of generative model a more versatile alternative to standard methods for dimensionality reduction. Specifically, we hypothesize that for a decoder-only model, the number of training samples required is almost independent of the feature dimensionality in most network architectures. ResultsThrough an extensive set of experiments on synthetic non-linear data, we validate this hypothesis. We also train the model on a downsampled version of the 1000 Genomes Project (1KGP) dataset to further assess its behavior under controlled reductions in sample size. Furthermore, we train a deep generative decoder (DGD) on a curated dataset from the International Cancer Genome Consortium (ICGC), which contains 4.4 million features. It is trained on approximately 4,000 samples and tested on 1,000 samples. The resulting latent representation exhibits clear clustering, and when methods are reduced to the same number of dimensions, it outperforms PCA and VAE for tumor type classification. Additionally, the DGD is computationally efficient and can be trained on a 16GB GPU. Availability and implementationCode is available at https://github.com/cpancott/ReceptiveDGD. Contactcorrado.pancotti@helmholtz-munich.de; akrogh@di.ku.dk Supplementary informationSupplementary data are available with this preprint.

bioinformatics↗

Using CRISPR/Cas9 to investigate the role of candidate human disease gene orthologs in Ciona

The tunicate Ciona robusta offers a tractable non-vertebrate chordate model for probing gene function via tissue-specific, CRISPR/Cas9-mediated mutagenesis in F0. Building on Arcadia Sciences Zoogle platform, which identifies and ranks orthologs of human genes from various non-traditional model organisms, we carried out a pilot project to probe the developmental roles of three notochord- and endoderm-expressed candidate orthologs of human disease genes (Fcho, Pgm3, and Nckap1) alongside a fourth gene (Plastin) implicated in papilla cell elongation. This preprint compiles and updates a series of research project milestones previously posted episodically on Zenodo. Here we summarize the full results and our conclusion about this pilot project. Using CRISPR/Cas9, we found that tissue-specific knockout of Pgm3 and, to a lesser extent, Fcho caused significant defects in larval tail elongation. Separately, CRISPR knockout of Plastin, an actin-bundling gene expressed throughout the sensory-adhesive papillae of the larva, caused a subtle reduction in papilla cell elongation when combined as a duoble knockout with another actin-bundling protein-encoding gene, Villin. These results identify Pgm3 as the most promising candidate for further development as a Ciona-based model of human disease and demonstrate the utility of tissue-specific CRISPR screening for prioritizing candidate disease gene orthologs identified through comparative genomics platforms like Zoogle.

developmental biology↗

Point-in-time evidence and cross-area clinical precedent anticipate clinical entry across 100 focal areas: retrospective validation of the Intangia triage layer

Early-opportunity teams face a combinatorial problem: once a focal target, mechanism or indication is fixed, the space of plausible partners runs to thousands of candidates per area. Intangia's triage layer ranks that space from point-in-time evidence (how much literature, patent and clinical activity a candidate pairing has accumulated, and whether the partner already has clinical precedent in other contexts) so that review starts where clinical activity is most likely to begin next. This preprint validates that capability retrospectively across 100 focal areas spanning drug targets, mechanisms and disease indications, replaying 24.1 million historically scored combination-years with every area scored by a model trained on the other 99 and never on itself. The headline is operational. At a twenty-partner review shortlist per focal area, the median area's four-year first-alert precision is 0.234, against a matched random-ranker median of 0.008: roughly one in four shortlisted partners subsequently entered the focal clinical context within four years, about 38 times each area's own background rate (95% CI 31 to 45). A panel-level permutation puts the result at p = 0.0005. Discrimination generalises: the full 13-feature specification reaches a median leave-one-focal-out ROC-AUC of 0.922 (95% CI 0.911 to 0.929), with no area below chance and all 100 areas beating their strongest count-based baseline. Shortlisted entrants are anticipated with a median observed lead of two years within the evaluation window, and three years (interquartile range one to five) once the window cap is removed and every realised entrant is counted. The core ranking is carried by two interpretable signal families: cumulative co-occurrence counts and leave-one-area-out clinical precedent. Burst detection serves a complementary role: it supplies the time-stamped, source-specific momentum evidence attached to every recommendation (what is accelerating, and why now) rather than additional ranking power. A conditional view of the same landscape ranks candidates with no cross-area precedent against one another, enriched relative to matched random ranking, supporting a lower-yield emerging-opportunities capability. Two worked examples, PD-1 combination immunotherapy and CTLA-4, are point-in-time historical replays of the same architecture in familiar territory, showing what an alert looked like with the dated evidence behind it. The endpoint throughout is first clinical entry, not clinical success; prospective validation is the next stage.

bioinformatics↗