During restricted timeframes in Drosophila development, re-replication occurs as physiological process causing the known developmental gene amplification in Drosophila. Gene amplification has also been found during differentiation in human stem cells but re-replication in human cells has been preferentially associated with tumor related genome instability. Here, we show that re-replication also occurs as physiological process in human stem cells. We used Rerep-Seq and fiber-combing to demonstrate re-replication during the differentiation of human myoblasts into myotubes and during the differentiation of mesenchymal stem cells into adipocytes, osteoblasts, chondrocytes, and neurons. Re-replication was detectable during specific timeframes in all differentiations analyzed. FACS sorting of re-replicating cells showed increased gene expression in re-replicated genome regions. Additionally, re-replicated DNA was identified as extranuclear DNA. This leads us to the hypothesis that cells that do not re-replicate and thus do not face an increased risk of chromosomal instability may ensure higher expression of certain genes and their encoded proteins during differentiation by incorporating re-replicated DNA from neighbouring cells with re-replication. We propose that human stem cells use an ancient re-replication mechanism to efficiently increase gene copy numbers, thereby meeting the heightened protein demands during differentiation.

High-throughput single-cell omics of non-human primate brain tissue provides a powerful platform to investigate the molecular basis of brain aging. Here, we present a comprehensive transcriptomic and chromatin accessibility atlas of 2,955,873 nuclei from eight brain regions of 23 female cynomolgus macaques spanning the adult lifespan, including exceptionally old individuals. Our analyses reveal dynamic, cell-subtype- and region-specific age-related changes in core brain functions, including synaptic communication and axon myelination. We identify multicellular networks in the pons and medulla as a previously unrecognized hotspot of primate brain aging, highlighting white matter vulnerability as a central feature of aging. Integration with human brain aging and neurodegeneration datasets reveals both shared and divergent molecular mechanisms. We further define transcription factors and age-related chromatin remodeling programs linked to longevity and neurodegeneration. This spatiotemporal atlas establishes a foundational framework for understanding the cellular and regulatory architecture of primate brain aging and its links to disease.

Abstract Macaque’s research centrality makes it critical to study their molecular aging. We accomplish this for their non-coding transcriptome by sequencing small RNA from 11 organs, with special focus on brain by including 24 brain regions, sampling males and females between ages 3-35 years. Heart, adrenal gland, corpus callosum and caudate putamen showed the most age-deregulated miRNA trajectories. The MIR-154 family, inside the imprinted, rejuvenation-associated Dlk1-Dio3 cluster, was particularly vulnerable. Known age-associated miRNA families LET-7, MIR-29, MIR-17 and MIR-92 were strongly deregulated, with heavy dependence on tissue and sex. MiRNA genomic clusters deregulation was concordant within tissue-sex combinations, implicating upstream regulation rather than random noise. Cross-species comparison with mouse showed ancient miRNAs dominating age-deregulated trajectories. Deregulation direction in tissues-sex was conserved between species at family/cluster levels, but conservation substantially weakened at individual miRNA level. Thus, we mark a decisive step in translating miRNA aging trajectories between two heavily used model organisms. Key Findings Heart, adrenal gland, corpus callosum, caudate putamen are hotspots of miRNA age deregulation, with dramatic influence from sex. Non-brain organs show tissue specific miRNA change, with inconsistent overlap between tissues. Genomic clusters of miRNAs were found to be concordant in their age deregulation direction, dependent on tissue and sex, suggesting upstream regulation. The MIR-154 family, housed inside the heavily imprinted Dlk1-Dio3 cluster and processed from the rejuvenation associated MEG3-MIRG host gene is prominently involved in both non-brain organs and brain regions. Concentration of age deregulation in evolutionarily ancient miRNAs across species implies regulatory program rather than epigenetic drift, involving MIR-154, LET-7, MIR-29, MIR-17 and MIR-92 families. Direction of change conserved between species at the family / genomic cluster level but diminished substantially at individual miRNA level.

Neurodegenerative diseases affect 1 in 12 people globally and remain incurable. Central to their pathogenesis is a loss of neuronal protein maintenance and the accumulation of protein aggregates with ageing1,2. Here we engineered bioorthogonal tools3 that enabled us to tag the nascent neuronal proteome and study its turnover with ageing, its propensity to aggregate and its interaction with microglia. We show that neuronal protein half-life approximately doubles on average between 4-month-old and 24-month-old mice, with the stability of individual proteins differing among brain regions. Furthermore, we describe the aged neuronal 'aggregome', which encompasses 1,726 proteins, nearly half of which show reduced degradation with age. The aggregome includes well-known proteins linked to diseases and numerous proteins previously not associated with neurodegeneration. Notably, we demonstrate that neuronal proteins accumulate in aged microglia, with 54% also displaying reduced degradation and/or aggregation with age. Among these proteins, synaptic proteins are highly enriched, which suggests that there is a cascade of events that emerge from impaired synaptic protein turnover and aggregation to the disposal of these proteins, possibly through microglial engulfment of synapses. These findings reveal the substantial loss of neuronal proteome maintenance with ageing, which could be causal for age-related synapse loss and cognitive decline.

SUMMARY:Visualization of multidimensional, categorical data is a common challenge across scientific domains and, in particular, the life sciences. The goal is to create a comprehensive overview of the underlying data which enables one to assess multiple variables. One application where such visualizations are particularly useful is gene or pathway analysis, which involves checking for dysregulation in known biological mechanisms and functions across multiple conditions. Here, we propose a new visualization approach that encodes such data in an intuitive representation: DicePlots visualize up to four distinct categorical classes in a single view using elements resembling dice faces, whereas DominoPlots add an additional layer of information for binary comparison. AVAILABILITY AND IMPLEMENTATION:The code is available as the diceplot R package and the pydiceplot on PyPI. All source code is available at https://github.com/maflot. CONTACT:The repo is managed actively and we encourage community contributions and requests.

The dysfunction of limbal epithelial cells (LECs) and limbal stromal cells (LSCs) in congenital aniridia remains incompletely understood. We aimed to analyze mRNA expression profiles of primary human LECs and LSCs, as well as microRNA (miRNA) expression in LSCs, from patients with congenital aniridia (AN-LECs and AN-LSCs). mRNA sequencing of primary human LECs and mRNA and miRNA sequencing of LSCs were performed from patients with aniridia and healthy controls. Gene ontology and pathway analyses were used to evaluate biological processes, cellular components, and molecular functions. Selected deregulated mRNAs and miRNAs were validated by quantitative real-time PCR (RT-qPCR). A total of 188 differentially expressed genes (DEGs) were identified in AN-LECs, and 3001 DEGs in AN-LSCs. In AN-LECs, the top hub genes were associated with inflammatory and interferon-related responses. In contrast, AN-LSCs showed predominant deregulation of mitochondrial and metabolic genes. Pathway analysis revealed involvement of inflammation-related pathways in AN-LECs and metabolic pathways in AN-LSCs. Additionally, 48 deregulated miRNAs were identified in AN-LSCs. This study provides comprehensive mRNA profiles of LECs and LSCs and miRNA profiles of LSCs in congenital aniridia. The findings emphasize the importance of LSC influence and offer insights into molecular mechanisms underlying aniridia-associated keratopathy (AAK), supporting future research and potential therapeutic target identification.

Post-Acute Infection Syndromes (PAIS) are medical conditions that persist following acute infections from pathogens such as SARS-CoV-2, Epstein-Barr virus, and Influenza virus. Despite growing global awareness of PAIS and the exponential increase in biomedical literature, only a small fraction of this literature pertains specifically to PAIS, making the identification of pathogen-disease associations within such a vast, heterogeneous, and unstructured corpus a significant challenge for researchers. This study evaluated the effectiveness of large language models (LLMs) in extracting these associations through a binary classification task using a curated dataset of 1000 manually labeled PubMed abstracts. We benchmarked a wide range of open-source LLMs of varying sizes (4B-70B parameters), including generalist, reasoning, and biomedical-specific models. We also investigated the extent to which prompting strategies such as zero-shot, few-shot, and Chain of Thought (CoT) methods can improve classification performance. Our results indicate that model performance varied by size, architecture, and prompting strategy. Zero-shot prompting produced the most reliable results: Mistral-Small-Instruct-2409 and Llama-3.1-Nemotron-70B-Instruct achieved balanced accuracy scores of 0.81 and 0.80, respectively, along with macro-F1 scores of up to 0.80, while maintaining minimal invalid outputs. While few-shot and CoT prompting often degraded performance in generalist models, reasoning models such as DeepSeek-R1-Distill-Llama-70B and QwQ-32B demonstrated improved accuracy and consistency when provided with additional context.

Background Primary biliary cholangitis (PBC) is a chronic autoimmune liver disease characterized by progressive biliary destruction and cholestasis. Current therapies, including ursodeoxycholic acid (UDCA), exhibit limited efficacy in advanced disease. In this study, we investigate the therapeutic potential of microbial intervention using Lactobacillus rhamnosus (Lbr) in the Mcpip1fl/flAlbCre knockout mouse model of PBC, which we described previously. Knockout mice develop human PBC-like features such as bile acid dysregulation, autoantibodies, cholangiocyte hyperplasia and fibrosis. Methods Six-week-old Mcpip1fl/fl (wild-type) and Mcpip1fl/flAlbCre (knockout) mice were treated with Lactobacillus rhamnosus supplementation, UDCA (15 mg/kg/day), UDCA + Lbr, and UDCA + OCA (obeticholic acid, 10 mg/kg/day) for six weeks. Treatment response was characterized by liver and gut pathology, serum biomarkers, transcriptomic profiles, and microbiome composition. Results Treatment of Mcpip1fl/flAlbCre animals with Lbr decreased serum bile acids and reduced pathological cholangiocyte dysplasia in the liver, decreased leukocyte infiltration and fibrosis. RNAseq of liver tissue revealed enrichment of humoral immune responses and T cell activation pathways in knockouts, all of which were significantly attenuated by Lbr monotherapy. Gut pathology marked by increased intraepithelial lymphocyte infiltration and mucosal hypertrophy, was also normalized upon Lbr administration. Finally, probiotic treatment modulated the microbiome by increasing the Firmicutes/Bacteroidetes ratio and enriching butyrate-producing Lachnospiraceae. Administration of UDCA and UDCA+OCA had less pronounced effects: only decreased serum bile acids was detected in both groups. Conclusions Probiotic intervention with Lbr represents a feasible strategy to attenuate fibrotic progression in a mouse model of autoimmune cholestatic disease by modulation of the gut-microbiome-immune crosstalk.

Bronchopulmonary dysplasia (BPD) is a chronic lung disease affecting 35% of extremely low birth weight infants and is defined by oxygen dependence at 36 weeks postmenstrual age. Preventive interventions carry severe risks and early prediction is crucial to avoid unnecessary toxicity in low-risk infants. Admission radiographs of extremely preterm infants are routinely acquired within 24 h of life and could serve as a non-invasive prognostic tool. We developed a deep learning approach using day 1 chest X-rays from 163 extremely low-birth-weight infants (<= 32 weeks gestation, 401-999 g). We fine-tuned a ResNet-50 pretrained specifically on adult chest radiographs, employing progressive layer freezing with discriminative learning rates to prevent overfitting and evaluated a CutMix augmentation and linear probing. Complementing prior insights that compare architectures and acquisition timing, we ablate the effects of initialization domain and computelight fine-tuning choices on performance on small day-1 neonatal CXR cohorts, yielding practical training guidance for site-level and federated deployment. For moderate/severe BPD outcome prediction, our best performing model with progressive freezing, linear probing and CutMix achieved an AUROC of 0.78 f 0.10, balanced accuracy of 0.69 f 0.10, and an F1-score of 0.67 f 0.11. In-domain pre-training significantly outperformed ImageNet initialization (p = 0.031) highlighting the importance of domain-specific pretraining. Routine IRDS grades showed limited prognostic value (AUROC 0.57 f 0.11), motivating learned image markers.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality, particularly in advanced stages where therapeutic options are limited. Cancer-associated fibroblasts (CAF) within the tumor microenvironment (TME) contribute significantly to tumor progression and represent a promising therapeutic target. In this study, we developed biocompatible and biodegradable polycarbonate nanogels for the improved lipid-free, CAF-targeted delivery of siRNA against microfibrillar-associated protein 5 (MFAP-5), a pro-angiogenic factor expressed by inflammatory CAF (iCAF). Using a cirrhotic murine HCC model (C-HCC), we demonstrated that intravenously injected anti-MFAP-5-siRNA-loaded nanogels (NG:siMFAP5) silenced the MFAP-5 expression, reduced fibroblast activation, and suppressed tumor growth in a dose-dependent manner. In vivo biodistribution studies revealed preferential uptake of nanogels by CAF, followed by dendritic cells and macrophages. Mechanistically, MFAP-5 was shown to promote angiogenesis via NOTCH/Hes1 signaling in fibroblasts. MFAP-5 expression in human HCC samples and conserved signaling pathways between mice and humans underscore the translational relevance of this target. Our findings highlight the therapeutic potential of CAF-targeted siRNA delivery using polycarbonate-based nanogels to inhibit stromal-driven angiogenesis and tumor progression in HCC.

Single-cell transcriptomic studies of peripheral blood mononuclear cells (PBMCs) offer valuable insights into immune states across diverse biological conditions, yet cross-study integration remains difficult due to divergent preprocessing and annotations. PBMCpedia addresses this by uniformly reprocessing 519 samples (over 4.3 million cells) from 24 publicly available single-cell RNA sequencing studies using a standardized pipeline with consistent quality control and hierarchical cell type annotation. Spanning 14 disease contexts, including autoimmune, infectious, and neurodegenerative disorders, as well as healthy controls, PBMCpedia supports metadata-aware comparisons across diseases, cell types, sexes, and age groups. It also includes T-cell receptor/B-cell receptor repertoire data for 75 samples and surface protein measurements for 56 samples, enabling integrative immune profiling at both the transcriptomic and proteogenomic levels. To support exploration and accessibility, we provide an interactive web interface (https://web.ccb.uni-saarland.de/pbmcpedia/) for querying gene expression, marker genes, and pathway enrichment across cell types, conditions, sexes, and age groups. PBMCpedia fills a critical gap by offering a transparent, harmonized, and disease-diverse PBMC resource designed for cross-study immune profiling and discovery.

The oral cavity harbours a complex microbial ecosystem and a key interface with the external environment. To gain a broader and more temporally resolved understanding of the oral microbiome, we analysed 1,242 samples from 585 individuals, including specimens from aligners, plaque, and saliva across healthy individuals and patients with caries or periodontitis. We found that clear aligners, worn continuously, provide a notably stable and comprehensive snapshot of oral microbial diversity, capturing 399 species and substantially overlapping with saliva. While only 25 species showed disease-associated differences, functional profiling revealed an extensive biosynthetic capacity, with 41,923 biosynthetic gene clusters organized into 1,786 families. Among these, 103 gene cluster families showed differential abundance in disease states and included both characterized antimicrobials and potentially novel metabolites. This study underscores the value of functional microbiome profiling in advancing precision oral health.

Endothelial cells (ECs) experience shear stress associated with blood flow. Such shear stress regulates endothelial function by altering cell physiology. Since most cell culture protocols and media compositions are designed for static cultures and experiments with ECs are predominantly conducted under these non-physiological conditions, a model for culturing ECs under flow conditions is developed, which more closely mimics their physiological environment. This approach also enables the isolation of EVs while minimizing FCS-derived contaminants. In this study, a comprehensive assessment of how physiologically relevant cultivation conditions influence the vesicle composition and function of ECs is provided. A detailed investigation is conducted for the effect of different cell culture media on morphology and marker expression of human umbilical cord endothelial cells (HUVECs) and EVs, and optimize the conditions to culture ECs under flow, tailoring them specifically to facilitate the efficient isolation of EVs using a hollow-fiber system model. These EVs are then characterized and compared to those isolated from traditional static culture conditions. Overall, this study presents a model on isolating EC-derived EVs under conditions that closely mimic physiological environments, and characterization at their proteome, gene expression, and microRNA profile.

The neurovascular unit is critical for brain health, and its dysfunction has been linked to Alzheimer's disease (AD). However, a cell-type-resolved understanding of how diverse vascular cells become dysfunctional and contribute to disease has been missing. Here, we applied Vessel Isolation and Nuclei Extraction for Sequencing (VINE-seq) to build a comprehensive transcriptomic atlas from 101 individuals along AD progression. Our analysis of over 842,646 parenchymal and vascular nuclei reveals that vascular dysfunction in AD is driven by transcriptional changes rather than shifts in cell proportions, with brain endothelial cells (BECs) and smooth muscle cells (SMCs) most affected. Strikingly, these molecular signatures emerge early at the mild cognitive impairment (MCI) stage, implicating vascular dysfunction early in AD pathogenesis. Stratifying by pathology reveals distinct vascular responses to β-amyloid and tau: β-amyloid burden primarily perturbs BECs and SMCs, while tau pathology predominantly impacts glial cells. We identify dysregulated angiopoietin signaling across multiple vascular cell types as a key axis, with antagonistic ANGPT2 in vascular cells and ANGPT1 in astrocytes becoming progressively dysregulated with AD. Together, this work provides a foundational resource that reveals early and pathology-specific pathways of vascular dysfunction in AD.

MiRNAs represent a non-coding RNA class that regulate gene expression and pathways. While miRNAs are evolutionary conserved most data stems from Homo sapiens and Mus musculus. As miRNA expression is highly tissue specific, we developed miRNATissueAtlas to comprehensively explore this landscape in H. sapiens. We expanded the H. sapiens tissue repertoire and included M. musculus. In past years, the number of public miRNA expression datasets has grown substantially. Our previous releases of the miRNATissueAtlas represent a great framework for a uniformly pre-processed and label-harmonized resource containing information on these datasets. We incorporate the respective data in the newest release, miRNATissueAtlas 2025, which contains expressions from 9 classes of ncRNA from 799 billion reads across 61 593 samples for H. sapiens and M. musculus. The number of organs and tissues has increased from 28 and 54 to 74 and 373, respectively. This number includes physiological tissues, cell lines and extracellular vesicles. New tissue specificity index calculations build atop the knowledge of previous iterations. Calculations from cell lines enable comparison with physiological tissues, providing a valuable resource for translational research. Finally, between H. sapiens and M. musculus, 35 organs overlap, allowing cross-species comparisons. The updated miRNATissueAtlas 2025 is available at https:// www.ccb.uni-saarland.de/tissueatlas2025.

High-throughput single-cell omics of non-human primate tissues present a remarkable opportunity to study primate brain aging. Here, we introduce a transcriptomic and chromatin accessibility landscape of 1,985,317 cells from eight brain regions of 13 cynomolgus female monkeys spanning adult lifespan including exceptionally old individuals up to 29-years old. This dataset uncovers dynamic molecular changes in critical brain functions such as synaptic communication and axon myelination, exhibiting a high degree of cell type and brain region specificity. We identify the multicellular networks of the pons and medulla as a previously unrecognized hotspot for aging. Furthermore, comparative analyses with human neurodegeneration datasets highlight both shared and distinct mechanisms contributing to aging and disease. In addition, we uncover transcription factors implicated in monkey brain aging and pinpoint aging-regulated loci linked to longevity and neurodegeneration. This spatiotemporal atlas will advance our understanding of primate brain aging and its broader implications for health and disease. ### Competing Interest Statement The authors have declared no competing interest.

The lack of a sufficient number of validated miRNA targets severely hampers the understanding of their biological function. Even for the well-studied miR-155-5p, there are only 239 experimentally validated targets out of 42,554 predicted targets. For a more complete assessment of the immune-related miR-155 targetome, we used an inverse correlation of time-resolved mRNA profiles and miR-155-5p expression of early CD4+ T cell activation to predict immune-related target genes. Using a High-throughput miRNA interaction reporter (HiTmIR) assay we examined 90 target genes and confirmed 80 genes as direct targets of miR-155-5p. Our study increases the current number of verified miR-155-5p targets approximately threefold and exemplifies a method for verifying miRNA targetomes as a prerequisite for the analysis of miRNA-regulated cellular networks.

Technological advances in single-cell RNA sequencing (scRNA-seq) allow us to sequence the transcriptomes of thousands of single cells in parallel, resulting in massive amounts of raw sequence data that must be processed efficiently to obtain a genes x cells expression matrix. In droplet-based scRNA-seq protocols, the sequenced mRNA molecules are tagged with a cell-specific barcode and a unique molecular identifier (UMI) within each cell. Both barcodes and UMIs may contain errors from production, amplification or sequencing. Correcting and resolving such errors before further processing yields more reliable data and more accurate expression measurements. We propose algorithmic advancements for barcode correction, read-to-gene mapping and UMI resolution, which we combine into a new method called arcane for efficient gene expression quantification from scRNA-seq data. We additionally provide an implementation as a workflow-friendly command-line tool, also called arcane. This work builds on the recently published Fourway method to efficiently discover DNA k -mers with a Hamming distance of 1, speeding up barcode correction and UMI resolution, and allowing for distinguishing k -mers into weakly and strongly unique ones during read-to-gene mapping. As a side result of separate interest, we show that for the mapping step, it suffices to store three genes per k -mer in order to cover almost all of the genes almost completely, thus avoiding arbitrarily large colors sets in the colored De Bruijn graph index. As a result, arcane is faster than existing methods while producing very similar results, as demonstrated in a comparison with CellRanger, Kallisto|bustools and Alevin-fry. ### Competing Interest Statement The authors have declared no competing interest.