Biology subjects

Zhu, Q.

Publications and source records attributed to Zhu, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

A cytotoxicity dataset for data-driven design of ionizable lipid nanoparticles

Ionizable lipid nanoparticles (LNPs) are widely used to deliver nucleic acid therapeutics, but the design of safe LNPs remains challenging due to the complex activity relationships among structure, composition, and physicochemical properties. Here, we present a curated dataset, the Lipid Nanoparticle Cytotoxicity Database (LNPCD), which aggregates 1,413 LNP cytotoxicity measurements across 1,288 unique ionizable lipids drawn from 11 high-throughput combinatorial studies. Lipid structures were generated computationally from the published libraries and manually verified against the original publications. Each record pairs a machine-readable SMILES representation of the ionizable lipid with its measured viability endpoint and the associated experimental descriptors, including cell line, dose, and cargo type. The dataset provides a traceable resource for examining how ionizable lipid structure and experimental conditions relate to in vitro cell viability, and for developing and evaluating computational models of lipid nanoparticle cytotoxicity.

bioengineering↗

bioRxiv2026

Coding region changes in the Hippo pathway component YAP1 contribute to body size differences among mammalian species

Animal species differ dramatically in their overall size, yet the mechanisms underlying these differences are poorly understood. The Hippo pathway, first discovered in Drosophila, and widely conserved in mammals, regulates the nuclear levels of YAP1, a transcriptional co-activator that enhances the expression of growth-promoting genes. While experimental manipulations of this pathway elicit dramatic effects on tissue growth and organ size, it is not known whether, and to what extent, evolutionary divergence of this pathway has contributed to size differences across animals. Here we show that although YAP1 protein sequence is highly conserved between diverse mammals such as humans, elephants and blue whales, it diverges considerably among rodent species. While the human YAP1 protein is very similar to that of the largest rodent, the capybara Hydrochoerus hydrochaeris, those of smaller rodents such as the mouse Mus musculus and the vole Microtus oregoni show considerable divergence. An increased ratio of non-synonymous versus synonymous substitutions (dN/dS) in clades of small rodents compared to the background is indicative of relaxed constraint in these lineages, suggesting relative positive selection. When expressed in the developing Drosophila wing, capybara YAP1 was more potent at promoting growth than that of the mouse or vole. Following transfection into mammalian cells, capybara YAP1 is more effective at promoting expression of a reporter gene than either mouse or vole YAP1. Thus, by combining computational and experimental approaches, we show that evolutionarily divergent coding-region changes in YAP1 have likely contributed to the evolution of smaller body size in clades of rodents.

developmental biology↗

bioRxiv2026

Pharmacological activation of mitophagy prevents calcific aortic valve disease by targeting dysregulated mitochondrial-to-nuclear communication

Abstract Background and Aims: Calcific aortic valve disease (CAVD) lacks pharmacologic therapy. Mitophagy impairment contributes to various degenerative diseases, but whether it occurs in calcified aortic valves and during human valvular interstitial cell (hVIC) osteogenic differentiation remains unknown. We therefore investigated the role of mitophagy in CAVD and whether its pharmacological treatment prevents disease progression. Methods: Single-cell RNA sequencing (scRNA-seq) was performed on human aortic valves and hVICs. TJ0113, a novel orally available mitophagy activator from our previous screening, was tested in two CAVD mouse models. Multi-omics analyses and functional rescue experiments were performed to elucidate the mechanism. Results: Mitophagy was impaired in calcified human aortic valves and during hVIC osteogenic differentiation. TJ0113 activated MCL1-mediated mitophagy and attenuated disease progression in vitro and in vivo. Mechanistically, the mitophagy receptor MCL1 anchors a fraction of PRMT3 on mitochondria. During osteogenic differentiation, a dysregulated mitochondrial-to-nuclear communication is initiated by the increased release of PRMT3 into the cytosol, where it interacts with BACH1 and impairs BACH1 nuclear translocation. This leads to a widespread loss of BACH1 genomic occupancy, relieving BACH1-mediated transcriptional repression of the pro-osteogenic factor PARM1 and promoting hVIC osteogenic differentiation. Mitophagy activation by TJ0113 restored MCL1-PRMT3 binding and reversed these alterations. Conclusions: Mitophagy impairment drives CAVD through dysregulated mitochondrial-to-nuclear communication mediated by the MCL1-PRMT3-BACH1-PARM1 axis. Pharmacological mitophagy activation by TJ0113 corrects this communication and attenuates disease progression, representing a promising therapeutic strategy for CAVD.

pathology↗

bioRxiv2026

In Utero MRI of Radial Glial Fibers Highlights Their Role in Modulating Fetal Cortical Folding

The process of cortical folding is fundamental to early human brain development. While the differential growth of the cortical layers is a known driver, the biomechanical contribution of key cellular microstructures remains unclear, and there is a lack of direct in vivo markers of cortical microstructures for time-resolved observations. Using a multimodal approach combining in utero and ex vivo fetal brain MRI, histology, and computational mechanical simulation, we investigated whether developmental reorganization of cortical radial microstructures, particularly the radial glial cell (RGC)-associated scaffold, is linked to cortical folding and may modulate its mechanical progression. We characterized this radial organization noninvasively using diffusion MRI-based radial fiber density (FDrad). ex vivo fetal brain MRI and histology supported that regional variations in FDrad were strongly associated with vimentin-labelled radial architecture. Our in utero MRI data revealed closely coordinated developmental changes in cortical FDrad and curvature, with their regional timings and spatial patterns significantly coupled across the cortex. Longitudinal in utero MRI data further supported the synchronized within-individual co-development of FDrad and curvature. Furthermore, biomechanical simulations showed that reducing radial reinforcement modulated differential-growth-driven buckling, producing earlier folding and a greater cortical curvature under otherwise matched model conditions. Collectively, this study introduces FDrad as a noninvasive in utero MRI measure sensitive to radial glial fibers. By integrating spatial, temporal, histological, and computational evidence, our findings suggested a model in which developmental disassembly of the radial scaffold may modulate the mechanical response of the fetal cortex to differential growth, thereby contributing to cortical folding.

neuroscience↗

bioRxiv2026

Tractable and Thermodynamically Consistent pKa Prediction via First-Dissociation Aggregation

Ionization governs molecular behavior, yet predicting aqueous pKa accurately and tractably remains a fundamental challenge. Rigorous ensemble methods require enumerating a protonation-state space that grows exponentially with the number of ionizable sites, while fast graph predictors return numbers without thermodynamic consistency. Here we derive an exact thermodynamic identity showing that the macroscopic first-dissociation constant is fully determined by protonated-microstate populations and unique first-deprotonation events, eliminating the deprotonated ensemble algebraically and reducing aggregation to O(n+E) operations. We implement this identity in DTi-pKa, a dual-head graph neural network whose free-energy and dissociation heads are coupled by thermodynamic constraints. On four external benchmarks (355 molecules), DTi-pKa achieves a pooled MAE of 0.5665 pKa units, with 0.6285 on the 169 records lacking training-cache matches, while providing site-resolved micro-pKa values and protonation-state populations. Controlled ablations show that constraint placement at the level of the reported macroscopic equilibrium matters more than microscopic label precision--a design principle transferable to physics-informed machine learning beyond chemistry. Closure diagnostics expose numerical self-consistency as an open frontier, which we report transparently. By replacing an intractable computation with a physical identity, DTi-pKa unifies macroscopic accuracy and microscopic interpretability in a single framework.

bioinformatics↗

bioRxiv2026

Beyond RMSD: Deterministic Dlow Matching for Ultrafast and Physically Validated Transition-State Generation

Transition state (TS) generation is typically evaluated by geometric similarity, yet low root-mean-square deviation (RMSD) does not establish first-order saddle-point character or reaction-path connectivity. Here we introduce Kairos-GFM, a deterministic equivariant flow-matching model that combines a two-dimensional reaction graph with the Kabsch-aligned mean of three-dimensional reactant and product geometries. Using 881 Transition1x reactions whose reference TSs passed strict saddle-point and bidirectional intrinsic reaction coordinate validation, Kairos-GFM generates one candidate in 0.0118 s with a median RMSD of 0.14 [A]. A hierarchical physical-validation framework--spanning reaction-center geometry, raw single-point energy, DFT saddle-point optimization, harmonic frequency analysis, and IRC endpoint matching reveals that low RMSD and saddle-point convergence do not guarantee the intended reaction channel. Kairos-GFM recovers the target channel in 75.94% of reactions, outperforming diffusion-based baselines but remaining below transport-based methods. These results position Kairos-GFM as a rapid initial-geometry generator for quantum-chemical refinement and provide a transferable validation standard that distinguishes geometric similarity from physical fidelity.

biochemistry↗

bioRxiv2026

SkeleSketch: An Open-Source Tool for Quantifying Microglial Morphology in Fiji/ImageJ

Microglial morphology is widely used as an indicator of cellular state, yet existing analytical approaches are often labor-intensive, require proprietary software, or depend on high-resolution imaging platforms. Here, SkeleSketch is presented as an open-source Fiji/ImageJ plugin that automates microglial skeletonization, morphological quantification, and data organization while allowing optional user-guided correction. Using spinal cord microglia from PBS- and LPS-treated mice, SkeleSketch accurately reconstructed cellular morphology and captured expected LPS-induced morphological remodeling, including enlarged soma size and reduced branching complexity. Comparable measurements were obtained from both CX3CR1-GFP reporter mice and Iba1 immunostaining, demonstrating robustness across labeling strategies. Additionally, SkeleSketch morphometrics were positively correlated with those generated by the commercial software Imaris. Our pipeline provides an accessible, reproducible, and flexible platform for quantitative microglial morphology analysis using standard epifluorescence microscopy.

neuroscience↗

bioRxiv2026

MINT infers the latent single-cell spatial transcriptome from paired histology

Sequencing-based spatial transcriptomics captures transcriptome-wide molecular information, yet the corresponding cell-resolved tissue map remains incomplete. Histology records dense cellular morphology, tissue architecture and local context. Here, we present MINT (Morphological Integrative Network for Transcriptomics), which combines this latent cellular organisation with sample-specific spatial measurements to infer tissue-wide, cell-resolved transcriptomes without an external single-cell reference. MINT reconstructs expression from sparse Slide-tags profiles across unmatched adjacent sections; its shared nucleus-centred representation also resolves pooled Visium measurements into cell-level profiles. MINT improved Slide-tags alignment and expression recovery under controlled nuclear loss and cross-section perturbation. It also outperformed reference-free Visium disaggregation methods against Xenium ground truth and was validated with Visium HD sequencing. In human lung adenocarcinoma, MINT reconstructed the tumour immune microenvironment cell by cell and resolved tertiary lymphoid structures and their maturity. These results establish paired histology as a quantitative, sample-intrinsic complement to molecularly rich but cellularly incomplete spatial-transcriptomic assays.

bioinformatics↗

bioRxiv2026

Adaptive introgression in Tibetans spans focal and distributed architectures

The Denisovan-derived EPAS1 haplotype is a paradigmatic example of adaptive introgression, but whether archaic ancestry contributed beyond such large-effect loci remains unclear. We analyzed genomes from 1,039 Tibetans, Han Chinese, archaic hominins and ancient Tibetan Plateau individuals. Denisovan-derived adaptive variation was highly localized around EPAS1, whereas Neanderthal-derived variation was distributed across the genome; temporal and elevational patterns reinforced this contrast. Despite individual-level heterogeneity, Neanderthal-introgressed gene repertoires repeatedly converged on immune, metabolic and signal-transduction pathways. A Tibetan-enriched Neanderthal PPARGC1A haplotype was associated with lower fasting glucose and showed concordant support from an independent East Asian type 2 diabetes GWAS. These findings reveal that adaptive introgression can contribute to complex human adaptation through functionally convergent combinations of archaic variants, rather than only through shared large-effect haplotypes.

evolutionary biology↗

bioRxiv2026

Diffusion MR Microscopy of the Human Hippocampus at 50 μm Resolution at 14.1 T for 3D Virtual Histology

Bridging the gap between macroscopic neuroimaging and microscopic histology remains a challenge in neuroscience. Here, we present a technical feasibility study of diffusion MR microscopy (dMRM) in the ex vivo human hippocampus using a 14.1 T ultrahigh-field MRI system. Mid-hippocampal blocks from control and Alzheimers disease (AD) patients were acquired at 50 x 50 x 100 {micro}m3, representing, to our knowledge, the highest resolution reported for human brain diffusion MRI. At a spatial scale approaching cellular dimensions, dMRM maps and tractography showed close correspondence with immunohistological markers of axons and dendrites. The acquired data delineated six hippocampal laminae, distinguished the inner and outer molecular layers, and preserved short, lamina-specific trajectories that became attenuated or blurred at 100 {micro}m resolution. Tractography further depicted the major components of the hippocampal tri-synaptic circuit--the perforant path, mossy fibers, and Schaffer collaterals in 3D. In the AD specimen, dMRM revealed reduced laminar contrast, local discontinuities, and altered radial and tangential fibers that were paralleled by pathological staining. With the 3D nondestructive characterization of human brain microstructure and circuitry, ex vivo dMRM showed its potential toward the goal of 3D virtual histology.

neuroscience↗

bioRxiv2026

Decoding the Transcriptome Dark Matter: Construction of Single-Cell Whole-Transcriptome Regulatory Atlas by dropTotal

To profile unknown ncRNAs-"dark matter" in single cells, we developed dropTotal, a high-throughput droplet-based total RNA-seq method that uses dU-modified GAT primer with temperature-ramp hybridization and droplet merge barcoding to co-detect coding and non-coding transcripts with record sensitivity (>13,500 genes/cell, including >2,000 lncRNAs and >500 sncRNAs), compatible with fresh, frozen, fixed, and FFPE tissues. Applied to ~75,000 human glioma nuclei, it captured 60,313 genes (18,681 lncRNA, 19,859 mRNAs and 6,753 sncRNAs), enabling ncRNA-driven regulatory landscape construction. In oligodendroglioma, module analysis identified recurrence-associated ncRNA-centered modules linked to therapy resistance and invasion; in glioblastoma, six cellular states showed hundreds of state-specific unannotated ncRNAs with divergent functions, from MIR222HG-mediated immune modulation to SCIRT-driven hypoxia adaptation. Alternative splicing analysis identified 428 state-specific junction markers and mapped cell-state-specific alternative splicing regulation. dropTotal offers broad application for decoding the underlying ncRNA biology and single-cell whole transcriptome regulatory mechanisms in cellular identity and disease progression.

genomics↗

bioRxiv2026

Resource acquisition is more sensitive than carbon storage in soil microorganisms under climate extremes

O_LIDrought and warming can disrupt soil microbial processes and ecosystem functioning. Although soil microorganisms can exhibit physiological adjustments to drought, it remains unclear how they allocate resources between extracellular resource acquisition, potential oxidative metabolism, and carbon storage during drought and recovery, particularly under constant warming and/or heat waves. C_LIO_LIHere, we tested the effects of drought on microbial resource allocation strategies across warming regimes during the resistance and recovery phases. We performed a full-factorial outdoor mesocosm experiment combining drought with constant warming and periodic heat waves, applied individually and in combination. We measured the potential activities of extracellular enzymes as proxy for the acquisition of microbial resources, the activity of dehydrogenase as a proxy for the potential active oxidative metabolism, and microbial glycogen pools as a proxy for carbon storage. We also quantified drought legacy effects by measuring microbial functioning before the new drought treatments, capturing the influence of the drought imposed in the previous year. C_LIO_LIDuring the resistance phase, dehydrogenase activity and glycogen pools remained stable, despite reduced extracellular enzyme production, while enzyme allocation shifted towards oxidative enzymes associated with acquisition of recalcitrant C in warming regimes. One month after rewetting, all microbial proxies no longer differed from the control soil moisture conditions. Drought legacy effects were observed in extracellular enzymes, dehydrogenase activity, and glycogen pools, with glycogen exhibiting the strongest legacy effect. C_LIO_LIWe conclude that the asymmetrical responses of extracellular resource acquisition and internal C storage to drought and warming may function as strategies for microbial survival in increasingly variable climates. C_LI

ecology↗

bioRxiv2026

Parallel and scalable balanced minimum evolution algorithm for large-scale phylogenetic inference

The rapid growth of biological data demands scalable yet robust phylogenetic methods. Distance-based approaches are widely adopted not only in alignment-based molecular phylogenetics but also in emerging applications involving alternative distance measures. Balanced minimum evolution (BME) is an important principle in distance-based phylogenetic inference. A heuristic for BME using a taxon addition strategy was developed and provided by the FastME package, producing accurate tree topologies compared with alternative methods. However, beyond the original FastME implementation, there has been little development aimed at scaling this algorithm to the size of modern datasets. We present a significantly redesigned implementation of the BME algorithm that substantially improves computational efficiency while preserving mathematical equivalence. The key algorithmic improvement is the replacement of recursive tree traversal with flattened, incrementally growing arrays representing tree topology, traversal order and node properties. This design reduces traversal overhead, improves memory locality, and enables parallelization of the BME algorithm for the first time. Benchmarks show that our implementation delivers multiple dozen-fold speedup while consuming half the memory of FastME on datasets with tens of thousands of taxa. It can effectively analyze datasets of over 100,000 taxa, which are prohibitive with FastME. In addition, this implementation compares favorably in both efficiency and solution quality with a modern implementation of neighbor joining (NJ), an alternative BME heuristic using an agglomerative clustering strategy. Our BME algorithm has been released as part of the open-source Python library scikit-bio. It substantially broadens access to BME-based phylogenetic inference at scale.

bioinformatics↗

bioRxiv2026

Probabilistic Retinotopic Parcellation of the Macaque Visual Cortex

Probabilistic brain atlases provide anatomically and functionally interpretable normative references that summarize population-level organization while explicitly representing spatial uncertainty. Yet such resources remain scarce due to the resource-intensive experimental efforts required to construct them. Here, we present a probabilistic retinotopic atlas of the macaque visual cortex, derived from contrast-enhanced phase-encoded fMRI data acquired in 13 subjects. The dataset includes a 50% probability parcellation covering 19 visual areas, individual subject labels, and voxel-wise probability maps for each area, all registered to the MEBRAINS macaque template. By combining a consensus parcellation with spatial estimates of confidence for each visual area, this atlas enables more informed anatomical localization and interpretation than deterministic or single-subject-based atlases. As a standardized reference for the macaque visual cortex, it supports experimental design, data interpretation, and multimodal data integration while providing a quantitative framework for investigating the developmental and evolutionary principles that shape the primate visual cortex.

neuroscience↗

bioRxiv2026

RD-OMICS: An Integrative Multi-Omics Data Inventory in Rare Diseases

Rare diseases (RD) impact over 30 million individuals in the United States, yet fewer than 5% of the identified conditions have FDA-approved treatments. Progress in RD research is hindered by small patient cohorts, biological heterogeneity, and the fragmented, inconsistently annotated publicly available omics data, which limits integrative analysis and translational discovery. Here, we present RD-OMICS, a data inventory with integrated and structured RD omics data from Gene Expression Omnibus (GEO), in the form of a knowledge graph. We developed a metadata harmonization pipeline that combines rule-based mapping and large language model (LLM)-assisted semantic categorization. The graph-based data model was defined to integrate different types of data including disease conditions, experiments, samples, platforms, projects, and publications into a centralized inventory graph. In this preliminary study, 11,049 GEO series for 126 rare diseases were processed and integrated into RD-OMICS, which includes 375,930 individual biospecimen samples, 1,578 sequencing and array platforms, 10,938 biological projects. Case studies demonstrate the use of RD-OMICS in supporting rare disease research, omics cohort construction, and transcriptome-based drug repurposing for amyotrophic lateral sclerosis (ALS). RD-OMICS provides a scalable foundation for transforming fragmented omics data into a structured, harmonized and interoperable resource, facilitating therapeutic development and other translational discoveries in rare diseases.

bioinformatics↗

bioRxiv2026

Nuclear phylogenomics clarifies the family-level backbone and gene-tree conflict in Zingiberales

Zingiberales includes eight morphologically distinctive families, but its family-level backbone has remained unstable, especially around Musaceae, Heliconiaceae, Lowiaceae, and Strelitziaceae. We analysed 1566 low-copy nuclear genes from 52 samples, representing all eight families and Pontederia crassipes as outgroup. Concatenated maximum likelihood and multispecies coalescent analyses recovered the same backbone: ((Zingiberaceae, Costaceae), (Cannaceae, Marantaceae)) is sister to (Musaceae, (Heliconiaceae, (Lowiaceae, Strelitziaceae))). Penalized-likelihood dating placed the sampled crown group in the Late Cretaceous, with several deep family-level divergences occurring on short internodes. Analysis of 1248 rerooted gene trees showed that conflict is concentrated on these deep branches and in several shallow clades. HyDe tests of empirical and simulated matrices, each including 62,475 triples, did not support widespread ancient hybridization among the major family-level lineages after filtering against the simulated null model. The nuclear data recover a stable Zingiberales backbone, and the long-standing instability of several deep nodes is best explained by rapid early divergence and extensive incomplete lineage sorting.

evolutionary biology↗

bioRxiv2026

Structural basis of the nucleotide incorporation cycle of bacterial DNA polymerase III

Bacterial DNA polymerase III (PolIII) is the primary replicative polymerase responsible for faithful genome duplication, yet high-resolution structural snapshots of the enzyme during DNA synthesis and proofreading have remained elusive. Here we determine cryo-EM structures of the Escherichia coli PolIII core-clamp-DNA binary, ternary and proofreading complexes at 2.4-2.7 [A] resolution, revealing the structural basis of nucleotide selection, incorporation and proofreading. Binding of an incoming nucleotide expels the single-stranded template overhang from the polymerase central channel and induces a large rotation of the polymerase index finger, which closes around the incoming nucleotide to form a compact nascent base-pair-binding pocket. A conserved tyrosine on the finger stacks against the incoming nucleotide to impose stringent steric constraints that promote nucleotide selection, whereas a conserved histidine acts as a steric gate to exclude ribonucleotides. The proofreading structures capture key intermediates that reveal how PolIII transfers a mismatched primer terminus to the 3'-5' exonuclease active site and excises the misincorporated nucleotide while avoiding unnecessary degradation of correctly paired DNA. Together, these findings define the molecular mechanism by which the bacterial replicative polymerase couples rapid and processive DNA synthesis with exceptional replication fidelity.

biochemistry↗

bioRxiv2026

Computational reconstruction of hierarchical cis-regulatory networks reveals synergistic transcription control and disease-associated rewiring

Gene regulation emerges from coordinated interactions among dispersed cis-regulatory elements, yet how these elements integrate into functional regulatory networks and collectively regulate gene transcription remains poorly understood. Here, we present ORIGAMI, a multi-omics, gene-centric deep learning framework that reconstructs functional cis-regulatory networks constrained by transcriptional output. ORIGAMI formulates cis-regulatory modeling as a latent graph inference task, which integrates DNA sequence, epigenomic signals, and three-dimensional chromatin priors to infer denoised regulatory graphs that capture functional interactions rather than structural proximity alone. The inferred regulatory graphs exhibit distinct topological regimes, where hierarchical and modular organization encodes cell-state-specific functional demands and enables synergistic transcriptional control. Furthermore, we show that these regulatory architectures undergo measurable state-dependent rewiring across disease contexts. Finally, ORIGAMI accurately predicts the transcriptional consequences of both cis- and trans-regulatory perturbations and links the rearrangement of regulatory architecture to perturbation response. Together, ORIGAMI advances a network-based view of gene regulation and establishes a foundation for virtual cell modeling of regulatory dynamics.

bioinformatics↗