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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

Systematic Evaluation of Nasal Immune Cell Sampling and Antigen-specific T cell Detection using Cryopreserved Nasal Swabs

The upper respiratory tract is a key entry point for pathogens, yet local tissue-resident memory T cells (Trm) remain underexplored compared to peripheral blood. We systematically compared nasal curettes and 8 different swab types for immune cell collection, assessing yield, operator variability, and T cell phenotypes across the three turbinates and nasopharynx. The use of flocked swabs yielded higher immune cell numbers while being similarly tolerated, especially with reduced sampling duration. Nasal Trm subsets were consistent across the turbinates, whereas nasopharyngeal Trm displayed a more recently recruited phenotype. Multiple cryopreservation media were evaluated and all demonstrated high viability after thawing. Antigen-specificity was assessed using the activation induced marker (AIM) assay, peptideHLA tetramers and bulk TCR-sequencing following expansion. Notably, influenza-specific T cell frequencies were reliably detected by AIM and correlated between fresh and cryopreserved nasal samples. Downregulation of the CD3/TCR complex was observed in nasal samples. These findings establish a robust approach for nasal Trm profiling, demonstrating that cryopreservation preserves functional antigen-specific T cells. This work enables centralized, minimally invasive nasal T cell analysis for multicenter studies, including mucosal vaccination trials and controlled human infection models.

immunology↗

bioRxiv2026

Stochastic Biophysics of Cellular Radiosensitivity: From Molecular Noise and Repair Kinetics to Evolutionary Demographics

Radiation-induced DNA double-strand breaks (DSBs) drive cellular mortality, mutagenesis, and severe evolutionary bottlenecks. While classical phenomenological models, such as the Linear-Quadratic (LQ) framework, reliably predict macroscopic population survival, they obscure the intrinsic single-cell stochasticity that governs critical rare events like tumor recurrence or the emergence of radioresistant persisters. To bridge this divide, we develop a mathematically exact stochastic differential equation (SDE) framework that models continuous DSB induction and repair as a Feller square-root process. By deriving exact closed-form expressions for the foci moments, we establish a highly efficient Maximum Likelihood Estimation (MLE) pipeline that circumvents computationally exhaustive Monte Carlo simulations, allowing the direct extraction of deterministic repair velocities and intrinsic molecular noise from empirical single-cell $\gamma$-H2AX data. Integrating this kinetic model with a cumulative damage hazard via the Feynman-Kac formalism, our framework seamlessly recovers the classic macroscopic LQ survival topology from microscopic first principles. Furthermore, systematic sensitivity analysis uncovers a fundamental evolutionary duality: while initial physical damage operates additively, ultimate cellular fate is driven by a nonlinear survival response governed by the trade-off between the damage hazard rate and intrinsic molecular noise strength. Crucially, we demonstrate that this molecular noise inherently enhances population survival. Governed by Jensen's inequality, stochastic variance acts as a non-genetic bet-hedging mechanism that buffers the population by favoring cells with transiently low damage loads. Ultimately, this exact stochastic framework bridges microscopic biophysics and macroscopic demographics, offering deep mechanistic insights into the evolutionary roots of radioresistance.

biophysics↗

bioRxiv2026

β4-integrins safeguard nuclear mechanics to suppress prostate cancer progression

Prostate cancer (PCa) progression is accompanied by profound alterations in cell-extracellular matrix (ECM) adhesion, nuclear architecture and mechanical adaptability, yet the molecular mechanisms linking these processes remain poorly understood. Hemidesmosomes (HDs), formed by 6{beta}4-integrins, anchor epithelial cells to the basement membrane and couple extracellular forces to the intermediate filament (IF) cytoskeleton. Here, we identify a previously unrecognized tumor-suppressive function of {beta}4-integrins in preserving nuclear integrity in prostate epithelial cells. Loss of {beta}4-integrins disrupted the cytokeratin-5 network and its coupling to the nucleus, leading to nuclear softening, lamin remodeling, reduced heterochromatin content and enhanced confined migration. Unexpectedly, proximity-labeling proteomics revealed that {beta}4-integrins engage nuclear pore complex (NPC) components in an 6-independent manner, particularly upon HD disassembly. Selected interactions were validated using proximity ligation and co-immunoprecipitation assays. {beta}4-integrin loss was associated with enlarged nuclear pores and aberrant nucleocytoplasmic transport, including nuclear accumulation of YAP1. Consistent with these findings, reduced {beta}4-integrin expression in a large PCa tissue cohort correlated with altered nuclear morphology, adverse clinicopathological features, metastatic progression, and poor patient survival. Collectively, our study establishes {beta}4-integrins as a critical molecular link between cell-ECM adhesion, nuclear mechanics and genome integrity.

cancer biology↗

bioRxiv2026

TomatoPGFM: A graph-conditioned foundation model for tomato pangenomes

Most genomic foundation models are pretrained on independent linear assemblies and therefore do not explicitly represent population-level segment sharing or local graph connectivity. We developed TomatoPGFM, a graph-conditioned model pretrained on 54.65 Gb of sequence from 66 tomato (Solanum spp.) accessions. Sequence tokens were conditioned on pangenome node attributes and local adjacency, and the model was optimised using masked language modelling and graph-feature reconstruction. To evaluate model responses to graph-conditioned input, we compared aligned, shuffled and disabled graph inputs in 25,000 windows from the training panel. Sequence-aligned graph input produced lower masked language modelling loss than graph-off at all five curriculum stages in both training-panel strata, while the shuffled perturbation generally yielded intermediate losses. We then assessed sequence-only transfer in Solanum sitiens LA1974 and S. lycopersicum MicroTom, neither of which was used for graph construction or pretraining. Frozen-probe AUROC values for gene-versus-intergenic and coding-sequence-versus-intergenic classification ranged from 0.8489 to 0.9593. TomatoPGFM produced higher AUROC point estimates than DNABERT-2 in all four comparisons. Enabling the zero-feature GraphAdapter pathway with adjacency messaging disabled changed throughput by less than 1% at 512-2,048 positions under the tested configuration. Together, these results show that TomatoPGFM responds consistently to sequence-aligned pangenome context in training-panel sequences and provides informative sequence representations for genic-region classification in accessions excluded from graph construction and pretraining.

bioinformatics↗

bioRxiv2026

SEDATION DIFFERENTIALLY AFFECTS DISTORTION-PRODUCT AND STIMULUS-FREQUENCY OTOACOUSTIC EMISSIONS IN CHINCHILLAS

Purpose: Otoacoustic emissions (OAEs) are used to assess outer hair cell (OHC) function. Clinical interpretation of OAE responses, however, is often limited to a present/absent binary since both physiological factors and measurement variability affect the measured OAE amplitude. Prior work showed elevated OAE responses in sedated compared to awake chinchillas, pointing to the potential influence of the medial olivocochlear (MOC) efferents on amplitudes, but this finding is inconsistent across species and OAE type. Here, we aimed to further investigate the effect of anesthesia on distortion- and reflection-type emissions in chinchillas using swept stimuli and more reliable calibration methods. Methods: Swept distortion-product (DP) and stimulus-frequency (SF) OAEs were measured in chinchillas with and without ketamine/xylazine sedation. Stimuli were presented using in-ear forward pressure level calibrations. DPOAE and SFOAE amplitudes and estimated Qerb from SFOAE group delays were compared across the two conditions. Results: We found that low-frequency DPOAE amplitudes were elevated when animals were sedated. The difference in SFOAE amplitudes was more variable across animals but appeared mildly reduced in sedated animals. Qerb estimates were slightly higher in sedated animals at some frequencies. The effect of sedation was not different across sexes. Conclusion: Taken together, these findings suggest that sedation impacts OAE measurements in chinchillas. MOC modulation could account for the present findings and differences across species. For diagnostic precision, OAE responses should be considered in the context of not only intrinsic OHC function but also extrinsic physiological processes that can modulate OHCs.

physiology↗

bioRxiv2026

Multidimensional diffusion MRI reveals heterogeneous microstructural remodeling associated with amyloid pathology

Alzheimer's disease (AD) pathology involves amyloid deposition, reactive gliosis, and localized tissue alterations that coexist within the same brain regions, creating heterogeneous microstructural environments within individual imaging voxels. Conventional diffusion MRI averages these environments into aggregate measures, potentially obscuring their distinct contributions. Frequency-dependent multidimensional MRI ({omega}MD-MRI) resolves distributions of water components with different diffusion length scales, anisotropies, and relaxation properties, providing sensitivity to microstructural restriction, heterogeneity, and shape-size correlations within a voxel. Whether these measurements reveal microstructural complexity associated with AD pathology remains unclear. Here, we performed {omega}MD-MRI on ex vivo brain specimens from approximately 8-month-old 5xFAD and wild-type mice and interpreted the imaging findings alongside complementary histology. {omega}MD-MRI revealed widespread but spatially nonuniform differences between 5xFAD and wild-type brains. Measurements sensitive to microstructural restriction, heterogeneity, and shape-size correlations consistently indicated greater microstructural heterogeneity in 5xFAD brains, with the most prominent differences in the hippocampal formation and major cerebral white matter tracts. Complementary qualitative histology demonstrated extensive amyloid deposition and glial activation in affected regions, while overall cytoarchitecture and myelin organization remained largely preserved. Thus, the {omega}MD-MRI abnormalities occurred in tissue characterized by multiple coexisting pathological and relatively preserved microstructural environments rather than widespread structural degeneration. These findings demonstrate that {omega}MD-MRI can reveal the spatial and microstructural heterogeneity associated with amyloid pathology and provide a more comprehensive characterization of AD-related tissue alterations.

neuroscience↗

bioRxiv2026

The first OpenBind release: An open experimental structure-affinity dataset and benchmark for structure-based AI

High-quality experimental datasets that link protein-ligand structures with binding affinity data are essential for developing and evaluating structure-based machine learning methods. To help address this need, we established OpenBind as an open-science initiative to generate large-scale experimental datasets for structure-based AI and molecular discovery. Here, we describe the first public OpenBind release, which, to the best of our knowledge, is the largest public single-target experimental structure-affinity dataset. The dataset focuses on enteroviral 2A protease, comprising 925 crystallographic binding events from 699 compounds and associated affinity measurements for 601 compounds. It combines structures from an initial fragment screen and follow-on molecules, together with affinity data, linking experimentally determined protein-ligand binding modes to biophysical measurements within a coherent antiviral discovery campaign. We used this dataset to evaluate protein-ligand structure prediction, binding-affinity prediction, and virtual screening using representative structure-based methods, including docking and cofolding. This exposed several challenges that are central to practical structure-based modelling: docking performance depends strongly on binding-pocket conformation, poses are difficult to rank, and structure-based affinity prediction remains challenging. Fine-tuning OpenFold3-p2 on the fragment-screen structures substantially improved pose prediction and virtual screening for related follow-on compounds, demonstrating how early-stage experimental structures can support target-specific model adaptation.

bioinformatics↗

bioRxiv2026

Cas12a cleavage and trimming kinetics reveal mismatches as a tool to steer editing

Gene knockouts by CRISPR-Cas nucleases rely on targeted DNA cleavage and error-prone DNA repair: end-joining pathways can introduce insertions and deletions that assist in disrupting the coding sequence. However, only a fraction of edits achieves this, and an unfavorable array of repair outcomes typically requires switching to another editing technology. Key factors that influence repair are the types and lengths of DNA ends following cleavage. Here, we investigated Cas12a's ability to produce different ends and if they can be used to redistribute editing outcomes. We determined the sites and rates of target cleavage by Cas12a in vitro by combining kinetic modeling with nucleotide-resolution assays. For the first time, we show that trimming - repeated cleavage of an already cut target - occurs about 4x faster than initial cleavage; it also presents alternative DNA end structures for cellular repair. We next introduced specific mismatches to the gRNA. Cas12a maintained fast target cleavage, but changed where the target was cleaved and how quickly it was trimmed, compared to matched gRNA. We exploited the differences in cleavage dynamics between matched and mismatched gRNAs to develop reprogrammed gRNAs, i.e. rpgRNAs. Intentionally-mismatched rpgRNAs retained the high editing efficiency observed with traditional gRNAs. However, they redirected editing between in-frame and out-of-frame outcomes to enhance gene knockout success across genes. Reprogrammed gRNAs offer an efficient way to steer editing toward such preferred outcomes, while retaining the simplicity of gene editing with CRISPR-Cas nucleases.

biochemistry↗

bioRxiv2026

The DYNAM-O Toolbox: Characterizing Individualized Neural Signatures in Sleep EEG

Conventional sleep electroencephalography (EEG) measures often rely on predefined bands, thresholds, and averages that incompletely capture transient oscillatory dynamics across an entire night. Here, we introduce the Dynamic Oscillation (DYNAM-O) Toolbox, an open-source, cross-platform (MATLAB, Python, and Rust) software package for data-driven characterization of individualized neural dynamics in sleep EEG. DYNAM-O identifies transient oscillations as time-frequency peaks on multitaper spectrograms using a novel multi-resolution procedure, computes intrinsic and sleep-state-dependent extrinsic features for each event, and represents the overnight distributions of tens of thousands of TF-peaks as feature histograms spanning oscillation frequency, slow oscillation power, and slow oscillation phase. This distributional representation preserves continuous brain-state variation that could be obscured by averaging within conventional sleep stages. The toolbox further provides Gaussian and spline basis-based dimensionality reduction, visualization, and whole-histogram statistical testing tools to support both exploratory and hypothesis-driven analyses. To demonstrate its use for group-level inference, we analyzed overnight C3-channel EEG from 133 adults (71 females, 72 males; ages 20-35 years) in the Cleveland Family Study. Whole-histogram and parameterized-mode analyses reproduced the established higher center frequency of fast-spindle activity in females and additionally revealed greater low-alpha transient oscillatory activity in females, a pattern outside the conventional sleep spindle range. By completing the analysis cycle from TF-peak extraction to statistical inference, DYNAM-O provides an accessible and interpretable framework for studying individualized sleep physiology and identifying subtle, reproducible electrophysiological patterns.

bioinformatics↗

bioRxiv2026

Structural mechanism defining product specificity in glycoside hydrolase family 66 cycloisomaltotetraose glucanotransferase

Cyclic oligosaccharides possess industrial advantages, including molecular encapsulation capability and high physicochemical stability, owing to the absence of a reducing end. Recently, a novel cyclic tetrasaccharide, cycloisomaltotetraose (CI4), consisting of four -1,6-linked glucose units, and the enzymes responsible for its synthesis, cycloisomaltotetraose glucanotransferases (CI4Tases), were discovered. Unlike known cycloisomaltooligosaccharide glucanotransferases (CITases) that yield a wide distribution of cyclic products with a degree of polymerization (DP) of 7 or higher, CI4Tases strictly produce CI4. To elucidate the molecular mechanism underlying this strict DP4 specificity, we determined the crystal structures of CI4Tase from Agreia sp. D1110, in its ligand-free form, as well as in complex with the linear hydrolysis product isomaltotetraose (IG4) and with CI4. Structural comparisons revealed that a loop (M247 to R251) blocks the region corresponding to the -5 subsite of typical CITases, narrowing the substrate-binding pocket. This "molecular ruler" mechanism ensures that only a glycan chain of exactly four glucose units is accommodated for cyclization. Among mutants of the residue positioned at the center of bound CI4, the formation of by-products other than CI4 was significantly suppressed in F245L, F245A, and F245W. While the cyclization activity of all F245 mutants decreased, the CI4 hydrolysis activity of these three mutants was also significantly reduced, resulting in an increased specificity for cyclic sugar production. These findings elucidate the strict size-control mechanism of CI4Tase and provide a structural foundation for engineering cycloisomaltooligosaccharide-producing enzymes with optimized transglycosylation efficiency and specificity for industrial applications.

biochemistry↗

bioRxiv2026

Structure-inspired design of Nsp8-based protein inhibitors to suppress SARS-CoV-2 replication

SARS-CoV-2 relies on a conserved RNA-dependent RNA polymerase (RdRp) complex composed of nsp12 and its cofactors nsp7 and nsp8 to replicate its RNA genome. Whereas most antiviral strategies target viral enzymes or surface proteins directly, an alternative approach is to disrupt the assembly or function of an essential viral molecular machine using a defective component derived from the pathogen itself. Here, guided by structural analyses of the nsp12-nsp7-nsp8 replication complex, we designed truncated nsp8 proteins that retain the ability to associate with nsp12 but are defective in engaging RNA. Using a purified nsp12-nsp7-nsp8 system capable of RNA primer extension, we show that selected truncated nsp8 variants inhibit polymerase activity when introduced into an otherwise functional complex. These results are consistent with a competitive mechanism in which the defective nsp8 variants associate with nsp12 and interfere with incorporation or function of wild-type nsp8, thereby compromising formation of a productive replication complex. To further explore this strategy, we used structure-guided in silico analysis of the nsp8-nsp12 interface to identify interaction hotspots and screened corresponding single-amino-acid substitutions. Several variants exhibited enhanced inhibitory activity in the reconstituted polymerase assay. Together, these findings establish a proof-of-concept strategy in which a structurally engineered, pathogen-derived protein can act as a dominant-negative inhibitor of an essential viral replication machinery. This approach provides a framework for developing protein- or peptide-based inhibitors that target conserved protein-protein interactions within viral replication complexes.

biochemistry↗

bioRxiv2026

Historical squid biomass increase is not explained by rising temperature but rather by loss of top predators.

Squid abundance has been reported to increase globally between 1970 and 2010. This increase has been hypothesized to result from two primary factors: the loss of top predators due to overfishing and rising ocean temperatures. The decline in apex predators may lead to the expansion of squid populations either through reduced predation pressure or diminished competition with juvenile predators. Concurrently, increased temperatures could enhance the somatic growth rates of squid, thereby accelerating their population growth. However, empirically disentangling the impacts of predator loss and temperature on squid biomass remains challenging, especially in a food-web context. In this study, we used a size- and trait-based model of upper trophic levels that resolves the ecosystem structure -- biomass and trophic interactions of fish and squid -- for varying depth, temperature, and secondary production, to investigate two hypotheses of the historical expansion of squid, i.e., the effects of predator depletion from fishing and rising temperatures on squid biomass. Our model reveals that intensified fishing of squid predators -- specifically large demersal fish in shelf systems and large pelagic fish in open oceans -- leads to a slight increase in squid biomass. Conversely, elevated temperatures are associated with a decline in squid biomass. This temperature-driven reduction in biomass is attributed to an increased metabolism of squids beyond the available food supply. If historic overfishing on large marine predators continues to be curtailed, we expect a corresponding reduction in global squid biomass and fisheries potential, which could be further exacerbated by rising temperatures.

ecology↗

bioRxiv2026

Antibody co-administration robustly improves proton therapy with radiosensitizing nanoparticles: a mathematical modeling study

Radiosensitizing nanoparticles represent a promising approach for enhancing the efficacy of proton radiotherapy; however, their performance is constrained by restricted penetration into tumor tissue, resulting in preferential perivascular accumulation. Here, we develop a spatially distributed mathematical model of a growing tumor undergoing proton therapy with intravenously administered radiosensitizing nanoparticles to investigate treatment optimization strategies. Using physiologically plausible parameter ranges informed by our own experimental measurements and published data, we demonstrate that co-administration of targeted nanoparticles with antibodies binding to the same tumor receptors can overcome transport-induced localization and promote a more uniform intratumoral redistribution of nanoparticles before irradiation. Population-level simulations across heterogeneous parameter sets suggest that moderate antibody doses consistently prolong tumor regrowth time, whereas higher antibody doses produce a pronounced and robust increase in tumor cure probability under a single high-dose irradiation regimen representative of preclinical settings. A key conceptual result of our analysis is the asymmetric risk associated with antibody co-administration. In contrast to antibody--drug conjugates, for which excessive dosing of unconjugated antibodies may severely compromise therapeutic efficacy, co-administration of antibodies with nanoparticle-based radiosensitizers constitutes a "safe-by-design" strategy with respect to tumor cell kill in the modeled single high-dose irradiation setting: although excessive antibody doses may yield suboptimal outcomes, they cannot reduce tumor cell kill below that achieved with targeted nanoparticles administered without antibodies. These findings identify antibody-mediated spatial redistribution of radiosensitizing nanoparticles as a favorable strategy that is expected to provide robust therapeutic benefit despite substantial variability in tumor characteristics.

cancer biology↗

bioRxiv2026

Trans-Allosteric Activation Releases Distinct Conformational Traps in Kinase Heterodimers

Protein kinases function as dynamic, mechanically coupled nodes, yet the conformational drivers of multimeric activation remain unclear. Here, we present AlloQuant, a computational suite that translates AlphaFold3 structural ensembles into quantitative metrics of kinase regulation, including internal network rigidity, metastable-state populations, and sub-angstrom conformational drivers. Applying AlloQuant to CDK1, we demonstrate that binding of the Cyclin B1 (CCNB1) cofactor mechanically decouples a hyper-rigid inactive kinase core, allowing activating phosphorylation (pT161) to subsequently re-impose localized tension on the catalytic machinery. Conversely, the C-terminal Src kinase (CSK) faces a distinct conformational trap. While nucleotide-free monomeric CSK spontaneously samples a pre-active geometry, ATP binding excludes the active C-In conformation in all but 1 of 225 models. We show that docking partner engagement overcomes this blockade. Autophosphorylation of SRC at the activation loop (Y419) redistributes SRC conformational states without altering bulk rigidity. This redistribution is structurally coupled to the conformational state of CSK via the regulatory spine, not the catalytic machinery. Rather than mechanically deforming CSK, SRC engagement acts by conformational selection, committing roughly a quarter of CSK molecules to a fully active state. Thus, trans-allosteric kinase activation operates by defining the accessible conformational landscape of the receiver kinase. That control is exerted through mechanical remodeling in cofactor-dependent complexes and through conformational selection in transient kinase-kinase heterodimers. These findings establish AlloQuant as a general framework for quantifying how a binding partner reshapes a kinase's conformational landscape, applicable across the kinome because it assigns landmarks by profile-HMM alignment.

biophysics↗

bioRxiv2026

Molecular and functional profiling distinguishes PACS1 syndrome variant from PACS1 loss-of-function in iNeurons

PACS1 syndrome is a rare neurodevelopmental disorder caused by a recurrent de novo missense variant (p.R203W) in the PACS1 protein. However, it remains unclear whether the p.R203W variant acts through a loss-of-function or alternative mechanism. Here, we used isogenic iPSC-derived neurons (iNs) to directly compare the effects of PACS1 p.R203W to complete loss of PACS1 function. Using a combination of proteomic, biochemical and electrophysiological approaches, we identified molecular and functional phenotypes associated with each genotype. While PACS1(+/R203W) and PACS1(-/-) iNs shared phenotypic abnormalities, the overall molecular and functional consequences of the p.R203W variant were distinct from those caused by PACS1 deficiency. Notably, PACS1(+/R203W) presented with unique proteomic and kinase signaling signatures and a shift in stimulus dependent excitability. These findings demonstrate that PACS1 syndrome is not caused by a simple loss of function and instead support a non-loss-of-function mechanism. Lastly, our interactome analysis suggests that the p.R203W variant retains aspects of canonical PACS1 function while acquiring novel molecular interactions that could contribute to PACS1 syndrome pathogenesis. Altogether, these findings provide a framework for future mechanistic studies and therapeutic development in PACS1 syndrome. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/747101v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@d1522corg.highwire.dtl.DTLVardef@69e4dforg.highwire.dtl.DTLVardef@30eebcorg.highwire.dtl.DTLVardef@899b9d_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Abundant Glomerular Neutrophil Extracellular Traps in C3 Glomerulopathy

Introduction: C3 glomerulopathy (C3G) is driven by fluid-phase alternative complement pathway dysregulation, with emerging evidence linking glomerular neutrophil infiltration to disease severity. Neutrophil extracellular traps (NETs) are implicated in other forms of glomerulonephritis. However, their participation in the pathogenesis of C3G remains undefined. Methods: Kidney biopsies from 33 patients with C3G (15 with dense deposit disease [DDD] and 18 with C3 glomerulonephritis [C3GN]) were compared with 15 anti-neutrophil cytoplasmic antibody associated vasculitis (AAV) biopsies as a neutrophil-rich disease control in this retrospective cross-sectional study. Glomerular neutrophils and NETs were identified using immunofluorescence, staining for myeloperoxidase, citrullinated histone H3, peptidyl arginine deiminase-4, and DNA. Supervised machine learning was used to quantify glomerular NET formation, and the data were correlated with kidney function at time of biopsy using linear regression. Results: Intraglomerular NETs were abundant and detected in the majority of glomeruli in C3G biopsies. Compared with AAV, C3G showed a significantly higher fraction of neutrophils forming NETs, despite similar neutrophil counts per glomerulus. NET abundance was similar in DDD and C3GN. In exploratory analyses, a greater proportion of glomeruli containing NETs was associated with lower kidney function (estimated glomerular filtration rate) at biopsy, and this association remained significant after adjustment for age, C3G subtype, and interstitial fibrosis. Conclusions: These observations demonstrate that intraglomerular NETs are a common and prominent observation in C3G and are associated with reduced kidney function at biopsy. These findings raise the possibility that NET deposition in glomeruli is a previously unrecognized driver of glomerular injury in C3G.

immunology↗

bioRxiv2026

Profiling and modulating astrocyte borders at injected biomaterials in mice

Astrocyte border formation is a conserved neuroprotective response to neural tissue disruption, yet astrocyte border states at implanted biomaterials remain less well characterized than injury responses. Here, we developed the Astrocyte Border Characterization (ABC) Tool, which leverages a shear-thinning, injectable biomaterial to locally deliver astrocyte-specific RiboTag AAVs and small molecule regulators in the mouse striatum, enabling molecular profiling and phenotypic modulation of astrocyte border (AB) cells. Spatially precise delivery of AAV using the ABC Tool yielded enhanced specificity and robust RiboTag expression in AB cells from 7-70 days post injection. Temporal transcriptomic profiling of AB cells revealed predominantly acute, transient changes in genes governing dedifferentiation, proliferation, metabolic reprogramming, and inflammation regulation. Persistent changes accounted for only 14% of regulated genes but involved critical gain of functions in immune regulation and host defense that mirrored astrocyte border responses at chronic CNS injuries. Local delivery of indiscriminate or astrocyte-selective ablation molecules delayed, rather than prevented, border formation, ultimately yielding thicker astrocytes borders with increased inflammation and fibrosis at the biomaterial-tissue interface. Conversely, local delivery of {beta}-hydroxybutyrate (BHB) from the ABC Tool altered key aspects of the transcriptional reprogramming to attenuate chronic astrocyte reactivity and prevent biomaterial contraction without exacerbating inflammation or fibrosis. Our findings establish the ABC Tool as a bioassay for studying and manipulating astrocyte borders at implanted biomaterials and identify focal metabolic regulation as a strategy to modulate AB cell phenotypes and enhance the CNS biocompatibility of biomaterials.

neuroscience↗

bioRxiv2026

Influence of trunk posture on spinal loading and paraspinal muscle forces in adolescent idiopathic scoliosis: a subject-specific musculoskeletal modelling study

Adolescent idiopathic scoliosis (AIS) alters spinal geometry and may influence the biomechanical response of the spine during functional postures. However, posture-dependent changes in spinal loading and paraspinal muscle forces in AIS remain poorly understood. This study investigated the effects of trunk posture on intervertebral loading and paraspinal muscle forces using a subject-specific musculoskeletal model of an adolescent with AIS. The spinal deformity was reconstructed from biplanar radiographs and incorporated into a full-body musculoskeletal model. Flexion, extension, lateral bending, and axial rotation were simulated at three incremental magnitudes, with motion distributed across the thoracolumbar spine. Intervertebral compressive and lateral forces around the curve apex and forces in the erector spinae (ES) and multifidus (MF) muscles were evaluated. Trunk flexion produced the greatest compressive loading, reaching 337 N at the curve apex and 372 N two levels below the apex at 30{degrees} flexion. Lateral bending produced pronounced direction-dependent loading: concave-side bending increased lateral forces, whereas convex-side bending increased compressive forces. Axial rotation produced similar but smaller direction-dependent changes. Paraspinal muscle forces were consistently asymmetric, with concave-side dominance of the ES and convex-side dominance of the MF. Flexion and convex-sided movements generally produced greater muscle imbalance, while increasing posture magnitude amplified spinal loading and muscle forces. These findings demonstrate that trunk posture, movement direction, and magnitude substantially influence the biomechanical environment of the scoliotic spine and should be considered when evaluating spinal mechanics in AIS.

bioengineering↗