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bioRxiv2026

AWET -- Arthropod Weight Estimation Tool

Arthropods drive essential ecosystem processes such as pollination, decomposition, and nutrient cycling and are widely used as indicators of ecosystem condition and function. Among various arthropod-derived metrics, body weight is a key variable in functional ecology and frequently assessed as dry body weight. However, drying arthropod specimens limits the samples future potential for research, as it prevents further processing such as trait measurements or species identification. Here, we present AWET (Arthropod Weight Estimation Tool), an open-source application for automated estimation of individual fresh body weight and extraction of morphometric measurements from standardized images of pre-sorted arthropod samples. AWET combines automated image analysis with taxon-specific allometric regression models to estimate fresh body weight while simultaneously quantifying body length, width, area, and specimen abundance. The software operates with standard imaging equipment, requires no machine-learning-based classification or segmentation, and allows users to define taxonomic groupings according to their objectives. By preserving specimens for downstream analyses while processing large numbers of individuals within milliseconds, AWET provides an efficient, non-destructive, and cost-effective workflow for high-throughput arthropod phenotyping. The software is a practical and expandable tool for biodiversity monitoring projects investigating changes in arthropod biomass, abundance and individual morphometric measures.

ecology↗

bioRxiv2026

Bioengineering of Pea (Pisum sativum) for the Expression of Myoglobin, a Heme-containing Animal Protein

Myoglobin, an oxygen-binding animal protein, was engineered in Pisum sativum (pea) to explore its potential as a food ingredient and balance the amino acid profile. In this study, minimal expression cassettes and binary vectors were used to express bovine myoglobin using particle gun and Agrobacterium-mediated transformation, respectively. Successful integration and expression of the myoglobin gene was achieved in P. sativum, with both methods yielding similar transformation efficiencies (~1%). Expression analysis of T2 seeds revealed that Agrobacterium-mediated transformation-derived transgenic lines that expressed myoglobin under the regulation of a Soybean 7S seed-specific promoter and Tobacco Etch Virus (TEV) translation enhancer and a chimeric Rb7MAR Terminator (Ps-BpRG13 events) consistently yielded the highest level of expression (0.32-1.57% of TSP), while transgenic lines with myoglobin expression under the regulation of a Soybean Phaseolin promoter and Rb7MAR Terminator (Ps-BpRG14 events) resulted in moderate levels of heterologous protein expression (0.13-0.83% TSP). Transgenic events with constitutive 2xCaMV35S promoter, TEV translation enhancer and Rb7MAR terminator (Ps-BpRG15 events) exhibited the lowest level of myoglobin expression (0.09-0.14% TSP). Co-bombardment of two minimal expression cassettes - one with myoglobin under the regulation of the Phaseolin promoter and Rb7MAR Terminator and the other with the nptII selectable marker under the regulation of a 2X constitutive CaMV35S promoter, TEV translational enhancer and TNOS Terminator, yielded lines that exhibited variable expression (0.03-0.77% TSP), with some events comparable in expression to Agrobacterium-derived Ps-pRG14 events. To the best of our knowledge, this is the first report of producing a heme-containing animal protein, myoglobin, in peas, with potential implications for sustainable production of food ingredients and nutritionally fortified and value-added plant products using molecular farming.

plant biology↗

bioRxiv2026

A Computational Re-evaluation of Spatial Trials for Zoonotic Tuberculosis Control: Model Misspecification, Diagnostic Miss-classification, and the Illusion of Wildlife Culling Efficacy

1. Wildlife reservoir management frequently relies on the Randomised Badger Culling Trial's (RBCT) trade-off hypothesis, which posits that reductions in cattle herd infections are offset by a perturbation effect driven by disrupted host dispersal. This paper evaluates the computational and epidemiological robustness of this historical trial, which serves as the foundational empirical experiment guiding zoonotic tuberculosis (Mycobacterium bovis) control policies. 2. Using generalized linear mixed models with a generalized Poisson error distribution to explicitly address historical data overdispersion, this study contrasts traditional parametric inference against exact cluster-constrained permutation tests across distinct operational definitions of disease incidence. 3. Non-parametric diagnostics reveal that previously reported treatment and perturbation effects render as statistical artifacts under exact non-parametric permutation. Inside culling zones, parametric significance fails to withstand exact permutation verification due to extreme data leverage in localized cluster blocks. 4. Crucially, when diagnostic misclassification biases are eliminated by analysing total reactor datasets, all apparent culling effects disappear, and information criteria overwhelmingly favour nested null architectures. Unconfirmed reactors likely represent true biological infections missed by low-sensitivity post-mortem macro-necropsy, proving that host removal tracks observation noise rather than genuine zoonotic transmission pathways. 5. Finally, empirical scaling conducted in this study identifies a novel mathematical saturation effect, demonstrating that this sub-linear scaling is an operational artifact of unmodelled herd-level disease recurrence over time. 6. Policy implications. Because current zoonotic tuberculosis intervention frameworks are built upon a structurally misspecified statistical model, they have driven large-scale veterinary policies resulting in substantial, unevidenced ecological and economic interventions while failing to provide genuine public health, animal health, or disease control benefits.

ecology↗

bioRxiv2026

VITAL-3D: Volumetric Single-Cell Quantification Reveals Microenvironment-Dependent Drug Responses in Breast Cancer

Preclinical drug evaluation relies heavily on two-dimensional (2D) monolayer assays, which fail to recapitulate the structural and functional complexity of the tumor microenvironment and may therefore misrepresent therapeutic efficacy. Here, we present VITAL (Volumetric Imaging-based Toxicity and Live Analysis), a high-throughput imaging platform that enables direct single-cell quantification of proliferation and cell death in both 2D and three-dimensional (3D) extracellular matrix (ECM) cultures using a 96-well format. By combining volumetric imaging with automated single-cell analysis, VITAL enables dynamic assessment of drug responses beyond conventional viability assays and EC measurements. Using breast cancer cell lines treated with anticancer agents, we systematically compared drug responses between 2D and 3D microenvironments. Although EC values were often comparable between culture formats, growth kinetics and concentrations required to induce complete growth arrest or net cell loss differed substantially in 3D cultures. In particular, drug concentrations required to induce net cell loss were consistently higher in 3D, revealing microenvironment-dependent survival responses that were not captured by EC alone. Furthermore, clinically expected subtype-specific responses, including tamoxifen sensitivity in ER-positive cells and olaparib sensitivity in BRCA1-mutant cells, were more accurately resolved under 3D culture conditions and extended treatment durations. Together, these findings demonstrate that growth-based, single-cell quantification provides a more comprehensive assessment of therapeutic efficacy than conventional endpoint measurements and establish VITAL as a scalable platform for physiologically relevant preclinical drug screening.

cancer biology↗

bioRxiv2026

EXTRARNAS: A Framework for Extracting RNA Structures with Multiple Tools

Accurate annotation of RNA base-pairing interactions is essential for structural analysis, benchmarking, and data-driven RNA structure prediction. Several tools can extract RNA interactions from three-dimensional coordinates, but their outputs are heterogeneous and may disagree, particularly for non-canonical base pairs. We present EXTRARNAS, a Java-based framework for automated, reproducible, and user-friendly large-scale extraction of RNA structural annotations with multiple tools. EXTRARNAS processes batches of RNA structures specified by PDB identifier and chain, or provided as local PDB files, executes annotation tools through a Docker-based environment, and parses tool-specific outputs using ANTLR4-based grammars. For each structure-tool pair, the framework generates standard BPSEQ files for canonical cis Watson-Crick interactions and introduces BPSEQE, a standardized text format for representing the extended secondary structure, preserving canonical, non-canonical, and multiple interactions per nucleotide. The current prototype supports RNAView, MC-Annotate, and RNAPolis Annotator. We demonstrate EXTRARNAS on eight RNA structures containing triple-helix motifs, comparing extracted canonical pairs against curated BPSEQ references and evaluating the recovery of manually validated Hoogsteen interactions. The results show consistent differences among tools, especially for non-canonical interactions, highlighting the need for standardized representations such as BPSEQE to support reproducible comparison and future consensus-based annotation.

bioinformatics↗

bioRxiv2026

Developments in the European parasitoid community of Dryocosmus kuriphilus

The invasive gallwasp Dryocosmus kuriphilus was first detected in Italy in 2002, although likely to have initially arrived in the late 90s. Its ability to utilise sweet chestnut species non-native to its original Chinese range has allowed it to spread rapidly, and throughout Europe via European sweet chestnut Castanea sativa. Given the severity of its impact on C. sativa crop production, particularly in Mediterranean countries, previous studies have aimed to assess damage levels caused by D. kuriphilus, the efficacy of and potential non-target effects of the introduced biocontrol agent Torymus sinensis, and the possibility of regulation by native parasitoids. As yet a broad overview and analytical synthesis of these native parasitoid communities are absent. This review focuses on important aspects of the D. kuriphilus invasion. In particular, the invasion history and currently known distribution of D. kuriphilus, and several aspects of its associated parasitoid community. For native species to plausibly suppress D. kuriphilus, we might expect rates of parasitoid attack to increase with establishment time as native populations adapt to exploit the new resource, and this is a key focus of the review. We answer the following questions: 1) What is the distribution of D. kuriphilus in Europe, and has D. kuriphilus fully utilised the available niche space within its 20+ years in Europe? 2) Which species of native parasitoids attack D. kuriphilus in Europe and what are their ecological characteristics? 3) How consistent is the parasitoid community of D. kuriphilus across its range, and are there signs of convergence over time? 4) What effect does establishment time have on the species richness and abundance of parasitoid communities? We report the following: 1) D. kuriphilus has expanded its range throughout Europe and is present in nearly every major region where sweet chestnut is present. Native and non-native naturalised chestnut forests may be less susceptible to invasion than areas of industry due to differing socioeconomic and ecological factors, though areas with large chestnut industries also tend to be in the most heavily forested areas in the non-native range of sweet chestnut. D. kuriphilus has reportedly been eradicated from some countries, and effectively eradicated in a number of countries implementing biocontrol with T. sinensis, although successive invasions from neighbouring regions are still possible, and eradication may be transient. 2) 72 parasitoid species are identified attacking D. kuriphilus in Europe (far more species than any other gallwasp in the Western Palearctic). Its members are predominantly oak gallwasp parasitoids (82% of species), followed by gall-specialists of different host plants, leaf miner parasitoids and a minority of others with differing host life stages and ecologies. Parasitoids attacking D. kuriphilus are dominated by idiobiont ectoparasitoids of the superfamily Chalcidoidea (>96%). 3) The parasitoid community is highly variable, both temporally and spatially, although the vast proportion (>95%) of parasitoids at any one time are composed of locally common generalist oak gall parasitoids. The most common members include Bootanomyia dorsalis, Eupelmus urozonus, Eurytoma brunniventris, Mesopolobus sericeus and Torymus flavipes. 4) The length of establishment time has minimal effect on the species richness, abundance, and composition of the community, suggesting that regulation by natives, if it occurs, may take longer than the 20+ years that D. kuriphilus has persisted. While little evidence of increasing parasitoid attack of D. kuriphilus is apparent, we exercise caution by stating that the heterogeneity in available data are large, and that common biocontrol interventions using T. sinensis interrupt the natural process of community development dramatically. D. kuriphilus has been present in Europe for nearly three decades and few localities have repeated years of data collection. Even fewer studies have communities with establishment times exceeding ten years. Proper biocontrol by natives may not occur within short timeframes, although studies of other gallwasp invaders find similar results over periods exceeding 40 years. Given that many countries have chosen to implement T. sinensis for biocontrol, the focus may be better spent monitoring native gall communities for potential non-target effects.

ecology↗

bioRxiv2026

Euchromatin Peripheral Organization Follows Anterograde Signalling Under Anaesthetic Stress

Anterograde and retrograde signalling establish bidirectional communication between the nucleus and chloroplasts. Retrograde signals from chloroplasts regulate nuclear gene expression while anterograde signals from the nucleus coordinate chloroplast development and maintain cellular homeostasis. How this bidirectional signalling framework extends beyond locus-specific regulation to shape the global spatial organization of nuclear chromatin across tissues remains unclear. Although anaesthesia can alter chromatin organisation, the role of chloroplast dysfunction in these changes remains unclear. Here, we investigate how chloroplast dysfunction and anaesthesia influence euchromatin and heterochromatin organisation in Solanum lycopersicum seedlings across tissues with contrasting photosynthetic competence. Using confocal and super-resolution radial fluctuation (SRRF) imaging with quantitative multiparameter analysis, we identify distinct, tissue-specific chromatin responses to chloroplast disruption and anaesthesia. Notably, anaesthesia induces distinct spatial chromatin changes across tissues that are independent of chloroplast dysfunction, suggesting a direct nuclear response to anaesthesia rather than a chloroplast-mediated retrograde effect. These findings highlight chromatin topology as a potential quantitative biomarker of cellular disruption and provide a framework for investigating anterograde chloroplast-nucleus coordination and stress-responsive nuclear organisation in plants.

plant biology↗

bioRxiv2026

Scorpion toxin peptide BMK86-P1 achieves mutation-reversible inhibition of KCNA2 at the cost of reduced efficacy in heteromers and murine neurons

The discovery of distinctive function-phenotype relationships in monogenetic channelopathies has turned out to be critical for the development of precision medicine approaches. However, the best prediction of clinical phenotypes depends on neuronal function, where existing models lack tools to isolate currents of individual voltage-gated potassium channel subunits and differentiate variant effects in complex systems. Ideally, one should be able to overexpress subunit variants with an additional mutation that confers resistance against the tool to isolate the variant effect. Therefore, we solid-phase synthesized the KV1.2 specific scorpion toxin peptide BMK86-P1 and oxidized it with modest efficacy. In mammalian cells this BMK86-P1 selectively inhibited KV1.2 homomers, but not heteromers with KV1.1. Critically, the KCNA2 p.Val381Tyr mutation, which reverses BMK86-P1's selective inhibition of KV1.2, also altered the activation of KV1.2 homomers to resemble those of KV1.1. In addition, BMK86-P1 in murine neurons did not alter passive membrane properties, single action potential properties, or action potential firing. Surprisingly, it induced only minimal changes in spontaneous excitatory postsynaptic currents. In summary, this KV1.2 subunit selective toxin peptide asserts its effects primarily on homomeric channels, while only weakly inhibiting KV1.2-heteromeric channels and consequently preventing any meaningful impact on neuronal function. This highlights the limits of peptide synthesis together with the need for testing specific compounds on complex systems.

neuroscience↗

bioRxiv2026

Test-Retest Reliability of Motor Evoked Potentials Across Eight Bilateral Lower-Limb Muscles

Objectives: Transcranial magnetic stimulation (TMS) is widely used to probe corticospinal excitability by eliciting motor evoked potential (MEP)s in targeted muscles, with MEP characteristics such as magnitude and latency reflecting the physiological state of the pathways being stimulated. Although numerous studies have examined MEP reliability in upper extremity muscles, less is known about the reliability of this measurement across the lower extremity. We hypothesized that inter-session, test-retest reliability of MEPs recorded simultaneously from multiple lower-limb muscles, from a single TMS location, would differ by muscle, stimulation intensity, and quantification method. Materials and Methods: Ten healthy participants (5 males, 5 females) completed three TMS sessions separated by atleast one week. At each session, the stimulation hotspot was identified using a five-location virtual grid anchored at the vertex, with electromyography (EMG) recorded from all eight muscles of interest at each grid location; the grid location producing the largest and most consistent MEPs in the tibialis anterior (TA), the primary target muscle, was selected as the stimulation site and held constant across all three sessions. MEPs were then recorded bilaterally from the TA, soleus, rectus femoris, and biceps femoris muscles at two stimulation intensities (110% and 120% resting motor threshold (RMT)). MEP size was quantified using mean rectified magnitude and peak-to-peak amplitude, and inter-session reliability was assessed using intraclass correlation coefficients (ICC). Bland-Altman analysis was used to characterize the range of measurement variability across all eight muscles. Results: MEP size differed across sessions, and reliability varied by muscle, intensity, and quantification method. The highest reliability was observed in the right TA, the muscle used to establish the stimulation hotspot, using mean rectified magnitude at 120% RMT. Reliability was comparatively lower in the seven non-target muscles recorded from the same fixed stimulation site, indicating that MEP consistency was not uniform across the lower-limb musculature. Conclusions: MEP reliability in the lower extremity depends heavily on the muscle, stimulation intensity, and quantification method used, and is highest in the muscle for which the stimulation site was optimized. These findings support the interpretation that coil positioning targeted to a specific muscle yields more consistent responses in that muscle than in others recorded from the same fixed site, and underscore the importance of careful muscle selection and hotspot optimization when designing TMS protocols for longitudinal or clinical lower-limb research.

neuroscience↗

bioRxiv2026

Single-Cell Profiling of Dynamic Epicardial Cell States During Myocardial Infarction

Background: The epicardium is reactivated after myocardial infarction (MI); however, the gene expression profiles of post-MI adult epicardial subpopulations remain incompletely defined. Methods: Single-cell RNA sequencing was performed on lineage-traced Wt1+ epicardial cells from Wt1CreERT2/+; R26tdT/+; PdgfranGFP/+ adult mice after sham surgery or at 7 and 14 days after permanent artery ligation to induce MI. Immunostaining was performed on Wt1-lineage-traced cardiac tissue to validate spatial expression after ischemic injury. Results: Unbiased clustering identified nine transcriptionally distinct epicardial populations, encompassing mesothelial, fibroblast/mesenchymal, transitional, and proliferative phenotypes. Fibroblast-like epicardial cells (Wt1+/Pdgfra+) showed time-dependent expression profiles associated with upregulation of epithelial-to-mesenchymal transition (EMT) and extracellular matrix (ECM) gene programs. At 7 days post-MI, there was notable enrichment of genes related to chemokines and Wnt components. By 14 days post-MI, the expression profile shifted toward immune regulation. In contrast, a Wt1high/Msln+ population showed minimal upregulation of EMT gene programs but enhanced paracrine signaling related to wound healing and semaphorins, suggesting reactivation of reparative and angiogenic functions akin to those of the epicardium during embryonic development. Immunostaining and in situ hybridization fluorescence analyses validated laminar epicardial cell placement after MI, comprising a surface Msln+ sheet, an overlapping Wt1-lineage band, and a subadjacent PDGFR+ and Periostin+ compartment that expands 7-14 days after MI and regresses by day 28 post-ischemia. Conclusions: Our data define epicardial gene programs in which a signaling epithelial cell surface overlays an effector mesenchymal cell stroma to coordinate angiogenesis, leukocyte recruitment, and ECM remodeling. This study presents the first integrated single-cell atlas of epicardial-derived cells across multiple post-ischemic timepoints, offering new insights into their reparative potential and dynamic signaling diversity in the injured adult heart.

molecular biology↗

bioRxiv2026

Taxonomic classification cost tracks neither sequencing depth nor community richness at single-sample scale: a measured resource protocol for 16S rRNA amplicon pipelines

Marker-gene amplicon workflows are routinely run on shared compute, yet the cores, memory and wall time they are given are chosen by convention and not by measurement. We present a protocol for measuring them, applied to the two dominant stages of a QIIME 2 16S rRNA pipeline, DADA2 denoising and Naive Bayes taxonomic classification, across nine upper-respiratory samples from a paediatric otitis media cohort. The two stages do not consume the same input: denoising reads every sequence, classification only those surviving it. Subsampling one library across a 27-fold range of sequencing depth, denoising wall time rose 14.3-fold while classification changed by 1% and its peak memory not at all (3.11 GiB). Amplicon sequence variant (ASV) richness rose 2.8-fold over that range, so this is not richness saturating: the stage is dominated by a fixed per-invocation cost. Across a body-site gradient of 5 to 70 ASVs, denoising followed read count (exponent 0.75) while classification followed neither: a 5-ASV effusion and a 70-ASV adenoid community cost 40.81 s and 40.79 s. One ASV took 36.20 s and 218 took 37.27 s, 97% fixed cost. Thread-level parallelism offered little benefit. Denoising peaked at 1.18x near 8 threads and then declined; classification was slower at every setting above one job, consuming 10.5 times the CPU at 40. Representative sequences and their taxonomic assignments were identical at 1, 4 and 40 threads, so a reduced allocation changes what the analysis costs, not what it reports. Extending the query set to 10,000 sequences located two distinct boundaries: eight jobs first beat one at roughly 5,000 queries, and fitted fixed and per-query costs become equal at 15,248. Both lie roughly two orders of magnitude above the richest single sample measured. Practically: size denoising by read count, calibrate classification once against the reference in use, request one job for classification below a few thousand sequences, and take throughput from sample-level parallelism. Protocol, data and analysis code are released with the pipeline.

bioinformatics↗

bioRxiv2026

Geometric causes of species rarity

Understanding the limits of species distributions is a central objective of biogeography and macroecology and has become increasingly important as climate change drives rapid shifts in geographic ranges. Species range sizes follow a highly skewed frequency distribution, with most species occupying ranges orders of magnitude smaller than those of the most widespread species. Range sizes also exhibit pronounced geographic patterns, with small-ranged species concentrated near continental margins and other geographic boundaries. No universally accepted explanation has been proposed for these patterns. Here we present a simple geometric model showing that species range size patterns emerge from the random placement of dispersal barriers within continental domains. The model predicts both the observed frequency distribution and the spatial distribution of range sizes across amphibians, birds, and mammals. It therefore provides a first-order explanation for global patterns of species rarity and can be refined by incorporating elevational barriers and spatial variation in species richness. Our findings suggest that species range size is constrained by the geometry of dispersal barriers and the geographic domain, with proximity to domain boundaries acting as a primary determinant of species rarity. These results have important implications for understanding species' evolutionary potential and vulnerability to extinction.

ecology↗

bioRxiv2026

Dissecting the TMEM132A-EGFR Dependency to Unlock Translational Therapeutic Opportunities for Pan-Solid Tumor

Solid tumors remain refractory to conventional treatments, yet cell surface proteins, by virtue of their extracellular accessibility and critical roles in tumor signaling, represent an attractive class of targets for precision-targeted therapy. Here, we report that TMEM132A is an essential and previously unrecognized pan-cancer target. TMEM132A interacts directly with EGFR and stabilizes its expression, thereby tethering EGFR at the plasma membrane and sustaining constitutive activation of lipid synthesis. Mechanistically, the TMEM132A-EGFR axis promotes lipogenesis by facilitating SREBP nuclear translocation, which in turn upregulates ACLY and ACSS2 expression to drive acetyl-CoA production and downstream lipid biosynthesis, ultimately disrupting lipid droplet homeostasis. To therapeutically target this axis, we developed a nanobody, LFNanoT132A#3, which effectively blocks the TMEM132A-EGFR interaction, abrogates downstream signaling activation, and potently inhibits proliferation across multiple solid tumor types. Notably, LFNanoT132A also exerts robust antitumor activity against H1975 xenografts, a model resistant to first- and second- generation EGFR inhibitors, underscoring its potential to overcome conventional drug resistance. Our findings establish TMEM132A#3 as a critical node in membrane-tethered oncogenic signaling and metabolic rewiring, and position LFNanoT132A#3 as a promising therapeutic candidate for precision cancer therapy.

cancer biology↗

bioRxiv2026

Microsecond molecular dynamics of SOD1 variants suggest a structural basis for divergent ALS clinical outcomes

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterised by progressive motor neuron degeneration. Mutations in the SOD1 gene represent the second most common genetic cause of ALS (ALS), and distinct SOD1 missense variants present with markedly different clinical profiles. A4V leads to an aggressive form of the disease (median survival [~]1y), H46R confers a mild, slowly progressive course and I113T exhibits an intermediate phenotype. The molecular basis by which these mutations produce divergent clinical outcomes remains poorly understood. We performed extensive classical molecular dynamics simulations of wild-type SOD1 and the three ALS-associated variants in the apo monomeric state to attempt to investigate the mechanisms behind such phenotypic differences. Structural stability, global compactness, and conformational flexibility, as well as analysis of collective motions between residues and estimation of free energy, were assessed. The H46R, A4V, and I113T variants exhibited distinct dynamic behaviours, highlighting differences in structural stability, local flexibility, and intramolecular interactions. These findings suggest that specific structural regions may contribute differently to protein dysfunction and could represent key elements for understanding the relationship between molecular dynamic properties and the differing clinical severity associated with these variants. Most strikingly, H46R exhibited exceptional structural stability across every analytical level, the lowest global deviation, most attenuated local flexibility, strongest internal dynamic coordination, and the deepest, most confined free energy basins of any system examined. This convergent multi-layered evidence of structural restraint provides a compelling mechanistic basis for the mild and slowly progressive clinical course of H46R ALS, suggesting that enhanced conformational rigidity, rather than bulk destabilisation, is the defining biophysical feature of this variant, and that its pathogenic mechanism operates through a route fundamentally decoupled from the aggregation-driven toxicity that characterises the more aggressive SOD1-ALS mutations.

genomics↗

bioRxiv2026

High-Resolution Subtyping of Pediatric Low-Grade Glioma Using an Integrated Meta-Clustering Framework

Pediatric low-grade glioma (pLGG) is the most common type of brain tumor in children, accounting for approximately 30% of all central nervous system tumors in children. pLGG has multiple molecular subtypes that differ in disease progression, recurrence patterns, and treatment responses. Conventional wet lab approaches including molecular profiling and histopathological studies for pLGG characterization are time consuming, costly, and laborious. Recently, methods based on artificial intelligence (AI) or machine learning (ML) have been widely used for pLGG molecular categorization, but most of them can only identify two or three pLGG subtypes. To more comprehensively characterize the molecular subtypes of pLGG and their potential biological and therapeutic significance, we develop an integrated meta-clustering approach, namely Meta-pLGG, that can explore high resolution molecular subtypes and their transcriptional heterogeneity for pLGG. Specifically, we first performed multiple rounds of random projection (RP) to generate dimension-reduced feature vectors from pLGG transcriptomics data, each of which was subsequently clustered by different clustering algorithms including hierarchical clustering, K-means, Self-Organizing Maps (SOM), Non-negative Matrix Factorization (NMF), Gaussian Mixture Model (GMM), and Spectral Clustering, as base clustering methods. Then, to yield robust clustering performance, we integrated the clustering results of these RP based individual clustering algorithms by adopting a weighted meta-clustering (wMetaC) approach. Results based on 532 pLGG patients suggested that our proposed approach demonstrated superior stability and discriminative powers for higher resolution pLGG subtyping compared to conventional approaches. Based on consensus matrix analysis, we identified two major pLGG mega-subtypes, with one further subdivided into three subgroups and the other into two. Then, we performed cluster specific differential gene expression analysis, molecular pathway analysis, and gene-drug-disease association analysis. The results showed that the identified five subgroups exhibited significant subtype-specific transcriptomic heterogeneity. In summary, our meta-clustering approach demonstrated much higher performance and robustness in identifying higher resolution molecular subtypes of pLGG, revealing the molecular heterogeneity within pLGG and potentially providing new insights for more precise molecular subtyping and precision therapy.

bioinformatics↗

bioRxiv2026

Layer 5 anterior cingulate cortical neurons engage dorsolateral periaqueductal gray excitatory neurons to facilitate the affective component of pain

Pain is a conscious perceptual experience characterized by its aversive quality and consequent motivation to quench pain perception. The anterior cingulate cortex (ACC) critically contributes to the emotional dimension of pain. In both humans and rodents, ACC neural activity increases during acute and chronic pain, whereas ACC lesioning or excitability reduction decreases emotional reactivity during pain. However, the ACC is connected to many brain regions and is engaged during experiences beyond pain. Thus, it remains unclear through which circuit mechanisms the ACC shapes pain experience, and how specific those circuits are to nociception. Here, we show that excitatory input from the ACC to the dorsolateral periaqueductal gray (dlPAG) facilitates the affective-motivational dimension of pain. We first examined ACC[->]dlPAG connectivity using histology, optogenetics, and electrophysiology. We found that the axons of layer 5 ACC neurons terminate in the dlPAG and monosynaptically excite Slc17a6+ (VGLUT2-expressing) dlPAG neurons. Second, we genetically targeted ACC[->]dlPAG neurons with viral vectors to express the inhibitory DREADD hM4Di and then exposed the animals to an array of pain tests. We found that, across acute and chronic pain states, inhibition of the ACC[->]dlPAG pathway reduced affective-motivational but not reflexive pain behaviors. Third, we used fiber photometry to record neural calcium activity in the ACC in behaving mice and found that ACC[->]dlPAG neurons are engaged during a broad array of aversive experiences, rather than exclusively during pain, and exhibit task-specific activity patterns. Collectively, these results uncover the direct contribution of ACC[->]dlPAG neural activity to pain unpleasantness and the necessity of this pathway for generating aversive behavioral responses in general, rather than specifically for encoding the unpleasant quality of noxious stimuli.

neuroscience↗

bioRxiv2026

In-cell structural analysis reveals a distinctive chloroplast ribosome in Chlamydomonas reinhardtii

Chloroplast ribosomes synthesize plastid-encoded components of photosynthetic machinery, yet their structure and organization remain poorly understood. We combined cryo-focused ion beam milling, cryo-electron tomography and subtomogram averaging to determine native chloroplast ribosomes in Chlamydomonas reinhardtii. The 4.4-4.9 [A] structure revealed a large arch-like extension on the small subunit (SSU). Comparisons with bacterial and plant chloroplast ribosomes, supported by proteomics, AlphaFold3 predictions and a recent atomic model, indicate that the arch is formed by insertions and extensions in SSU proteins. Classification resolved active, thylakoid-associated ribosomes with density adjacent to the nascent peptide exit and an arch-moved state enriched among thylakoid-associated particles, with coordinated displacement of the arch and beak. Phylogenetic analysis revealed an evolutionary mosaic: the uS3c insertion is broadly distributed across Chlorophyceae, whereas the uS2c insertion, uS5c and PSRP7 are concentrated in Chlamydomonadales, with PSRP7 also in Sphaeropleales. Nuclear-encoded components were recruited stepwise onto a plastid-encoded scaffold, with all four under comparable purifying selection. These findings link a lineage-specific SSU extension to ribosome dynamics, thylakoid association and evolution, highlighting the value of in-cell structural analysis.

plant biology↗

bioRxiv2026

Embedding wear assessment in musculoskeletal simulation: A proof-of-concept application to total hip arthroplasty

Predicting wear in artificial joints requires integrating joint dynamics, contact mechanics and progressive surface evolution, yet these processes are often treated separately. In total hip arthroplasty (THA), finite-element approaches remain the reference standard, but they are computationally demanding and usually rely on boundary conditions from independent musculoskeletal (MSK) models, hindering consistent coupling and feedback between wear progression and movement dynamics. As a single-subject proof of concept, we present a computational framework that embeds wear estimation within forward MSK simulations through OpenSim-MATLAB integration. Contact variables are computed using an elastic-foundation formulation, and wear is updated through the Archard law, enabling cyclic prediction of contact mechanics and surface evolution within a single workflow at practical computational cost. The framework was evaluated in one subject with right THA during five activities of daily living and numerically benchmarked against finite-element simulations. A long-term walking analysis of 4 million cycles was also performed to assess geometry updating. Across tasks, peak contact pressures remained within 7% of finite-element predictions. Linear wear depth and volumetric loss showed maximum deviations of 16% and 13%, respectively. Accounting for progressive geometry changes yielded a maximum wear depth about 31% lower than linear extrapolation. These preliminary results support the framework's computational feasibility and numerical consistency for the tested case; nevertheless, multi-subject evaluation is required before broader predictive or clinical use.

bioengineering↗