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Topological Closure Drives Structural Stabilization and Fast Cooperative Dynamics in Crowded Circular Polysomes

In linear polysomes, excluded-volume interactions among ribosomes can induce dimensional reduction of mRNA. Yet linear architectures allow steric stress to relax at open ends-- limiting how strongly crowding can remodel the mRNA's structure and dynamics. Using coarse-grained molecular-dynamics simulations, we compare circular and linear polysomes over a range of ribosome densities. Circular closure selects a predominantly quasi-planar global conformational ensemble, as indicated by a shape dimensionality dshape {approx} 2 over a range of ribosome densities. Crucially, circular topology and ribosome crowding act cooperatively to suppress structural fluctuations. While closure alone or linear crowding reduces relative global size fluctuations ({Delta}Rg/Rg) only to {approx} 0.16, their combined effect drives this fluctuation down to {approx} 0.07. Within this stabilized architecture, increasing ribosome density drives a distinct in-plane reorganization: the ring becomes more isotropic, global size fluctuations are strongly suppressed, and the scaling exponent increases toward {nu} [~=] 0.74 - 0.77, consistent with two-dimensional self-avoiding walk-like value over the accessible finite-size window, 1000 [≤] N [≤] 4969. Closure shortens the radius-of-gyration decorrelation time of circular polysomes by 40-fold relative to matched linear systems, reflecting the topological elimination of free ends. Within this closureselected ensemble, ribosome crowding further reduces the decorrelation time by up to 20% at the highest density. A fluctuation-informed crossover model links the density dependence of the global scaling exponent to inter-ribosomal subchain statistics. These results distinguish the geometric role of circular closure from the density-dependent steric response that it enables, revealing a confined yet dynamically responsive conformational regime for circular polysomes.

biophysics

Time-averaged and Time-varying Structure of the Gastric Network Revealed Through fMRI-Electrogastrogram Synchronization

The gastric network, comprised of brain regions whose activity synchronizes with the stomach's slow-wave rhythm, offers a unique window into the brain-body interaction involved in interoceptive processing. While previous work has established the existence of this network, its intrinsic organization and temporal unfolding remain poorly understood. Here, we reanalyzed resting-state fMRI-electrogastrogram data from 43 healthy adults of both sexes to characterize the time-averaged architecture and time-varying reconfiguration of the gastric network. We identified regions exhibiting phase-locked synchronization with the stomach slow electrical rhythm (0.05 Hz) and characterized cortical parcels comprising this network. Time-averaged graph-theoretical analysis revealed a fixed unimodal organization of functional communities, with primary visual, default mode network (DMN) and dorsal attention regions emerging as the principal time-averaged hubs. Next, we applied edge-centric functional connectivity (eFC) to capture the network state during transient high-amplitude "bursts". Time-varying community detection revealed communities whose compositions formed integrative combinations of DMN, visual, attentional and control elements. Edge-derived hubs shifted away from primary visual dominancy in the time-averaged analysis, and were instead directed by DMN regions, suggesting that moments of heightened connectivity in the network are coordinated by multisensory integration rather than passive sensory processing. These findings demonstrate that the gastric network is not merely a time-averaged, sensory-bound system, but rather a flexible and dynamically reconfiguring interoceptive network whose organization is selectively coordinated by transient cofluctuation events. This work provides a comprehensive network analysis of gastric-brain coupling and reveals a temporally structured mode of interoceptive integration that may support adaptive physiological and cognitive regulation.

neuroscience

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

Magnesium induces iron starvation and metabolic rewiring to support the viability of cell envelope mutants and antibiotic-stressed cells

Magnesium supplementation permits deletion of otherwise essential genes involved in cell envelope biogenesis in the Gram-positive model bacterium Bacillus subtilis. Yet, the specific underlying mechanism has remained elusive. To address this key knowledge gap, we made use of a mutant lacking ezrA and gpsB. Deletion of both of these genes involved in cell wall synthesis leads to severe growth inhibition which is ameliorated by magnesium addition. Our results indicate that, in the absence of magnesium, this mutant contains elevated levels of labile iron, is impaired in activating the oxidative stress response, and displays extreme sensitivity to iron and manganese intoxication. Intriguingly, we find that an ezrA single deletion, but not gpsB, exhibits heightened susceptibility to excess iron and manganese. This observation allowed us to investigate the source of toxicity and how EzrA may support metal homeostasis. Our data suggests that the major contributor of ROS is the electron transport system involved in cellular respiration. Both genetic and chemical means to reprogram the cells in favor of fermentation alleviate the metal toxicity in cells lacking ezrA. Collectively, our data shows that magnesium limits iron availability and redirects metabolism towards pathways that are preferred during iron scarcity. Consequently, these mechanisms result in reduced ROS production and oxidative stress mitigation. This explains why magnesium supplementation may render essential genes dispensable. In support of this model, we find that addition of magnesium helps cells to circumvent lysis typically caused by the treatment of an antibiotic that disrupts cell wall synthesis. Taken together, our results suggest that unmitigated oxidative stress fueled by labile iron is likely responsible for the detrimental effects of specific gene disruptions and certain antibiotic treatments. By reducing the pool of free iron and reprogramming cellular metabolism, magnesium mitigates oxidative damage and protects cells from ROS-mediated death.

microbiology

Genetic Disruption at the CIP2A Locus Modulates T Cell Responses and Attenuates Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) driven by pathogenic T cell-mediated inflammation. Fingolimod (FTY720), an approved therapy for MS, is an established activator of protein phosphatase 2A (PP2A). However the contribution of PP2A in autoimmune neuroinflammation remains incompletely understood. Here, we addressed this question using experimental autoimmune encephalomyelitis (EAE), a murine model of MS, in mice carrying a genetic disruption of the locus encoding cancerous inhibitor of protein phosphatase 2A (CIP2A), an endogenous inhibitor of PP2A. Mice with disruption of the CIP2A locus, the knock out (KO) mice, exhibited attenuated EAE severity compared with wild-type (WT) controls. Histological and flow-cytometric analyses revealed markedly reduced infiltration of mononuclear cells, including CD4 and CD4CXCR6 encephalitogenic T cells, in the CNS of diseased KO mice. Reduced numbers of these T cell populations were also observed in peripheral lymphoid organs of the Cip2a-deficient mice during EAE, while T cell abundance was comparable under steady-state conditions, suggesting impaired activation-induced expansion rather than altered homeostasis or migration. Single-cell RNA sequencing of CNS and lymph node immune cells revealed changes in cell-type abundance and gene expression. Notably, Il17a expression was reduced in CNS CD8+ T cells and showed a similar trend in {gamma}{delta} T cells. Together, our findings reveal that genetic disruption at the CIP2A locus attenuates EAE, possibly by limiting the expansion and accumulation of encephalitogenic T cell populations in CNS. These results identify the CIP2A locus as a previously unrecognized regulator of T cell-driven autoimmune neuroinflammation and provide new insights into mechanisms that restrain pathogenic T cell responses during EAE.

immunology

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

Evolution and Human Neural Individuality

Individuality is a defining feature of human biology. The functional network architecture of the human brain harbors person-specific qualities and forms individualized connectivity profiles that function as a neural fingerprint, both stable and unique across time. Here, using fMRI data from 431 Human Connectome Project participants, we examined whether neural individuality is more strongly exhibited in brain regions bearing signatures of recent human evolution. We calculated region-wise fingerprinting accuracy and associated it with four properties of evolutionary cortical organization: cortical expansion, myelin content estimate (T1w/T2w), human-specific gene-expression profiles, and functional homology to other primates. Across all four measures, neural individuality was strongest in cortical areas showing greater evolutionary novelty in humans, particularly frontoparietal control and default mode networks, and weaker in more conserved primary regions. Our findings connect evolutionary variation across species with stable functional variation among individuals.

neuroscience

A family-wide atlas of human connexin docking compatibility

Gap junction (GJ) channels mediate direct intercellular communication by allowing the exchange of ions, metabolites, and signaling molecules between neighboring cells. Humans express 21 connexin (Cx) isoforms that can assemble into homotypic or heterotypic channels, creating a large potential interaction landscape that shapes tissue-specific communication networks. However, the rules governing which connexin isoforms can compatibly dock remain incompletely defined. Extracellular loop 2 (EL2) sequence features have been implicated in docking specificity and used to classify connexins into two canonical compatibility groups, K-N and H, but these assignments remain largely predictive. Most potential heterotypic connexin pairings have never been experimentally tested. This incomplete interaction map limits our ability to predict which connexin combinations can assemble, how isoform co-expression shapes intercellular communication, and how these relationships are altered or exploited in disease and engineered systems. Here, we used the FETCH (Flow Enabled Tracking of Connexosomes in HEK Cells) assay to evaluate docking compatibility across the complete human connexin family. To support family-wide compatibility mapping, we used literature-supported heterotypic interactions to define a data-driven FETCH score threshold for high-confidence interaction compatibility. Homotypic FETCH measurements varied substantially across the 21 connexin isoforms, with 15 producing mean scores above the empirical threshold. We then extended FETCH analysis to all 210 pairwise heterotypic isoform combinations. The resulting interaction landscape largely recapitulated expected motif-class relationships, including enrichment within the two canonical compatibility groups, but also identified neighboring-group interactions and unexpected cross-group pairings that represented clear exceptions to class-based predictions. Consistent with these findings, pairwise EL2 motif similarity was only modestly associated with threshold-based interaction classification, indicating that EL2 similarity alone was insufficient to predict compatibility outcomes. Together, these findings suggest that motif class provides a broad organizing framework for connexin compatibility, but that pairwise docking specificity also depends on yet-unresolved isoform-specific determinants that produce neighboring-group relationships and clear cross-group exceptions. Notably, Cx46, a lens Cx also associated with melanoma and breast cancers, emerged as a broadly permissive isoform capable of interacting with partners from both major compatibility groups and more than half of the connexin family. Together, these findings establish the first family-wide experimental atlas of human connexin docking compatibility, defining canonical interactions, previously unrecognized pairings, and exceptions to established compatibility rules. This atlas provides a foundation for defining the molecular determinants of connexin specificity, understanding how isoform diversity shapes intercellular communication, and designing gap junction channels with controlled docking behavior.

biochemistry

Both environmental filtering and intraspecific variation shape small mammals' elementomes

The biogeochemical niche hypothesis (BNH) proposes the multi-elemental composition of organisms - their elementome - as a new ecological dimension. However, which ecological factors shape elementome assembly remains little known, especially in animals. Here, we studied the mandibular elementome of two sympatric small mammals - Apodemus flavicollis and Clethrionomys glareolus - to assess how intraspecific variability (ontogenetic changes in body mass and sex under the vertebrate bone hypothesis; VBH) and environmental filtering (season and habitat) shape essential and non-essential elementome assembly. Species showed moderate elementome segregation and seasonal niche partitioning, with implications for coexistence. Ontogenetic body mass predicted elemental variation and calcium substitution, with several hypermetric scalings in autumn indicating strong departures from mass-invariant homeostasis. Finally, our results suggest a dichotomy: essential elementomes were mainly driven by intraspecific variation, whereas non-essential elementomes were rather shaped by environmental filtering. Our results position animal elementomes as an integrative ecological dimension linking organismal biology, species interactions, and environmental filtering across individuals, populations, and species.

ecology