Biology subjects

Lee, J.

Publications and source records attributed to Lee, J..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

MicroRNA-223 Enhances Microglia-Dependent Clearance of Amyloid Beta Plaques and Ameliorates Behavioral Deficits in a Mouse Model of Alzheimer's Disease

The Alzheimers disease (AD) brain is characterized by dysregulated expression of multiple microRNAs (miRNA), positioning them as promising diagnostic and therapeutic targets. The levels of glia-enriched miR-223 are abnormal in the brains and plasma of AD patients and miR-223 is neuroprotective in models of stroke. However, whether miR-223 can be beneficial in AD is not known. Here, we report that intracerebroventricular (ICV) injection of miR-223 oligonucleotide mimic alleviated cognitive impairment, reduced amyloid beta (A{beta}) pathology, and ameliorated the defects in synaptic marker expression in AppNL-G-F AD model mice. Mechanistically, miR-223 induced microglial clustering around A{beta} plaques with a concomitant upregulation of microglial phagocytic receptors AXL, TREM2 and CD11c, while pharmacological microglial depletion abolished the plaque-clearance phenotype. Moreover, in human iPSC-derived microglia miR-223 directly targeted multiple genes in the endo-lysosomal pathway, including AD risk gene SPPL2A, indicating that it acts as a major regulator of microglial phenotype. Lastly, long-term AAV-mediated overexpression of miR-223 recapitulates its beneficial effects on cognition, pathology, and synaptic marker expression. Our study demonstrates a novel approach for the treatment of AD using miR-223 and highlights the potential of RNAi-based therapeutics in neurodegenerative disease.

neuroscience↗

bioRxiv2026

A Chairside Multimodal Platform for Temporomandibular Joint Biomechanical Assessment: Technical Evaluation and Illustrative Application

BackgroundTemporomandibular joint (TMJ) biomechanics can be characterized by mandibular motion, masticatory muscle activity, and bite force generation. When acquired synchronously, these functional variables can serve as model-ready inputs for subject-specific computational analyses of internal joint mechanics. However, existing tools typically measure these signals using separate hardware and software platforms, limiting synchronized acquisition within a clinically practical chairside workflow. MethodsWe developed and technically evaluated a compact multimodal platform for chairside acquisition of TMJ functional data and demonstrated its analytical utility in an illustrative orthognathic surgery application. The platform integrates motion, bite force, muscle activity, acoustic, and event-timing measurements with software for real-time preview, protocol guidance, and synchronized export. We assessed technical performance and chairside feasibility and analyzed representative pre- and postoperative data from an orthognathic surgery patient using kinematic, force-control, and computational modeling workflows. FindingsMotion capture demonstrated submillimeter accuracy, with static and dynamic errors of approximately 0.04 mm and 0.12 mm. Bite force sensors showed excellent linearity (R{superscript 2} = 0.998). Chairside deployment required approximately 15 minutes each for setup and data collection. The illustrative case demonstrated that synchronized chairside data can support preoperative and postoperative kinematic analysis, bite force control capacity assessment, and estimation of TMJ disc stress. InterpretationThe proposed platform enables time-efficient chairside acquisition of synchronized, model-ready multimodal datasets for quantitative TMJ biomechanical assessment. This platform and workflow could support subject-specific biomechanical analysis and future clinical studies of temporomandibular joint function.

bioengineering↗

bioRxiv2026

Multiscale Biomechanical and Electrophysiological Modeling of Nociceptive Activation in Musculoskeletal Joint Disorders: Insights from the Temporomandibular Joint

Background and objectiveMusculoskeletal joint disorders often show inconsistent relationships between structural degeneration and nociceptive pain. Temporomandibular joint (TMJ) disc displacement represents a clinically relevant model for investigating the structure-function-pain relationship. This study aimed to develop a multiscale computational framework integrating biomechanics, three-dimensional (3D) neural morphology, and electrophysiology to quantitatively link TMJ structural alterations, biomechanical loading, and peripheral nociceptive activation. MethodsStrain distributions in the TMJ disc and retrodiscal tissue during mouth opening and clenching were computed in ArtiSynth under varying degrees of displacement. Human TMJ 3D nerve architecture was reconstructed using porcine TMJ nerve mapping data as an anatomical reference, and ion channel dynamics were implemented in NEURON. Model coupling was achieved by mapping biomechanical strain fields onto nociceptor membranes to simulate mechanosensitive currents and action potential propagation to the trigeminal ganglion. ResultsAnterior DDwoR induced a severity dependent strain pattern in the TMJ disc and retrodiscal tissue, including posterior redistribution, increased strain magnitude, prolonged activation, and broader retrodiscal tissue involvement. Displacements of 4, 6, and 8 mm produced larger mechanosensitive currents, broader terminal depolarization, and higher trigeminal firing rates during mouth opening (6, 18, and 28 Hz) and clenching (8, 20, and 28 Hz), whereas 0- and 2-mm displacements produced negligible neural activation. ConclusionsThis study establishes a multiscale biomechanical-electrophysiological framework linking TMJ structural alterations to peripheral nociceptive activation. The framework quantitatively connects macroscale strain patterns with microscale neural activation, suggesting that anterior disc displacement may amplify peripheral nociceptive signaling by increasing the overlap between elevated strain and densely innervated retrodiscal tissue.

bioengineering↗

bioRxiv2026

Coexisting but dissociable place and spatial view codes in the primate hippocampus

In rodents, hippocampal activity is classically described in terms of position-anchored place cells, whereas nonhuman primate work has emphasized spatial view cells, in which activity depends on the region of space being viewed. This contrast has fueled a longstanding debate over whether primate and rodent spatial codes are biologically distinct. We recorded single units in the hippocampus of macaques as they navigated linear tracks in two visually distinct contexts, intermittently making context-dependent object choices. Using a generalized linear model to dissociate position coding from spatial view coding, we identified three coexisting populations in the macaque hippocampus: Position cells, View cells, and Conjunctive cells encoding both variables. Position cells were prevalent and showed rodent-like properties--localized firing, directional tuning, and contextual remapping--even after accounting for visual sampling, whereas View cells stably encoded allocentric visual space. Population decoding confirmed this dissociation at the ensemble level. Robust position codes thus coexist with, yet remain dissociable from, view codes in the primate hippocampus, suggesting that the apparent scarcity of place-like responses in earlier primate work reflects methodological and task-related differences rather than a fundamental species-level divergence.

neuroscience↗

bioRxiv2026

Deep learning representations of human Immune Health for precision immunology

The human immune system is composed of [~]30-50 distinct cell types, each of which can exist in different states of activation or differentiation. Indeed, the mammalian immune system has evolved to sense and respond to infections, cancers, injuries, and changes in tissue or host homeostasis (1). Moreover, an increasingly large fraction of approved drugs target the immune system directly, and/or cause immune changes (2-4). A key feature of the immune system is to store some of this information, for example as innate or adaptive immune memory (5). In addition, rewiring of immune network architecture induced by disease, environmental exposures, drug treatments, and/or chronological age allows the immune system to store information in the pattern of connections and activity across populations of immune cells. This ensemble information storage, in addition to changes to individual cells, functions as a major way the immune system encodes aspects of immune history and future potential. Genetic information can identify inherited risk alleles, but cannot capture the continual remodeling of the immune system shaped by exposures, infection, inflammation, therapy, and aging (6, 7). To define and use such ensemble immunotypes, we developed a self-supervised deep learning framework that transforms high-dimensional immune profiles into representations of immune health. MAESTRO (MAsked Encoding Set TRansformer with self-distillatiOn) encodes a set of cells from an individual into an embedding that captures immune cell population-level organization. Pretrained on 1,792 peripheral blood samples comprising over 418 million immune cells across 13 clinical diagnoses, MAESTRO learns immune fingerprints that are stable within individuals yet diverse across populations, states of health, disease, and treatment, providing a quantitative basis for comparing immune states across individuals and over time. These fingerprints capture immune architecture beyond coarse cell type proportions, enabling patient-efficient clinical prediction using simple task specific models. MAESTRO model embeddings retain a temporal dimension of immune history and potential, reflecting signatures of past exposures and baseline features that predict future immune responses. Finally, we demonstrate a translational precision immunotherapy application by testing this approach in metastatic Pancreatic Ductal Adenocarcinoma (PDAC), where pretreatment immune landscape circuitry maps enable patient stratification and therapeutic response prediction. Overall, we developed a large, attention-based model that captures deep network architecture of immune states through self- supervised representations of immune cytometry data as a reusable foundation for precision immunology, converting immune complexity into clinically actionable embeddings for diagnosis, monitoring, and therapy selection.

immunology↗

bioRxiv2026

ProteinSketch translates spatial intuition into protein design with bimanual interaction in VR

Generative AI-based protein design can create diverse structures for desired functions but offers human designers limited control over three-dimensional architectures. We developed ProteinSketch, a bimanual virtual reality platform in which immersive backbone sketches and volumetric envelopes are directly created and translated into constraints for diffusion-based protein generation. RFdiffusion-based real-time refinement enabled interactive exploration and construction of user-specified protein topologies. Volumetric conditioning of sketched envelopes enabled high-fidelity control of anisometric geometries, confirmed by cryo-electron microscopy. These user-defined volumetric constraints enabled functional-binder design and extension of pre-existing minibinders to surfaces otherwise difficult to access within complex molecular environments using conventional design approaches. This collaborative human-AI framework integrates human spatial reasoning with generative AI for spatially directed, shape-controlled design of protein structure and function. One-sentence summaryImmersive ProteinSketch embeds human spatial reasoning in AI-guided design of protein topology, shape, and function.

bioengineering↗

bioRxiv2026

Gene-metabolite networks reveal physiological trade-offs but not transcriptional co-regulation between carotenoids and dry matter in cassava (Manihot esculenta) roots

Provitamin A biofortification of cassava (Manihot esculenta) is constrained by a negative genetic correlation between total carotenoid (TC) and dry matter (DM) contents, but its underlying biological mechanism remains unclear. We examined this relationship in 24 African, Latin American, and hybrid cassava genotypes by measuring gene expression and metabolites in inner and outer storage root layers that varied spatially in carotenoid accumulation, enabling comparisons across and within genotypes. TC, and particularly upstream cis-carotenes, were negatively associated with DM after accounting for genotype, and this relationship strengthened across developmental timepoints, consistent with a physiological component of the trade-off. Gene-metabolite co-expression networks constructed from genetic, non-genetic, and overall phenotypic trait components showed no significant topological overlap between carotenoid- and starch-related gene sets, indicating that the TC/DM relationship is not driven by transcriptional co-regulation of the main pathways, although individual associations between carotenoids and carbohydrate-related genes suggested possible indirect metabolic links. Instead, TC accumulation was most strongly associated with regulatory, stress-, redox-, and plastid-related genes, enriched for heme-binding and oxidoreductase functions. These findings suggest that the TC/DM trade-off is not a fixed constraint, and identify candidate regulators of carotenoid content for future functional validation to support cassava provitamin A biofortification. HighlightGenetic, spatial, and developmental variation in cassava storage roots implicate cis-carotenes, but not direct transcriptional regulation of the carotenoid and starch pathways, in the trade-off between carotenoids and dry matter.

plant biology↗

bioRxiv2026

Maternal vaccination timing shapes the composition and maturation of antibody clonotypes transferred to the newborn

Newborns rely on maternally transferred antibodies for immune protection, acquired across the placenta and through breast milk. Despite this importance, how closely the inherited antibody repertoire resembles the mothers has not been examined at the clonotypic level. We combined BCR-Seq with proteomic Ig-Seq to track SARS-CoV-2-specific antibody clonotypes across maternal blood, cord blood, and breast milk from six mRNA-immunized pregnant individuals. Vaccination earlier in gestation generated more diverse peak IgG repertoires but greater contraction before delivery, yielding fewer transferred clonotypes. Vaccination later in gestation produced more restricted peak repertoires, but more clonotypes persisted to delivery and transferred to cord. Infant cord was enriched for persistent, highly somatically mutated, and intraclonally diverse IgG clonotypes, consistent with preferential transfer of affinity-matured antibodies. In contrast, breast milk IgA repertoires were largely distinct from systemic repertoires and underwent substantial remodeling despite stable antigen titers. These findings define molecular determinants of passive immunity shaped by vaccination timing relevant to optimizing maternal immunization.

immunology↗

bioRxiv2026

Molecular-level analysis of serum IgG repertoires in COVID-19-vaccinated people with cystic fibrosis identifies abundant convergent antibodies

BackgroundPeople with cystic fibrosis (pwCF) are at increased risk of severe disease following respiratory viral infections including influenza and respiratory syncytial virus, and were therefore given priority for COVID-19 vaccination. Retrospective epidemiological data have revealed a lower incidence of SARS-CoV-2 infection and a reduced fatality rate among pwCF than in the general population, possibly from the stringent infection control measures and early adoption of protective behaviors. Despite several reports of adequate binding and neutralizing titers after vaccination, the molecular features of vaccine-elicited serum antibody repertoires in pwCF remain unknown. MethodsWe performed high-resolution proteomic analysis of serum IgG, combined with next-generation sequencing of B cells, to quantitatively profile Spike (S)-reactive serological repertoires from nine infection-naive pwCF after two doses of COVID-19 mRNA vaccine. We recombinantly expressed 20 IgG clonotypes from 6 pwCF as monoclonal antibodies (mAbs) and measured their binding and neutralization against vaccine-strain and variant viruses. ResultsAll donors mounted strong binding and neutralizing titers to vaccine-strain virus. Ig-Seq revealed diverse serum repertoires in all vaccinees, with antibodies targeting the receptor-binding domain (RBD) comprising 64% of each circulating repertoire by abundance. Several serum IgG clonotypes identified across our cohort shared identical or similar IGHV and CDRH3 amino acid sequences with serum IgG from other pwCF or S-reactive mAbs isolated from non-CF individuals. These convergent antibodies made up 14.6% of the anti-S repertoires in our cohort, reaching 24.8% in one pwCF. Convergent antibodies tended to be RBD-reactive and enriched in specific IGHV; surprisingly, a higher abundance of convergent antibodies in serum correlated with a lower breadth of serum neutralization. All 20 mAbs bound Wuhan S with high affinity (EC50 < 10 nM), and only RBD-reactive mAbs conferred neutralization to vaccine or variant pseudovirus. While most mAbs bound both the B.1.617.2 (Delta, 17/20) and B.1.1.529 (Omicron, 12/20) strains, convergent mAbs were less likely to bind either variant. ConclusionsPost-vaccine serum IgG repertoires in pwCF are dominated by RBD-focused, high-affinity antibodies and include a substantial convergent component shared with non-CF vaccinees. These findings demonstrate that pwCF mount antibody responses comparable to the general population, and a large group of convergent antibodies may contribute to strain-specific rather than cross-variant immunity.

immunology↗

bioRxiv2026

VESTA: Machine Learning-Enabled Estimation of ViscoElastic Ratios from On-Axis Spatio-Temporal ARFI Features

Viscoelastic characterization of tissue has significant diagnostic value in oncology, as tumor progression alters both elasticity and viscosity in ways that neither property alone can fully capture. Existing acoustic radiation force (ARF)-based methods such as Viscoelastic Response (VisR) ultrasound estimate relative elasticity and viscosity through per-A-line nonlinear model fitting, which is computationally intensive and requires auxiliary simulations to correct elasticity-dependent bias. This work presents VESTA (Machine Learning-Enabled Estimation of ViscoElastic Ratios from On-Axis Spatio-Temporal ARFI Features), a two-stage data-driven pipeline that predicts elasticity ratio (ER) and viscosity ratio (VR) directly from seven normalized ARFI displacement features at the A-line level, without model fitting or compensation. Stage 1 is an MLP classifier that detects inclusion boundaries from normalized peak displacement and negative peak velocity ratios; Stage 2 is a dilated Conv1D regression model that estimates ER and VR along the full axial sequence using the predicted mask alongside displacement features. The pipeline was trained on 500 simulated inclusion scenarios spanning three geometries, five focal depths, two F-numbers, and a broad range of material contrasts. In silico, mean predicted ER and VR were within 12% of ground truth across all geometries, with performance best when ER and VR were moderate or decoupled. Experimental validation on a chicken breast phantom demonstrated plausible generalization to real tissue heterogeneity. Applied to an in vivo murine 4T1 breast cancer model, the pipeline tracked treatment-related attenuation of mechanical contrast in paclitaxel-treated tumors relative to controls over a 36-day imaging period, supporting its relevance for tumor monitoring.

bioengineering↗

bioRxiv2026

Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition

Determining the structural basis of antigen recognition by antibodies and T cell receptors (TCRs) provides critical insights into effective immune targeting and can inform design of biotherapeutics and vaccines. Accurate computational modeling of antibodies and TCRs in complex with their targets poses a major challenge for predictive methods, including AlphaFold, which is generally accurate for modeling protein complexes but has shown limited success for immune recognition. In this study we assessed the performance of AlphaFold2, AlphaFold3, increased sampling protocols, and related deep learning methods for modeling antibody-protein, antibody-peptide, and TCR-peptide-major histocompatibility complex (pMHC) recognition. We show that increased sampling and AlphaFold3 generally improve performance relative to default sampling and AlphaFold2, however predictive accuracy and improvement levels varied considerably among interface classes, with antibody-peptide complexes representing a challenge despite their small antigen size. Comparing per-case success across methods showed some complementarity, indicating opportunities for increased success through model pooling approaches, for instance increasing antibody-peptide near-native success from 41% to 59%. Analysis of AlphaFold confidence scores and modeling of a noncanonical complex provided further insights into predictive performance. These results highlight considerations for predictive antibody and TCR complex modeling efforts, while revealing key distinctions among protocols, scoring, and immune complex classes.

bioinformatics↗

bioRxiv2026

Dynamically actuated reconfigurable topographical surface enables active control of implant-associated infections

Implant-associated infections are driven by bacterial biofilm formation and remain difficult to eradicate using conventional antibiotic-based strategies. Here, we present a dynamically actuated reconfigurable topographical surface (DARTS) that integrates intrinsically bactericidal nanoscale surface topography with programmable mechanical actuation to achieve durable, antibiotic-free infection control. Using a scalable bottom-up nanofabrication strategy, we generate tunable wrinkled MXene topographies that exhibit contact-mediated bactericidal activity against both Gram-positive and Gram-negative bacteria without chemical leaching. Integration with a soft robotic actuator enables reversible modulation of surface geometry, which synergistically enhances bacterial removal and killing, resulting in near-complete disruption of mature biofilms. Dynamic actuation further sensitizes released bacteria to antibiotic treatment. In a mouse subcutaneous implant infection model, DARTS with actuation achieves sustained suppression of bacterial burden and markedly improves host tissue outcomes. Remote, noninvasive actuation using near-infrared laser stimulation further highlights the translational potential of this platform for implantable antibacterial applications. Significance StatementImplant infections are difficult to treat because bacteria form biofilms that protect them from antibiotics and the immune system. Current materials often rely on chemical release, which can lose effectiveness over time. Here, we present a new surface that both kills bacteria and removes them. The surface uses nanoscale features to physically damage bacterial cells, while dynamic motion clears attached bacteria and biofilms. This allows continuous, chemical-free control of infection. In a mouse implant model, the system greatly reduced bacterial burden and improved tissue healing. This work introduces a new way to control bacteria using dynamic surface design and could be applied not only to medical implants but also to environmental, food, textile, and marine systems.

bioengineering↗

bioRxiv2026

Dynamic Patterns of Nuclear Transcription Factor Abundance in Plant Basal Immunity Revealed by Spatial Proteomics of Arabidopsis Nuclei

O_LIThe control of amount of nuclear proteins is fundamental in regulating plant gene expression, but the mechanisms of quantitative dynamics of the nuclear proteome are largely unstudied during adaptive responses to pathogens. C_LIO_LIHighly specific labeling, enrichment and measurement of the nuclear proteome was performed using TurboID LC-MS of Arabidopsis thaliana leaves treated with the pathogen-associated molecular pattern (PAMP), flg22, and/or cycloheximide. The chosen experimental approach allowed discrimination of the effects of translation, nuclear protein import, trafficking of preexisting proteins, derepression, and nuclear protein turn-over upon elicitation of basal immunity. C_LIO_LIThe highly specific, deep coverage of proteins in the nucleus makes this study a resource for anyone interested in plant nuclear proteome dynamics and defense. C_LIO_LIAround 2,000 nuclear proteins were repeatedly quantified, including more than 300 transcription factors or other proteins related to transcription. Several proteins with documented activity in endosomes were newly synthesized and imported into nuclei upon PAMP challenge, suggesting alternative nuclear functions in PAMP-triggered immunity (PTI). Circadian clock components, including the transcription factor, CIRCADIAN CLOCK ASSOCIATED 1 (CCA1)-HIKING EXPEDITION (CHE), were depleted upon PAMP challenge, suggesting a safeguard against untimely induction of systemic acquired resistance (SAR). C_LIO_LIBased on proteomic patterns, proteins moonlighting in the nucleus as well as trafficking and turn-over regulation of the proteome are common elements during plant immunity. C_LI

plant biology↗

bioRxiv2026

APRIL: Adaptive Regression-Based Two-Dimensional Quantitative Anisotropy Imaging Using Acoustic Radiation Force Impulse

ObjectiveThis study aims to develop and validate a quantitative, depth-resolved anisotropy imaging framework that extends ARFI-based focal degree-of-anisotropy (DoA) estimation into two-dimensional mapping by modeling the depth-dependent relationship between shear modulus ratio (SMR) and peak displacement ratio (PDR). MethodsWe propose APRIL (Adaptive Polynomial Regression for anisotropy Imaging via ARFI-induced DispLacements), a framework for quantitative, depth-resolved DoA imaging that adaptively selects polynomial regression or shape-preserving spline interpolation based on excitation PSF asymmetry. Training data were generated using an LS-DYNA3D + Field II simulation pipeline in homogeneous transversely isotropic media (SMR 0.9-4.9). Testing included shifted SMRs under varied acoustic conditions and three heterogeneous inclusion configurations (anisotropic inclusion in isotropic background and vice versa). Experimental validation was performed in an in-vivo murine tumor model over the time, ex-vivo chicken breast, and tissue-mimicking gelatin phantoms, using a Verasonics system with an L11-5v transducer. ResultsAPRIL achieved depth-resolved SMR prediction errors below 9% over 10-30 mm, with highest accuracy in the focal region (MAE 2.3%, RMSE < 0.1) and stable performance across PSF transition zones. In heterogeneous phantoms, it reconstructed anisotropy maps with SSIM up to 86% and MPE below 7%, accurately delineating inclusion boundaries. Under acoustic parameter variations, mean absolute errors remained below 10%, demonstrating robustness to system and tissue heterogeneity. ConclusionAPRIL enables robust, two-dimensional anisotropy imaging beyond focal estimates. SignificanceThe method provides a physically grounded and generalizable framework for clinically viable anisotropy biomarkers in muscle, tendon, kidney, tumor and breast tissues. HighlightsO_LINovelty: APRIL introduces LoA-conditioned adaptive polynomial-spline regression to extend ARFI-based anisotropy estimation from focal point estimates into full 2D depth-resolved SMR imaging. C_LIO_LIResults: APRIL achieved SMR prediction errors below 9% over 10-30 mm, SSIM up to 86% in heterogeneous phantoms, MAE below 10% under acoustic variations, tracked tumor anisotropy progression in vivo, and differentiated anisotropic inclusion versus isotropic background in tissue-mimicking gelatin phantom. C_LIO_LISignificance: APRIL enables clinically viable, spatially resolved anisotropy biomarker imaging in muscle, tendon, kidney, and tumor tissues without requiring heterogeneous training data. C_LI

bioengineering↗

bioRxiv2026

Retinal resuscitation in post-mortem eyes

Vision loss compromises the quality of life of millions of people worldwide. Currently, vision-restoring therapies are lacking. Post-mortem preservation of human eyes may enable whole eye transplantation (WET) or therapeutic development. We developed an approach to cannulate the ophthalmic artery and perfuse post-mortem pig and human eyes using a custom-built device, Eye-in-Care-Box (ECaBox). Retinal vasculature imaging and reconstruction were used to assess perfusion efficacy using a supervised deep learning model. Without intervention, the retina degrades post-mortem, whereas perfusion preserves retinal structure and cell viability for up to 24-hours. Eyes were perfused within 30 minutes post-extraction, and regained light-responses persisted for up to 10 hours after death, challenging the notion that response to light ends at death. Our findings show that intact eyes can be resuscitated and preserved outside the body, supporting the ECaBox platform for WET preservation and pre-clinical therapeutic testing. Ultimately, ECaBox may bring vision-restoring treatments to patients.

neuroscience↗

bioRxiv2026

Latitude, not geography, globally structures Oscheius tipulae into three deeply divergent lineages

Free-living nematodes are among the most abundant animals on Earth and play critical ecological roles in soil ecosystems. However, the global population structure and evolutionary history of most species remain poorly understood. Here, we analyzed genome-wide variation in Oscheius tipulae using whole-genome sequence data from 31 isolates, including 28 publicly available genomes and three newly collected strains from Korea. Population structure analyses, phylogenomic inference, and ancestry estimation consistently identified three deeply divergent lineages. These analyses did not detect admixture among lineages and collectively supported a predominantly tree-like evolutionary history. Notably, the lineages were structured by latitude rather than geographic proximity. Isolates from similar latitudinal zones clustered together regardless of continental origin, forming three major groups: northern mid-latitude (NML), low-latitude (LL), and southern mid-latitude (SML). This pattern indicates that the lineages have maintained largely independent evolutionary trajectories over extended timescales despite the potential for long-distance dispersal. Furthermore, environmentally associated variants showed significant differentiation among lineages, indicating that environmental selection may contribute to the maintenance of this latitudinally structured diversity. Our results reveal unexpectedly deep global divergence within O. tipulae, and highlight the importance of ecological divergence and long-term lineage retention in shaping the global diversity of this group.

ecology↗

bioRxiv2026

Appetitive Pavlovian goal-tracking memory reconsolidation is reduced by both adrenergic and NMDA receptor antagonism

RationaleAppetitive Pavlovian cues can drive maladaptive reward seeking via stimulus-reward memories. Disrupting memory reconsolidation offers a potential strategy to reduce their influence, but evidence for {beta}-adrenergic blockade with propranolol is inconsistent across behavioural paradigms, particularly relative to NMDA receptor antagonism. ObjectivesWe tested whether propranolol disrupts reconsolidation of appetitive sucrose memories in a discriminative goal-tracking paradigm, and compared its effects with those of the most commonly used NMDA receptor antagonist, MK-801. MethodsAdult Lister hooded rats underwent discriminative Pavlovian conditioning. Thirty minutes before a brief memory reminder (non-reinforced or reinforced), rats received systemic drug treatment or saline control. In study 1, MK-801 (0.1 mg/kg) was administered to male rats. In study 2, propranolol (10 mg/kg) was administered to equal numbers of male and female rats. Goal-tracking was tested drug-free at 1 and 8 days. ResultsIn study 1, MK-801 impaired subsequent discriminated responding at test. These effects were observed not only when reminder was non-reinforced as in previous successful demonstrations, but also with reinforced reminder. In study 2, Propranolol also impaired subsequent goal-tracking, regardless of reminder type, and the effects were consistent across sexes. ConclusionsPropranolol can disrupt reconsolidation of appetitive goal-tracking memories to a similar extent as MK-801 under conditions that promote memory destabilisation. These findings demonstrate that {beta}-adrenergic blockade can impair appetitive memory reconsolidation in a goal-tracking paradigm, challenging prior null findings and revitalising the potential for propranolol-based interventions in maladaptive reward-seeking behaviours.

neuroscience↗

bioRxiv2026

Acute Slow Oscillation Power as a Biomarker of Injury Severity After Photothrombotic Stroke: Dissociation from Week 1 Functional Recovery

A central goal in translational stroke research is to identify neurophysiological biomarkers that index injury severity and provide information about subsequent functional outcome. Cortical slow oscillations (SOs; 0.1-1.0 Hz) are suppressed after ischemic stroke and recover over the following days to weeks. Whether SO recovery actually tracks behavioral recovery, and whether pre-stroke network organization relates to outcome, has not been tested within individual animals. Using longitudinal wide-field calcium imaging in Thy1-GCaMP6f mice (n = 25), we tracked ipsilateral and contralateral SO power across baseline, 24 hours, and one week after photothrombotic stroke of the left somatosensory forepaw cortex, classifying animals by the presence (STI+; n = 14) or absence (STI-; n = 11) of secondary thalamic injury. Acute ipsilateral SO power was suppressed and tracked concurrent behavioral deficit ({rho} = -0.718, p < 0.001), remaining associated with deficit after adjustment for infarct volume (partial {rho} = -0.448, p = 0.025). By one week SO power had partially recovered, yet its recovery was dissociated from forelimb use. Week 1 SO power showed no association with behavior in any region or hemisphere (all |{rho}| [≤] 0.074, all p > 0.5), and SO recovery did not differ significantly between STI groups despite STI+ animals remaining more impaired (p = 0.011). Pre-stroke SO laterality was associated with week 1 behavioral outcome, independent of infarct size ({rho} = -0.518, p = 0.008; partial {rho} = -0.446, p = 0.026). Acute SO suppression therefore indexes injury severity beyond infarct volume, whereas spontaneous recovery of SO power is not a reliable surrogate biomarker of week 1 functional outcome. Pre-stroke interhemispheric SO balance emerged as an exploratory candidate source of prognostic information, identifying pre-injury brain state as a dimension that warrants prospective validation.

neuroscience↗