Biology subjects

Ji, S.

Publications and source records attributed to Ji, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Single-nucleus chromatin accessibility time course of excisional wound repair in rat skin

We present a time-series single-nucleus ATAC-seq dataset from full-thickness excisional wounds in Sprague-Dawley rats. Samples were taken from unwounded skin (normal control) and at 1, 2, 5, 10, and 19 days post-wounding, spanning the inflammatory, proliferative, and remodeling phases of skin repair. We extracted nuclei with a two-step tissue dissociation protocol and prepared libraries using the DNBelab C Series Single-Nucleus ATAC Kit, then sequenced on the MGI DNBSEQ-T1 platform. After stringent quality filtering, 37,555 nuclei passed quality control; the resulting chromatin accessibility profiles cover 23 cell types: fibroblast subpopulations, keratinocytes, vascular endothelial cells, immune cells, and skin appendage cell types. This genome-wide chromatin accessibility dataset is a resource for studying regulatory dynamics during excisional wound repair and for comparing results with other wound healing systems.

bioinformatics↗

bioRxiv2026

Regional macrophage specialization shapes intestinal neuroimmune function

Tissue-resident macrophages adapt to local environments to support organ-specific functions, but whether their regulation differs across regions of the same organ is poorly understood. The gastrointestinal tract provides an ideal system to address this question because its anatomically distinct regions perform specialized physiological functions and contain different cellular environments. Here, we found that intestinal muscularis macrophages (MMs) exhibited distinct regional trophic requirements and neuroimmune functions across the gut. Small-intestinal MMs were highly sensitive to CSF1 neutralization but recovered robustly, whereas colonic MMs were less sensitive to CSF1 depletion yet showed limited recovery. Disruption of CSF1-dependent MMs selectively reduced nitrergic neurons and altered motility in the small intestine, whereas the colonic neuronal compartment was comparatively preserved. Csf1 was enriched in small-intestinal nNOS+ neurons, and neuron-specific Csf1 deletion reduced both MMs and nitrergic neurons and altered small-intestinal transit, with limited effects in the colon. Together, these findings reveal that macrophage trophic requirements and neuroimmune functions are regionally specialized within the intestine and identify neuronal CSF1 as a key component of the trophic relationship between nitrergic neurons and MMs in the small intestine.

neuroscience↗

bioRxiv2026

Lactate epigenetically shapes tumor cell states in H3K27M diffuse midline gliomas

H3K27M diffuse midline gliomas (DMGs) are lethal and lack treatment options. These tumors exhibit tumor heterogeneity with aggressive oligodendrocyte precursor (OPC)- and mesenchymal (MES)-like cell states. Because all tumor cells bear H3K27M, tumor heterogeneity has been attributed to microenvironmental cues that remain obscure. H3K27M DMGs exhibit increased glycolysis and the Warburg effect to produce lactate. Lactate can directly modify histone lysines including H3K27Lac, and we hypothesized that lactate epigenetically regulates tumor cell states in H3K27M DMGs. We undertook a comprehensive and integrated analysis of H3K27M DMG cell lines, animal models, tumor tissues, and magnetic resonance spectroscopy in patients to decipher the epigenetic roles of lactate. Here, we report that H3K27M cells uniquely exhibit elevation of the activating mark H3K27Lac. We observed significant heterogeneity in lactate levels within tumors, and the addition of exogenous lactate resulted in marked increases in H3K27Lac and the expression of critical OPC- and MES- like gene signature genes, which correlates with poorer patient outcomes. Our therapeutic approach leverages the inhibition of CBP/p300, which deposits both H3K27Lac and H3K27ac. Targeting CBP/p300 effectively reduces both H3K27Lac and H3K27ac levels, suppresses key OPC- and MES-like signatures, and shows efficacy in preclinical models. Collectively, our findings identify lactate as a key player in the epigenetic regulation of tumor cell state heterogeneity and suggest that targeting this pathway offers promise for addressing the heterogeneous complexities of H3K27M DMGs.

molecular biology↗

bioRxiv2026

Stress-recovery dynamics reveal a separatrix in transcriptomic landscapes across organs and aging

Aging is often characterized statically as molecular profiles, but how these profiles may affect the capacity of systems to respond to the external environment remains elusive. We perturbed young and aged mice via transient sleep deprivation and profiled transcriptomes from six organs immediately after stress and following recovery. The same perturbation induced complex temporal dynamics for each gene in an organ- and age- dependent manner. A shape parameter distinguished genes that recovered toward control expression from those that continued to drift away during recovery. Transcriptomic vector fields were inferred from these transitions using neural ordinary differential equations, revealing distinct stability regimes across organ systems. Interestingly, that of testis from the young mice contained a separatrix bounding the region within which perturbed state can return toward control. These findings establish transient perturbation and recovery as a framework for probing age-dependent transcriptomic stability and identifying boundaries that determine whether a perturbed system can return.

systems biology↗

bioRxiv2026

A Temporal Reliability and Sustainability Score Framework for Ranking Heart Rate Variability Metrics During Pharmacological Autonomic Blockade in Rats

Background: While Heart Rate Variability (HRV) is a cornerstone of non-invasive autonomic assessment, the sensitivity and sustainability of specific HRV parameters remain debated. This study introduces a "sustainability score" to systematically validate which metrics best reflect autonomic nervous system (ANS) modulation following pharmacological blockade. Methods: Ten male Sprague-Dawley rats were implanted with ECG electrodes. After recovery, rats underwent randomized atropine (1 mg/kg, intraperitoneal) and propranolol (10 mg/kg, intraperitoneal) sessions separated by at least 3 days. Baseline ECG was recorded for 30 min before each session, followed by 90-min post-drug ECG recording. HRV parameters were analyzed in sequential 15-min and 30-min segments. Reliability was assessed using average p-values across post-drug segments and a sustainability score, defined as the number of segments significantly different from baseline. Results: After atropine, HF Power showed the strongest rapid parasympathetic-related response in 15-min segments, with the lowest average p-value (0.1476) and highest sustainability score (4), followed by RSA (p=0.16148; score=4). HFn was less reliable in 15-min segments (p=0.23147; score=2) but became the most reliable parasympathetic-related metric in 30-min segments (p=0.0001; score=3). After propranolol, SI was the most reliable sympathetic-related metric in both 15-min (p=0.18225; score=2) and 30-min segments (p=0.0393; score=2), while SD2/SD1 showed the strongest 30-min sympathovagal-balance response (p=0.0200; score=3). Conclusion: HF Power is recommended for rapid parasympathetic-related assessment in short windows, HFn for longer-window parasympathetic assessment, SI for sympathetic-assessment, and SD2/SD1 for 30-min sympathovagal-balance analysis. Sustainability scoring provides a structured framework for selecting ECG-derived autonomic markers.

pharmacology and toxicology↗

bioRxiv2026

A Five-Gene Stromal-EMT Signature Predicts Prognosis, Immunotherapy Resistance, and Therapeutic Vulnerability in Bladder Cancer

Background: Bladder cancer has entered an era in which immune checkpoint blockade (ICB) and antibody-drug conjugate (ADC)-based combinations are reshaping clinical management. However, transcriptomic scores that connect prognosis, tumor microenvironment state, and treatment response are incompletely defined. Methods: Open-access TCGA-BLCA RNA-seq, clinical, mutation, copy-number, and RPPA data were downloaded from the Genomic Data Commons (GDC). Tumor-normal differential expressions, survival screening, LASSO-Cox modeling, train-test validation, GEO validation, pathway enrichment, immune signature scoring, mutation/CNV/RPPA support, drug sensitivity prediction, single-cell/spatial localization, and ICB validation were performed using reproducible Python and R scripts. A reduced model was derived using only genes shared by TCGA, GSE13507, and GSE31684. The fixed formula was then applied without refitting to IMvigor210 and GSE176307. Results: A five-gene model composed of EMP1, AHNAK, TNFRSF14, CLEC2D, and GSDMB retained TCGA internal prognostic value (train C-index 0.693, test C-index 0.605, all-sample C-index 0.667; TCGA test log-rank p = 0.015), although GEO survival validation in GSE13507 and GSE31684 was modest. High-risk tumors were enriched for epithelial-mesenchymal transition (EMT), TNF-alpha/NF-kB signaling, inflammatory response, hypoxia, complement, CAF, macrophage, checkpoint, and cytotoxic programs. Single-cell and spatial analyses localized the score to basal tumor, endothelial, fibroblast, and perivascular compartments. In IMvigor210, risk scores were higher in ICB non-responders than responders (Wilcoxon p = 0.044; AUC for non-response = 0.580), high-risk tumors had a lower responder rate (17.6% vs. 28.0%), and high risk predicted poorer OS (log-rank p = 0.016; multivariate continuous risk HR = 3.15, p = 0.044). GSE176307 showed directionally consistent but non-significant response results (AUC = 0.576). Conclusions: The five-gene score is best interpreted not as a standalone universal prognostic classifier, but as a compact stromal-EMT and immune-suppression phenotype associated with inferior ICB response. These findings support a framework linking prognosis, microenvironment biology, immunotherapy resistance, and therapeutic hypotheses in bladder cancer.

bioinformatics↗

bioRxiv2026

Effects of different shading levels on growth, physiology and leaf surface micromorphology of Sorbus sibirica "Dong Hong" seedlings

BackgroundSorbus sibirica Dong Hong is a promising ornamental cultivar, but its optimal light conditions remain unclear. AimsThis study evaluated the effects of shading on seedling growth, physiology, root morphology, and leaf surface micromorphology. MethodsOne-year-old seedlings were grown under full sunlight (CK) and 30%, 50%, or 70% shade for 100 days. Growth, biomass, root traits, chlorophyll, invertase, soluble protein, stomatal characteristics, and epicuticular wax morphology were determined. ResultsShading significantly affected all measured traits. The 30% shade treatment produced the greatest seedling height, which increased by 118.18% compared with CK, and the highest chlorophyll content, which increased by 120.21%. Soluble protein content was slightly increased, whereas invertase activity decreased under moderate shading. Although total biomass decreased by 18.63%, root development remained relatively stable under 30% shade, with slight increases in total root length and average root diameter. Stomatal density was highest under this treatment, and the epicuticular wax structure remained relatively regular. In contrast, 70% shade markedly inhibited biomass accumulation and root development. ConclusionsModerate shading, particularly 30%, provided the most favorable light environment for Sorbus sibirica Dong Hong seedlings and is recommended for summer nursery cultivation in Northeast China.

plant biology↗

bioRxiv2026

Tumor extracellular vesicle RNA profiling predicts treatment response in pediatric diffuse midline glioma

Detection of reliable markers of therapy response and drug resistance remains a major unmet need in brain cancer, as serial tumor biopsy is often not feasible. This challenge is particularly acute in diffuse midline glioma (DMG), a fatal pediatric brain tumor for which new targeted therapies are entering clinical use, yet tools for real-time molecular analysis of tumor evolution during therapy remain lacking. Here, we demonstrate that plasma tumor-derived extracellular vesicle (EV) profiling provides a minimally invasive and complementary approach for diagnosis and longitudinal molecular monitoring in H3K27M-mutant DMG. Across patient-derived tumor models and clinical plasma samples, EV mRNA levels correlated strongly with parental tumor transcriptomes. EV H3K27M mRNA enabled discrimination of DMG from non-DMG controls, and exploratory EV response-associated mRNAs were linked to radiographic response and progression-free survival in patients receiving ONC201. To enable tumor-selective EV enrichment and multiplexed molecular profiling within a clinically practical workflow, we developed a new integrated platform supporting same-day EV analysis from small plasma volumes. This work represents the first proof-of-concept demonstration of the diagnostic and treatment response relevance of tumor-derived EV RNA in pediatric DMG and establishes a generalizable framework for minimally invasive longitudinal molecular monitoring in diseases where tissue access is inherently limited.

cancer biology↗

bioRxiv2026

The Magnaporthe oryzae Effector AvrPii Attenuates Rice Immunity by Targeting the Calcium-Associated ANK Protein AVIN8

Rice blast, caused by the fungus Magnaporthe oryzae, poses a severe threat to global rice production. Although numerous M. oryzae effectors have been identified, the molecular mechanisms remain poorly understood. The effector AvrPii triggers ETI upon recognition by NLR receptor Pii and has been shown to target host exocytosis and oxidative metabolic pathways to suppress immunity. Here, we identify AVIN8 (AvrPii-interacting protein 8) as a new target of AvrPii. AVIN8 is an ankyrin-repeat (ANK) protein localized to the plasma membrane and nuclear envelope, with sequence similarity to known ANK calcium channels. AVIN8 expression is induced during early M. oryzae infection. Overexpression of AVIN8 enhances blast resistance, whereas its silencing increases susceptibility. AVIN8 promotes chitin-triggered ROS production in a Ca2+-dependent manner. In contrast, AvrPii impairs Ca2+ influx and chitin-triggered ROS burst. Our findings reveal a virulence strategy in which M. oryzae effector AvrPii hijacks the Ca2+ influx-associated ANK protein AVIN8 to suppress early calcium and PTI signaling in rice.

plant biology↗

bioRxiv2026

Tumor cell specific total mRNA expression informed neural networks predicts cancer progression

Inferring tumor molecular phenotypes from high-dimensional multi-omic data is a fundamental challenge in computational biology. Current methods for estimating tumor cell-specific total mRNA expression (TmS) require matched DNA and RNA sequencing data and rely on computationally intensive deconvolution pipelines. We present TmSNet, a deep learning framework that predicts TmS using mRNA, DNA methylation, miRNA, and immune cell proportions as input features. TmSNet integrates structured feature selection (gradient boosting, LASSO, elastic net) with specialized neural architectures to predict continuous TmS. Across 12 TCGA cancer types, TmSNet achieved cross-validated performance up to concordance correlation coefficient (CCC) = 0.93 and correlation R{superscript 2} = 0.88 and generalized to external cohorts with correlations of 0.54 (SCAN-B) and 0.43 (FUSCC). Predicted TmS values effectively stratify patients by risk and preserve known transcriptional profiles across tumor subtypes. These results demonstrate that TmSNet can infer biologically meaningful phenotypes from multi-omic data and provide a scalable framework for modeling tumor transcriptional activity in heterogeneous cohorts.

bioinformatics↗

bioRxiv2026

Multi-Modal Deep Learning Integrates Spatial Topologies and Sequential Motifs to Identify Class I HDAC Inhibitors as Pan-Cancer Therapeutics

The molecular characterization of human solid tumors has introduced immense genomic complexity and intra-tumoral diversification. Converting these detailed, multi-omic profiles right into workable, broad-spectrum therapeutics continues to be an formidable bottleneck in precision oncology. Traditional computational drug repurposing strategies largely rely on single-modality chemical descriptors, which frequently fail to capture the systemic transcriptomic interactions within the highly dynamic tumor microenvironment. Here, this study presents a robust multi-modal deep learning framework that synergistically integrates two-dimensional (2D) molecular graphs via Graph Neural Networks (GNNs) and chemical functional group patterns via self-attention Transformers. By mapping this dual-stream chemical feature space to the perturbational transcriptomic signatures (LINCS L1000) of 22 distinct cancer types from The Cancer Genome Atlas (TCGA), a vast library of over 28,000 small-molecule compounds was computationally screened. The developed multi-modal architecture achieved state-of-the-art predictive accuracy, significantly outperforming traditional single-modality baseline models. Strikingly, the comprehensive pan-cancer transcriptomic reversal landscape identified a persistent convergence of non-oncology drugs exhibiting potent broad-spectrum anti-tumor potential. Specifically, Class I Histone Deacetylase (HDAC) inhibitorsmost notably TC-H-106, RG2833, and Tianeptinaline, agents originally developed to penetrate the blood-brain barrier for neurodegenerative and psychiatric disordersemerged as top therapeutic candidates across lung adenocarcinoma (LUAD), bladder urothelial carcinoma (BLCA), and rectum adenocarcinoma (READ). Subsequent high-dimensional network pharmacology and functional enrichment analyses confirmed that these agents robustly suppress essential oncogenic pathways, specifically collapsing the G1/S phase transition and DNA damage repair machineries. Furthermore, structural validation via molecular docking and force-field thermodynamics confirmed the highly stable physical binding affinity (Vina score: -7.0 kcal/mol, MMFF94 Energy: 64.76 kcal/mol) of TC-H-106 to the HDAC1 catalytic pocket. Kaplan-Meier survival analysis based on TCGA gene expression stratification underscored the significant prognostic benefit of targeting this epigenetic axis. Collectively, these findings introduce a powerful multi-modal AI framework for systems-level drug repurposing and highlight brain-penetrant Class I HDAC inhibitors as highly promising candidates for pan-cancer epigenetic therapy.

bioinformatics↗

bioRxiv2026

Revisiting the genome assembly of Lupinus species reveals differential diploidization after a shared whole-genome duplication

Accurate genome assemblies are essential for comparative genomics, yet Hi-C-guided scaffolding can introduce structural errors that misrepresent chromosome architecture and bias evolutionary inferences. Here, we identified pervasive scaffolding errors - including artificial fusions, internal inversions, and incomplete contig mounting - in two previously published Lupinus genomes (L. cosentinii and L. digitatus) using a segmentation method based on LTR retrotransposon density. We re-assembled both genomes, producing chromosome-level references of 472.7 Mb (16 chromosomes) and 427.2 Mb (21 chromosomes), with BUSCO completeness >98.5%. Synteny validation and re-application of LTR profiling confirmed that all prior errors were resolved. Using these corrected genomes together with four additional Lupinus species and two outgroup legumes, we investigated post-polyploid evolution. Synonymous substitution rate (Ks) analysis revealed a genus-specific whole-genome duplication (WGD) event (Ks = 0.17) shared by all six Lupinus species. The proportion of WGD-derived genes varied markedly, from 60% in L. digitatus to only 36% in L. mutabilis, indicating differential diploidization. While all species retained a core set of WGD duplicates enriched in cytoskeleton organization, ion transport, and defense responses, each exhibited lineage-specific functional trajectories: cell wall modification in L. cosentinii and L. digitatus, nitrogen metabolism in L. albus and L. angustifolius, flower development in L. luteus, and stress/lipid metabolism in L. mutabilis. Our corrected assemblies provide optimal references for Lupinus comparative genomics, and our findings demonstrate that a shared WGD event can lead to both conserved and highly divergent post-polyploid fates, likely underpinning adaptive diversification within the genus.

genomics↗

bioRxiv2026

BaCas12a3 represents a new subtype of type V CRISPR effector with collateral activity toward tRNA

The CRISPR-Cas12 family encompasses diverse RNA-guided nucleases with both DNA-targeting and RNA-targeting subtypes. They can trigger antiviral activities mainly through either direct elimination invading nucleic acids, or activating broad collateral cleavage to induce abortive infection. Here, we report a novel type V CRISPR effector BaCas12a3 that causes growth inhibition through a unique tRNA-cleavage mechanism. Plasmid interference assays indicated that BaCas12a3 inhibits host growth arrest without invoking the DNA damage response, suggesting that the immune responses may not involve double strand breaks of DNA. Indeed, biochemical characterization of the BaCas12a3-crRNA ribonucleoprotein (RNP) unraveled that the effector is an RNA-activating nuclease that cleaves 3' terminus of tRNAs. Cryo-EM structures of BaCas12a3 reveal a conserved bilobed architecture featuring a unique nucleic acid-loading (NL) domain adjacent to the RuvC catalytic center. Structural and mutagenesis analyses show that the NL domain, together with a zinc ribbon domain, form a gated substrate groove. Target RNA binding induces conformational changes that open this groove and expose the RuvC active site, enabling specific tRNA cleavage while preventing other non-specific degradation. Our findings identified the NL domain aside the RuvC active site responsible for the tRNA recognition in BaCas12a3, expanding the functional diversity of CRISPR immunity.

molecular biology↗

bioRxiv2025

MRMhub: one-stop solution for automated processing of large-scale targeted metabolomics data

Data processing and quality control are essential for complex targeted mass spectrometry (MS) assays in large-scale metabolomics studies. However, existing software solutions have significant gaps in robustness and scalability. We report MRMhub, a one-stop solution for streamlined processing of large-scale targeted MS data. MRMhub consists of a novel peak integration engine with unique algorithmic design to address the scalability challenge and a comprehensive collection of post-acquisition data processing and analytical quality control tools. The ensemble facilitates rapid and consistent processing of complex chromatograms, quantification, drift and batch correction, quality assessment and control, feature filtering, and data/workflow sharing and reporting. MRMhub can process data from highly complex assays in population-scale studies within minutes, with full digital footprints warranting reproducibility and traceability. We demonstrate its performance using two large-scale lipidomics data sets. We distribute the source code and data sets freely for community development.

bioinformatics↗

bioRxiv2025

Developmental Trajectories of Addition and Subtraction in Early School-aged Children

Mastering basic arithmetic lays the foundation for lifelong mathematical achievement, yet how the neural mechanisms underlying addition and subtraction calculations develop during childhood remain unclear. This study investigated the developmental trajectories of addition and subtraction calculations in school-aged children, and explored how arithmetic-specific neural responses in the right parieto-occipital region are related to age-related improvements in behavioral performance. Here, we recorded electroencephalography (EEG) signals from 115 typically developing children divided into three age groups (7-8-, 9-10-, and 11-12-year-olds) during an arithmetic task involving addition and subtraction calculations. We analyzed the P300 component from the original waveforms and the {Delta}P300 component from the difference waveforms, which were generated by subtracting the event-related potentials (ERPs) elicited by the first operand from those elicited by the second operand to isolate arithmetic-specific neural processes. The results revealed that, in both calculations, older children showed better behavioral performance (faster reaction time and larger PI) and greater right parieto-occipital {Delta}P300 amplitudes, with a key developmental stage at 11-12 years. Furthermore, all groups of children exhibited greater right parieto-occipital P300 and {Delta}P300 amplitudes in subtraction, whereas the smaller right parieto-occipital {Delta}P300 amplitudes in addition significantly mediated the relationship between age and PI. These findings reveal distinct patterns for addition and subtraction calculations over development, highlighting the right parieto-occipital {Delta}P300 amplitude as a neural marker of arithmetic performance, particularly for addition calculation.

neuroscience↗

bioRxiv2025

Transcriptomic and protein analysis of human cortex reveals genes and pathways linked to NPTX2 disruption in Alzheimer's disease

BackgroundCognitive resilience to Alzheimers disease (AD) pathology is associated with preserved expression of NPTX2, an activity-regulated synaptic protein involved in circuit plasticity, excitation-inhibition balance, and complement-linked synapse regulation. However, the broader molecular programs coordinated with NPTX2 in resilient individuals remain unclear. MethodsWe analyzed postmortem middle temporal gyrus tissue using targeted PRM-MS proteomics in 135 individuals and bulk RNA-seq in an expanded 575-sample cohort. NPTX2-associated molecular coordination was assessed within cognitively normal low-pathology controls (CN-Lo), cognitively normal high-pathology controls (CN-Hi), mild cognitive impairment (MCI), and AD. Correlation-based approaches were applied using NPTX2 protein and NPTX2 mRNA expression as anchors to define resilience mechanisms in CN-Hi subjects. ResultsNPTX2 protein abundance was preserved across all controls regardless of age and pathology but reduced in MCI and AD. NPTX2 mRNA expression was also invariant across pathology within controls and reduced in MCI and AD but decreased markedly with age. Targeted proteomics identified NPTX2 relationships with synaptic and inhibitory-circuit proteins that were preserved across control groups, alongside CN-Hi-specific recruitment of trafficking, lysosomal, metabolic, and proteostasis-associated proteins. Transcriptome-wide correlations with NPTX2 revealed differences in gene co-expression between groups, identifying a prominent activity-dependent program including BDNF, VGF, SCG2, SST, SERTM1, DUSP4, and EGR4, that was preserved in both CN-Lo and CN-Hi subjects, while genes recruited to the NPTX2 network specifically in CN-Hi implicated immune, neuroprotective, translation, and proteostasis-related pathways. Coupling differential gene expression analysis with co-expression, we further identified five candidate resilience genes whose expression and NPTX correlation was preserved across controls, but lost in MCI and AD: SST, MAL2, TAC1, SERTM1, and RFK. Expression of genes in distinct NPTX2 co-expression classes can be freely explored in our bulk RNA-seq data and other public AD transcriptomic datasets at NeMO Analytics. ConclusionFindings suggest that cognitive resilience in the context of AD neuropathology engages a coordinated molecular state distinct from both persevered cognition without pathology and MCI/AD, which is organized around preserved and selectively remodeled NPTX2-associations. Rather than reflecting broad transcript abundance changes, resilience was characterized by maintained synaptic and inhibitory programs, and adaptive proteostasis and trafficking pathways that distinguish resilient high-pathology individuals from low-pathology controls or symptomatic AD.

bioinformatics↗

bioRxiv2025

Altered NPTX2 dynamics associated with impaired cognitive aging

Changes in synaptic integrity and neural activity homeostasis are hallmarks of brain aging and are closely tied to cognitive outcomes. Yet, defining their relationship across the continuum from normal aging to neurodegenerative disease has proven challenging. Recent research investigating the dynamic changes of neuronal pentraxin 2 (NPTX2, or Narp, neuronal activity-related pentraxin) in cerebrospinal fluid (CSF) of Alzheimers disease (AD) subjects supports its promise as a prognostic marker of disease progression, possibly as an expression of synaptic damage related to cognitive impairment. However, studies in human subjects are unable to clearly differentiate age-related and disease-related processes. Here we took advantage of a well-characterized rat model that displays substantial individual differences in hippocampal memory during aging, uncontaminated by slowly progressive, spontaneous neurodegenerative disease. Through this approach, we aimed to interrogate the underlying neural substrates that mediate aging as a uniquely permissive condition and the primary risk for neurodegeneration. We found that successful cognitive aging is associated with an elevation of NPTX2 levels above that found in young or cognitively impaired subjects. Pharmacological engagement of neural activity was sufficient to increase NPTX2 levels in all subjects, but cognitively-impaired aged subjects failed to recruit NPTX2 in response to a hippocampus-dependent memory task. Together the findings demonstrate that changes in NPTX2 are coupled to differential cognitive outcomes of aging, and that successful neurocognitive aging is associated with adaptive upregulation of NPTX2, not simply the persistence of youthful synaptic dynamics. Significance StatementAlthough aging is the most prominent risk factor for Alzheimer Disease (AD), the age-dependent processes that disrupt neurophysiological homeostasis leading to neurodegenerative disease remain poorly defined. Alterations in NPTX2, a synaptic protein biomarker for AD, may elucidate aging processes underlying pathological trajectories. We examined NPTX2 in an aging context and identified circuit specific alterations of NPTX2 that are coupled with distinct memory outcomes in aging in the absence of potential confounds of neurodegenerative disease. Greater NPTX2, associated with successful cognitive aging, may reflect coordinated molecular and circuit-level adaptations that sustain memory-relevant hippocampal activity. Development of targets and interventions that promote neuroadaptive network homeostasis, bending the trajectory of aging away from neurodegeneration, are a potentially valuable alternative to current therapeutic strategies.

neuroscience↗

bioRxiv2025

ProteinReasoner: A Multi-Modal Protein Language Model with Chain-of-Thought Reasoning for Efficient Protein Design

Reasoning has emerged as a central capability of large language models, yet how it should be formulated for scientific foundation models remains unclear because scientific knowledge is distributed across interdependent, domain-specific representations. Here we introduce modality-chain reasoning, which organizes representations into ordered computational chains, each conditioning prediction or generation of the next. Based on this principle, we develop ProteinReasoner, a multimodal generative protein foundation model that sequentially connects amino acid sequence, evolutionary constraints and three-dimensional structure within a shared autoregressive architecture. Across zero-shot structure prediction, inverse folding and fitness prediction, ProteinReasoner outperformed two multimodal protein foundation models, while controlled comparisons supported the functional contribution of the modality chain. We further extended this principle beyond pretraining: reorganizing the chain across successive structural states enabled multiple-conformation prediction, while introducing experimental feedback as an additional modality enabled an in-context learning paradigm for protein optimization without target-specific parameter updates. In particular, across thermostability and affinity-maturation evaluations, this paradigm improved over matched fine-tuned models and showed stronger mean performance than target-specific active-learning baselines. These results establish modality-chain reasoning as a unified and effective foundation-modelling strategy in protein science. More broadly, they suggest a general route towards reasoning across interdependent representations in other scientific domains.

bioinformatics↗