Biology subjects

Deng, Y.

Publications and source records attributed to Deng, Y..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Whole-genome sequencing reveals variant associations with brain imaging phenotypes

Whole-genome sequencing (WGS) enables comprehensive discovery of genetic variation underlying brain imaging traits beyond the limits of SNP arrays, particularly for rare coding variants with potentially large effects. Here, we integrated WGS data from 45,755 UK Biobank participants with 4,016 derived imaging phenotypes (IDPs) spanning macrostructure (volumes, cortical thickness/area), microstructure (diffusion metrics), functional connectivity, and perfusion MRI measures. We performed variant-level association testing across 2,751,139 coding SNVs under dominant, genotypic, and recessive models. Then, we conducted gene-based rare-variant collapsing analyses across 18,762 genes using multiple qualifying-variant models to improve power for ultra-rare alleles and enhance biological interpretability. We detected 66,893 significant genotype-IDP associations at the variant level and 184 significant gene-IDP associations from collapsing analyses, including many signals driven by protein-truncating and damaging missense variants with larger effect sizes than common variants. Burden heritability analyses supported a contribution of rare coding variation to population variability in IDPs. This study provided a WGS framework for mapping rare coding variant effects on brain structure and function, advancing mechanistic insight into imaging endophenotypes relevant to neuropsychiatric and neurodegenerative disease.

genomics↗

bioRxiv2025

OmniCell: Unified Foundation Modeling of Single-Cell and Spatial Transcriptomics for Cellular and Molecular Insights

A cells transcriptional programme is not fully defined by gene expression alone, but by the tissue context in which that programme is enacted. Single-cell RNA sequencing resolves molecular identity after dissociation, whereas spatial transcriptomics preserves tissue architecture but remains constrained by assay-specific sparsity and gene coverage. Here we present OmniCell, a tissue-contextual transcriptomic foundation model pretrained on 67 million dissociated and spatially resolved profiles. By integrating gene identity, expression magnitude and tissue context, OmniCell links transcriptional programmes to the cellular neighbourhoods and anatomical contexts in which they operate. OmniCell organised transcriptomes across molecular, cellular and tissue scales. It recovered cell-type-specific programmes and tissue-aligned gene modules, preserved robust cell-state structure across batches, species and rare populations, and improved the reconstruction of spatial cell identity, anatomical domains and cell-type composition. In human liver cancer Stereo-seq data, OmniCell resolved a tumour-margin transition zone characterised by immune infiltration, acute-phase inflammation, coagulation/complement activity and metallothionein-linked metal-ion detoxification. Contextual gene-embedding similarity analysis showed that gene relationships differed across tumour core, transition-zone and paratumour/adjacent non-malignant niches, indicating that OmniCell captures tissue-dependent gene function rather than expression similarity alone. In mouse brain development and macaque cortex, spatial virtual perturbations mapped regulatory genes onto stage- and region-specific anatomical programmes. Together, these results establish tissue context as a primary axis of transcriptomic representation and provide a framework for studying how cellular programmes acquire context-dependent biological meaning in intact tissues.

bioinformatics↗

bioRxiv2025

Unraveling Candidatus Dermatophostum as a Novel Genus of Polyphosphate-Accumulating Organisms for High-Strength Wastewater Treatment

Dermatophilaceae polyphosphate-accumulating organisms (PAOs), formerly classified as Tetrasphaera PAOs, play pivotal roles in enhanced biological phosphorus removal (EBPR). However, their phylogenetic diversity, ecological preferences, and metabolic traits remain poorly characterized, and a robust marker gene for their classification is lacking. Here, we performed an extensive phylogenomic and metabolic analysis of Dermatophilaceae PAOs utilizing 46 newly recovered metagenome-assembled genomes (MAGs) from a laboratory-scale EBPR reactor treating high-strength wastewater and full-scale wastewater treatment plants. These analyses revealed a previously uncharacterized PAO genus, named Candidatus Dermatophostum, which is adapted to high-phosphorus environments. Its representative species, Ca. D. ammonifactor, was enriched in the EBPR reactor and its PAO phenotype was confirmed by polyphosphate staining and fluorescence in situ hybridization. Genomic, transcriptomic, and protein structure analyses revealed its specialized metabolic capabilities for phosphate metabolism, glycogen synthesis and dissimilatory nitrate reduction to ammonium. Moreover, Ca. Dermatophostum was found to be widely distributed across WWPTs worldwide, underscoring both its ecological importance and its potential role in mitigating nitrous oxide (N2O) emissions. Finally, we propose a ppk1-based classification framework that resolves Dermatophilaceae PAOs into six distinct clades, consistent with whole-genome phylogeny, and demonstrates that ppk1 can serve as a reliable marker gene for tracking these populations. Together, these findings expand the ecological and functional understanding of Dermatophilaceae PAOs and highlight their promise for advancing sustainable wastewater treatment and resource recovery.

microbiology↗

bioRxiv2025

Metabolic dysfunction related to specific genetic variant sites of methylmalonic acidemia

Methylmalonic acidemia (MMA) is a genetic metabolic disease, with mut (mut-MMA, caused by MMUT gene variation) and cblC (cblC-MMA, caused by MMACHC gene variation) being the predominant subtypes. MMA patients carrying c.729_730insTT and c.609G>A exhibit severe clinical manifestations and have poorer outcomes. Little information is known on the potential mechanism. The metabotypes of MMA patients carrying c.729_730insTT and c.609G>A were profiled. The potential effect of genetic variation sites on the metabolism were explored. Leveraging the gene variation spectrum and the targeted metabolomics, propionic acid, indolelactic acid, myristoleic acid, tetradecenoic acid, tridecanoic acid, and oxoadipic acid showed strong enrichment in c.729_730insTT carrying mut-MMA patients. Whereas mutation c.609G>A caused adipic acid, pimelic acid, fructose, AMP, hexanylcarnitine, and methionine significnatly altered in cblC-MMA patients. Furthermore, the metabolomic profiles were obviously different in c.729_730insTT and non-c.729_730insTT carrying mut-MMA patients after treatment. Different metabolic alterations in cblC-MMA patients carrying c.609G > A and non-c.609G > A under treatment were also observed. Our findings provide unique insights into the metabolic basis of MMA specific subtypes and its implications across different variants.

molecular biology↗

bioRxiv2025

Gasdermin E couples mitochondrial damage to pyroptotic neurodegeneration in Parkinson disease

Parkinsons disease (PD) features progressive loss of nigrostriatal dopamine neurons, but how mitochondrial damage engages programmed cell death pathways remains unresolved. Here, we identify gasdermin E (GSDME), the caspase-3-activated executor of pyroptosis, as a critical mediator of neurodegeneration in toxin-based PD models. In primary neurons and SH-SY5Y cells, the mitochondrial complex I inhibitor MPTP/MPP triggered caspase-3 activation, GSDME cleavage, and lytic membrane rupture. Genetic silencing of Gsdme or its transcriptional regulator SP1 reduced neuronal death. In vivo, Gsdme deficiency preserved substantia nigra pars compacta dopaminergic neurons, improved motor performance, and mitigated anxiety- and depression-like behaviors after MPTP administration. Loss of Gsdme also dampened microglial and astrocytic activation and lowered proinflammatory cytokines in striatum and substantia nigra. Mechanistically, cleaved GSDME localized to mitochondria, disrupted membrane potential, increased reactive oxygen species, and precipitated organelle injury, thereby coupling mitochondrial dysfunction to pyroptotic cell death. These findings identify GSDME-mediated pyroptosis as a mechanistic link between mitochondrial toxicity and neuroinflammation in PD and nominate GSDME as a therapeutic entry point to slow disease progression. SignificanceHow mitochondrial injury kills dopamine neurons in Parkinsons disease is a central unresolved question. We show that the pyroptosis executor GSDME is required for neurodegeneration and neuroinflammation in MPTP models, mechanistically linking caspase-3 activation and mitochondrial damage to lytic cell death. Targeting GSDME may provide a strategy to protect vulnerable neurons in PD. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=191 SRC="FIGDIR/small/694264v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@15364e7org.highwire.dtl.DTLVardef@57b65org.highwire.dtl.DTLVardef@1e85108org.highwire.dtl.DTLVardef@1200d34_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsGSDME drives PD-linked neuronal loss. Silencing GSDME (or its transcriptional factor Sp1) ameliorates MPTP-triggered neuronal cell death. Genetic ablation of Gsdme is protective in the MPTP-induced PD mouse model. Gsdme-/-mice retain nigrostriatal DA neurons, show improved motor and affective behaviors, and exhibit reduced microglial and astrocytic activation and cytokines release upon MPTP treatment. Cleaved GSDME accumulates on mitochondria, collapses {Delta}{Psi}m, raises ROS, and links mitochondrial toxicity to pyroptosis, thus positioning GSDME as a tractable target to slow PD progression.

neuroscience↗

bioRxiv2025

Astrocyte cell-surface proteomics identified CD44 as an OPN/SPP1 receptor regulating lipid metabolism and glial crosstalk in Alzheimer s disease

Abstract/SummaryThe development of {beta}-amyloid (A{beta}) pathology in Alzheimers disease (AD) is accompanied by profound changes in astrocytes and microglia. How these responses are orchestrated by cell surface proteins, key mediators of cell-cell communication, remain unclear. Using in situ astrocyte cell-surface proteome profiling in 5xFAD mice, we identified a set of dysregulated surface proteins induced by A{beta} pathology, including CD44. CD44 was selectively upregulated in plaque-adjacent astrocytes and interacted with osteopontin (OPN), encoded by the disease-associated microglia gene Spp1, to promote lipid accumulation, and this effect is {gamma}-secretase dependent. Astrocytic CD44 in turn regulated Spp1 expression and microglial activity. Conditional deletion of Cd44 in adult astrocytes of 5xFAD mice attenuated glial reactivity, reduced A{beta} pathology, and improved cognition. These findings define a plaque-proximal OPN-CD44 axis that controls astrocyte lipid metabolism and glial activity, positioning CD44 as a surface-accessible therapeutic target in AD.

neuroscience↗

bioRxiv2025

Robustness of Ancestral Recombination Graph Inference Tools to Phasing Errors

Ancestral Recombination Graphs (ARGs) are fundamental population genetic structures that encode the genealogical history of a sample of haplotypes along the genome. They have recently received substantial attention as they can be used to provide accurate estimates of population history, form the foundation for selection scans, provide time-labeled estimates of changes in mutation rates, and more. ARGs can be inferred using multiple different methods, but these methods all rely on computational haplotype phasing. Previous studies have shown that the accuracy of haplotype phasing can be low when done in small or medium-sized samples, which are typical for most non-model organisms. Conventional wisdom would, therefore, suggest that ARG inferences are of limited utility in most non-model organisms. To test this assumption, we benchmark the robustness of four ARG inference methods -- Relate, SINGER, Threads, and tsinfer+tsdate -- to phasing errors. Their performance with imperfect phasing was tested under simple and realistic demographic models, and evaluated in terms of estimated pairwise coalescence times, counts of inferred recombination breakpoints, and estimated branch-length-based diversity. We observe only a slight degradation in performance when using computational phasing across all four methods and all tested demographic scenarios, demonstrating a surprising robustness of ARG inference methods to phasing inaccuracies. These findings support broader application of ARG inference in settings where large reference panels are not available.

genetics↗

bioRxiv2025

A stress-dependent TRIM28-ALKBH2 feedback loop modulates chemotherapy response

Chemoresistance to DNA-damaging agents, including platinum and alkylating compounds, limits treatment efficacy in non-small cell lung cancer (NSCLC) and is frequently associated with elevated DNA repair activity. Here, we identify a stress-responsive feedback loop between the E3 ligase TRIM28 and the demethylase ALKBH2. TRIM28 binds ALKBH2 and promotes its K48-linked polyubiquitination and proteasomal degradation, whereas ALKBH2 enhances TRIM28 transcription and protein levels, forming a feedback loop. Notably, alkylation stress induces a biphasic response: acute MMS exposure enhances TRIM28-ALKBH2 association and accelerates ALKBH2 degradation, whereas prolonged exposure promotes TRIM28 degradation, leading to ALKBH2 stabilization and transcriptional upregulation. Clinically, ALKBH2 is frequently elevated in lung adenocarcinoma and is associated with worse survival, whereas TRIM28 exhibits prognostic value specifically in chemotherapy-treated patients. Functionally, MMS-cisplatin co-treatment increased DNA damage and reduced clonogenic survival by counteracting ALKBH2-dependent alkylation tolerance, linking the TRIM28-ALKBH2 loop to chemoresistance in NSCLC.

biochemistry↗

bioRxiv2025

De Novo Hepatic Pyrimidine Synthesis Regulates Systemic Energy Homeostasis

Fasting blood uridine is increased in obesity and type 2 diabetes (T2D), but the significance of hepatic uridine biosynthesis to the etiology of both remains elusive. We found that de novo pyrimidine synthesis in the liver is reduced by fasting and diet-induced obesity, while suppression of hepatic pyrimidine synthesis promotes obesity and insulin resistance. The metabolic sequalae of hepatic pyrimidine synthesis suppression, however, is not associated with altered plasma uridine concentration. Instead, it is associated with an increased hepatic glucose production and a decreased hepatic insulin clearance, two key functions of hepatocytes in regulating systemic energy homeostasis. We found that enhanced gluconeogenesis is the primary reason for increased hepatic glucose production. Moreover, uridine, which was maintained stable in the circulation by adipose tissue and the liver, preferentially shut down pyrimidine synthesis in hepatocytes but not adipocytes at blood concentrations that occur with fasting. Remarkably, uridine, at fasting levels, increases gluconeogenesis further in hepatocytes when de novo pyrimidine synthesis is suppressed, indicating a synergistical action of uridine and its biosynthesis pathway in promoting hepatic glucose production, a mechanism highly relevant to the pathophysiology of insulin resistance in obesity. Theologically, maintenance of blood uridine within the narrow range protects mammals from high-rate spontaneous tumorigenesis. Since obesity promotes an increase in blood uridine from adipocytes, suppressing uridine synthesis in hepatocytes becomes a critical response to lower spontaneous tumorigenesis. Pyrimidine synthesis suppression in hepatocytes, however, promotes gluconeogenesis and ultimately triggers obesity and T2D. These findings suggest a new paradigm for the etiology of metabolic deterioration in diet-induced obesity, in which perturbations in uridine promotes obesity and T2D.

pathology↗

bioRxiv2025

Cardiomyocyte-specific plakophilin-2 loss is sufficient to induce aging and senescence of nonmyocytes. Relevance to arrhythmogenic cardiomyopathy.

IntroductionPathogenic variants in PKP2 are the most common cause of familial arrhythmogenic right ventricular cardiomyopathy (ARVC). ObjectiveTo test whether PKP2 deficiency only in cardiomyocytes is sufficient to provoke premature aging and pro-inflammatory senescence in non-myocytes, cardiac resident cells. MethodsWe studied mice with cardiomyocyte-specific, tamoxifen-activated loss of PKP2 (PKP2cKO) using conventional and multiplex imaging, cytokine arrays, epigenetic clocks, spatial transcriptomics, expansion and structured illumination microscopy, and correlative data analysis. We examined non-myocytes and cardiomyocytes for premature aging and senescence. ResultsWe observed senescence-associated heterochromatin foci (SAHFs) and p21 staining in non-myocytes. Cytokines in media of non-myocyte cells were consistent with senescence-associated secretory phenotype (SASP). Epigenetic clocks identified premature aging. Multiplex immunohistochemistry showed non-myocyte cells in niches, intermingled with cardiomyocytes. Spatial transcriptomics showed over-representation of SASP-related transcripts, predominantly in myocyte-rich areas of the left ventricle. SAHFs, p21 staining and increased epigenetic age were not found in cardiomyocytes from PKP2cKO hearts, though we observed structural features associated to premature aging. Cross-reference analysis showed correlation between the PKP2cKO cardiac proteome and that of mice 5 or 6 times their chronological age, as well as transcriptional signatures of neurodegenerative diseases. ConclusionLoss of PKP2 expression only in adult cardiac myocytes is sufficient to induce pro-inflammatory senescence in non-myocytes, and overall premature cardiac aging. This is the first study to intersect cellular senescence and premature aging in desmosomal arrhythmogenic cardiomyopathies. We speculate that cell-agnostic molecular signatures, biomarkers, and pharmacology of senescence and of neurodegenerative diseases may be relevant to diagnose or treat PKP2-ARVC. UNSTRUCTURED ABSTRACTPathogenic variants in PKP2 are the most common cause of familial arrhythmogenic right ventricular cardiomyopathy. We used the PKP2cKO model (cardiomyocyte-specific, tamoxifen-activated PKP2 knockout) to examine whether PKP2 deficiency only in cardiomyocytes is sufficient to provoke premature aging and pro-inflammatory senescence in non-myocyte, cardiac resident cells. Through a variety of methods, we identified senescence-associated heterochromatin foci (SAHFs), p21 staining, and cytokines consistent with senescence-associated secretory phenotype (SASP) in cells and media of non-myocytes. Epigenetic clocks identified premature aging. Spatial transcriptomics showed over-representation of SASP-related transcripts, predominantly in myocyte-rich areas of the left ventricle. SAHFs, p21 staining and epigenetics suggesting advanced age were not found in cardiomyocytes, though we observed structural features associated to premature aging. Cross-reference analysis showed correlation between the PKP2cKO cardiac proteome and that of mice 5 or 6 times their chronological age, as well as transcriptional signatures of neurodegenerative diseases. HIGHLIGHTSO_LIPKP2-ARVC is a leading cause of sudden unexpected death in the young. C_LIO_LIThe molecular path from the variant of a gene to the clinical disease remains unclear. An inflammatory component has been postulated. C_LIO_LIWe show that loss of PKP2 only in myocytes is sufficient to induce a pro-inflammatory senescence in non-myocytes and premature aging of cardiac cells. C_LIO_LISimilarities to the molecular profile of neurodegenerative diseases and novel paths to therapy are discussed. C_LI

physiology↗

bioRxiv2025

BiomarkerML: A cloud-based proteomics ML workflow for biomarker discovery

BackgroundHigh-throughput affinity and mass-spectrometry-based proteomic studies of large clinical cohorts generate high-dimensional proteomic data useful for accelerated disease biomarker discovery. A powerful approach to realizing the potential of these big, complex, and non-linear data, whilst ensuring reproducible results, is to use automated machine learning (ML) and deep learning (DL) pipelines for their analysis. However, there remains a gap in comprehensive ML workflows tailored to proteomic biomarker discovery and designed for biomedical researchers who need pipelines to optimally self-configure and automatically avoid over-fitting. FindingsWe present BiomarkerML, a cloud-based workflow for automated, reproducible, and efficient ML/DL analysis of proteomic data for biomarker discovery, designed for novice-ML users and implemented in Python, R and Workflow Description Language (WDL). BiomarkerML: ingests proteomic and clinical data alongside sample labels; pre-processes data for model fitting and optionally performs dimensionality reduction and visualization; fits a catalogue of ML and DL classification and regression models; and calculates model performance metrics for model comparison. Next, the workflow applies mean SHapley Additive exPlanations (SHAP) to quantify the contribution of each protein to model predictions across all samples. Finally, proteins with high mean SHAP values, and their co-expressed protein network interactors, are identified as candidate biomarkers. Importantly, hyperparameters - configuration variables set prior to training models - are automatically fine-tuned via grid-search, and BiomarkerML employs weighted, nested cross-validation to avoid model over-fitting and data leakage. ConclusionsBiomarkerML is scalable, provides a standardized, user-friendly interface, and streamlines analyses to ensure reproducibility of results. Overall, BiomarkerML is a significant advancement, enabling novice-ML researchers to use cutting-edge ML/DL tools to identify disease biomarkers in complex proteomic data.

bioinformatics↗

bioRxiv2025

EPAS1 regulates host antibacterial defense in response to bacterial quorum sensing

Hypoxia-inducible factors (HIFs) are a family of transcription factors that function as sensors of hypoxia. However, it remains unclear whether and how HIFs modulate host immunity by responding to other ligands. Here, we describe an immune regulatory function of HIF-2 (also known as EPAS1) in response to cis-2-dodecenoic acid (BDSF), a quorum sensing (QS) signal, secreted by Burkholderia cenocepacia. Upon ligand binding, EPAS1 activation leads to the production of inflammatory cytokines and the initiation of antibacterial defense. Inoculation with diffusible BDSF or liposome-encapsulated BDSF improves survival in mice infected with B. cenocepacia or Acinetobacter baumannii by preconditioning the immune system. Our findings reveal a previously unidentified role of EPAS1 as an intracellular pattern recognition receptor (PRR) for bacterial QS signal to control host antibacterial defense.

microbiology↗

bioRxiv2025

PymolFold: A PyMOL Plugin for API-driven Structure Prediction and Quality Assessment

Deep learning has transformed protein structure prediction, yet many experimental scientists face barriers in accessing state-of-the-art (SOTA) models due to technical complexity and hardware requirements. To address this, we present PymolFold, an open-source PyMOL plugin that seamlessly integrates cutting edge API-based protein structure predictors such as ESM-3 and Boltz2 into the molecular visualization environment. PymolFold supports both graphical and command-line interfaces for flexible usage and incorporates PXMeter, an open-source Python package for quantitative evaluation of protein structure predictions against reference data. Together, these features establish a unified "predict-visualize-analyze" workflow, lowering technical entry barriers and broadening access to advanced structural modeling. PymolFold is freely available at https://github.com/jinyuansun/PymolFold.

bioinformatics↗

bioRxiv2025

Population-level migration modeling of North American birds through data integration with BirdFlow

BackgroundAccurate information on population-level movements of migratory animals is essential for understanding migration and for designing effective conservation strategies in a changing world. Yet such information remains scarce for most migratory species due to the effort and expense needed to collect data across their full distribution ranges. BirdFlow is a probabilistic modeling framework that infers population-level movements from weekly species distribution maps produced by the participatory science project eBird. However, BirdFlow models have only been tuned for a handful of species using high-resolution individual tracking data, which is not available for most migratory species. MethodsHere, we introduce a general tuning and evaluation framework for BirdFlow that enables the first large-scale integration of distributional and individual-level data to infer animal movement across continents and hundreds of migratory species, eliminating reliance on any single individual-tracking data source. By generalizing the BirdFlow model parametrization, we enable tuning and validation using multiple complementary data sources, including GPS tracks, banding recoveries, and radio telemetry data from the Motus Wildlife Tracking System. We investigate the efficacy of this approach by (1) investigating predictive performance compared to null models; (2) validating the biological plausibility of BirdFlow models by comparing movement properties such as route straightness, number of stopovers, and migration speed between model-generated routes and real movement tracks; and (3) comparing the performance of models tuned on species-specific movement data to models tuned using hyperparameters transferred from other species. ResultsOur results show that BirdFlow models produced by the new tuning framework achieve biologically realistic performance, even for prediction horizons of thousands of kilometers and several months. When species-specific data are unavailable, models can still be tuned using data from other phylogenetically adjacent species to achieve improved performance. ConclusionsBy integrating eBird Status & Trends abundance surfaces with data from banding recaptures, radio telemetry, and GPS tracking, we scale BirdFlow model to 153 North American migratory species, representing the first collection of continental-scale population-level movement and forecasting models. Species-specific tuning improves population-level movement forecasts, while taxonomically informed hyperparameter transfer supports the modeling of data-limited species. Overall, our work offers a foundation for more accurate predictions across hundreds of species for research in ecology and conservation, disease surveillance, aviation, and public outreach.

ecology↗

bioRxiv2025

Programmable Aptamer-Embedded Circular RNAs for Targeted Antigen-Presenting Cells Immunotherapy

The targeted delivery of mRNA to specific cell types in vivo remains a major unmet need in mRNA-based therapeutics. Conventional strategies rely on nanocarriers engineered with various modifications. However, these exogenous materials could cause adverse reactions, and their complex manufacturing processes often hinder clinical application. By leveraging the innate programmability of RNA sequences, we herein report a carrier-free, scalable, and programmable aptamer-embedded circular RNAs (Apt-circRNAs) design that confers targeting capability through the strategic incorporation of different aptamers at varying densities, while retaining circular RNA stability and protein production capability. Experimental results show that antigen-loaded Apt-circRNAs enable targeted delivery to antigen-presenting cells (APCs), drive endogenous antigen expression, activate antigen-specific T cells, and elicit potent immune responses that mediate clearance of both early-and late-stage tumors in mouse models. In humanized models of colorectal cancer, the combination of Apt-circRNA and PD-1 blockade produced synergistic antitumor effects and significantly reshaped the tumor microenvironment. In a first-in-human (FIH) clinical trial, Apt-circRNA vaccine encoding KRAS G12D/G12V neoantigens exhibited a favorable safety profile and induced robust immune activation, T cell mobilization, and neoantigen-specific immune responses. With this study, we have established a new paradigm in carrier-free, APC-targeted RNA vaccine design, offering a safe and effective platform for next-generation cancer immunotherapy.

bioengineering↗

bioRxiv2025

Domain-Specific Functional Network Adaptations Supporting Dual-Task Performance in Older Adults

Aging is associated with declines in both motor and cognitive functions, which are well captured by dual-task gait paradigms. However, the functional brain network mechanisms supporting motor and cognitive aspects of dual-task performance in aging remain unclear. We examined 40 older adults (50-80 years) and 20 younger adults (20-40 years) who performed a motor single-task (pedaling), a cognitive single-task (Go/NoGo), and a combined cognitive-motor dual-task during functional magnetic resonance Imaging (fMRI) using a custom-built MRI-compatible pedaling device. Behaviorally, older adults showed significant dual-task costs in motor performance, while cognitive performance was preserved. Neurally, older adults showed selective increases in connectivity within executive and motor-planning regions of cognitive networks, consistent with compensatory recruitment, whereas motor networks underwent broader reorganization, with strengthened frontoparietal control circuits but weakened cerebello-parietal and sensorimotor pathways. Multivariate analyses further revealed age-related differences in latent connectivity- behavior relationships: motor-network patterns in older adults were more dispersed, reflecting heterogeneous reorganization, whereas cognitive-network patterns were more overlapping across groups, suggesting relative preservation. These findings suggest that aging involves a domain-specific balance of resilience and vulnerability across brain networks and highlight motor-network adaption as a promising target for understanding why some older adults maintain function while others decline.

neuroscience↗

bioRxiv2025

Sleep deprivation exhibits age-dependent effect on infra-slow global brain activity

Infra-slow (< 0.1 Hz) global brain activity, quantified by the global mean BOLD (gBOLD) signal in resting-state fMRI, is elevated during sleep and closely associated with cerebrospinal fluid (CSF) dynamics, a key mechanism for the brain waste clearance implicated in neurodegenerative disorders such as Alzheimers disease (AD). However, the effect of sleep deprivation on gBOLD activity and its interaction with aging remain poorly understood. Using a rigorously controlled in-laboratory total sleep deprivation (TSD) protocol, we demonstrate that TSD significantly increases both the amplitude of the gBOLD signal and its coupling with CSF flow, suggesting a compensatory mechanism that may enhance glymphatic clearance following acute sleep loss. Notably, these TSD-induced enhancements exhibit robust age dependency, with diminished responses in individuals at midlife (40-50 yrs). The absence of this compensatory mechanism in these midlife participants may exacerbate age-related impairments in neurotoxic clearance and increase dementia susceptibility, thereby offering mechanistic insights into the nexus between sleep disruption, aging, and neurodegeneration.

neuroscience↗

bioRxiv2025

Memorability of Images Positively Influences Associative Memory Retention

Enhancing memory function is essential for daily living and cognitive health, particularly amid population aging and cognitive decline. However, current methods for memory enhancement often require specialized interventions or effortful practice. Here, we present evidence that the intrinsic memorability of images can serve as a simple, scalable, and involuntary strategy for improving associative memory. We studied its effects on associative memory in adults of distinct ages, memory retention in cognitively impaired older adults, and vocabulary learning in foreign language learners. Our results show that highly memorable images significantly enhance the recall of associated words, especially when the cue image and target word are semantically unrelated. Notably, these effects persist for at least one week and are robust across age groups and cognitive status. In a foreign language vocabulary task, pairing words with memorable images led to either improved recall accuracy or reduced learning time. These findings highlight that, in addition to being an intrinsic memory-enhancing property, image memorability also serves as a general facilitator of associative memory, via a method that is easy to adopt, requires minimal conscious effort, and can benefit the general public, particularly learners and cognitive impairment patients in educational and clinical settings.

neuroscience↗