bioRxiv Science⌕ Search

Biology subjects

Jiang, J.

Publications and source records attributed to Jiang, J..

At least 73 records · Page 4Linked to original sources

The diversity of lesion network mapping findings

Lesion network mapping (LNM) has emerged as a popular framework to map the network mechanism of brain disorders using lesions and normative brain connectome (NBC)1. It was first demonstrated in neurological symptoms and was rapidly extended to a broad range of brain disorders in the past decade. A recent study by Van den Heuvel et al. questioned the methodological foundations of LNM2. We here raise concerns regarding their errors and biases in the methodology and visualization. The conclusion of that study--LNM maps circumscribed brain changes mostly to one and the same outcome--is not supported by the data presented.

neuroscience↗

Circadian-Modulated Thresholds as a Mechanistic Basis for Sleep-Wake Transitions, Recovery, and Sleepiness

Human sleep-wake cycles arise from the interplay between homeostatic sleep pressure and circadian rhythms, yet the underlying mechanistic basis by which these drives jointly govern state transitions, recovery from sleep loss, and subjective sleepiness remains unclear. Here, we use the extended Phillips-Robinson model incorporating circadian excitation of orexin and locus coeruleus populations, yielding analytically tractable, circadian-modulated thresholds for sleep onset and awakening, and delineating the roles of circadian and homeostatic drives. We show that homeostatic feedback alone generates intrinsic sleep-wake oscillations via a saddle-node on invariant circle bifurcation, while circadian drive reshapes the stability landscape to account for immediate sleep onset and partial first-night recovery after prolonged deprivation, and enables analytic predictions of sleep timing and duration. We further define sleepiness as the distance between the homeostatic state and the active circadian sleep threshold, which robustly predicts subjective sleepiness across various deprivation, restriction, extension, and recovery protocols. Together, these results establish circadian-modulated thresholds as a unifying dynamical principle linking sleep-wake transitions, recovery dynamics, and sleepiness, with implications for circadian misalignment, shift work, and individualized sleep interventions. Author summarySleep and wakefulness arise from the interaction between circadian timing and the gradual accumulation and dissipation of sleep pressure. Although existing computational models have advanced understanding of these processes, most rely on fixed or heuristic rules for switching between sleep and wake states, limiting their ability to explain behavior under sleep deprivation, extension, or restriction. Here, we present a mechanistic description of state switching in which circadian and homeostatic influences act as separable but interacting control dimensions, providing a framework for how circadian modulation shapes state stability, recovery sleep, and subjective sleepiness, without invoking separate mechanisms for normal and perturbed conditions. By recasting sleep regulation in terms of state-dependent dynamical boundaries, our results offer a unified perspective on sleep timing, duration, recovery, and vulnerability to fatigue. This work provides a more physiologically grounded foundation for sleep-wake modeling and a principled basis for understanding circadian misalignment, shift work, jet lag, and other real-world challenges to sleep health.

neuroscience↗

On the sensitivity of qPCR diagnostics for the canola clubroot pathogen Plasmodiophora brassicae

Clubroot, caused by Plasmodiophora brassicae, is an important disease of canola and other Brassica crops. Polymerase chain reaction (PCR), particularly probe-based quantitative PCR (qPCR), is widely used for the detection of P. brassicae in soil samples. To improve consistency in clubroot detection while maintaining efficiency, diagnostic laboratories would benefit from adopting a single, highly efficient qPCR system for routine testing. In this study, we analyzed the primer and probe sequences of all published PCR and qPCR systems for P. brassicae detection. Based on these analyses, three independently developed probe-based qPCR systems were selected and their performance was evaluated using synthesized target DNA (gBlock). One probe-based qPCR system exhibiting superior sensitivity on gBlock was subsequently evaluated on P. brassicae genomic DNA. This system consistently detected DNA equivalent to four resting spores per reaction, corresponding to a soil sample containing 1,000 spores per g soil when the DNA extraction protocol was considered as a component of the qPCR system. The sensitivity of the system was further validated using DNA extracted from soil samples collected from multiple locations across Alberta, where P. brassicae was detected at levels below those associated with visible clubroot symptoms. Based on these results, we recommend this qPCR system for routine clubroot diagnostics in laboratories across Canada.

microbiology↗

A brain dynamic model based on graph neural network reflect the inter-region interaction of cortical areas

A central objective in neuroscience is to elucidate how the brain generates complex dynamic activity through the interactions of brain areas. In this study, we utilized Interaction Network, a graph neural network model, to develop a computational framework for predicting whole-brain cortical blood oxygenation level dependent (BOLD) signals. We derived an Inter-Regional Interaction (IRI) metric to quantify information exchange among brain areas probing the underlying dynamical mechanisms. In addition, the total IRI emitted from each brain region was calculated and defined as the IRI sent by region (RS-IRI). Our model predicted the following 10 time points BOLD activity from initial BOLD signals, and achieved a mean absolute error of 0.04. The predicted functional connectivity (FC) achieves a correlation coefficient of 0.97 compared to the empirical FC. The fluctuation amplitude of the IRI increases with the length of the connection and the largest RS-IRI oscillation amplitude is observed in visual areas. The RS-IRI demonstrates a hierarchical organization, characterized by more concentrated distributions in association regions and larger fluctuation amplitudes in unimodal regions. Applying our approach to Alzheimers disease (AD), we demonstrate that the frequency-specific amplitudes of IRI oscillations discriminate AD patients from healthy controls and correlate with Mini-Mental State Examination scores. Together, this work presents a deep learning-based framework for modeling brain dynamics as well a quantitative index of inter-areal interactions, and offers a new perspective for disease characterization. Author SummaryThe human brain comprises distinct regions that interact through complex fiber tracts, forming the functional dynamics for diverse cognitive processes. We employed fMRI to assess functional activity and DTI to reconstruct fiber tract connectivity. To elucidate how brain function emerges from these inter-regional interactions, we developed a novel computational framework based on Graph Neural Network (GNN) to model the brains interactive dynamics for its capacity to uncover hidden and intricate patterns within data. From this model, we derived a quantitative metric termed Inter-Regional Interaction (IRI), which characterized the fine-grained, dynamic fluctuations in communication between brain areas. Our results suggest that this GNN-based model can accurately simulate brain functional activity and provide a quantitative description of neural interaction patterns. Applying this model to a cohort of Alzheimers disease patients, we demonstrated that the IRI metric not only effectively distinguished patients from healthy controls but also significantly correlated with clinical cognitive performance (MMSE scores). This approach advances our understanding of the fundamental principles of brain function and offers a promising tool for identifying the underlying mechanisms of neurological disorders.

neuroscience↗

Evolutionary genomics of local adaptation, climate vulnerability, and linarin metabolism in Opisthopappus longilobus

Global climate change and human activities are posing substantial threats to biodiversity. The genus Opisthopappus (O. taihangensis and O. longilobus), endemic to Chinas Taihang Mountains, possesses great ecological, ornamental and medicinal value. However, it is confronted with the pressures of habitat fragmentation and climate change. Here, we present the first haplotype-resolved, chromosome-scale genome assembly of O. longilobus ([~]2.95 Gb) and re-sequence 115 individuals across its range. Comparative analyses show Opisthopappus is sister to Artemisia-Chrysanthemum, with Opisthopappus and Chrysanthemum diverging at 5.15-5.18 million years ago. A profound genetic divergence is evident between O. taihangensis and O. longilobus, resulting in two distinct lineages within each species, driven by geography and climate. Our analyses indicate restricted gene flow, low diversity, and recurrent demographic bottlenecks collectively contribute to their endangerment. By integrating population genomics and environmental variables, we identified 4,437 core adaptive genes linked to water deprivation, and metabolism. Genomic offset predicts higher maladaptation risk in populations under drastic climate change. Furthermore, diverged promoters of two O-methyltransferase genes, OMT250 and OMT310, likely underlie the differential acacetin/linarin accumulation between C. morifolium and O. longilobus. These findings advance understanding of Opisthopappus evolution and climate vulnerability, offering a model for genomics-guided biodiversity conservation.

plant biology↗

NORAD orchestrates KLC1-mediated SFPQ transport via liquid-liquid phase separation

Neuronal function requires precise long-distance axonal transport mediated by molecular motors and RNA-binding proteins like SFPQ, though regulatory mechanisms remain poorly defined. We identify long non-coding RNA NORAD as a master regulator of this process through liquid-liquid phase separation (LLPS). While SFPQ and kinesin-1 mediate cargo delivery, the specific RNA coordinating their interaction was unknown. We demonstrate NORAD directly binds kinesin light chain 1 (KLC1) and promotes SFPQ condensation into dynamic LLPS droplets, enabling efficient transport. CRISPR-assisted mapping and functional assays show NORAD depletion disrupts granule dynamics, impairs neuroprotective mRNA localization, and induces axonal degeneration. In vitro reconstitution confirms NORAD-KLC1 synergy enhances SFPQ phase separation, and neuron-specific knockout mice exhibit motor deficits with reduced neuronal density. These findings establish the first evidence of lncRNA NORAD-mediated LLPS in axonal transport, revealing a new paradigm for RNA-guided neuronal maintenance.

molecular biology↗

Genetic Drivers of Sensitivity or Resistance to RAS(ON) Multi-Selective Inhibitors in NRAS-Mutated Melanoma

Most patients with advanced BRAF or NRAS-driven melanoma receive front-line immunotherapy. However, if immunotherapy fails, BRAF-mutated patients have effective second-line therapies, whereas NRAS-mutated patients lack pathway-targeted options. Recently, RAS(ON) multi-selective inhibitors like RMC-7977, and the investigational agent daraxonrasib, were described that, in partnership with cyclophilin-A (CYPA), inhibit RAS[GTP] signaling. Both compounds demonstrate potent anti-proliferative activity against NRAS-mutated melanoma cell lines and robust anti-tumor activity against preclinical melanoma models. However, in preclinical models, resistance to RMC-7977 monotherapy arose through mutations in Ppia (encoding CYPA) or Map2k1 (encoding MEK1). Moreover, two clinical case studies in patients with NRAS-mutated melanoma treated with daraxonrasib demonstrated clear anti-tumor activity in one patient, but progressive disease in another with co-occurring NRAS and MAP2K1 mutations at baseline. These findings support the potential for daraxonrasib in treatment of patients with NRAS-mutated melanoma, and reveal candidate mechanisms of monotherapy resistance, underscoring the need for combination therapies to improve outcomes. SIGNIFICANCEThere are no pathway-targeted therapies for patients with NRAS-mutated melanoma. Here we demonstrate that direct pharmacological inhibition of RAS[GTP] with RMC-7977 or daraxonrasib (RMC-6236) has profound inhibitory effects in preclinical models of NRAS-mutated melanoma. Furthermore, we identify mechanisms of resistance to RMC-7977 through mutational inactivation of CYPA or mutational activation of MEK1.

cancer biology↗

RAF isoform selectivity of MEK inhibitors and rational design of a covalent ARAF-MEK inhibitor

Aberrant activation of the RAS/RAF/MEK/ERK pathway is a frequent cause of cancer. Allosteric MEK inhibitors block this pathway by binding RAF-MEK complexes to prevent activation of MEK by RAF. However, how MEK inhibitor potency varies across the three RAF isoforms remains poorly understood. We profiled seven allosteric MEK inhibitors and observed a striking hierarchy of sensitivity: all most potently inhibited CRAF-driven MEK activation while relatively sparing ARAF-driven activation. We identified point mutations in ARAF and CRAF proximate to the MEK inhibitor binding site that markedly altered inhibitor sensitivity. Using a rational design approach, we developed a more potent inhibitor of ARAF-driven MEK signaling, TWG-07-148. Our cryo-EM structure shows how this acrylamide-containing analog of MEK inhibitor trametinib covalently targets Cys514, a residue unique to ARAF. Our studies highlight the importance of the activating RAF isoform as a determinant of MEK inhibitor sensitivity and provide proof-of-concept for development of MEK inhibitors that more effectively block ARAF-driven MEK signaling via covalent targeting of Cys514.

biochemistry↗

Overcoming EGFR resistance by monovalent and bident inhibitors targeting Cys775

Covalent targeting of EGFR cysteine 797 by osimertinib is one of the most successful breakthroughs in targeted therapy, fundamentally transforming the treatment landscape for non-small cell lung cancer (NSCLC) patients. However, resistance driven by mutation of C797 remains a major clinical challenge. Developing novel covalent strategies beyond C797 targeting presents a compelling opportunity for next-generation EGFR inhibitors. We first demonstrated that cysteine 775, located deep within the ATP-binding pocket, is accessible by a rationally designed covalent molecule ZNL-3, which as the first-in-class covalent cysteine 775 inhibitor exhibited strong efficacy in osimertinib-resistant mouse models. To further enhance resilience to resistance-causing mutations, we developed a dual-warhead, bident compound--YNW-1--which covalently targets both cysteine 775 and 797 simultaneously. YNW-1 is the first intramolecular lock to exhibit balanced reactive efficiency on both cysteines, rendering single-site mutations ineffective to confer resistance. The discovery of ZNL-3 and YNW-1 represents significant advancements in EGFR-targeted drug development, and further optimization toward clinical translation is a worthwhile strategy. SIGNIFICANCE: This study establishes the therapeutic potential of an EGFR covalent inhibitor through unprecedented targeting of cysteine 775 and provides the first demonstration that dual cysteine engagement offers superior efficacy over conventional covalent inhibitors by delaying resistance.

cancer biology↗

Integrated proteogenomics uncovers ancestry-specific and shared molecular drivers in localized prostate cancer

Our integrative proteogenomics (genome, proteome and phosphoproteome) of localized prostate cancer (PCa) in an equal-access Military Health System patient cohort (57 Black and 55 White) revealed significant ancestry-associated differences. Somatic and germline regulatory differences converged on androgen, metabolic, PI3K/AKT/mTOR, and DNA damage response (DDR) pathways, with ancestry-specific immune- and stromal-associated signals. Black patients displayed greater genomic variability, enhanced androgen response, fatty-acid metabolism, and epithelial-mesenchymal transition, while White patients showed prevalent DDRG alterations, activated oncogenic signaling (MYC, E2F, mTORC1), and cell cycle regulation. Phosphoproteomics highlighted distinct kinase activities and candidate druggable dependencies. Multiomics integration revealed three exploratory tumor subtypes whose distinct biological programs were reproducibly validated. Ancestry-associated eQTLs supported inherited regulation of the proteome independent of CNAs. Ancestry-specific CNA and protein panels improved progression risk prediction beyond PSA and pathology models. These findings provide a framework for ancestry-informed prognostic models and generate testable hypotheses for precision therapies to reduce outcome disparities.

cancer biology↗

Associations between volumes of grey matter regions and white matter hyperintensities with cognitive empathy in oldest-old adults

OBJECTIVESTo study the differential associations of regional volumes of grey matter (GM) and white matter hyperintensities (WMH) with behavioural and informant-reported measures of cognitive empathy (CE), especially in brain regions understood to have functional connectivity involvement with CE abilities. METHODSCommunity-dwelling participants from the Sydney Memory and Ageing Study (Sydney MAS) underwent whole brain MRI. Regional cortical GM volumes were derived using FreeSurfer v7.1 for, and WMH volumes were derived using UBO Detector. On follow-up four years later, CE was indexed via the Reading the Mind in the Eyes Test (RMET; a behavioural task) and Interpersonal Reactivity Index - Perspective Taking subscale (IRI-PT; an informant-reported measure). RESULTSIn 129 participants (mean age 87.01 years), Structural equation modelling (SEM) showed associations between insula GM volumes and RMET scores (p=0.001), and between supramarginal gyrus (SMG) GM volumes and IRI-PT scores (p=0.016). Associations remained significant after inclusion of covariates accounting for age, global cognition, affective symptoms, and social networks. DISCUSSIONCE abilities assessed with RMET (a behavioural task) were positively associated with insula GM volumes. CE abilities on the IRI-PT (an informant-reported measure) were positively associated with SMG GM volumes. No associations between WMH volumes and CE measures were found. These findings may inform clinical workflows that use structural MRI investigations looking at social cognitive disturbances in older adults and provide further evidence of the divergent nature of behavioural and self-report measures of CE.

neuroscience↗

Elevated Temperatures Representing Heatwave Conditions Shift Active Nitrifying Communities and Their Viruses in Tidal Flats and Agricultural Soils

Global heatwave intensification associated with climate change will impact the nitrogen cycle, yet its effect on specific nitrifier groups or their interactions with viruses remains unclear. Using 13CO2-DNA-based stable isotope probing (SIP) coupled with metagenomics, we show that elevated temperatures associated with heatwave conditions restructure active nitrifying communities and their viruses in Yangtze River estuary tidal flats and adjacent agricultural soils. In tidal flats, high temperatures shifted active ammonia-oxidizing archaea and bacteria (AOA and AOB), and nitrite-oxidizing bacteria (NOB) from marine to terrestrial ecotypes. In contrast, heatwave conditions stimulated terrestrial ecotypes of AOA but suppressed AOB in agricultural soils. 13C-labeled nitrifier-infecting viruses also showed temperature-driven shifts in activity, lifestyle, and auxiliary metabolic genes in concert with hosts. Notably, AOA viruses carried the plastocyanin gene, potentially augmenting host metabolism. These findings demonstrate heatwaves drive complex shifts in nitrifier communities and their interactions with viruses, impacting global nutrient cycling under climate extremes.

microbiology↗

Deep Learning of Brain-Behavior Dimensions Identifies Transdiagnostic Biotypes in Youth with ADHD and Anxiety Disorders

Attention-deficit/hyperactivity disorder and anxiety disorders are highly prevalent in youth and are characterized by substantial heterogeneity and frequent co-occurrence. This transdiagnostic complexity challenges conventional diagnostic frameworks that rely on symptom-based categories, which often obscure underlying dimensional and neurobiological mechanisms and offer limited neurobiological specificity. To address these issues, we developed a deep learning-based brain-behavior modeling framework that integrates clinically salient functional connectivity with cognitive and behavioral measures to identify interpretable dimensions and biologically grounded subtypes (biotypes). We applied our model to the Adolescent Brain Cognitive Development (ABCD) dataset comprising 3,508 children aged 9-11 years and revealed two reproducible brain-behavior dimensions that captured variation in cognitive control and emotion-attention regulation. These dimensions further yielded three distinct biotypes, each exhibiting unique symptom profiles and distinct brain development. We tested the robustness and generalizability of the dimensions and corresponding biotypes in an independent cohort of 224 age-matched participants from the Healthy Brain Network (HBN) and documented their early expression before symptom onset during adolescence. These findings highlight the utility of brain-behavior dimensions for elucidating heterogeneous psychiatric presentations and advance a biologically grounded framework for early classification and potential clinical translation in youth mental health.

neuroscience↗

Single-cell spatial mapping reveals dynamic bone marrow microarchitectural alterations and enhances clinical diagnostics in MDS

Myelodysplastic neoplasms (MDS) disrupt bone marrow hematopoiesis, yet clinical assessment relies largely on blast enumeration and qualitative morphology, which incompletely capture marrow architecture and disease state. We applied whole-slide multiplex immunofluorescence imaging with single-cell phenotyping to map bone marrow microarchitecture in MDS. Diagnostic biopsies (n=36), longitudinal treatment samples (n=29), precursor states (n=13), and normal controls (n=21) were analyzed, comprising >5 million spatially resolved cells. MDS marrow exhibited coordinated, genotype-imprinted architectural remodeling, including altered progenitor composition and spatial patterning, disrupted erythroid island organization, and displacement of hematopoietic stem and progenitor cells from perivascular niches. Interrogation of 82 cellular and spatial features yielded a composite Microarchitectural Perturbation Score (MDS-MAPS), derived from diagnostic samples and fixed prior to longitudinal analyses. In leave-one-patient-out cross-validation, MDS-MAPS discriminated remission from active disease more accurately than blast percentage (AUC 0.883 vs 0.660) and distinguished low-blast MDS from clonal cytopenia of undetermined significance (CCUS) (AUC 0.815). Mixed-effects modeling showed MAPS decreased in remission statistically independent of blast burden, with architectural normalization during remission and re-emergence at relapse. These findings define quantitative bone marrow architecture as a dynamic tissue-state biomarker that complements molecular and blast-based assessment in MDS.

pathology↗

Temporal Dynamics of Flexible Cognitive Control

In dynamic environments, flexible cognitive control adaptively adjusts processing through proactive mechanisms deployed in advance and reactive mechanisms engaged upon conflict. Previous studies have primarily focused on identifying neural networks supporting specific control components, while less is known about how multiple components interact over time to support adaptive control. To characterize these temporal dynamics, we combined EEG recordings with a face-word Stroop paradigm under changing conflict environment. A hierarchical Bayesian model was used to estimate trial-wise learning rate, predicted conflict level, and prediction error, providing computational indices of cognitive control flexibility. Neural correlation analysis revealed that these variables correlated with Theta, Alpha, and Beta oscillations in distinct brain regions. Connectivity analysis among these regions indicated enhanced cross-frequency directional interactions triggered by stimuli. Furthermore, connections reflecting updates to predicted conflict level prior to stimulus onset indexed individual strength in proactive control, while connections reflecting learning rate updates after stimulus onset indexed reactive control. These findings highlight how oscillatory dynamics coordinate multiple control components and provide new insight into how proactive and reactive control emerge as distinct modes within this interconnected neural architecture of flexible cognitive control.

neuroscience↗

Cerebellar outputs for rapid directional refinement of forelimb movement

Much of our interaction with the world relies on the ability to move our limbs with speed and precision. The cerebellum is critical for movement coordination, yet how outputs from the cerebellum continually guide the limb and whether discrete pathways differentially contribute to adjusting motor output remain unclear. Using intersectional viral approaches in mice, we identify two spatially intermingled yet anatomically distinct cerebellar populations that drive the forelimb either toward or away from the body. Neural recordings reveal cerebellar activity that correlates with and precedes these opposing directional changes in limb movement. Both cerebellar output pathways influence motor neuron and muscle activity within milliseconds, producing reliable effects on limb trajectory despite substantial underlying variability in muscle recruitment patterns. Our findings disentangle a subtype organization to cerebellar limb control, revealing a subcortical circuit basis for online directional refinement during movement execution.

neuroscience↗

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↗

IRF2 degradation tunes the innate immune response

The transcription factor IRF2 protects against skin inflammation in mice and humans but, paradoxically, promotes pyroptosis by inducing Gsdmd. How IRF2 activates some proinflammatory genes, but suppresses others is unclear. We show that skin inflammation in Irf2-deficient mice is driven by IRF1 activation of interferon-stimulated genes (ISGs). Chromatin profiling revealed that IRF1 and IRF2 occupy the same ISG regulatory sites, but as a weaker transcriptional activator, IRF2 limited ISG transcription by IRF1. Toll-like receptor signaling favored IRF1-driven transcription by inducing Irf1. In addition, IRF1 recruited the ubiquitin ligase SPOP to ISG sites, resulting in proteasomal degradation of IRF2. This shift from IRF2 to IRF1 occupancy enhanced ISG transcription. Collectively, these findings define a hierarchical transcriptional circuit in which IRF2 limits IRF1 activity under homeostatic conditions but is displaced during an immune response, allowing IRF1-dependent gene programs central to innate immunity and autoinflammation.

immunology↗