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Zhang, L.

Publications and source records attributed to Zhang, L..

At least 235 records · Page 13Linked to original sources

Echoes as Signal, Not Noise: Reverberation Sharpens Sensitivity to Temporal Structure

Sensitivity to temporal structure is fundamental to hearing, yet how natural reverberation shapes this sensitivity is unclear. Here we identify echo-facilitated temporal sensitivity (EFTS), a principle whereby the auditory system exploits echoes to selectively enhance responses to rapid temporal changes. Using transitional click trains with subtle inter-click-interval (ICI) shifts, we first show that increasing echo strength systematically enlarges the sound-level step at ICI transitions in both recorded and simulated stimuli, sharpening the physical boundary between segments of distinct temporal structure. In humans, psychophysical detection of ICI changes improves monotonically with echo level in both simulated and real free-field environments, while a late EEG change response scales with echo strength as onset responses remain comparatively stable. In awake rats, electrocorticography over auditory cortex reveals parallel echo-dependent enhancement of transition-evoked activity. Single units exhibit echo-level-dependent amplification of change-related firing and improved neurometric discriminability. Laminar local field potential and current source density analyses further show that echo-dependent divergence emerges first in granular and infragranular layers before propagating to supragranular cortex, consistent with thalamocortical drive followed by intracortical amplification. Together, these findings establish EFTS as a cross-species mechanism that reframes echoes as structured signals the brain uses to sharpen temporal integration in everyday listening.

neuroscience↗

Mapping Core Components of Membrane-less Organelles in Living Cells by Phase-APEX2 Proximity Labeling

Membrane-less organelles (MLOs), formed via liquid-liquid phase separation, are crucial for organization of biomacromolecules and cellular processes, yet their dynamic nature challenges compositional analysis. Conventional proximity labeling methods lack the specificity to overcome high background and systematic biases inherent in studying these condensates. Here we introduce Phase-APEX2, a three-input AND-gate strategy that dramatically enhances labeling specificity. By integrating a split-APEX2 system with a light-controlled H2O2 generator, we developed Phase-APEX2 platforms for two application contexts: Phase-APEX2-MS for proteomics and Phase-APEX2-seq for genomics. Our analyses revealed not only the core interactomes of the nucleolus and stress granules with high accuracy but also uncovered distinct "molecular grammars" governing their assembly and a surprising link between nucleolar dynamics and the transcriptional regulation of mitosis-related genes. This highly specific and adaptable platform opens new avenues for exploring the composition and function of diverse biomolecular condensates.

cell biology↗

Multilevel HierCC typing scheme for global genomic epidemiology and antimicrobial resistance surveillance of Campylobacter jejuni

Campylobacter jejuni is the most common bacterial cause of human gastroenteritis around the world. The disease burden and financial cost associated with C. jejuni pose significant challenges to the global public health system. A stable, scalable and standardised typing scheme is essential for epidemiological and AMR surveillance for prevention and control of C. jejuni infections. We curated and assembled a C. jejuni global whole genome sequencing (WGS) dataset of 63,012 publicly available Illumina short-read genomes. A C. jejuni global cgMLST scheme with 1161 core loci was developed using a representative subset of 2,587 genomes. HierCC clustering of the cgMLST profiles was performed for all levels and suitable HierCC levels were selected to enable epidemiological analysis. Antimicrobial resistance (AMR) prediction was performed using AbritAMR. A HierCC cluster was classified as a resistant cluster if [≥]80% of the isolates were resistant to at least one antibiotic.We selected 9 HierCC levels (HC2, HC4, HC6, HC12, HC19, HC55, HC100, HC167 and HC264) to form the multilevel HierCC scheme. The multilevel design allowed natural and genetically discrete clusters to be described consistently at both global and local scale. We showcased the utility of the scheme with identification of country and continent specific clusters at HC264 to HC19 levels and differentiation of animal host specific (specialist) from human infection (generalist) clusters at HC264 to HC55 levels. In the USA dataset from 2016 to 2022, a total of 276 resistant clusters were identified with 22 resistant clusters increasing in frequence in recent years. An increased prevalence of C. jejuni carrying 50S_L22 mutations in the USA was observed from 2016 to 2022, suggesting continuing selection pressure from macrolide use in the farm animals. We developed a novel multilevel HierCC typing scheme to standardise AMR surveillance and provide flexible typing resolution for both short- and long-term epidemiological investigations of C. jejuni at global and local levels.

microbiology↗

Enhanced Hydrogen Production Through Two-Stage Fermentation Coupling Clostridium pasteurianum and Rhodobacter sphaeroides

Biological H2 production via dark fermentation is constrained by low yields and inhibitory metabolite accumulation. Coupling dark and photo fermentation effectively overcomes these issues by enhancing substrate utilization and reducing wastewater pollution, yet scalable systems for industrial application remain rare. This study presents a 10-L two-stage fermentation system (5L dark/5L photo bioreactors) using Clostridium pasteurianum DSM 525 and Rhodobacter sphaeroides ZX-5. Dark fermentation generated 3372 mL H2 from glucose, yielding effluent with 1.29 g/L acetic and 3.11 g/L butyric acids. After centrifugation, pH adjustment, and clinoptilolite deamination ([&ge;]60% efficiency), ammonium was reduced to <100 mg/L. The pretreated effluent, supplemented with concentrated RCVBN medium, served as photo-fermentation substrate. A butyric acid feeding strategy extended the process by 120 h, boosting H2 yield by 16.4%. The coupled system produced 6480 mL H2 (80% increase), degrading 50% acetic acid and 42% butyric acid. This work demonstrates a scalable bioreactor configuration integrating efficient biohydrogen production with value-added wastewater treatment for industrial bioenergy applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/694164v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1f324a4org.highwire.dtl.DTLVardef@1eab711org.highwire.dtl.DTLVardef@98e50dorg.highwire.dtl.DTLVardef@1e5f02e_HPS_FORMAT_FIGEXP M_FIG Graphic abstract C_FIG

bioengineering↗

NicheAgent: LLM-Guided Zero-Shot Niche Identification for Spatial Transcriptomics

Spatial transcriptomics provides high-resolution maps of gene expression within intact tissue architecture, enabling the study of cellular niches, functional layers, and microenvironmental structure. Yet, accurately assigning niche or layer identities remains challenging across platforms such as 10x Visium, MERFISH, and STARmap due to batch variability, incomplete marker panels, and the lack of universally consistent domain boundaries. Existing methods including SpaGCN, BayesSpace, STAGATE, and DeepST rely heavily on supervised labels, dataset-specific fine-tuning, or deep representation learning, which often over-smooth boundaries, fail to generalize across technologies, and provide limited interpretability. We introduce NicheAgent, a zero-shot, training-free framework for spatial niche identification guided by lightweight large language models (LLMs). NicheAgent constructs interpretable nichecards for each region, encoding canonical marker genes and prototype expression centroids. Each cell is first assigned using a deterministic nearest-prototype rule based solely on gene expression and 2-hop spatial neighborhoods. Low-confidence assignments are then selectively reviewed and corrected by an LLM using only interpretable signals: marker-gene coherence, neighborhood label consistency, and an allowed label set. A final spatial smoothing step enforces local structural coherence. Applied across Visium, MERFISH, and STARmap tissues without any retraining or domain-specific supervision, NicheAgent achieves robust and biologically meaningful niche delineation, outperforming many supervised and graph-based baselines on homogeneity, completeness, and mutual information, while offering transparent reasoning traces for each corrected decision. Our results demonstrate that LLM-guided refinement, when coupled with lightweight rule-based prototypes, provides a scalable, explainable, and cross-platform alternative to heavy deep learning models for spatial transcriptomics annotation.

bioinformatics↗

Small Molecule Binding to EDS1/PAD4 in LRR-RP-Mediated Pattern-Triggered Immunity

Pattern-triggered immunity (PTI) is a key defense mechanism initiated when pathogen-associated molecular patterns are recognized by receptors, including leucine-rich repeat receptor proteins (LRR-RPs)1,2. EDS1 and PAD4 are crucial for LRR-RP-mediated PTI activation3. Small molecule (SM) phosphoribosyl-AMP/ADP, generated by TIR-domain NADase activity, promote the recruitment of helper NLRs into EDS1-PAD4 complex4,5. Here, we show that BAK1 recruitment to LRR-RP complexes is unaffected in eds1-2 or pad4-1 mutants, but is abolished in the sobir1-12 mutant, highlighting the essential role of SOBIR1 in surface immune receptor complex formation. Furthermore, SM-binding to EDS1 and PAD4 is critical for LRR-RP-mediated PTI, as SM-binding-deficient mutants fail to restore immune responses. De novo SM synthesis is required for late PTI responses, including PR1 expression and bacterial resistance, but not for early responses such as ROS and ethylene production. The TNL SADR1 functions only in late PTI responses, suggesting distinct roles of multiple TIR-domain proteins in PTI signaling.

plant biology↗

Cationic heme-mimetic gallium porphyrin kills bacteria and disrupts biofilms

The emergence of antimicrobial resistance in ESKAPE pathogens remains a clinical challenge and limits the utility of conventional antibiotics. Antimicrobial photodynamic inactivation (aPDI) using metal porphyrins is of interest, but the activity of heme-mimetic gallium porphyrins against structured biofilms has not been well defined. In this study, we evaluated a newly synthesized cationic heme-mimetic gallium porphyrin (GaCHP-2-3) activated with visible light against biofilms formed by ESKAPE representatives under static and flow conditions and on titanium surface. Light-activated GaCHP-2-3 reduced biofilm viable counts by up to 4 log10 CFU/mL. Prolonged serial passaging of planktonic bacteria in the presence of GaCHP-2-3 for 20 passages did not yield increases in MIC, indicating no detectable resistance development under these conditions. This work presents GaCHP-2-3 aPDI as a candidate approach for biofilm control and treatment of infections where antibiotic resistance limits the option.

microbiology↗

An in situ generated CAR-M with IFNg and negative dominance Sirpa isoform augments hepatocellular carcinoma immunotherapy

Background and AimsChimeric antigen receptor (CAR) T cells have shown strong efficacy in hematological cancers but limited success in solid tumors. Macrophages, with their natural ability to infiltrate tumors, modulate immunity, and phagocytose cancer cells, offer a promising alternative when engineered with CARs. While studies have demonstrated the feasibility and anti-tumor activity of CAR macrophages (CAR-M), enhancing their persistence and phagocytic capacity remains a key challenge. Methods and ResultsBuilding on first-generation CD3{zeta}-based CAR-M, we developed a novel CAR targeting human GPC3, incorporating IFN-{gamma} and the extracellular domain of SIRP (SIRPECD) to improve CAR-M persistence and block the CD47-SIRP immune checkpoint. Following delivery via lipid nanoparticle-encapsulated mRNA (LNP-mRNA), the self-secreted IFN-{gamma} sustained M1 polarization through phospho-STAT1 activation. Meanwhile, the ectopically expressed SIRPECD competitively bound to CD47 on tumor cells, thereby blocking the endogenous SIRP-SHP2 interaction in a dominant-negative manner. This design enhanced pro-inflammatory activity and anti-tumor efficacy compared to CD3{zeta}-only CAR-M. Single-cell RNA sequencing and cellular analysis showed that in situ programmed CAR-M reprogrammed the tumor microenvironment toward inflammation in a murine HCC model. Moreover, CAR-M derived from human peripheral blood mononuclear cells (PBMCs) effectively phagocytosed human HCC organoids while sparing healthy tissues, indicating clinical potential. ConclusionsCollectively, our work presents a novel CAR design that enhances phagocytic function and sustains anti-tumor activity, offering a promising strategy for human solid tumor immunotherapy.

cancer biology↗

Restoring Amyloid Clearance via Astrocytes: Z17 Is a Selective Inhibitor of CHI3L1 in Alzheimers Disease

Alzheimers disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, accumulation of hallmark protein aggregates and substantial neuroinflammation. Chitinase-3-like protein 1 (CHI3L1) which is predominantly produced by activated astrocytes in the central nervous system (CNS). Overexpression of CHI3L1 has been implicated with AD progression and worsening of symptoms. Herein, we report the identification of Z17 as a novel and selective CHI3L1 inhibitor which directly bind to CHI3L1 an equilibrium dissociation constant (KD) of 6.0 {micro}M. In human iPSC-derived astrocytes, Z17 acted as a dual-action regulator by reinstating astrocytic function and suppressing inflammation. Additionally, Z17 rescued CHI3L1-induced impairment by dose-dependently restoring A{beta} uptake and normalizing lysosomal proteolytic activity and pH. Furthermore, Z17 effectively blocked CHI3L1-driven activation of the NF-{kappa}B pathway in human astrocytes, providing a mechanistic explanation for the functional rescue. The in vitro pharmacokinetic (PK) profiling of Z17 demonstrated favorable drug-like properties for CNS development. These findings support the advancement of Z17 as a selective CHI3L1 inhibitor capable of simultaneously mitigating neuroinflammation and restoring astrocytic clearance mechanisms, making it a highly promising therapeutic candidate for Alzheimers disease. Abstract Figure O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/692801v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@5cfc38org.highwire.dtl.DTLVardef@b2e291org.highwire.dtl.DTLVardef@38d243org.highwire.dtl.DTLVardef@746330_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

Normative modeling of brain morphology reveals neuroanatomical heterogeneity and biological subtypes in major depressive disorder

BACKGROUNDMajor Depressive Disorder (MDD) is characterized by high neurobiological heterogeneity, which hinders precise diagnosis and treatment. Traditional group-level neuroimaging analyses fail to capture individual differences, while normative modeling offer a promising approach to quantify individual deviations from healthy brain structure patterns, facilitating the identification of biological subtypes and offering a data-driven framework to dissect this heterogeneity. METHODSUsing 1,190 healthy controls, we constructed normative developmental trajectories of gray matter volume (GMV) across 246 Brainnetome-defined regions using Bayesian linear regression. Deviation maps were derived for 398 MDD patients. k-means clustering was employed to identify GMV-based biotypes. Then, the clinical characteristics and anatomical differences among these subtypes were explored, along with the post-treatment clinical features and treatment responses of participants who completed the 8-week antidepressant treatment within each subtype. RESULTSPatients with MDD exhibited widespread yet individually variable GMV deviations. Clustering analysis revealed two subtypes: Subtype 1 displayed predominantly negative deviations in sensorimotor and occipital cortices, whereas Subtype 2 showed widespread positive deviations in temporal and posterior cingulate regions. Subtype 1 had higher extraversion and symptom-linked deviation patterns; in Subtype 2, deviation burden correlated with generalized anxiety. Longitudinally, Subtype 1s GMV deviation changes predicted symptom improvement, while Subtype 2s deviations correlated with baseline severity. CONCLUSIONSNormative modeling of GMV reveals marked neuroanatomical heterogeneity in MDD and identifies subtypes with distinct clinical and treatment-related characteristics, laying a foundation for precision psychiatry and individualized interventions.

neuroscience↗

Phenotypic and functional characterization of tumor-reactive T cells in malignant pleural effusions

BackgroundAdoptive cell therapy using tumor-infiltrating lymphocytes (TIL) is approved for the treatment of advanced melanoma but is limited by the need for patients to undergo surgical tumor resection. Malignant pleural effusions (MPE) may represent a more accessible source of tumor-reactive T cells. Here, we characterize the cellular composition as well as the transcriptional and functional properties of T cells from MPE compared with pulmonary metastasis and blood from a patient with melanoma. MethodsThe immune cellular composition was immunophenotyped by high-dimensional flow cytometry from synchronously collected MPE, a lung metastasis, and blood from a patient with metastatic melanoma. Sorted CD3+ T cells were profiled by single-cell RNA sequencing (scRNA-seq) and T cell receptor sequencing (scTCR-seq). TCR reactivity to autologous tumor was evaluated through in vitro activation assays with TCR-transduced Jurkat and autologous cancer cells. The killing capacity of ex vivo expanded T cells of autologous cancer cells was assessed through in vitro cytotoxicity assays. ResultsMPE had higher proportions of CD45+ immune cells and CD3+ T cells (70.5% vs 50%) compared with tumor and was enriched for effector CD8+ T cells, CCR7-CD45RA- effector memory CD4+ T cells, and quiescent CD25highCD127low regulatory CD4+ T cells. MPE T cells exhibited lower levels of co-inhibitory receptors (PD-1, LAG-3, TIGIT, TIM-3) expression relative to tumor. ScRNA-seq showed enrichment of NK-like effector CD8+ T cells in MPE. Pseudotime analysis indicated that MPE T cells were less exhausted than tumor T cells. The clonal repertoire of MPE and tumor highly overlapped, including 62.2% of predicted neoantigen-specific (NeoTCR) clonotypes. Notably, clonally-related NeoTCR T cells in MPE exhibited higher cytotoxic and stemness, and lower exhaustion signatures compared with sister clones in the tumor. Two of four selected NeoTCR clonotypes transduced in Jurkat cells demonstrated MHC class I-restricted reactivity in co-culture with autologous cancer cells. MPE T cells also readily expanded in the presence of high-dose IL-2 and demonstrated MHC class I-dependent killing of autologous cancer cells. ConclusionsMPE harbors polyclonal, tumor-reactive T cells with lower features of terminal exhaustion and higher cytotoxic potential relative to tumor T cells. MPE may therefore serve as a more accessible source for TIL therapy.

immunology↗

From features to slice: parameter-cloud modeling of spatial transcriptomics for simulation and 3D interpolatory augmentation

Computational simulation and data augmentation of spatial transcriptomics (ST) are essential for quantitative benchmarking, reproducibility, and methodological innovation. Yet current models often lack flexibility in controlling spatial and transcriptional heterogeneity, fail to capture higher-order gene dependencies, and rarely extend to three-dimensional or alignment-aware contexts. Here we present FEAST, a computational infrastructure that models ST data within a parameter cloud - a latent manifold encoding gene-level mean, variance, and sparsity. By sampling and perturbing this manifold, FEAST generates high-fidelity synthetic slices with tunable spatial and transcriptional variation, enabling systematic evaluation of clustering, deconvolution, and spatial alignment algorithms. Beyond two dimensions, FEAST performs 3D parameter-cloud interpolation guided by optimal transport and benchmark alignment, reconstructing continuous tissue architectures while preserving molecular coherence. Together, these capabilities establish FEAST as a foundational platform for standardized benchmarking, data augmentation, and 3D reconstruction in spatial transcriptomics. The source code and tutorials for FEAST are publicly available at https://github.com/maiziezhoulab/FEAST, and can be installed via Pypi at https://pypi.org/project/FEAST-py/.

bioinformatics↗

Identification of Patient Trajectories in Timeseries Clinical Transcriptomics Data

In clinical trials, it is common for only a subset of patients to respond to a given therapy. Such variability may arise from genetic differences, environmental influences, or the presence of distinct disease endotypes. Longitudinal transcriptomic profiles collected in phase 2a/2b studies provide a unique opportunity not only to investigate drug-induced biological mechanisms in humans, but also to understand why certain individuals fail to respond and to uncover previously unrecognized disease endotypes--ultimately informing the development of targeted therapeutics. However, analyzing these datasets is challenged by substantial patient heterogeneity, variability in disease severity at each visit, and the coarse temporal resolution due to sparse sampling. To address these limitations, we introduce a classification-guided autoencoder framework that jointly optimizes gene-expression reconstruction and classification objective to learn disease-relevant sample embeddings. Sample embeddings from all patients are leveraged to establish a continuous representation of disease dynamics, which can be clustered to delineate discrete disease states. We then construct a patient-sample graph in the learned latent space and apply a multi-commodity-flow based algorithm to infer patient trajectories through these states, enabling the identification of different patient trajectories. We evaluated our approach on three interventional datasets--ulcerative colitis, psoriasis, and atopic dermatitis, each containing both responders and non-responders. The method recapitulates known pathway perturbations associated with anti-IL17 and anti-IL6 therapies, identifies intermediate states reflecting disease/treatment progression, and reveals biologically meaningful patient trajectories within the patient population. Code and data are available in a public GitHub repository - https://github.com/Sanofi-Public/EndotypeDetection-Timeseries

bioinformatics↗

Network-based analysis reveals microRNA regulation of oncogenic pathways in SOX10-depleted uveal melanoma

SOX10 is essential for melanocyte development and maintenance and plays a critical role in uveal melanoma (UM) initiation and progression. While SOX10s transcriptional regulation of protein-coding genes is well characterized, its role on microRNA (miRNA) regulatory landscape in UM remains unexplored. Here, we employed network-based modeling to systematically characterize miRNA regulatory functions following SOX10 depletion in UM. First, we profiled mRNA and miRNA expression levels in SOX10 wild-type and knockdown UM cells. Then, we integrated the transcriptomic data, a UM network, and a Bayesian model to quantify miRNAs regulatory activities and identify key miRNAs. Subsequently, we employed pathway enrichment analysis combined with literature mining to elucidate the functional roles of identified miRNAs through their target genes and associated signaling pathways in UM. We identified 17 miRNAs that show significant changes in regulatory activities following SOX10 knockdown in UM cells. These miRNAs regulate the expression of genes involved in cancer hallmark pathways, including cell cycle progression, mTORC1 signaling, and fatty acid metabolism. Notably, miR-34a, miR-25, miR-186, and miR-211 have tumor-suppressive potential by targeting genes involved in UM progression and metastasis. Our results suggested that SOX10 depletion in UM can activate tumor-suppressive mechanisms through regulating miRNAs.

cancer biology↗

Neddylation Regulates Mitochondrial Dynamics and Turnover in the Adult Heart

BACKGROUNDDisruption of mitochondrial homeostasis drives cardiomyopathy and heart failure, yet upstream regulatory mechanisms remain poorly defined. Neddylation, a reversible post-translational conjugation of the ubiquitin-like protein NEDD8 by E1/E2/E3 enzymes, is essential for cardiac morphogenesis, but its role in the adult heart is unknown. METHODSWe assessed the relevance of neddylation to human cardiac disease by gene set enrichment analysis of ischemic (ICM) and non-ischemic cardiomyopathy (NICM) datasets and by immunoblotting and qPCR of ventricular tissue from patients with ICM or dilated cardiomyopathy (DCM). In adult mice, we induced cardiomyocyte-restricted deletion of the NEDD8-activating enzyme 1 (NAE1) by tamoxifen injection and monitored cardiac function at baseline and after transverse aortic constriction (TAC). Bulk RNA-seq 4 weeks post-tamoxifen was combined with bioenergetic, biochemical, and ultrastructural analyses. To assess mitochondrial dynamics, we generated NAE1/MFN2 and NAE1/DRP1 double-knockout mice. Cullin activity, mitochondrial ubiquitination, and mitophagy were measured in hearts and cultured cardiomyocytes. RESULTSNeddylation pathways were dysregulated in human ICM and NICM datasets and in failing ICM/DCM myocardium. Cardiomyocyte-specific NAE1 deletion caused systolic dysfunction and heart failure by 10 weeks post-tamoxifen, culminating in premature death and exacerbating TAC-induced pressure-overload heart failure. At 4 weeks, NAE1 loss repressed metabolic and mitochondrial bioenergetic programs, reduced ATP production, and impaired respiration. Electron microscopy revealed elongated mitochondria and accumulated mitophagic vesicles, with dysregulation of DRP1, MFN2, PINK1, LC3-II, and p62. DRP1/NAE1 co-deletion accelerated systolic failure relative to either single knockout, whereas MFN2/NAE1 co-deletion did not alter early disease progression, implicating pathogenic mitochondrial hyperfusion. Genetic NAE1 depletion in vivo and pharmacologic NAE1 inhibition in vitro impaired mitophagic vesicle formation and flux, inactivated cullin scaffold proteins, reduced mitochondrial ubiquitination, and blunted mitophagic clearance. CONCLUSIONSCardiac neddylation preserves adult heart function by coordinating mitochondrial fusion-fission dynamics and sustaining cullin-dependent ubiquitination and turnover of damaged mitochondria. These findings identify neddylation as a key regulator of mitochondrial quality control and link its disruption to human cardiomyopathy. Therapeutically, targeting the neddylation-cullin axis may limit mitochondrial dysfunction, enhance mitophagy, and improve energetic reserve in failing hearts, while neddylation signatures in patient myocardium may help guide stratification and precision therapy for cardiomyopathy. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABS* Demonstrates for the first time that the NEDD8-activating enzyme (NAE1)driven neddylation pathway is indispensable for maintaining mitochondrial quality control in the adult heart. * Links loss of neddylation to mitochondrial hyperfusion, impaired mitophagy, and rapid progression to heart failure. * Reveals that neddylation promotes cullin-RING ligase-mediated ubiquitination of damaged mitochondria, coupling mitochondrial dynamics with turnover. What Are the Clinical Implications?* Restoring or enhancing cardiac neddylation may represent a novel therapeutic avenue for cardiomyopathies characterized by mitochondrial dysfunction. * Pharmacologic agents that bolster DRP1-dependent fission or activate cullin neddylation could potentially normalize mitochondrial dynamics and improve myocardial energetics. * Conversely, systemic neddylation inhibitors now in oncology trials warrant careful cardiac monitoring, as they may precipitate mitochondrial injury and heart failure. * Circulating or tissue markers of neddylation might help stratify patients at heightened risk for mitochondrial-driven cardiac disease and guide precision therapy.

physiology↗

BrainBridge Characterizes Key Factors affecting Alzheimer's Disease and Associated Phenotypes

Single-cell RNA sequencing (scRNA-seq) has significantly advanced our understanding of Alzheimers disease and aging by revealing cellular heterogeneity and shifts in cell-type composition between diseased/old and healthy/young individuals. However, few existing studies utilize the rich information in single-cell transcriptomic atlases for robust patient-level modeling and biological feature selection. To address this gap, we present BrainBridge, a deep learning-based framework designed to integrate atlas-scale single-cell transcriptomic data with phenotypic information to model the biomolecular complexity of the human brain. BrainBridge functions both as a powerful predictor and an embedding model for representing sample-level expression profiles and covariates through comprehensive benchmarking. We also demonstrate its effectiveness in prioritizing key genes and cell types associated with disease progression, aging, and sex differences. We further validate our findings using external resources, including genome-wide and epigenome-wide association studies (GWAS and EWAS), spatial transcriptomics, and perturb-seq experiments. Finally, we deploy BrainBridge within an interactive, agent-powered interface that enables intuitive and user-friendly model interactions, promoting broader accessibility and application in biomedical research.

bioinformatics↗

Molecular basis of high-torque transmission of the Vibrio polar flagellar motor

The bacterial flagellar motors are huge protein nanomachines that drive rotation of the flagellum for bacterial motility, and have considerable diversity in structure among bacterial species, which enables the transmission of different torques to the flagellar filaments to propel bacteria and renders various swimming abilities. Relative to the bacterial peritrichous flagellar motors, the polar flagellar motors are the faster rotational machines and transmit high torque to drive bacterial high-speed motility in liquid and empower swimming in viscous environments. However, the structural basis of high-torque transmission of the polar flagellar motors is still unclear. Here we present an atomic-resolution cryo-electron microscope structure of the polar flagellar motor in complex with the hook from Vibrio alginolyticus, comprising 295 subunits from 18 proteins. Extensive inter-subunit interactions and additional phospholipids generate the higher rigidity of the rod. The LP ring utilizes more electrostatic charges on the inner surface and less physical contacts to facility the higher-speed rotation of the rod. The additional HT ring tightly binds to the outer surface of the LP ring to enhance the LP-ring stability. A previously function-unknown component FlrP enhances the interactions of 15 FliF peptides of the MS ring with the rod and stabilizes the LPHT and MS rings. The hook has two different states, L- and R-state, which provides structural flexibility of the hook to drive the unique forward-reverse-flick motility of the bacteria in the flicking process. This study provides unprecedented molecular insights into evolution and structural adaptions of the bacterial polar flagellar motors for high-torque transmission.

microbiology↗

Robust brain complexity measurement using T2* informed multivariate sample entropy from multi-echo BOLD fMRI

Sample entropy is a useful tool to analyze resting-state fMRI data and evaluate the complexity of neural activity. However, sample entropy computed from conventional BOLD signals is not highly resistant to artifacts. In contrast, T2* may be more sensitive to certain neural-related changes, and directly incorporating T2* information enables the detection of features that are often lost in BOLD-only sample entropy due to noise influences. To further improve the robustness and reliability of complexity estimation, we introduce a multivariate sample entropy approach that incorporates T2* signals derived from multi-echo BOLD signal. We applied this method to compare a cohort of 23 elder adults and 12 younger adults, and observed significant group differences in several brain regions. Notably, the proposed method yielded more pronounced group differences than conventional sample entropy computed without T2* information. Moreover, in regions with reduced neural activity due to ischemia, as well as in ventricular areas, our approach demonstrated superior performance. These results indicate that the proposed method enhances the ability to characterize the complexity of neural activity.

biophysics↗