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Biology subjects

Zhou, H.

Publications and source records attributed to Zhou, H..

At least 73 records · Page 4Linked to original sources

Exploration of the screening and regulatory mechanisms of biomarkers related to ac4C modification in laryngeal squamous cell carcinoma patients based on single-cell analysis and machine learning

BackgroundN4-acetylcytidine (ac4C) modification plays a critical role in cancer development. Exploring ac4C modification in laryngeal squamous cell carcinoma (LSCC) may help elucidate its pathogenesis. MethodsLSCC-related datasets were obtained from GEO. After preprocessing and annotating single-cell data, malignant cells were identified by CNV scoring and further divided into subpopulations. Malignant epithelial cells (MECs) were identified and subclustered based on ac4C-related gene activity. Prognostic genes were screened using Cox regression and machine-learning approaches, followed by validation in clinical samples using qPCR. The biological and immunological relevance of these genes was further explored through immune infiltration, immunotherapy response, and mutation analyses. ResultsThe 14,465 identified MECs were classified into five subgroups (MEC1-5), among which MEC3 showed the strongest association with the ac4C gene set. Machine-learning analysis of MEC3-derived genes yielded seven prognostic markers, including BARX1, FHL2, NXPH4, PKMYT1, TNFAIP8L1, CRLF1, and CENPP. qPCR confirmed their differential expression between tumor and adjacent normal tissues. These genes were significantly associated with alterations in the tumor immune microenvironment, with high-risk patients showing increased immune infiltration and immune activity. ConclusionSeven ac4C-related prognostic genes were identified that may contribute to LSCC progression by modulating the tumor immune microenvironment, providing potential therapeutic insights.

developmental biology↗

Sex-specific Genetic Regulatory Effects in Chickens

Sexual dimorphism is a defining vertebrate feature, yet its sex-specific molecular architecture remains poorly understood. Here we established a sex-balanced, uniformly reared chicken cohort to map this landscape, integrating individual whole-genome sequencing with 7,969 bulk and 779,380 single nucleus transcriptomes across 32 tissues from 280 birds. We identified 495,098 independent expression quantitative trait loci for 20,194 genes, including 10,937 loci modulated by cell-type composition. Notably, 340 genes were regulated by 449 loci in a sex-dependent manner, significantly enrichment in endocrine tissues like adipose and the adrenal gland. Furthermore, we fine-mapped 1,219 structural variants, demonstrating their unique roles to tissue- and sex-specific expression beyond SNPs. Ultimately, we showed the utility of these regulatory effects in elucidating the molecular basis of metabolism and complex traits in both chickens and humans. This comprehensive atlas of regulatory effects provides profound insights into the genomic and molecular basis of sexual dimorphism in vertebrates.

genomics↗

p63 and p73 regulate convergent and factor-specific transcriptional programs in cutaneous squamous cell carcinoma

Aberrant transcriptional regulation is a defining feature of squamous cell carcinoma (SCC), yet how lineage transcription factors coordinate shared and factor-specific oncogenic programs remains poorly understood. Although TP63 (p63) is frequently amplified in SCC, the contribution of its paralog TP73 (p73) has remained unclear. Here we show that p73, together with p63, is upregulated in skin SCC and is required for tumorigenesis. Mechanistically, p63 and p73 form heteromeric complexes and co-occupy distal enhancer elements, establishing a shared chromatin regulatory framework. Integration of chromatin and transcriptomic profiling reveals that this common enhancer landscape supports both convergent and divergent transcriptional outputs. Both factors cooperatively sustain core proliferation but also exert regulatory biases, with p63 preferentially reinforcing epithelial lineage circuits and p73 contributing to DNA replication and stress-associated pathways. Among shared downstream targets, p63/p73 co-regulation of multiple epidermal growth factor receptor (EGFR) ligands establishes a feed-forward signaling module that amplifies mitogenic signaling. Amphiregulin emerges as a dominant functional mediator, and its depletion phenocopies key aspects of p63/p73 loss, including impaired proliferation and tumor formation. Together, these findings support a model in which shared enhancer occupancy by p63 and p73 drives cooperative and factor-specific transcriptional programs, linking chromatin regulation to signaling and tumor maintenance.

molecular biology↗

In Vivo Cardiac Prime Editing Corrects the Pathogenic Mutation and Rescues Cardiomyopathy Phenotypes in a Novel Humanized RBM20 Mouse Model

Heart disease affects millions of individuals and prime editing (PE) may enable curative therapies that address the underlying drivers of heart disease. Here we describe the establishment and optimization of an in vivo cardiac PE platform which mediates efficient editing in the heart with no detectable editing in the liver. We performed a proof-of-concept test on RNA binding motif protein 20 (RBM20), which if mutated, can cause dilated cardiomyopathy (DCM) in humans. Our dual-AAV based PE therapeutic rescued cardiomyopathy phenotypes in the heterozygous Rbm20R636Q mouse model. To further develop PE targeting human RBM20, we introduced a novel humanized mouse model carrying human RBM20 wildtype (WT) or R634Q mutant sequences and displaying RBM20 cardiomyopathy phenotypes. Our human RBM20 PE therapeutic efficiently corrected the pathogenic mutation and rescued phenotypes in the humanized RBM20 mouse model. Our findings demonstrate the potential of in vivo cardiac PE in treating heart disease, offer a valuable humanized DCM mouse model for developing various therapies, and present an optimized in vivo PE platform that can be adopted for targeting other organs and tissues.

bioengineering↗

Stereoselective methyl-swapping demonstrates target specificity of cognitive enhancer

The Integrated Stress Response (ISR) couples cellular stress sensing to translational control, playing a critical role in the homeostatic regulation of cell health. However, prolonged and unmitigated ISR activation becomes maladaptive and drives the progression of a wide range of pathologies, including cognitive decline. Pharmacological inhibition of the ISR with the small, drug-like molecule ISRIB has proven remarkably effective in reversing cognitive deficits and pathology in animal models, highlighting its potential for therapeutic intervention in humans. We engineered an allele-specific ISRIB analog (mISRIB) that selectively targets a mutant form of eIF2B, the molecular target of ISRIB, without affecting wild-type eIF2B. Notably, mISRIB treatment in mice homozygous for the eIF2B mutant allele enhances synaptic plasticity and long-term memory, confirming the on-target mechanism underlying ISRIBs cognitive benefits. Our results provide a framework for dissecting the ISRs contributions within complex cellular networks, such as those governing brain function, with precise temporal and spatial resolution.

biochemistry↗

Translational regulation of GAD1 identified by circadian and light-responsive ribosome-bound transcriptome analysis in the mouse hypothalamic suprachiasmatic nucleus

The suprachiasmatic nucleus (SCN) serves as the master circadian pacemaker, integrating regulation of clock genes in the SCN has been extensively studied, whether gene expression in the SCN is regulated at the level of mRNA translation has remained largely unexplored. Here, we report the first ribosome-profiling (Ribo-seq) dataset generated from the mouse SCN, enabling a genome-wide assessment of translational regulation in this central circadian clock. Combined time-series Ribo-seq and RNA-seq analyses identified 385 genes that exhibit rhythmic ribosome binding without corresponding oscillations in mRNA abundance, revealing widespread translational regulation in the SCN. Among these, light stimulation induced an approximately twofold increase in ribosome binding of Gad1, which encodes the major GABA-synthetic enzyme Gad67, despite only marginal changes in Gad1 mRNA levels. Importantly, immunohistochemical analyses demonstrated light-dependent accumulation of Gad67 protein selectively in light-activated SCN neurons, establishing that translational regulation of Gad1 gives rise to overt protein-level changes. In contrast, canonical clock genes were regulated predominantly at the transcriptional level and showed little evidence of translational modulation. Our data allow a systematic comparison between transcriptionally and translationally regulated genes, including their relative rhythm-amplitudes and phases, and thereby revealed translational control as a distinct modulatory layer shaping time-of-day-dependent and light-dependent gene expression in the SCN.

neuroscience↗

Efficient delivery of gene editors using intein-engineered virus-like particles

Virus-like particles (VLPs) represent a promising next-generation drug delivery platform. However, conventional VLPs rely on multiple viral components for effective cargo encapsulation and delivery, raising safety concerns. Here, we present a novel strategy to engineer immature VLPs using a self-cleaving intein system. We employed viral Gag proteins as sorting domains, linking cargo proteins to Gag through inteins, thereby eliminating the need for the conventional protease cleavage typically mediated by the gag-pol protein. During VLP biogenesis, intein-mediated cleavage released cargo proteins into the lumen, enabling efficient intracellular delivery when VLP surfaces are pseudotyped with VSV-G. Optimal candidates for delivering Cre recombinase and gene editing tools (Cas9, Cas12a and base editors) were identified by screening various Gag proteins. Notably, these VLPs achieved robust gene editing in primary cells, including naive and activated T cells, as well as hematopoietic stem and progenitor cells (HSPCs). A single local intracerebroventricular (ICV) infusion of optimized particles induced up to 60% tdTomato expression in the brain regions of reporter mice, while intravenous injection resulted in significant recombination (up to 70%) of a variety of cell types across organs. Collectively, we developed a simplified, efficient VLP platform for intracellular cargo delivery with broad therapeutic potential for gene editing and treatment of human diseases.

molecular biology↗

Adaptive evolution to thermal stress underpins climate resilience in a cosmopolitan arthropod

Adaptive evolution enables species to survive and thrive under changing environmental conditions. In the face of accelerating global climate change, thermal stress represents a major challenge to the persistence of terrestrial arthropods. Understanding the genetic mechanisms underlying thermal adaptation is therefore critical for predicting species evolutionary potential and future success. Here, we combine experimental evolution, phenotypic assays, and multi-omics analyses to investigate the adaptive responses of the diamondback moth (Plutella xylostella), a globally destructive pest of cruciferous crops, to contrasting thermal environments. Populations evolved under hot (32{degrees}C/27{degrees}C) and cold (15{degrees}C/10{degrees}C) regimes exhibited distinct life history and fitness traits relative to those maintained under favorable conditions (26{degrees}C). The hot strain showed accelerated development, higher fecundity, and increased survival under extreme heat, while the cold strain exhibited lower supercooling and freezing points, indicating enhanced cold hardiness. Integrated transcriptomic and metabolomic analyses revealed extensive transcriptional reprogramming and convergent metabolic adjustments, notably a reduction in lipid metabolism to conserve energy under thermal stress. Crucially, non-synonymous mutations in PxSODC enhance superoxide scavenging efficiency, enabling effective oxidative stress management at lower gene expression levels. Furthermore, we identified epigenetic regulation via DNA methylation as a key mediator of this thermal tolerance. Together, these coordinated mutational, epigenetic, and metabolic insights highlight this arthropods capacity for global dispersal and likely persistence under climate change, establishing a framework for understanding equivalent effects in other species.

evolutionary biology↗

Scalable Generation of Clinical-Grade Universal Human cDC1s Enables Potent Antitumor Immunotherapy

Despite decades of intensive clinical effort, monocyte-derived dendritic cell (DC) vaccines have not yet achieved sufficient clinical benefits in cancer therapy. Conventional type 1 DCs (cDC1s), a subset of antigen-presenting cells with superior cross-presentation capacity, are well established as pivotal mediators of antitumor immunity. However, their clinical translation has been hindered by the absence of scalable and efficient generation methods. Here, we develop a three-step strategy addressing this critical unmet need: a cost-effective, feeder cell-free, GMP-compatible approach enabling large-scale generation of cDC1s from human umbilical cord blood CD34+ hematopoietic stem and progenitor cells (CD34+ HSPCs). Starting from a single umbilical cord blood unit of CD34+ HSPCs, our method yields approximately 3.5x109 pure cDC1s--sufficient for over 700 therapeutic doses. These cDC1s exhibit robust antigen cross-presentation activity and substantial production of antitumor cytokines. Critically, in various humanized tumor mouse models, they elicit significantly stronger antitumor efficacy than either moDCs or PD-1 monoclonal antibody (mAb) alone, pronouncedly remodel the tumor microenvironment (TME), and synergize with PD-1 mAbs to achieve enhanced therapeutic effects. Furthermore, our system recapitulates the complete in vivo DC differentiation trajectory: from CD34+ HSPCs through early-pre-DCs and pre-DCs to mature subsets (cDC1s, cDC2s, DC3s, mregDCs, ASDCs). This platform thus provides a powerful tool to dissect the regulatory mechanisms governing human DC subset specification. Overall, this work overcomes a long-standing bottleneck in cDC1-directed cancer immunotherapy and accelerates the clinical translation of DC subset-selective immunotherapeutic strategies.

immunology↗

Constructing the ensemble of representative structures for a protein via neural-surrogate-guided MSA recombination

AO_SCPLOWBSTRACTC_SCPLOWStructural dynamics is essential for the functional and mechanistic illustration of proteins. Previous research attempted to generate diversified protein structures by utilizing the multiple sequence alignment (MSA), but failed to provide physically relevant representative conformations without state annotations. In this work, we propose a framework named ProCEDiS to generate a compact ensemble of representative conformations for the target protein without prior knowledge. Adopting a neural surrogate to assist the exploration of MSA recombination and integrating with AlphaFold2 to model structures, this method can automatically find high-quality, mutually dissimilar conformations for the target sequence. Parallel short-timescale molecular dynamics (MD) simulations on these structure seeds enable quick while crude free energy estimation, from which physically plausible representative states could be identified. In the benchmark on four protein systems, the ProCEDiS + MD pipeline is capable of providing valuable structural dynamics information within acceptable running time.

bioinformatics↗

Bioengineered extracellular vesicles mitigate neuroinflammation by neutralizing pneumolysin and delaying disease onset in experimental pneumococcal meningitis

Bacterial meningitis is a life-threatening neurological disorder frequently caused by a Streptococcus pneumoniae (the pneumococcus) infection of the brain. Standard treatment consists of antibiotics to eliminate bacteria and dexamethasone to reduce inflammation. Despite this, mortality reaches 20% in treated individuals, and half of the survivors suffer long-term neurological sequelae. This is largely due to the poor capacity of antibiotics to reach the brain and the lack of antimicrobial treatment capable of neutralizing the pneumococcal toxin pneumolysin (Ply). To address these limitations, we isolated extracellular vesicles (EVs) derived from human HEK293T cells and evaluated their therapeutic potential in pneumococcal meningitis. Alongside wild-type EVs (WT.EVs), we bioengineered EVs to express RVG peptides (RVG.EV) for targeting neuronal acetylcholine receptors, signal incompetent IL-6 signal transducer (IL-6ST) decoy receptors (IL-6.EV) to block the pro-inflammatory signalling of IL-6, or EVs expressing both RVG peptides and IL-6ST (DB.EV). In vitro, all EVs reduced pneumococcal adhesion to neurons and mitigated cytotoxicity by binding and sequestering Ply. In a bacteremia-derived pneumococcal meningitis model, EV treatment significantly increased the survival of the mice without affecting bacterial load in the brain or the periphery. Among all groups, RVG.EV treatment was most effective in reducing pro-inflammatory cytokine release in the periphery and brain. These findings highlight the therapeutic potential of bioengineered EVs, particularly RVG peptides expressing EVs, as an adjunctive treatment for pneumococcal meningitis thanks to their (i) sequestration and neutralization of Ply, (ii) increased blood-brain barrier crossing, and (iii) dampening of inflammation.

neuroscience↗

A Unified and Interpretable Framework for Evaluating Fluorescence Trace Quality in Transcription Kinetics

Quantifying transcriptional dynamics from fluorescence traces is a powerful approach to understanding gene regulation, but such analysis critically depends on the quality of the fluorescence signal. Experimental researchers often lack an objective and computationally simple way to assess trace quality before kinetic modeling. In this study, we fill in this gap via systematically investigating two key factors (i.e., signal-to-noise ratio (SNR) and trace length) using synthetic data generated from a composite-state Hidden Markov Model (cpHMM) simulator. By analyzing thousands of simulated traces, we identified quantitative thresholds (SNR [≥] 30 dB and length [≥] 360) beyond which transcriptional dynamics can be reliably captured for kinetic inference. Building on these findings, we further discovered a unified and easily computable quality indicator based on the difference between the first two autocorrelation lags. A threshold value of approximately 0.07 effectively separates reliable from low quality traces, providing a simple yet robust criterion for data selection. Together, these results establish a practical framework for assessing fluorescence trace reliability, offering experimental researchers an interpretable and computationally efficient tool to ensure data quality prior to transcription kinetics modeling.

bioinformatics↗

Emerging Pathogens in Urinary Tract Infections: Virulence and Phenotypic Characterization of Pseudomonas aeruginosa strains

Urinary tract infections (UTIs) affect a broad patient population and inflict a substantial financial burden on the U.S. healthcare system. While uropathogenic Escherichia coli (UPEC) causes the majority of cases, other pathogens are emerging. Analysis of patient data from our healthcare system in the Gulf Coast region of Alabama revealed that Pseudomonas aeruginosa accounted for 4.0% of UTI cases, roughly double the national average, prompting further investigation into this historically understudied uropathogen. Here, we performed whole-genome sequencing and phenotypic assays on 55 urinary P. aeruginosa isolates to identify key drivers of pathogenicity in the context of UTI. Multilocus sequence typing identified 19 novel sequence types, underscoring the uncharacterized diversity of urinary P. aeruginosa isolates. Serotype O6 was most common and enriched in patients with indwelling catheters, whereas O4 was linked to diabetes mellitus. Antibiotic susceptibility testing (AST) revealed high levofloxacin resistance (30.9%), with 23.6% multidrug-resistant (MDR) and 9.1% extensively drug-resistant (XDR) isolates. Resistance patterns correlated with demographics, including significantly higher meropenem and aztreonam resistance in isolates from African American patients. Phenotypic assays of growth, motility, and biofilm formation revealed negative correlations between antibiotic resistance and virulence. Specific virulence genes predicted enhanced iron acquisition, hemolysis, and colonization potential. Notably, motility and exotoxin profiles emerged as strong predictors of P. aeruginosa ascension in a murine UTI model. Together, these findings provide new biological and clinical insight into P. aeruginosa as a uropathogen and emphasize the need for continued research. IMPORTANCEPseudomonas aeruginosa is an emerging but understudied pathogen in urinary tract infections (UTIs). Given its resilience, adaptability, and the growing threat of multidrug resistance, P. aeruginosa remains a significant challenge in clinical microbiology and infection control. Our data reveal an increased prevalence of P. aeruginosa in our local patient population. In this study, we examined both genotypic and phenotypic traits of clinical isolates and correlated them with colonization in murine models and extensive patient metadata. We identified strong associations between antibiotic resistance patterns and patient demographics. Novel sequence type strains were linked to motility phenotypes in vitro. Additionally, specific flagellar alleles were associated with enhanced murine kidney colonization and recurrent UTIs in patients. These findings provide new insight into the evolutionary adaptations that contribute to P. aeruginosa uropathogenicity and support a more nuanced understanding of its clinical significance.

microbiology↗

Fast Loading and Transformation of Large-Volume Bioimaging Data Consistently Approaching the I/O Peak Speed

High-resolution large-volume biological imaging techniques are now widely used in biological research, but inefficiencies in data processing and visualization persist due to bottlenecks in loading/saving pipelines and limitations of conventional pyramid formats. To address these issues, we have decoupled data loading process into reading from disk and in-memory decompression, while data saving has been separated into in-memory compression and writing to disk. This approach allows us to dedicate more CPU cores to decompression and compression tasks, optimizing resource allocation and maximizing disk I/O throughput. As a result, both loading and saving processes operate near the disks peak data transfer capacity. Further, we integrated a video stream-inspired format into the pyramid structure, allowing direct access to regions of interest (ROIs) without loading extraneous data into RAM, reducing memory overhead. Compared to the latest methods, our approach improves pyramid data transformation efficiency by at least 6x and dramatically accelerates downstream tasks like visualization and deep learning inference. TeaserNovel bioimaging data processing pipeline achieves near-peak I/O throughput via decoupled architecture and video-formatting.

bioinformatics↗

Revealing the antibiotic resistome in the global hadal trenches by large-scale cultivation and metagenomics

The global hadal trenches that reside more than 6000 meters below the sea level, represent one of Earths most remote ecosystems, potentially harboring a microbial reservoir for antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs). However, the global hadal environments remain the least investigated ecosystem for ARB/ARG compositions and distribution. This study took three-fold approaches to investigate the ARB/ARGs in the global hadal trench sediments, i.e., large-scale cultivation to isolate and verify ARB/ARGs from Challenger Deep sediments, metagenomic analysis of sediment samples from Challenger Deep over a six-year period, and comparative study of resistomes across six hadal trenches through metagenomic analysis. The Challenger Deep sediments had a consistent average ARG abundance of 0.02 copy/cell over a six-year period, whereas some ARG subtypes fluctuated and showed distinct temporal dynamics. Large-scale screening of ARB via microbial cultivation using 13 classes of antibiotics led to enriching distinct ARB, for which eleven genera were identified by metagenomic sequencing as major host for ARGs. The global hadal trench sediments showed a variable ARG abundance, which was significantly lower than those from environments in proximity to human activities, representing a relatively pristine reservoir. Phylogenetic analysis suggested the hadal ARGs underwent niche-specific selections and formed hadal trench-specific clusters that diverged from human-associated lineages, which can be outward transported when disturbed. The study established the hadal trench sediments, as a relatively pristine reservoir of natural ARGs, providing a crucial environmental baseline for assessing their impacts on the ecosystems and public health risks.

microbiology↗

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↗

ClustSIGNAL identifies cell types and subtypes using an adaptive smoothing approach for scalable spatial clustering

Unsupervised clustering of spatial transcriptomics data is challenging due to sparsity and complex tissue structures. We introduce ClustSIGNAL spatial clustering method that employs neighbourhood complexity-based expression smoothing. ClustSIGNAL uses entropy to measure neighbourhood compositions and generate cell-specific weights that control the effective smoothing radius within neighbourhoods. Simulation analysis demonstrates its robustness to segmentation errors and sparsity. Benchmarking across diverse SRT datasets shows its ability to perform scalable, multi-sample clustering of atlas-level data. By stabilising expression in homogeneous regions and preserving distinct expression in heterogeneous regions, ClustSIGNAL avoids over-smoothing and identifies biologically meaningful spatially-informed cell states. ClustSIGNAL Bioconductor package: bioconductor.org/packages/clustSIGNAL.

bioinformatics↗

Representation, Alignment, and Generation: A Comprehensive Survey of Foundation Models for Non-Invasive Brain Decoding

The ability to decode human thoughts, intentions, and perceptions directly from non-invasive brain recordings holds transformative potential for healthcare, communication, and human-computer interaction. However, translating the safety and scalability of methods like Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), and Magnetoencephalography (MEG) into real-world utility has traditionally been hindered by low signal-to-noise ratios, limited spatial-temporal resolution, and the difficulty to collect large-scale high-quality data from an individual user. Recently, the emergence of Foundation Models (FMs)--large-scale, pre-trained architectures--has expanded the feasible operating region of non-invasive brain decoding under controlled protocols, primarily through representation learning, neuro-semantic alignment, and strong generative priors. However, evidence for robust cross-subject and real-world deployment remains uneven, as many results are still demonstrated on limited cohorts or highly controlled settings. This survey provides a comprehensive overview of how FMs are redefining the boundaries of non-invasive brain decoding. We propose a unified methodological framework that synthesizes recent advancements into a coherent process: extracting robust, transferable representations from noisy neural signals; aligning these signals with the rich semantic spaces of pre-trained vision and language models; and leveraging powerful conditional generative priors to reconstruct high-fidelity outputs. We systematically review state-of-the-art applications across three key domains: visual reconstruction, language and speech decoding, and auditory processing. Furthermore, we critically examine the persisting challenges of computational efficiency, cross-subject generalization, and privacy governance. By mapping the current landscape and identifying key gaps, this work outlines a strategic research agenda aimed at transitioning FM-driven neurotechnology from laboratory proofs-of-concept to reliable, real-world applications.

neuroscience↗