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Liu, Q.

Publications and source records attributed to Liu, Q..

At least 91 records · Page 5Linked to original sources

Population-level genome sequencing reveals distinct Mycobacterium tuberculosis intrahost mutational trajectories in simian immunodeficiency virus co-infected and antiretroviral treated non-human primates

Whole genome sequencing of Mycobacterium tuberculosis (Mtb) populations from clinical samples has increasingly identified genes undergoing selection within and between hosts that drive differential infection and treatment outcomes. However, the intrahost Mtb mutational landscape--especially in the context of human immunodeficiency virus coinfection and antiretroviral therapy (ART)--remains less clear, as do the potential impacts of such mutations on Mtb infection dynamics. Here, we performed whole genome sequencing of Mtb populations isolated from 477 infected tissues across 20 non-human primates, including animals co-infected with simian immunodeficiency virus (SIV) with or without virological suppression by ART. We identified 116 mutations that emerged during infection, including those that are overrepresented within individual tissues and a subset that are shared across tissues during Mtb dissemination. We further find differential mutation trajectories across treatment groups, with higher mutation rate and bacterial outgrowth in SIV-infected hosts and increased prevalence of oxidative damage-associated mutations in coinfected animals on ART. Finally, we demonstrate a common pattern of mutation in Mtb lipid metabolism and polyketide synthase genes and identify a subset of NHP-derived mutations that have also independently arisen in human clinical isolates. Together, our population-based sequencing uncovers Mtb diversification during early infection, captures discrete bacterial dissemination events and infers differential immune pressures faced by Mtb in the setting of SIV-Mtb coinfection and ART suppression. ImportanceTuberculosis remains a leading cause of death worldwide, especially in people living with HIV. How HIV infection and antiretroviral therapy impacts Mycobacterium tuberculosis (Mtb) intrahost evolution remains unclear. Using whole genome sequencing from hundreds of infected tissues from non-human primates, we find that simian immunodeficiency virus co-infected hosts and those receiving antiretroviral therapy exact different immune pressures on Mtb leading to different mutation rates and types of DNA damage that are incurred. Mtb mutations were enriched in genes involved in lipid metabolisms and some of these are also seen in human TB strains. This work highlights the role of immune pressure to alter bacterial pathways that may enable Mtb adaptation to the host.

microbiology↗

Harnessing Diacylglycerol-Terminated Cationic Oligomers for Next-Generation Antibacterial Therapeutics

Cationic polymers, which mimic the structure of antimicrobial peptides (AMPs), are increasingly recognized as promising antimicrobial materials. Here, we report the synthesis and evaluation of a new class of cationic lipid-terminated oligomers (CLOs), comprised of 2C18-hydrophobic lipid tails, and short oligomeric cationic chains synthesised via Cu(0)-mediated reversible-deactivation radical polymerization (RDRP). Two 2-vinyl-4,4-dimethyl-5-oxazolone (VDM) oligomers with degrees of polymerization (DP) of 20 or 50 were synthesized using the lipid functional initiator (R)-3-((2-bromo-2-methylpropanoyl) oxy)propane-1,2-diyl dioctadecanoate (2C18-Br). Post-polymerization modification of the pendant oxazolone moieties was carried out using reactive amines, including N-Boc-ethylenediamine (BEDA) and N,N-dimethylethylenediamine (DMEN). Subsequent deprotection of the BEDA groups and quaternization of DMEN groups enabled the synthesis of six functional CLOs exhibiting distinct cationic functionalities. Antimicrobial assays against a panel of WHO bacterial and fungal priority pathogens (methicillin-resistant Staphylococcus aureus [MRSA], Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Candida albicans, and Cryptococcus neoformans) revealed that these CLOs exhibited potent and selective structure-dependent antibacterial activity, particularly against MRSA, with minimum inhibitory concentrations (MICs) in the clinically relevant range, below 4 {micro}g mL-1, comparable to antibiotics vancomycin and colistin. Among these, BEDA-functionalized CLOs demonstrated the strongest antimicrobial profile, which was significantly increased by increasing DP, as evidenced by a reduction in MIC values from 64 {micro}g mL-1 (for DP20) to [≤] 4 {micro}g mL-1 (for DP50) against A. baumannii. Biocompatibility assays against red blood cells and HEK293 cells indicated negligible toxicity, with haemolytic (HC50) and cytotoxic (CC50) values exceeding 512 {micro}g mL-1 across all CLOs. All CLOs displayed minimal activity against C. albicans (MIC [≥] 512 {micro}g mL-1). In contrast, activity against C. neoformans was influenced by both cationic functionality and DP, with DMEN-based CLOs exhibited superior antifungal activity at higher DP relative to their BEDA-based counterparts. Most CLOs displayed high selectivity (SI) toward MRSA (SI >128), while 2C18-O(BEDA)50 exhibited the broadest spectrum, showing potent antimicrobial activity and high selectivity against E. coli (MIC [≤] 4 {micro}g mL-1, SI [≥] 128), A. baumannii (MIC [≤] 4 {micro}g mL-1, SI [≥] 128), and MRSA (MIC [≤] 4 {micro}g mL-1, SI [≥] 128), along with moderate activity against P. aeruginosa (MIC = 32 {micro}g mL-1, SI > 16). Taken together, these findings elucidate the combined influence of end-group lipidation, cationic functionality, and polymer length in modulating antimicrobial activity, thereby establishing 2C18-terminated CLOs as a rationally tunable and biocompatible platform for antimicrobial material development.

microbiology↗

Hierarchical Assembly of Native Cytoplasmic Lattices Revealed by Cryo-EM

Oocytes depend on maternal factors for maturation and early embryogenesis. Cytoplasmic lattices (CPLs) are distinctive fibrillar structures in mammalian oocyte cytoplasm implicated in maternal factor storage and developmental competence, yet their molecular composition and architecture remain elusive. Here, we use cryo-electron microscopy to resolve the high-resolution structure of native mouse oocyte CPLs. We identify 14 intrinsic components of multiple copies that assemble into filaments in which PADI6-mediated self-assembly and two subtypes of subcortical maternal complexes (SCMCs) form the core scaffold. Unexpectedly, we discover that /{beta}-tubulin dimers and two autoinhibited ubiquitination modules (UHRF1-UBE2D3, SKP1-FBXW18) are internal components of CPLs. We also uncover multivalent interactions that organize adjacent CPL filaments into higher-order helical bundles. By integrating CPL structure with biochemical and proteomic data, we propose a hierarchical assembly mechanism of CPLs, from subcomplexes to filaments to supramolecular lattices. Our study offers mechanistic insights into how maternal proteins are spatially organized to ensure successful early embryonic development and provides a structural foundation for understanding female infertility related to CPL-associated gene mutations.

developmental biology↗

An atlas of transcriptional dynamics in maternal blood over the course of healthy pregnancy

Pregnancy results in profound physiological changes driven by dynamic and precisely programmed molecular processes. Maternal peripheral blood is generally the specimen of choice for studying these processes, as it is easily accessible and essential for many aspects of maintaining a healthy pregnancy. Here, we present a high-resolution atlas of the dynamic temporal changes in the transcriptome of maternal peripheral blood in healthy human pregnancy. We generated comprehensive RNA sequencing data in 802 weekly samples from 31 healthy pregnant women from the first trimester until after delivery. Using a strict discovery and replication setup, our longitudinal analysis of gene expression identified 720 genes with robust pregnancy-specific expression patterns. Using weighted graph correlation network analysis, we identified nine pregnancy-associated transcriptional modules that reveal a strong, coordinated enrichment of innate/neutrophil and antiviral immune programs, alongside changes in adaptive immunity (T cell differentiation and signaling), erythropoiesis and hemoglobin metabolism. Cell-type deconvolution revealed that these transcriptomic shifts were accompanied by increased relative neutrophil proportions and reduced naive CD4 and CD8 T cells in pregnancy. We provide a comprehensive characterization of dynamic changes across pregnancy, highlighting maternal blood as a key systemic regulator in healthy gestation. Together, our findings establish a reference atlas of healthy pregnancy, which can be used to identify dysregulated processes and mechanisms in women with pregnancy complications. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC="FIGDIR/small/715300v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@e6dd97org.highwire.dtl.DTLVardef@de217dorg.highwire.dtl.DTLVardef@168ad94org.highwire.dtl.DTLVardef@15c0dd1_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LI720 genes showed robust pregnancy specific expression patterns. C_LIO_LICo-expression analysis clustered the genes into nine modules with distinct dynamics. C_LIO_LIEnrichment in pathways involved in innate and neutrophil-mediated immunity, antiviral responses, T cell differentiation and signaling, erythropoiesis and hemoglobin metabolism. C_LIO_LICell-type deconvolution showed increases in neutrophils and decreases in naive CD4 and CD8 T cells. C_LIO_LIThe atlas of detailed longitudinal transcriptional changes provides a baseline reference for healthy pregnancy. C_LIO_LIResults for all genes and protein-protein interaction networks are made available for interactive exploration. C_LI

genomics↗

Transcriptional landscape of cardiac-specific Gpx4 deletion recapitulates human cardiomyopathy

Glutathione peroxidase 4 (GPX4) is an antioxidant enzyme important for the reduction of toxic lipid peroxide products. Previous studies revealed the importance of mouse Gpx4 in protecting cardiomyocytes from ferroptosis and, subsequently, the development of cardiovascular disease. In this paper, we investigate the transcriptional consequences of cardiac-specific deletion of Gpx4 in mice and compare this response with that observed in human cardiomyopathy. The findings in this study highlight the importance of GPX4 in maintaining both structural and functional stability of the heart and identify key pathway changes resulting from excessive ferroptosis in cardiac tissue. By overlapping common transcriptional programs perturbed in this animal model and human cardiomyopathy, our findings identify putative mechanisms through which ferroptosis contributes to the development and progression of heart disease. These studies may help guide future cardiovascular therapeutics targeting ferroptosis-dependent pathways.

genomics↗

Self-supervised learning for a gene program-centric view of cell states

Single-cell omics has extended the biological interrogation of cell state from examining the expression of individual genes to unbiased profiling of tens of thousands of genes at once. However, extracting biological insights from such high-dimensional data remains challenging. To enable downstream analyses, many computational approaches compress cell state into a single latent representation. This can obscure the structure of underlying gene programs (GP), defined as coordinated sets of biologically related genes, such as signalling pathway response modules or transcription factor targets. Here, we present Tripso, a self-supervised transformer deep learning model which learns multiple GP-specific embeddings from predefined GPs, while also enabling the discovery of novel, data-driven GPs. Tripso facilitates principled comparisons across development, disease, and experimental systems. Firstly, in a dataset of human hematopoietic cells spanning prenatal development through adulthood and aging and including newly generated data, Tripso resolved age-specific GP patterns, including elevated JAK-STAT activity in pediatric hematopoietic cells and postnatal shifts in IKZF1 GP activity during B cell differentiation. Secondly, leveraging Tripso GP embeddings and comparing in vivo to in vitro data, we hypothesized and experimentally validated that inhibition of the SEC61 translocon improved maintenance of hematopoietic stem cells in culture. Finally, Tripsos capacity for data-driven GP discovery revealed a previously uncharacterized tissue-resident memory T cell GP with increased activity in atopic dermatitis. Its spatial co-localization with sebaceous gland-associated immune niches was demonstrated in spatial transcriptomic and proteomic data. Thus, by moving beyond single embeddings of cellular states, Tripso enables interpretable and actionable discoveries, demonstrating how GP-centric modelling can generate hypotheses with substantial biomedical relevance. By anchoring cellular representations in meaningful GPs, Tripso establishes a principled and biologically grounded framework towards the development of interpretable virtual cell models.

bioinformatics↗

Coronavirus envelope protein drives iron sensing disorder by hijacking the TAp73-FDXR axis

Iron overload is increasingly recognized as a critical contributor to coronavirus pathogenesis1, yet the underlying induction mechanisms remain unclear. Here, we uncover a fundamental pathway by which coronavirus drives IRP1 RNA-binding activity to induce iron accumulation2 via targeting the TAp73-FDXR axis. Specifically, coronavirus infection represses transcription of FDXR (encoding the key rate-limiting enzyme in host iron-sulfur cluster synthesis3), thereby impairing host iron-sulfur cluster generation to trigger the functional conversion of the cytosolic aconitase 1 (ACO1) into iron-regulatory protein 1 (IRP1)4, ultimately leading to the hosts persistently false perception of iron deficiency. We identify TAp73 as the primary transcription factor governing FDXR expression, and demonstrate that the coronavirus envelope protein (CoV-E) orchestrates TAp73 nuclear export. Subsequently, CoV-E binds TAp73 through a critical valine residue within its C-terminal PBM domain, inducing the K48-linked ubiquitination and proteasomal degradation of TAp73. Furthermore, we developed a CoV-E-targeting molecule, DPTP-FC, which blocks CoV-E-TAp73 interaction via forming steric hindrance and effectively alleviates iron accumulation and tissue damage caused by PEDV, PDCoV, and SARS-CoV-2 infection. Our study reveals the central role of the TAp73-FDXR axis in CoV-induced iron accumulation, highlighting CoV-E as an attractive antiviral target and DPTP-FC as a promising therapeutic candidate.

microbiology↗

Generalizable Cysteine Quantification in Pea Cultivars from SERS Spectra Using AI

Rapid quantification of sulfur-containing amino acids, particularly cysteine, in legumes is critical for assessing nutritional quality, supporting breeding program screening, and ensuring consistency in quality control processes. However, conventional methods, such as high-performance liquid chromatography (HPLC), are time-consuming and resource-intensive for high-throughput applications. This study evaluated artificial intelligence models for predicting cysteine concentration from surface-enhanced Raman spectroscopy (SERS) spectra of pea extracts. SERS spectra were acquired from 20 cultivars grown at three geographically distinct locations, with HPLC-measured cysteine concentrations as a ground truth reference. Linear regression, partial least squares regression, support vector regression, random forest regression, and a one-dimensional convolutional neural network (1D-CNN) were compared using within-cultivar splits and leave-one-cultivar-out (LOCO) evaluation. The 1D-CNN achieved RMSE 0.008 g/100 g within cultivars and maintained performance under LOCO, while other models showed limited generalization. Shapley Additive Explanations highlighted informative bands in the 630-760 cm-1 range, and noise modeling optimized scan-count selection.

bioengineering↗

Paternal behavior is controlled by preoptic Trpc5 neurons

Male parenting behavior is highly conserved and activated only after offspring are born. Here we show that the behavioral switch from infanticide in virgin male mice to caregiving in wild-type sires is associated with enhanced expression and activation of Transient receptor potential channel 5 (Trpc5) in estrogen receptor (Esr1)-expressing neurons in the hypothalamic medial preoptic area (MPOA). While selective deletion of Trpc5 from Esr1MPOA neurons diminishes paternal behavior in sires, overexpression of Trpc5 in these neurons converts the otherwise infanticidal virgin males to exhibit care to pups. Mechanistically, Trpc5-dependent changes in neuronal excitability underlie fatherhood-associated Esr1MPOA neuron plasticity. Notably, Trpc5 overexpression also enhances escape behavior and elicits exploratory diving behavior, suggesting that these neurons control a broader adaptive parenting response in males. These findings establish a Trpc5-dependent MPOA neural signal as a critical regulator of paternal behavior.

neuroscience↗

The enhanced multi-tissue atlas of regulatory effects in cattle

Cattle are integral to global food security, yet the molecular architecture of their complex traits remains poorly understood. Here, we present the Cattle Genotype-Tissue Expression (CattleGTEx) Phase 1 resource (https://cattlegtex.farmgtex.org/), a substantial expansion of the pilot study. By leveraging 12,422 RNA-seq profiles across 43 tissues and 82 breeds, we characterized 433,972 primary and 161,428 non-primary regulatory effects spanning seven molecular phenotypes. This high-resolution atlas resolves 75% of GWAS signals for 44 complex traits, significantly addressing the "missing regulation" in livestock. We propose a genetic regulatory model demonstrating how variants across multiple biological layers interact with specific biological contexts to shape phenotypic variation. Furthermore, CattleGTEx elucidates mechanisms underlying adaptive evolution between Bos taurus and Bos indicus, as well as artificial selection in dairy and beef breeds. Finally, by mapping evolutionary constraints on these regulatory effects, we demonstrate the translational value of this resource for prioritizing causal variants in human complex diseases. Together, Phase 1 of CattleGTEx provides a transformative framework for functional genomics, precision breeding, and comparative genetics.

genetics↗

ProteinSage: From implicit learning to explicit structural constraints for efficient protein language modeling

While protein language models typically rely on sequence-only pretraining objectives, this approach often fails to capture structural regularities and demands large datasets. To address this, we introduce ProteinSage, a pretraining framework that learns protein representations under explicit structural constraints. ProteinSage incorporates structural signals via structure-guided masking and a causal objective designed to model longrange dependencies. This structure-constrained pretraining equips ProteinSage with transferable representations using less data and computation, yet achieves competitive or superior performance across diverse structure-aware and general protein modeling benchmarks. To determine whether these gains stem from genuine structural generalization rather than task-specific fitting, we applied ProteinSage to a structure-driven protein discovery task, focusing on proteins with multi-pass transmembrane helical architectures such as distantly related microbial rhodopsins. The model successfully identified six previously unannotated microbial rhodopsin homologs. Together, our work establishes structure-constrained pretraining as an effective pathway toward data-efficient and structurally faithful protein representation learning.

bioinformatics↗

CHPT1-LCAT rewires lipolysis towards ferroptosis

Ferroptosis is driven by iron-dependent lipid peroxidation, yet how metabolic flux through central lipid pathways is selectively routed towards pro-ferroptotic lipid species remains unclear. Here, through an unbiased chemical-genetic screen targeting core metabolic enzymes, we identify diacylglycerol (DAG) as a licensing lipid intermediate whose pro-ferroptotic activity depends on its intracellular routing. Systematic manipulation of lipolytic flux reveals that ferroptotic vulnerability is not determined by bulk lipolytic output or downstream intermediates, but by the selective channelling of DAG into a distinct metabolic fate. Mechanistically, DAG is selectively routed through a previously unrecognized intracellular metabolic axis composed of choline phosphotransferase 1 (CHPT1) and lecithin-cholesterol acyltransferase (LCAT). We uncover an enzymatically active intracellular pool of LCAT (iLCAT) that cooperates with CHPT1 on Golgi-trans-Golgi network membranes to generate polyunsaturated cholesteryl esters that execute ferroptosis. Functionally, enforced DAG routing through this axis suppresses tumour growth via ferroptosis in vivo, whereas hepatocyte-specific inhibition of the CHPT1-iLCAT axis attenuates lipid peroxidation and disease progression in metabolic dysfunction-associated steatohepatitis. Together, these findings establish subcellular lipid routing, rather than lipid abundance per se, as a fundamental determinant of ferroptotic vulnerability.

cell biology↗

Single-cell transcriptomic atlas of mouse oocyte development from growth to ovulation

Oocyte growth and maturation depend on tightly coordinated programs within oocytes and their surrounding granulosa cells, yet defining the transcriptional continuum of growing oocytes has been challenging due to their large size and the limitations of current droplet-based and spatial transcriptomic platforms. Here, we optimized a high-density array-based platform called Stereo-cell for high-throughput dual-modality profiling of large mouse oocytes, allowing for both the preservation of morphology and transcript capture. By integrating unsupervised transcriptomic clustering with cell morphological features, we delineated successive temporal windows from growing oocytes to metaphase II and uncovered stage-linked shifts from early programs toward later programs. We also profiled the ovarian somatic fraction, reconstructed granulosa-cell subtype relationships, and placed ovarian cell states in tissue context using single-cell-resolution spatial data.

developmental biology↗

Functional Network Analysis of Fungal Pathogen Colletotrichum sublineola Effectors in Sorghum Anthracnose

Colletotrichum sublineola (Cs) is a hemibiotrophic fungal pathogen that causes anthracnose in Sorghum bicolor, leading to significant yield losses. To enable infection, Cs secretes effectors - proteins, small RNAs, and metabolites - that damage the plant cell wall or enter the plant cell to suppress immune responses and manipulate host metabolism. Effectors can detoxify host antimicrobials, alter nutrient processing, and evade host immunity. Paradoxically, some effectors can also trigger pattern-triggered immunity (PTI), especially in biotrophic and necrotrophic fungi. More than half of fungal protein effectors lack conserved domains and functional network annotations. In this study, we identified prospective Cs effectors, separating those with non-conserved domains and classifying those with conserved domains by protein families. Comparative genomics is employed to predict effector functions and analyze their roles. Using their predicted locations and domains, we mapped the effectors into functional subsystems related to PTI. These include interactions in the apoplast, oxidative stress response, protein modification and degradation systems, and Cysteine-rich Fungus-specific Epidermal Growth Factor-like Module (CFEM) domain proteins involved in immune regulation. Our functional network analysis advances the understanding of Cs pathogenicity and offers insights into effector infection mechanisms.

pathology↗

Towards building a World Model to simulate perturbation-induced cellular dynamics by AlphaCell

Predicting cellular responses to perturbations is crucial for therapeutic discovery, yet experimental screening is severely constrained by the combinatorial vastness of biological space. While computational simulations offer a scalable alternative, current models are limited by the incomplete latent representation----mainly relying on highly variable genes in feature representation; the poor genome-wide reconstruction fidelity; and the ungeneralizable dynamic laws across diverse contexts. Consequently, they fail to mechanistically transfer learned dynamics to unseen cellular contexts. To address these systemic flaws, we introduce AlphaCell, a generative Virtual Cell World Model that unifies genome-wise representation with continuous state transition modeling. AlphaCell achieves three synergistic innovations: (1) Latent Manifold Rectification, processing the full protein-coding transcriptome to construct a differentiable Virtual Cell Space, effectively filtering noise while preserving intrinsic cellular topology; (2) Biological Reality Reconstruction, utilizing a massive, knowledge-rich decoder to translate abstract latent states back into high-fidelity, genome-wide expression profiles; and (3) Universal State Transition, applying Optimal Transport Conditional Flow Matching to model perturbations as continuous, deterministic vector fields. By abstracting perturbation mechanisms into generalized dynamic laws, AlphaCell makes robust prediction of perturbation responses in a compositional generalization scenario and enables zero-shot prediction of cellular dynamics in entirely unseen cellular contexts, providing a foundational engine for cellular-context-generalizable perturbation prediction and perturbation-induced cellular dynamics simulation.

bioinformatics↗

A mouse-adapted Yezo virus model for antiviral testing in immunocompetent mice

Emerging tick-borne orthonairoviruses pose a growing public health threat, yet few animal models fully recapitulate human disease. Here, we report the development of a mouse-adapted Yezo virus (MA-YEZV) strain that causes lethal infection in immunocompetent mice, mirroring key clinical features of human infection, including thrombocytopenia, leukopenia, and severe liver injury. Serial passaging of YEZV in C57BL/6J mice selected for 31 non-synonymous mutations, enhancing viral replication and pathogenicity. MA-YEZV exhibited broad tissue tropism, with the highest viral loads in the liver, and induced a robust inflammatory response marked by elevated proinflammatory cytokines (e.g., IFN-{gamma}, TNF-, IL-6) and inflammasome activation. Ribavirin treatment effectively suppressed viral replication, prevented mortality, and mitigated tissue damage, whereas remdesivir showed no efficacy. This model provides a critical tool for studying YEZV pathogenesis and antiviral development, while the identified mutations offer insights into viral adaptation and virulence mechanisms. Our findings underscore the potential of MA-YEZV as a platform for evaluating countermeasures against emerging orthonairoviruses.

microbiology↗

Behavioral hierarchy without a hierarchical brain

Behavior is inherently hierarchical. The prevailing view holds that hierarchical behavior arises from the brains hierarchical organization. However, this view is primarily derived from experiments in highly controlled laboratory settings, and it remains unknown whether the same principles apply during natural, freely moving behavior. Here, we show that, under naturalistic and freely moving conditions, hierarchical mouse behavior can emerge from localized cortical dynamics alone, independent of anatomical or functional brain hierarchies. We first established a naturalistic neuroethological platform that enables quantitative characterization of hierarchical behavior alongside its corresponding neural activity. Using this platform, we find that localized cortical dynamics encode multiple levels of behavioral hierarchy. Specifically, low-dimensional neural dynamics encode high-level behavioral composites, whereas higher-dimensional neural dynamics encode low-level behavioral kinematics. Finally, by selectively perturbing high-dimensional components of cortical dynamics using optogenetics, we observe a selective reduction in low-level kinematic behaviors, providing causal evidence for this relationship. Together, these findings challenge a central assumption in systems neuroscience by demonstrating that hierarchical behavior does not require a hierarchically organized brain. Instead, hierarchy emerges from the dimensional organization of localized cortical dynamics, revealing a previously unrecognized principle by which complex behavior can arise from relatively simple neural substrates. This dynamic principle offers a unifying framework for understanding how biological systems achieve behavioral flexibility under natural conditions and suggests new directions for artificial intelligence that rely on adaptive local dynamics rather than increasingly deep architectures.

neuroscience↗

Connectome lateralization in autism across the first 14 years: heterogeneity related to developmental stage, hemisphere, and pathophysiology

Hemispheric lateralization is fundamental feature to neurodevelopment, yet its dynamic evolution in autism across childhood and underlying molecular mechanisms remain unknown. Thus, using a large-scale resting-state fMRI dataset (n = 1553, ages 1-14), we investigated developmental heterogeneity in connectome lateralization. At the group level, abnormalities in dynamic connectome lateralization strength (DCLS) progressed from focal patterns in early childhood ([≤] 6 years) to widespread distributions by late childhood ([≤] 14 years), independent of symptom severity. The late-stage patterns were validated using the ABIDE dataset (n=153). Late childhood also showed marked increases in inter-individual heterogeneity. These alterations were significantly associated with clinical phenotypes, transcriptomic profiles, and multiple neurotransmitter systems, with distinct patterns across childhood groups. Our findings reveal a developmentally dynamic trajectory of connectome lateralization in autism and highlight late childhood as a critical window for stage- and individual-specific interventions tailored to substantial individual heterogeneity.

neuroscience↗