Biology subjects

Zhang, D.

Publications and source records attributed to Zhang, D..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

A mitochondrial program encodes brain vascular reserve

Brain resilience depends on collateral vessels whose geometries preserve blood flow when primary arteries are perturbed. How these protective vascular architectures are developmentally established remains unknown. Using longitudinal in vivo imaging in zebrafish, we show that mitochondrial state in embryonic angiogenic tip cells encodes the topology of basal and surface brain collateral networks. Mechanistically, microRNA-125a establishes the bioenergetic and redox balance of endothelial tip-cell mitochondria through conserved repression of the metabolic regulator PGC1a. Disruption of the microRNA-125a-PGC1a axis uncouples mitochondrial capacity from redox buffering in developing brain tip cells, redirecting their migration toward sparse, incompletely connected collateral network topologies and increasing adult cerebrovascular vulnerability. Consistent with this mechanism, humans with subclinical cerebrovascular injury exhibit reduced circulating microRNA-125a levels associated with incomplete basal collateral configurations. Together, these findings identify mitochondrial state as an instructive and conserved developmental program that encodes brain vascular reserve.

developmental biology↗

bioRxiv2026

Cross-Species Multi-Omics Profiling Identifies Conserved Activated Valvular Interstitial Cell Population Driving Myxomatous Mitral Valve Degeneration

BackgroundPrimary mitral regurgitation resulting from mitral valve prolapse can lead to life-threatening complications, including arrhythmias, heart failure, and sudden cardiac death. Mitral valve prolapse is classically associated with myxomatous mitral valve degeneration, characterized by leaflet thickening, extracellular matrix disorganization, and progressive structural remodeling. Valvular interstitial cells, the predominant stromal population within the valve, maintain extracellular matrix homeostasis; however, their molecular heterogeneity, and state-specific contributions to disease pathogenesis remain incompletely defined. MethodsUsing a fibrillin-1 deficient mouse model and human tissue specimens we integrated single-cell RNA sequencing with spatial transcriptomic profiling to construct a comprehensive atlas of cellular composition and extracellular matrix organization across normal mitral valves, sporadic mitral valve prolapse, and Marfan syndrome-associated mitral valve prolapse. ResultsAnalyses revealed spatially organized cellular niches and substantial heterogeneity within the valvular interstitial cell population. Across murine and human datasets, we identified a conserved activated valvular interstitial cell population enriched for profibrotic extracellular matrix remodeling programs and preferentially localized to mechanically vulnerable leaflet tip regions. This population exhibited coordinated upregulation of collagen- and matrix-associated genes, metabolic signatures consistent with enhanced mitochondrial activity, and transcriptional features suggesting fibro-inflammatory signaling. ConclusionsWe identified a transcriptionally and spatially distinct activated valvular interstitial cell state conserved across species and disease etiologies that is strongly implicated in fibrotic remodeling during myxomatous mitral valve degeneration and provides a candidate therapeutic target.

molecular biology↗

bioRxiv2026

3D vascular quantitation with application to computational modeling: a pre-clinical light sheet microscopy, high resolution ultrasound, nano-computed tomography comparison study

It is increasingly necessary to both study biology in 3D and obtain quantitative measurements. Not all 3D-reconstructions are created equal, particularly when using the anatomical model as a basis for force calculations, i.e. computational modeling. Here, we compare 3D anatomical reconstructions from two emerging imaging modalities: 4D ultrasound (4DUS) and light sheet fluorescent microscopy (LSFM) against our previous nano-computed tomography (nanoCT) cohort data, using the tortuous highly intricate pharyngeal arch artery system of the chick embryo as a test bed. We highlight modality-specific morphological image acquisition discrepancies and their influence on subsequent computational fluid dynamics results. Overall, LSFM accurately captured quantitative volumetric measurements of small rapidly-changing vascular morphologies while 4DUS systematically inflated small tortuous vessels. Differences in image-based morphology changes led to significant changes in computationally-obtained force magnitudes and flow patterns linked to vessel angle and tortuosity. This validates LSFM as a comparative preclinical vascular quantitative imaging tool and suggests that 4DUS needs extensive 3D anatomical validation for non cardiac chamber vessels.

bioengineering↗

bioRxiv2026

Multiple nuclei means multiple chromosome sets in Botrytis cinerea and Neurospora crassa

We often think of fungi as mysterious organisms that do not follow the general principles of other eukaryotes. Thus, when exciting results are found, these organisms do not always receive the rigorous level of scrutiny seen in other fields. For many fungal species, dispersal and reproduction relies on spores, either sexual or asexual. These spores can either have a single nucleus, or multiple nuclei, and the purpose of these presumably mitotic copies was unclear. Recently it was described that the multiple nuclei in these spores are not mitotic duplicates, but instead they share a single haploid set of chromosomes distributed across nuclei. Here, we provide fluorescent microscopy and UV mutagenesis data that is inconsistent with this hypothesis. Contrasting these previous results, we observe multiple sets of chromosomes in spores of both B. cinerea and N. crassa. We also observed a strong linear relationship between the number of nuclei in spores and the total acriflavine fluorescence, further supporting mitotic copies. Genome sequencing of colonies arising from UV-irradiated colonies also recovered variants at intermediate frequences, instead of the fixed 100% expected from the new model proposed. This evidence suggests that, as long suspected, these nuclei are indeed mitotic copies, and that a re-evaluation of fungal biology is not currently necessary.

genetics↗

bioRxiv2026

EnsAgent: a tool-ensemble multiple Agent system for robust annotation in spatial transcriptomics

MotivationAutomated domain annotation in spatially resolved transcriptomics (SRT) remains challenging since it depends on gene expression, morphology, and clinical conventions, which vary across cohorts and platforms. While Large Language Model (LLM)-driven agents show promise, current approaches typically condition semantic reasoning on static, single-method partitions. This reliance makes annotation pipelines fragile to upstream partition errors and prone to hallucinations when molecular evidence is ambiguous. A robust framework integrating ensemble intelligence with iterative, evidence-based reasoning is required to ensure reproducibility and accuracy. ResultsWe introduce EnsAgent, a tool-ensemble multi-agent system designed for robust SRT annotation. Uniquely, EnsAgent decouples structural partitioning from semantic labeling via a Consultation-Review workflow. A Tool-Runner Agent orchestrates a diverse portfolio of clustering algorithms via the Model Context Protocol (MCP), generating a consensus partition optimized by a multimodal Scoring Agent. Subsequently, a Proposer-Critic feedback loop coordinates four specialized experts (Marker, Pathway, Spatiality, and Visual) to formulate annotations with explicit evidence trails and uncertainty estimates. Benchmarking on three SRT datasets demonstrates that EnsAgent effectively neutralizes batch effects and resolves subtle tumor microenvironment niches missed by single-paradigm baselines, delivering state-of-the-art accuracy and interpretability. Availability and ImplementationEnsAgent is available at github.com/keviccz/ensAgent. Contactdongqishi@sztu.edu.cn, kexiao@sztu.edu.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2026

Exploring Links between Brain Image-Derived Phenotypes and Accelerometer-Measured Physical Activity in the UK Biobank

A broad range of neurodegenerative disorders are associated with altered functional connectivity (FC) patterns and atrophy of gray matter volume (GMV). Similarly, there are links between physical activity (PA) and a number of neurodegenerative disorders. However, studies investigating the link between brain image-derived phenotypes (IDPs) and PA remain limited. Using data from the UK Biobank, we investigated the multivariate association between two sets of brain IDPs (related to FC and GMV) and PA using canonical correlation analysis (CCA). We further quantified the importance of individual PA variables in modeling each set of IDPs using both supervised and unsupervised approaches, and assessed their predictive performance for individual brain phenotypes. Finally, we evaluated the predictive performance of brain IDPs and PA variables for diabetes, stroke, coronary heart disease (CHD), and cancer using nested logistic regression models, with their relative contributions to explained variation in disease status quantified using a coefficient of determination specifically designed for logistic regression. Our analyses identified a statistically robust but low-dimensional axis of shared variation between PA and FC (canonical correlation r = 0.50), whereas the corresponding association between PA and GMV was weaker (r = 0.19). Brain features contributing most strongly to these associations were located in motor- and attention-related networks. Across predictive models, a small set of correlated PA measures reflecting activity intensity and circadian rhythm consistently emerged as representative predictors of both FC and GMV variation. Finally, we found that PA variables demonstrated greater predictive utility than either FC or GMV alone, particularly for CHD and diabetes, as assessed by both the area under the receiver operating characteristic (ROC) curve (AUC) and the proportion of explained variation. Together, these findings indicate that objectively measured PA is strongly associated with a set of motor-related brain features and provides substantial predictive information for cardiometabolic disease risk, while cross-sectional neuroimaging measures offer more modest incremental explanatory value.

neuroscience↗

bioRxiv2026

Mapping the North American Terrestrial Carbon Cycle: A Process-based Reanalysis Using State Data Assimilation (SDA)

AbstractThe ability to accurately assess ecosystem C budgets across scales from individual sites to continents is essential for C accounting, management, and ultimately mitigating climate change. State data assimilation (SDA) provides a framework for harmonizing observations with models, while robustly accounting for and reducing multiple sources of uncertainty. In this study, we employed a hybrid SDA framework that combines process-based terrestrial biosphere modeling, hierarchical Bayesian inference, and machine learning to harmonize bottom-up and remotely-sensed data streams for 8,000 pre-selected 1km2 locations across North America within a hybrid structure. Combining bottom-up soils data (SoilGrids) with spectral (MODIS and Landsat) and microwave (SMAP) remote sensing helps constrain the major C and water stocks through space and time. Machine learning is used both to identify and correct systematic errors in the process model (SIPNET) and to interpolate the pre-selected locations onto a 1km grid, making it computationally feasible to generate annual ensemble maps of the North American carbon budget. Furthermore, the uncertainties for each variable were reduced compared to those from observations or models alone. Spatiotemporal analysis showed a slight decrease in aboveground biomass (AGB) across the western US, a loss of leaf area across the boreal, and a slight greening of the Alaskan tundra. The uncertainty trends suggest a significant reduction in the uncertainty about soil organic carbon (SOC), the largest C reservoir. Validation results show that we accurately estimate C pools, compared to the assimilated data streams and held-out observations of AGB from GEDI, ICESat-2, and the US FIA, and SOC from the ISCN network. Our ML-debiasing algorithm further improved the accuracy of major C pools (AGB, SOC). In general, our continental SDA framework will facilitate global C MRV (monitoring, reporting, and verification) by providing accurate and precise C-cycle estimates, along with their corresponding spatiotemporal uncertainties.

ecology↗

bioRxiv2026

A cryo-EM processing pipeline for microtubules using CryoSPARC

Microtubules are cytoskeletal filaments typically characterized by a discontinuous helical lattice of /{beta}-tubulin heterodimers. Microtubules can also adopt variable lattice architectures both in vitro and in cellular contexts. Pseudo-helical averaging processing strategies have been developed to generate cryo-EM reconstructions of microtubules with and without decorating protein-binding partners, but these pipelines can be difficult to implement for the average user, especially for undecorated filaments. Here, we describe MiCSPARC, a cryo-EM processing pipeline developed around CryoSPARC (Punjani et al., 2017), which leverages automated particle picking and fast 3D refinement times in CryoSPARC to determine structures of both decorated and undecorated microtubules. We generated reconstructions of undecorated GDP microtubules, as well as kinesin-1 motor domain-decorated GMPCPP filaments at resolutions of up to 2.8 [A], demonstrating the robustness of the pipeline. Based on its convenient implementation and ability to routinely generate high-resolution, seam-corrected microtubule reconstructions, MiCSPARC should provide a valuable tool for understanding microtubule dynamics, microtubule-associated proteins, and microtubule-targeting agents.

biophysics↗

bioRxiv2026

Wildfire emitted particulate matter induces ovarian hyperandrogenism through aryl hydrocarbon receptor activation

Wildfires have become more frequent and intense worldwide. Wildfire emitted particulate matter (WFPM) can be more toxic than urban background PM due to its greater content of nanoscale size (WFPM0.1) and presence of more polar organic compounds, including polycyclic aromatic hydrocarbons (PAHs). While exposure to WFPM has been linked to cardiovascular and respiratory diseases, its impact on female reproduction remains elusive. Here, we used an in vivo mouse intratracheal exposure model and a 3D ovarian follicle culture system, together with molecular, transcriptomic, and computational approaches, to examine the female reproductive effects of lab-synthesized (LS-WFPM0.1) and real-world Canadian WFPM0.1 (C-WFPM0.1), collected from the New York City and New Jersey metropolitan area during the June 2023 wildfire events. Intratracheal exposure to environmentally relevant dose of LS-WFPM0.1 disrupted mouse estrous cycles and elevated serum concentrations of estradiol and testosterone. RT-qPCR and single-follicle RNA-sequencing (RNA-seq) analysis revealed altered steroidogenic genes, transcriptomic changes, and activation of aryl hydrocarbon receptor (AhR) in antral follicles from mice treated with LS-WFPM0.1. LS-WFPM0.1 consistently increased testosterone secretion and stimulated genes related to androgen synthesis and AhR in vitro. Single-follicle and single-oocyte RNA-seq analysis identified differentially expressed genes related to inflammation in somatic cells and mitochondrial respiratory chain in oocytes. Both C-WFPM0.1 and benzo[a]pyrene, a high-molecular-weight PAH, reproduced these ovarian defects. Mechanistically, AhR inhibition reversed hyperandrogenism induced by WFPM0.1. Together, our findings suggest that WFPM0.1, an increasingly pervasive environmental exposure, adversely impacts female reproductive functions by disrupting ovarian steroidogenesis and inducing hyperandrogenism through AhR activation, highlighting an urgent unmet need for further mechanistic studies and epidemiological investigations to define the reproductive risks of wildfire smoke exposure in human populations.

pharmacology and toxicology↗

bioRxiv2026

Epigenome-informed prioritization of bivalent chromatin SNPs enhances genomic prediction robustness: a proof-of-concept study in Pacific white shrimp (Litopenaeus vannamei)

BackgroundGenomic selection (GS) has revolutionized animal breeding, spanning livestock sectors such as pigs and cattle to aquatic species like fish and shrimp. However, its broader application across these industries is often constrained by high genotyping costs and reduced predictive reliability across divergent populations or generations. Developing cost-effective, biologically informed genotyping strategies to overcome these limitations remains a critical goal in animal agriculture. Epigenetic annotations, particularly histone modifications, provide direct functional insights into regulatory elements underlying complex trait variation and represent a promising but underexplored resource for marker prioritization. ResultsHere, using the Pacific white shrimp (Litopenaeus vannamei) as a model organism, we conducted a proof-of-concept study integrating resequencing and phenotypic data from 972 individuals. We generated high-resolution epigenomic maps by profiling four histone marks (H3K4me1, H3K4me3, H3K27me3, and H3K27ac) across multiple embryonic stages and adult muscle tissue using CUT&Tag. These functional annotations were then leveraged to prioritize single nucleotide polymorphism (SNP) subsets for genomic prediction. Among the tested strategies, SNPs located in the muscle-specific bivalent promoter/enhancer (E6) state--characterized by the co-occurrence of active and repressive marks--consistently maximized prediction accuracy under the BayesA model. Notably, even at a moderate density (15k), E6-derived SNPs achieved prediction accuracies exceeding those obtained using substantially larger genome-wide SNP sets. Most importantly, in a challenging cross-population validation using an independent strain, the E6-derived SNP subset significantly improved prediction accuracy by 47.6% (increasing from 0.21 {+/-} 0.05 to 0.31 {+/-} 0.04, p < 0.05) compared to random subsets at equivalent density. ConclusionsThese results demonstrate that epigenetic annotation-guided SNP prioritization provides a biologically informed and cost-effective strategy to enhance genomic prediction accuracy and stability. This framework is broadly transferable across species and offers a practical strategy for designing low-density genotyping panels that reduce costs while maintaining reliable selection outcomes in large-scale breeding programs.

genetics↗

bioRxiv2026

Enzyme Classification via Semi-Supervised Functional ResidueLearning

Predicting enzymatic function from a protein sequence is a fundamental task in protein discovery and engineering. In this paper, we present Semi-supervised Learning for Enzyme Classification (SLEEC): a semi-supervised learning framework that learns a function-aware protein representation for Enzyme Commision (EC) number prediction. SLEEC achieves SOTA performance on standard bench-marks and provides interpretable, residue-level annotations. We further demonstrate that our framework is robust to benign sequence modifications routinely observed in protein engineering workflows- such as appending functional tags- a desirable property that current ML frameworks lack. Our main technical contribution is a multiple sequence alignment (MSA)-based data augmentation technique for discovering sparse residue activations within a given enzyme sequence.

bioengineering↗

bioRxiv2026

Molecular basis of enfumafungin inhibition and resistance in Candida glabrata β-1,3-Glucan synthase FKS1

{beta}-1,3-Glucan synthase FKS1 is essential for fungal cell wall biogenesis and serves as a validated target of widely prescribed antifungal drugs. However, the molecular mechanism of pathogenic FKS1, its modes of inhibition, and the associated resistance mechanisms remain elusive, hindering the antifungal development. Here, we focus on Candida glabrata FKS1, a clinically relevant target frequently linked to antifungal resistance. We present cryo-EM structures of C. glabrata FKS1 in multiple detergent environments and in complex with the triterpenoid antifungal enfumafungin. Integrated functional studies revealed a key catalytic residue within the conserved ED motif and uncovered structural adaptations to different membrane-mimetic environments, rationalizing FKS1s sensitivity to its surrounding membrane context. Enfumafungin binds at the extracellular membrane leaflet of cgFKS1 transmembrane domain, engaging a convex surface separated from the cytosolic active site, consistent with its role as a non-competitive inhibitor. Further analyses identified key enfumafungin-binding residues from TM5-TM6 and elucidated the molecular basis of drug resistance in C. glabrata. Collectively, these findings establish a mechanistic framework for pathogenic FKS1 function and inhibition and provide a molecular basis for the rational design of next-generation antifungal therapeutics.

microbiology↗

bioRxiv2026

A Novel Bioprocess Control Strategy Under Uncertainty via Operational Space Identification

Bioprocesses are critical for sustainable industrial development but face challenges from their inherent uncertainties that affect efficiency and scalability. This study in-troduces a worst-case operational space design framework, integrating symbolic optimization with scenario-based validation, to preemptively mitigate uncertainties so that key performance indicators are consistently satisfied even under adverse conditions. The methodology is demonstrated through two case studies: a lab-scale fermentation for astaxanthin production and a site-scale anaerobic digestion for biogas production. Process uncertainty is quantified through model parameter variations (2% - 13%) to reflect real-world scenarios. The results indicate that highly flexible operational spaces are identified in both case studies, with control variables able to vary by up to 25% and 15% in the respective systems, while consistently adhering to system constraints. Validation over 10,000 scenarios confirmed 0 violation per case study. The proposed framework delivers validated operational flexibility with modest computational requirements, making it practical for lab-to-site deployment.

microbiology↗

bioRxiv2026

PRISM: Niche-informed Deciphering of Incomplete Spatial Multi-Omics Data

Spatial multi-omics data, characterizing the knowledge of diverse molecular layers, have become indispensable for the in situ analysis of tissue architecture and complex biological processes. Nevertheless, current spatial multi-omics sequencing protocols are often hindered by incompatible protocols, resulting in incomplete spatial multi-omics pairing due to inconsistent field-of-view or spatial resolution. To address this, we present PRISM, a novel computational method tailored for this scenario. PRISM leverages a niche-informed graph to propagate information from paired to unpaired regions, jointly achieving the spatial domain identification and spatial omics imputation. Extensive benchmarking on five diverse simulated and real experimental datasets demonstrated that PRISM outperformed existing methods in spatial multi-omics analysis tasks. Application to the human Parkinsons disease data revealed that PRISM accurately recovered dopamine-associated spatial domains and metabolite distributions masked by incomplete data gaps. PRISM offers a robust solution for bridging the integration gap inherent in incompatible sequencing protocols, thereby facilitating more accurate downstream biological interpretation.

bioinformatics↗

bioRxiv2026

Volumetric mechanoplasticity couples melanoma drug tolerance to susceptibility to CD8+ T cell killing

Cell swelling has been reported in physiological tumor contexts, but whether sustained cell volume expansion leaves a durable state that reshapes drug and immune responses in melanoma is unknown. Using controlled hypotonic dilution as an experimental handle, we compare two priming regimens with comparable hypotonic exposure but different magnitude and persistence of volume expansion, enabling us to test which post-recovery phenotypes track with sustained enlargement beyond hypotonic exposure alone. Sustained enlargement produces a measurable size imprint after return to isotonic conditions, accompanied by nuclear lamina and chromatin remodeling with p53 pathway engagement and suppression of replication and growth programs. After recovery, primed cells reinforce F-actin organization, migrate faster in 3D collagen, and induce antioxidant and anti-ferroptosis defenses consistent with improved stress survival. A gene expression signature derived from this response is associated with poorer outcome in TCGA skin cutaneous melanoma. Unexpectedly, the same volume history also increases IFN-{gamma} response, elevates MHC-I, reduces sialylation, and increases susceptibility to CD8+ T cell killing. These findings indicate that persistent volume history can couple drug tolerance programs to an exploitable increase in immune visibility.

biophysics↗

bioRxiv2026

Melatonin alleviates acid-induced stress in peanut (Arachis hypogaea L.) through physiological, antioxidative regulation and molecular defense mechanisms

Acidic stress severely restricts crop growth by disrupting nutrient uptake, redox homeostasis, and membrane stability, yet mitigation strategies remain limited. Here, we investigated the role of melatonin (MT) in regulating growth, photosynthesis, oxidative stress, antioxidant defense and proton transport in peanut seedlings under controlled hydroponics acidic (pH 4.0) and near-optimal (pH 6.5) conditions, and validated these findings in naturally acidic field soil (pH 4.3-4.5). Acid stress markedly reduced biomass accumulation, chlorophyll content, and redox balance, while enhancing ROS (H2O2) and lipid peroxidation (MDA). Exogenous MT application, particularly at 50-100 {micro}M, significantly improved shoot and root biomass, restored chlorophyll pigments and reduced H2O2 and MDA accumulation, with more pronounced effects under pH 4.0 than pH 6.5. MT strongly activated antioxidant enzymes (SOD, CAT, APX), while POD activity declined, reflecting melatonins dual role as both a direct ROS scavenger and a regulator of enzymatic redox networks. Notably, MT induced strong, dose-dependent upregulation of HL-ATPase genes (AH1 and AH2) in both leaves and roots under acidic conditions, suggesting enhanced proton extrusion, intracellular pH homeostasis, and stress adaptation. The soil validation experiment confirmed the agronomic relevance of these findings, where MT dose-dependent concentrations improved germination, vegetative growth, chlorophyll fluorescence (Fv/Fm), and yield-related traits under natural acidic conditions. Although MT also conferred benefits at pH 6.5, responses were generally moderate compared with acid stress. Collectively, these results demonstrate that MT enhances peanut tolerance to acid stress across both controlled and natural field-relevant environments, highlighting its potential application for sustainable crop production on low-pH soils.

plant biology↗

bioRxiv2025

A Hybridization-Based Novel DNA Storage Technology with Rapid Read Performance

The development of traditional silicon-based microelectronic storage media has increasingly lagged behind the rapidly growing demands of contemporary data storage. DNA storage, with its ultra-high information density and long-term preservation advantages, has rapidly become a research hotspot for next-generation storage technologies. However, current mainstream DNA storage methods based on synthesis and sequencing suffer from slow read/write speeds, hindering practical applications. To address this limitation, we propose an innovative hybridization-based DNA storage scheme. Through principle validation experiments, short-text read/write and error-correction tests, and high-density multi-format file storage experiments, we verify the feasibility of this approach. The proposed method exhibits high parallelism, rapid read speeds, and robust encryption capabilities, demonstrating promising application prospects in scenarios such as confidential data storage.

synthetic biology↗

bioRxiv2025

Neocortical temporal patterning by a two-layered regulatory network

In the developing neocortex, a diverse array of neurons with defined types and abundances are systematically generated by a limited population of radial glial progenitors (RGPs) as they undergo successive fate changes. The molecular regulation behind this intricate temporal patterning remains elusive. We undertook in-depth single-cell multi-omics analyses, discovering a two-layered regulatory framework at the core of this process. Central to this are global temporal regulators positioned above a temporal network, consisting of series of transcriptional factor (TF) hub groups under sequential state transitions. This temporal network operates not by restricting TF expressions to discrete temporal windows, but through coordinated transcriptional and chromatin-accessibility dynamics that modulate transient TF regulatory activity. Moreover, global temporal regulators specify the duration of each cascading stage and, consequently, the number of progenies generated at each stage. Loss of global temporal regulators protracts RGP lineage progression, whereas their increased activity accelerates it. These findings suggest a two-layer temporal regulatory system controlling RGP lineage progression and neural progeny output duality in mammalian neocortical development.

neuroscience↗