Biology subjects

Pang, L.

Publications and source records attributed to Pang, L..

14 recordsLinked to original sources

bioRxiv2026

Brain state locks silent memories in a trained fly connectome

Complete connectomes now exist for insect nervous systems, but whether a fixed wiring diagram can learn, and what its memories consist of, is unknown. Here, we trained a spiking model of the whole male Drosophila central nervous system, 167,106 neurons with fixed wiring, to plan moves and to remember a visual cue. Spikes write the cue into neuronal adaptation, which holds it silently until the next input reads it out. Cells that hold the trace are enriched for transcripts of a calcium-activated potassium channel in fly cell atlases. The learned readout recalls the trace only in the brain state of learning: the same trace evokes a different response at another delay, and a disease-like loss of potassium current rewrites the trace and changes how it is read. Learning in the new state is spared. Memory failure can arise from a change of state rather than a loss of storage.

neuroscience↗

bioRxiv2026

IEKB: a comprehensive knowledge base for inner ear genetics integrating curated associations, cochlear interactions, Bayesian candidate prioritisation, explainable dark-gene support relations, and a scientific entity network

Inner-ear genetics has expanded rapidly, yet the supporting evidence remains dispersed across a vast literature and across resources that typically emphasise loci, variants, or expression data rather than integrated biological interpretation. Here we present the Inner Ear Knowledge Base (IEKB; https://earkb.org), an open database that unifies curated associations, cochlear interaction evidence, candidate prioritisation, explainable support relations, and network exploration for inner-ear research. IEKB was built with an automated agent-assisted curation workflow that combines schema-constrained literature extraction, continuous human monitoring, and final expert review by inner-ear genetics researchers. By systematically analysing 250,696 PubMed-indexed records retrieved across 16,563 screened genes, IEKB curates 6,051 gene-phenotype-disease associations from 2,494 genes across 43 phenotype categories and 4,102 cochlear gene-gene interactions with pathway, cell-type, and experimental context. IEKB further includes a Bayesian "dark matter" module that prioritises 243,071 candidate gene-phenotype associations for 13,229 genes across all 43 phenotypes (global AUC-ROC = 0.8603; global AUC-PR = 0.1674), together with a supervised dark-relation layer that ranks phenotype-specific known-gene support for each candidate and a multi-entity scientific network containing nearly 4,000 entities, 28,616 deterministic edges, and 83,712 literature-derived relational links. The web resource supports interactive search, multi-parameter filtering, gene-detail pages, bibliometric exploration, domain-specific enrichment against IEKB phenotype and disease gene sets, network visualisation, bulk download in CSV, JSON, SQLite, and XLSX formats, and natural-language evidence-grounded question answering through a companion conversational interface (IEKB QA). To our knowledge, IEKB is the first openly accessible inner-ear resource that integrates curated associations, cochlear interactions, probabilistic candidate prioritisation, auditable known-gene support relations for novel candidates, and a multi-entity scientific network within a single database. All data are released without registration under the CC BY 4.0 license.

bioinformatics↗

bioRxiv2025

Development of Replay-DMN Coordination Predicts Entorhinal Grid Codes

Neural replay, the reactivation of experience-related activity patterns during offline periods, has been implicated in organising memories into cognitive maps. However, how replay processes mature through childhood and adolescence remains unclear. Here we studied 106 participants aged 8-25 who learned a hidden two-dimensional (2D) associative structure and then underwent magnetoencephalography (MEG) during a map-based inference task and post-task rest to detect spontaneous replay. We found that during post-task rest, younger individuals relied primarily on replay alone to represent the 2D relationships, whereas older individuals showed increasingly precise timing alignment between replay events and activity in the default mode network (DMN), particularly when replay occurred at the trough of a DMN theta oscillation. Such replay-DMN coupling predicted the strength of a grid-cell-like code in the entorhinal cortex identified in this cohort with fMRI. Furthermore, resting-state fMRI revealed that DMN functional connectivity strengthened with age, in parallel with reduced reliance on replay and more efficient inference performance. These results reveal a developmental progression in which replay shifts from an isolated process in youth to a coordinated DMN mechanism by adulthood. This transition predicts the maturation of grid-like schema representations, shedding light on how children gradually build internal knowledge structures to support flexible inference.

neuroscience↗

bioRxiv2025

The differential mechanisms of eIF4A1-mediated translational activation instructed by distinct RNA features

All mRNAs require eukaryotic translation initiation factor (eIF) 4A1 for translation through its different functions: loading of the pre-initiation complex onto mRNAs and unwinding of RNA structure. eIF4A1 is the catalytic subunit of the cap- binding eIF4F complex and presumed to select the mRNAs for translation through these activities, instructed by signalling pathways driving cell fate. The mechanisms underlying activation of the distinct eIF4A1 functions and establish translational selectivity are unknown. Here, we have unravelled the complexity of mRNA selection by eIF4A1. We have mechanistically characterised the biological and atomic basis of inhibition by gain- and loss-of-function eIF4A1-inhibitors eFT226 and hippuristanol, and used machine learning to model the mRNA features associated with specific inhibition. This uncovered the eIF4A1 function - mRNA sequence relationship: 5UTRs containing C/CG-rich require efficient mRNA loading by eIF4F which is specifically targeted by hippuristanol, while 5UTRs harbouring alternatives starts sites together with AG-rich motifs utilise eIF4A1 for start site selection, specifically perturbed by eFT226. Our model is validated through a massively parallel reporter assay using 5UTRs from a distinct evolutionary origin. This prompted us to examine the conservation between mRNA sequence and eIF4A1 function, and revealed their co- development. Our findings highlight opportunities for novel therapeutic strategies targeting eIF4A1 and for improved design of mRNA-based therapeutics.

cell biology↗

bioRxiv2025

Single-cell spatial transcriptome reveals pathological features of human hippocampus with sclerosis

More than half of epileptic patients ultimately turned to intractable epilepsy. Mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS), the most common type of intractable epilepsies, whose pathological mechanism remains elusive. Here, using 42 human hippocampal samples from surgical donors of MTLE (32 with and 10 without HS) through single-cell resolution Stereo-seq and histologcial experiments, we revealed spatially pathological changes of gene expression and cell type composition with HS systematically. After precise parcellation of hippocampal subregions and differentially expressed gene (DEG) analysis between each region with and without sclerosis, we found Cornu Ammonis (CA) subregions with higher number of DEGs were vulnerable to sclerosis, especially CA1 and CA3. Within CA1, we found that CA1-superficial and proximal areas were more vulnerable than CA1-deep and distal areas in sclerosis. Meanwhile, after analyzing 350,795 segmented cells from Stereo-seq, we found dramatically increasing density of astrocyte accompanied with significantly decreasing density of excitatory neurons in CA1, especially superficial and proximal CA1, and CA3 in sclerosis. In these two vulnerable subregions, proliferative astrocyte (P_astrocyte) and reactive astrocyte (R_astrocyte) were found to be enriched whereas apoptotic subtype of astrocyte (A_astrocyte), related with apoptotic pathway, was mainly located in alveus, which strengthened cell communication with reactive microglia (R_microglia) in HS, revealing the novel pathological feature in our work. The pseudotime analysis indicated that CA excitatory neurons underwent synaptic impairment, energy dysfunction, aging, and finally losing cell identity until death through autophagy or apoptosis. Besides, we also found a resilient subtype, EX_CA2-4.3, highly expressed extracellular matrix related genes including PDYN, and was increasing the interaction of BDNF-NTRK, NFASC-CNTN1 to withstand the damage from sclerosis. Together, our study provided a reference of human hippocampus with and without HS caused by MTLE, and highlighted the potential pathological mechanism on molecular and cellular level of MTLE-HS.

neuroscience↗

bioRxiv2024

Development of Non-Spatial Grid-Like Neural Codes Predicts Inference and Intelligence

Piagets theory posits that children develop structured knowledge schemas for inferring and assimilating new information, yet the underlying neural mechanisms remain unclear. In 203 participants aged 8-25 years, we investigated how maturation of a two-dimensional (2D) knowledge map underpins inferential reasoning and knowledge assimilation. Grid-cell-like codes in the entorhinal cortex (EC) strengthened with age, reflecting schema representations in non-spatial conceptual spaces, and were directly linked to improved inferential reasoning. These grid-like codes also supported the medial prefrontal cortex (mPFC) in encoding distance relationships between objects on the 2D map. As participants assimilated new information, they integrated it into existing grid patterns in the EC. Moreover, the maturation of these neural codes predicted real-world intelligence measures, particularly in reasoning abilities. Our findings demonstrate that the development of non-spatial grid-like neural codes offers a mechanistic account of cognitive development, bridging psychological theory with a fundamental cellular representation of cognitive map.

neuroscience↗

bioRxiv2024

Inter-Kingdom Interactions and Environmental Influences on the Oral Microbiome in Severe Early Childhood Caries

Dental caries arise from intricate interactions among oral microorganisms, impacting ecological stability and disease progression. This study delves into the bacterial-fungal dynamics in severe early childhood caries (S-ECC) among 61 children aged 3-4 years with complete deciduous dentition. We evaluated environmental factors such as saliva pH, buffering capacity, and trace elements (iron, fluoride). We examined the performance of 16S rRNA V1-V9 regions gene and internal transcribed spacer (ITS) primers for bacteria and fungi from plaque and saliva to characterize community compositions and diversity. Saliva pH and buffering capacity were also measured. Findings revealed significant shifts in bacterial diversity in S-ECC saliva samples, marked by decreased diversity and elevated abundance of cariogenic species, particularly Streptococcus mutans. Candida albicans was notably more prevalent in the S-ECC group, implicating its potential role in pathogenesis. Iron and fluoride concentrations showed no significant correlation with microbial community structure. Network analyses uncovered complex intra- and inter-kingdom interactions, underscoring cooperative and competitive dynamics. S-ECC children exhibited higher abundances of bacteria (Streptococcus mutans, Granulicatella, Actinomyces) and fungi (Candida albicans), with specific microbial taxa associated with reduced saliva pH. ImportanceThis study illuminates the intricate relationship between bacteria and fungi within the oral microbial community of children, specifically highlighting differences between those with severe early childhood caries (S-ECC) and those without caries. Through an extensive analysis of the microbial composition in both saliva and dental plaque, we identified a significant increase in the abundance of specific bacterial taxa (e.g., S. mutans, Granulicatella, Actinomyces) and fungal species (e.g., C. albicans) in the oral cavities of children with S-ECC. This finding underscores the potential role of these microorganisms in the development of caries. Contrary to previous studies that emphasize the importance of iron and fluoride in oral health, our research found no significant correlation between the concentrations of these elements and the composition of oral microbial communities. This result challenges conventional understanding and opens new avenues for future research. Additionally, we discovered an association between certain microbial species and reduced salivary pH, offering fresh insights into the relationship between the oral microenvironment and caries development. The implications of our findings are substantial for the development of prevention and intervention strategies targeting childhood caries. They also underscore the critical need for a deeper exploration of oral microbial interactions and their environmental influences.

microbiology↗

bioRxiv2024

Multimodal Protein-Ligand Contrastive Pretraining for Effective and Efficient Drug Discovery

Recent advancements in genomics and proteomics have identified numerous clinically significant protein targets, with notably 85% categorized as undruggable. These targets present widespread challenges due to their complex structures and dynamics, rendering conventional drug design strategies not always effective. In this study, we introduce Uni-Clip, a contrastive learning framework that incorporates multi-modal features of proteins (structure and residue) and ligands (conformation and graph). Optimized with a specifically designed CF-InfoNCE loss, Uni-Clip enhances the modeling of protein-ligand interactions for both undruggable and druggable proteins. Uni-Clip demonstrates superior performance in benchmark evaluations on widely acknowledged datasets, LIT-PCBA and DUD-E, achieving a 147% and 218% improvements in enrichment factors at 1% compared to baselines. Furthermore, Uni-Clip proves to be a practical tool for various drug discovery applications. In virtual screening for the challenging protein target GPX4 with flat surface, it identified non-covalent inhibitors with an IC50 of 4.17 M, in contrast to the predominantly covalent inhibitors currently known. Through target fishing for benzbromarone, Uni-Clip identified the intrinsically disordered protein c-Myc as a potential target, highlighting benzbromarones potential for repurposing in cancer therapy. Explainable analyses effectively identified binding sites consistent with molecular dynamics and experimental results, even for challenging undruggable targets.

bioinformatics↗

bioRxiv2024

Coordinated molecular and ecological adaptations underlie a highly successful parasitoid

The success of an organism depends on the molecular and ecological adaptations that promote its beneficial fitness. Parasitoids are valuable biocontrol agents for successfully managing agricultural pests, and they have evolved diversified strategies to adapt to both the physiological condition of hosts and the competition of other parasitoids. Here, we deconstructed the parasitic strategies in a highly successful parasitoid, Trichopria drosophilae, which parasitizes a broad range of Drosophila hosts, including the globally invasive species D. suzukii. We found that T. drosophilae had developed specialized venom proteins that arrest host development to obtain more nutrients via secreting tissue inhibitors of metalloproteinases (TIMPs), as well as a unique type of cell-- teratocytes--that digest host tissues for feeding by releasing trypsin proteins. In addition to the molecular adaptations that optimize nutritional uptake, this pupal parasitoid has evolved ecologically adaptive strategies including the conditional tolerance of intraspecific competition to enhance parasitic success in older hosts and the obligate avoidance of interspecific competition with larval parasitoids. Our study not only demystifies how parasitoids weaponize themselves to colonize formidable hosts but also provided empirical evidence of the intricate coordination between the molecular and ecological adaptations that drive evolutionary success.

ecology↗

bioRxiv2022

Determination of expression profiles for Drosophila ovarian Follicle Stem Cells (FSCs) using single-cell RNA sequencing

Drosophila ovarian Follicle Stem Cells (FSC) present an excellent paradigm for understanding how a community of active stem cells maintained by population asymmetry is regulated. Here we describe single-cell RNA sequencing studies of a pre-sorted population of cells that include FSCs and the neighboring cell types, Escort Cells (ECs) and Follicle Cells (FCs), which they support. Cell-type assignment relies on anterior-posterior (AP) location within the germarium. We clarify the previously determined location of FSCs and use spatially targeted lineage studies as further confirmation. The scRNA profiles among four clusters are consistent with an AP progression from anterior ECs through posterior ECs and then FSCs, to early FCs. Several genes with graded profiles from ECs to FCs are highlighted as candidate effectors of the inverse gradients of the two principal signaling pathways, Wnt and JAK-STAT, that guide FSC differentiation and division.

developmental biology↗

bioRxiv2021

Resting-state functional connectivity of social brain regions predicts motivated dishonesty

Motivated dishonesty is a typical social behavior varying from person to person. Resting-state fMRI (rsfMRI) is capable of identifying unique patterns from functional connectivity (FC) between brain networks. To identify the relevant neural patterns and build an interpretable model to predict dishonesty, we scanned 8-min rsfMRI before an information-passing task. In the task, we employed monetary rewards to induce dishonesty. We applied both connectome-based predictive modeling (CPM) and region-of-interest (ROI) analysis to examine the association between FC and dishonesty. CPM indicated that the stronger FC between fronto-parietal and default mode networks can predict a higher dishonesty rate. The ROIs were set in the regions involving four cognitive processes (self-reference, cognitive control, reward valuation, and moral regulation). The ROI analyses showed that a stronger FC between these regions and the prefrontal cortex can predict a higher dishonesty rate. Our study offers an integrated model to predict dishonesty with rsfMRI, and the results suggest that the frequent motivated dishonest behavior may require a higher engagement of social brain regions.

neuroscience↗

bioRxiv2021

An exploration of metabolic and transcriptional responses in mouse skeletal muscles responding to acute sedentary hypoxia

Skeletal muscles are involved in responses to acute hypoxia as the largest organ in the body. However, as a hypoxic-tolerant tissue, responses in skeletal muscles caused by acute sedentary hypoxia are much less studied. We measured metabolites in skeletal muscles from mice exposed to 8% O2 for 0 minute, 15 minutes and 2 hours and studied the potential relationship between metabolite levels and mRNA levels by reconstructing genome-based metabolic networks and meta-analyzing differentially expressed genes acquired in skeletal muscles after 2 hours of 8% O2 exposure. The metabolite measurement indicated a significant increase in glutamine metabolism but not lactate metabolism in mouse skeletal muscles after 2 hours of hypoxia, where the metabolic responses as a whole were moderate. The central-dogma based metabolic flux analysis suggested an involvement of glutamine metabolism, though, as a whole, metabolite changes and gene changes didnt show a high correlation. Among metaoblites, glutamine metabolism indicated a significant response and a consistent change which could be interpreted by genome-based network analysis. In summary, though this study suggested a moderate metabolic response which has a weak correlation with gene expression change as a whole, glutamine metabolism indicated rapid responses in skeletal muscles responding to acute sedentary hypoxia.

systems biology↗

bioRxiv2021

Delineating the molecular and phenotypic spectrum of the SETD1B-related syndrome

Pathogenic variants in SETD1B have been associated with a syndromic neurodevelopmental disorder including intellectual disability, language delay and seizures. To date, clinical features have been described for eleven patients with (likely) pathogenic SETD1B sequence variants. We perform an in-depth clinical characterization of a cohort of 36 unpublished individuals with SETD1B sequence variants, describing their molecular and phenotypic spectrum. Selected variants were functionally tested using in vitro and genome-wide methylation assays. Our data present evidence for a loss-of-function mechanism of SETD1B variants, resulting in a core clinical phenotype of global developmental delay, language delay including regression, intellectual disability, autism and other behavioral issues, and variable epilepsy phenotypes. Developmental delay appeared to precede seizure onset, suggesting SETD1B dysfunction impacts physiological neurodevelopment even in the absence of epileptic activity. Interestingly, males are significantly overrepresented and more severely affected, and we speculate that sex-linked traits could affect susceptibility to penetrance and the clinical spectrum of SETD1B variants. Finally, despite the possibility of non-redundant contributions of SETD1B and its paralogue SETD1A to epigenetic control, the clinical phenotypes of the related disorders share many similarities, indicating that elucidating shared and divergent downstream targets of both genes will help to understand the mechanism leading to the neurobehavioral phenotypes. Insights from this extensive cohort will facilitate the counseling regarding the molecular and phenotypic landscape of newly diagnosed patients with the SETD1B-related syndrome.

genetics↗

bioRxiv2017

Computational Model for Simulating Drug-Induced Arrhythmia Sensitivity of Human iPSC-derived Cardiomyocytes

A mathematical model describing the electrophysiology and ion handling of cardiomyocytes is a complement to experimental analysis predicting drug-induced proarrhythmic potential in humans as proposed by Comprehensive in vitro Proarrhythmia Assay (CiPA). While CiPA endorses the use of the OHara Rudy (ORd) model, which was developed to simulate electrophysiology of human adult ventricular cardiomyocytes (hAVCMs), to predict drug-induced proarrhythmias; the human induced pluripotent stem cell derived-cardiomyocytes (hiPSC-CMs) was proposed for experimental verifications. The hiPSC-CMs, especially cultured in 2D culture dishes, are inherently different from hAVCMs exhibiting different ion channel density and an immature sarcoplasmic reticulum function. To reconcile this mismatch, we have developed a mathematical electrophysiology model of an hiPSC-CM by incorporating differences in gene expressions of ion channels, pumps and receptors in hiPSC-CMs against those found in hAVCMs. This model can be used to model any hiPSC-CM cell line where expression data has been obtained and replaces the background currents for K+ and Na+ in the ORd model with the known ultra-rapid K+ channel and hyperpolarization activated K+/Na+ channel currents. With this new model, three batches each from two different hiPSC-CM cell lines are compared to experimental data of action potential duration. This mathematical model recapitulates a ventricular-like action potential morphology with a Phase 2 plateau lasting a few hundred milliseconds. However, the resting membrane potential is not as depolarized (-65 to -70 mV) as that of hAVCM (-80 mV). The elevated resting membrane potential matches experimental data previously and is thought to keep rapid sodium channels from triggering membrane depolarization instead being replaced by an overexpression of L-Type Ca2+ channel current. This model is a key step in identifying the variability between different hiPSC-CM lines and even batches of the same line, opening the door to realizing analysis of patient specific preparations in the future.

physiology↗