Biology subjects

Pan, N.

Publications and source records attributed to Pan, N..

7 recordsLinked to original sources

bioRxiv2025

Diagnosing linearity along the carbon cascade in terrestrial biosphere models

Elevated carbon dioxide (eCO2) fertilises photosynthesis, driving an increase in terrestrial gross primary production (GPP). However, it is unclear how effectively increased GPP propagates along the "carbon (C) cascade" to increase net primary production (NPP) and vegetation C stocks (Cveg) in different plant compartments. Vegetation models simulate divergent C cycle projections and have been criticised for being overly photosynthesis-driven (source-driven), neglecting processes that lead to non-linear behaviour in response to the GPP increase, which may attenuate (or amplify) changes in NPP and vegetation C stocks. Here, we introduce an analytical framework to diagnose linearity (L) of the land C cycle as the ratio of relative changes in linked fluxes and pools and apply it to outputs from 16 models of the TRENDY v11 ensemble. We found widely varying patterns in L across models and for the different links. Six models showed a clear dominance of larger relative changes in NPP than in GPP in global simulations (LNPP:GPP >1 for >60% of gridcells), indicating increased carbon use efficiency under eCO2. Only three models had LNPP:GPP < 1 for >60% of gridcells. Four models showed a clear dominance of larger relative changes in steady-state Cveg than in NPP, while five models showed an opposite pattern - in both cases with a large spread of LCveg*:NPP across gridcells within models. Three models showed a larger relative increase in root C than in Cveg, while two models showed a clear dominance of the opposite pattern. Widely differing distributions of L across models and links reveal a strong influence of alternative process representations (nonlinear behaviour) in individual models. However, for all links, L deviations from 1 were roughly balanced across the model ensemble, leading to an overall linear behaviour of terrestrial C cycle representations.

ecology↗

bioRxiv2025

China Autism Brain Imaging Consortium: Charting Brain Growth in Chinese Children with Autism

Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental condition characterized by atypical brain growth. While advances in neuroimaging and openly sharing large-sample datasets such as the Autism Brain Imaging Data Exchange (ABIDE) have improved understanding of ASD, most studies focus on adolescents and adults, with early brain development-critical for diagnosis and intervention-remaining underexplored. Existing research predominantly involves Western samples, offering limited insight and generalizability into non-Caucasian populations. We introduce the China Autism Brain Imaging Consortium (CABIC) (https://php.bdnilab.com/resources/), a grassroots effort by researchers across the country to aggregate previously collected multi-site structural MRI datasets and phenotypic information from 1,451 autistic children and 1,119 typically developing children, covering an age range from early childhood to school age (1.0 - 12.92 years). Here, we present this resource and depict brain growth charts to push forward a more comprehensive understanding of the brain development in Chinese autism children. We constructed brain growth charts that reveal a developmental shift in autistic children, transitioning from early overgrowth to delayed maturation. Regional analyses identified distinct atypical trajectories across specific brain regions. Individual deviation scores quantified inter-subject variability, characterizing the heterogeneity of brain development in ASD. Comparative analyses between CABIC and ABIDE highlighted differences potentially attributable to ethnicity and culture, advancing our understanding of cross-population neurodevelopmental diversity. CABIC MRI datasets will be shared publicly to foster investigation of the potential neural mechanisms underlying ASD in non-Western populations and support efforts toward precision medicine for autistic individuals across diverse backgrounds.

neuroscience↗

bioRxiv2024

Genomic evolution of pancreatic cancer at single-cell resolution

We adapted a previously developed targeted single-nucleus DNA sequencing (snDNA-seq) method and constructed a new suite of computational analysis tools to study 137,491 single-nucleus DNA libraries from 24 pancreatic cancers collected under a variety of clinical scenarios including early and late diagnoses, different metastatic sites and before- and after-treatment. We refined the mutational landscape of pancreatic cancer by capturing events missed by bulk sequencing, and validated the evolution pattern of early fixation of driver single-nucleotide variants (SNVs) followed by generation of intratumoral heterogeneity for copy number variations (CNVs). Intertumoral convergent evolution was common, including subclonal inactivation of TGF-{beta} pathway by mutating various components of it; intratumoral convergence was rarely observed, likely due to strong selective force in pancreatic cancer development. Continuous evolution was frequently seen manifesting as CNVs. In the context of non-targeted treatments, no particular pattern was found across metastases or through treatment. In six pancreatic cancers with germline BRCA2 mutation, we discovered varied timing of biallelic inactivation of BRCA2, which sculpted different evolutionary trajectories and could presumably contribute to differential response to treatment. As the first large-scale application of targeted snDNA-seq on pancreatic cancer, this work provides a sample processing and computational analysis pipeline that warrants further clinical utility.

cancer biology↗

bioRxiv2023

Spatio-temporal patterns of ovarian development and VgR gene silencing reduced fecundity of parthenogenetic Artemia

Halophilic zooplankton brine shrimp Artemia has been used as an experimental animal in multidisciplinary research. However, the reproductive patterns and regulation mechanisms of Artemia remain a mystery. In this study, the ovarian development process of parthenogenetic Artemia (P. Artemia) was distinguished into five stages, and oogenesis or egg formation process was identified with six phases. The mode of oogenesis was assumed polytrophic. Moreover, we traced the dynamic translocation of germline stem cells (GSCs) by EdU labeling, elucidated several key cytological events in oogenesis through HE staining and florescent image. Notably, distinguished from the ovary structure of insects and crustaceans, P. Artemia germarium originated from ovariole buds and located in the base of the ovarioles. RNA-seq based on five stages of ovarian development revealed that 2657 up-regulated genes related to reproduction were obtained by pair-to-pair comparison of RNA-seq. Furthermore, Gbb, Dpp, piwi, vasa, nanos, VgA and VgR associated with GSCs recognition and reproductive development genes were screened and also verified by qPCR. Silencing of the VgR gene in P. Artemia (PA-VgR) at stage L of ovarian development led to a low level of gene expression (<10%) within five days, which resulted variations of oogenesis-related gene expression and significantly inhibited vitellogenesis, impeded oocyte maturation, and eventually decreased the offspring number. In conclusion, we illustrated the patterns of ovarian development, outlined the key spatio-temporal features of oogenesis and established a platform for gene function research using P. Artemia as an experimental animal. These results lay the foundation for studying the reproductive biology of invertebrates, may also provide a novel insight in the reproductive regulation mechanism of aquatic animals in extreme environments. SUMMARY STATEMENTArtemia is a novel experimental platform and potential "model" crustacean for studying specific process and mechanism of reproduction.

developmental biology↗

bioRxiv2019

Integrative single-cell and bulk RNA-seq analysis in human retina identified cell type-specific composition and gene expression changes for age-related macular degeneration

Age-related macular degeneration (AMD) preferentially affects distinct cell types and topographic regions in retina. To characterize the impact of AMD on gene expression changes across retinal cell types and regions, we generated both single-cell RNA-seq (scRNA-seq) and bulk RNA-seq data from macular and peripheral retina in postmortem human donors with and without AMD. The scRNA-seq data revealed 11 major cell types with many previously reported AMD risk genes showing substantial cell type and region specificity. Cell type proportional changes with advancing AMD stage were significant for Muller glia, rods, astrocytes, microglia and endothelium.

genomics↗

bioRxiv2019

Selective Activation of TASK-3-containing K+ Channels Reveals Their Therapeutic Potentials in Analgesia

The paucity of selective agonists for TASK-3, a member of two-pore domain K+ (K2P) channels, has contributed to our limited understanding of its biological functions. By targeting a novel druggable transmembrane cavity using a structure-based drug design approach, we discovered a biguanide compound, CHET3, as a highly selective allosteric activator for TASK-3-containing K2P channels, including TASK-3 homomer and TASK-3/TASK-1 heteromer. CHET3 displayed unexpectedly potent analgesic effects in vivo in a variety of acute and chronic pain models in rodents that could be abolished by pharmacology or genetic ablation of TASK-3. We further found that TASK-3-containing channels anatomically define a unique subset population of small-sized, TRPM8, TRPV1 or tyrosine hydroxylase-positive nociceptive sensory neurons and functionally regulate their membrane excitability, supporting CHET3 analgesia in thermal hyperalgesia and mechanical allodynia under chronic pain. Overall, our proof-of-concept study reveals TASK-3-containing K2P channels as a novel druggable target for treating pain.\n\nOne Sentence SummaryIdentification of a novel drug target and its new hit compounds for developing new-generation non-opioid analgesics.

pharmacology and toxicology↗

bioRxiv2018

Functional In vivo Single-cell Transcriptome (FIST) Analysis Reveals Molecular Properties of Light-Sensitive Neurons in Mouse V1

Vision formation is classically based on projections from the retinal ganglion cells (RGC) to the lateral geniculate nucleus (LGN) and the primary visual cortex (V1). Although the cellular information of the retina and the LGN has been widely studied, the transcriptome profiles of single neurons with specific functions in V1 still remain unknown. Some neurons in mouse V1 are tuned to light stimulus. To determine the molecular properties of light-stimulated neurons in layer 2/3 of V1, we developed a method of functional in vivo single-cell transcriptome (FIST) analysis that integrates sensory evoked calcium imaging, whole-cell electrophysiological patch-clamp recordings, single-cell mRNA sequencing and three-dimensional morphological characterization in a live mouse, based on a two-photon microscope system. In our study, 58 individual cells from layer 2/3 of V1 were identified as either light-sensitive (LS) or non-light-sensitive (NS) by single-cell light-evoked calcium evaluation and action potential spiking. The contents of every single cell after individual functional tests were aspirated through the patch-clamp pipette for mRNA sequencing. Furthermore, the three-dimensional (3-D) morphological characterizations of the neurons were reconstructed in the live mouse after the whole-cell recordings. Our sequencing results indicated that V1 neurons with high expression of genes related to transmission regulation, such as Rtn4r, Nr4a1, and genes involved in membrane transport, such as Na+/K+ ATPase, NMDA-type glutamatergic receptor, preferentially respond to light stimulation. Our findings demonstrate the ability of FIST analysis to characterize the functional, morphological and transcriptomic properties of a single cell in alive animal, thereby providing precise neuronal information and predicting its network contribution in the brain.

neuroscience↗