Biology subjects

Pu, Z.

Publications and source records attributed to Pu, Z..

8 recordsLinked to original sources

bioRxiv2026

An information-borrowing Bayesian method for inferring high-dimensional population-level brain connectivity from small samples

Estimating population-level dependence between brain regions is challenging when the number of regions greatly exceeds the number of individuals. We introduce an information-borrowing generalized Bayesian method for high-dimensional covariance estimation from region-level brain measurements. A divide-and-conquer parameterization separates marginal variances from correlation calibrations: an empirical \emph{pilot} correlation matrix--by default, obtained by standardizing a sample covariance matrix (SCM)--provides a reference structure that is adaptively calibrated through region-specific parameters shared across pairwise correlations, reducing the number of free parameters from $\mathcal{O}(d^2)$ to $\mathcal{O}(d)$ ($d$ is the number of regions) while guaranteeing a positive-definite covariance through the inclusion of a ridge term. Horseshoe priors on the calibration parameters enable selective borrowing and shrinkage of pilot information. Under suitable conditions on pilot accuracy, we establish theoretical guarantees for covariance estimation while retaining scalability in ultra-high-dimensional settings via a low-rank likelihood representation and a Woodbury-accelerated Hamiltonian Monte Carlo algorithm. Simulations showed lower estimation error than the SCM, bagging and iteratively refined principal orthogonal complement thresholding (POETRY). Applications to a semi-synthetic cortical-thickness and ADHD resting-state fMRI data revealed significant group differences in the default-mode--visual network and somatomotor network--limbic network blocks after Benjamini--Hochberg correction.

neuroscience↗

bioRxiv2026

scSpark: an AI-assisted cloud platform for traceable interpretation of single-cell transcriptomic results

Single-cell RNA sequencing now routinely produces detailed maps of cell types and states, but interpreting a finished project remains harder than it should be. Once the analysis is done, the results are usually handed over as static reports, figure panels and supplementary tables. A biologist who later wants to revisit an annotation, recompute a cell-type proportion or check whether a pathway is specific to one group typically has to return to a bioinformatician rather than explore the data directly. We developed scSpark to close this gap. The platform takes the completed outputs of a single-cell project: cell annotations, embeddings, differential-expression tables, trajectories, cell-cell communication networks and enrichment results--and serves them through a web browser as an interactive workspace. Heavy computation stays upstream: scSpark indexes the precomputed objects under a single project structure and exposes them through six modules for cell annotation, differential analysis, trajectory exploration, cell-cell communication, functional interpretation and AI-assisted result interrogation. Every action in these modules, from a query to a label change, an export or an AI-generated summary, is linked to a specific project version, data object, parameter set and output file, so that any conclusion can be traced back to the evidence behind it. We illustrate the platform by reworking a published periodontitis dataset through this interface. scSpark does not replace upstream pipelines or expert judgement; it is a layer that makes their results easier to inspect, revise and reuse, and that turns a single-cell project from a one-off report into an interpretation others can follow and check. Significance StatementSingle-cell studies produce increasingly intricate maps of tissues, but those maps are hard to interrogate once they have been written up as static reports. scSpark tackles this post-analysis bottleneck by holding a projects annotations, marker evidence, differential results, pathways, communication networks, AI-generated summaries and publication-ready figures together in one workspace, where each item is linked to the data and settings that produced it. The platform is built to support expert decisions rather than to make them: its aim is to let researchers check, revise and reuse a result, and to see exactly how it was reached.

bioinformatics↗

bioRxiv2026

An Integrated Framework for Transcriptomic Characterization and Lorentzian Hyperbolic Visualization of a High-Risk Topological Branch in Alzheimer's Disease

AO_SCPLOWBSTRACTC_SCPLOWAlzheimers disease (AD) is a highly heterogeneous brain disorder in which molecular alterations vary across brain regions, disease stages, and patient subgroups. This study introduces an integrated analytical framework for characterizing transcriptomic variation associated with a high-risk topological branch, which was identified based on Lorentz distance in postmortem Brodmann area 36 samples from the Mount Sinai Brain Bank cohort, where over 70% of samples were in Braak stages V--VI. The framework integrates weighted gene co-expression network analysis, repeated stability-based differential expression analysis, network-level gene filtering, Gene Ontology enrichment, and nested stratified cross-validation to evaluate whether topological branch-associated genes capture biologically meaningful signals and carry predictive information for high-Braak group status. The identified gene sets were functionally enriched for neuronal development, neuron projection organization, synaptic signaling, vesicle fusion, and regulated synaptic release, suggesting that the high-risk topological branch reflects biologically relevant transcriptomic programs linked to neurodegenerative progression. Nested cross-validation further showed that the selected genes achieved measurable internal predictive performance for distinguishing high-Braak samples. As a second methodological contribution, we introduced a Lorentzian hyperbolic variant of t-distributed stochastic neighbor embedding (Lorentz t-SNE) to explore latent non-Euclidean structure in transcriptomic data. This method embeds samples in hyperbolic space, providing an alternative to Euclidean embeddings for representing hierarchical or nonlinear structures. Compared with conventional Euclidean embeddings, the proposed Lorentz t-SNE revealed a more localized organization of high-Braak samples. Together, these results demonstrate the utility of the proposed analytical framework and Lorentz t-SNE for investigating heterogeneous, potentially non-Euclidean organization in AD transcriptomes.

bioinformatics↗

bioRxiv2023

Rapid intracellular acidification is a novel plant defense response countered by the brown planthopper

The brown planthopper (BPH) is the most destructive insect pest in rice. Through a stylet, BPH secrets a plethora of salivary proteins into rice phloem cells as a crucial step of infestation. However, how various salivary proteins function in rice cells to promote insect infestation is poorly understood. Among them, one of the salivary proteins is predicted to be a carbonic anhydrase (NlCA). The survival rate of the NlCA-RNA interference (RNAi) BPH insects was extremely low on rice, indicating a vital role of this salivary protein in BPH infestation. We generated NICA transgenic rice plants and found that NlCA expressed in rice plants could restore the ability of NlCA-RNAi BPH to survive on rice. Next, we produced rice plants expressing the ratiometric pH sensor pHusion and found that NlCA-RNAi BPH induced rapid intracellular acidification of rice cells during feeding. Further analysis revealed that both NlCA-RNAi BPH feeding and artificial of lowering intracellular pH activated plant defense responses, and that NICA-mediated intracellular pH stabilization is linked to diminished defense responses, including reduced callose deposition at the phloem sieve plates and suppressed defense gene expression. Given the importance of pH homeostasis across the kingdoms of life, discovery of NICA-mediated intracellular pH modulation uncovered a new dimension in the interaction between plants and piecing/sucking insect pests. The crucial role of NICA for BPH infestation of rice suggests that NICA is a promising target for chemical or trans-kingdom RNAi-based inactivation for BPH control strategies in plants. HighlightsO_LIRapid intracellular acidification is a novel plant defense response. C_LIO_LIBrown planthopper delivers into rice tissues a major virulence protein, carbonic anhydrase (NlCA), critical for survival. C_LIO_LINlCA counters intracellular acidification to suppress plant defense. C_LIO_LIResults implicate existence of pH-responsive regulators of defense responses in the rice-brown planthopper interaction. C_LI In briefThe brown planthopper (BPH) is the most devasting insect pest in rice. Jiang et al. discovered that BPH secretes a salivary carbonic anhydrase (NICA) to regulate the intracellular pH of the rice cell to facilitate its feeding and survival on rice plants and that NICA-counters host intracellular pH acidification to diminished defense responses. These findings uncovered that intracellular pH homeostasis is a previously uncharacterized battleground in plant-insect interactions, but also open a door to future discovery of pH-responsive intracellular regulators of defense responses, which could add a new research dimension in the study of plant-biotic interactions.

plant biology↗

bioRxiv2023

Reprogramming Intrahepatic Cholangiocarcinoma Immune Microenvironment by Chemotherapy and CTLA-4 Blockade Enhances Anti-PD1 Therapy

Intrahepatic cholangiocarcinoma (ICC) has limited therapeutic options and a dismal prognosis. Anti-PD-L1 immunotherapy combined with gemcitabine/cisplatin chemotherapy has recently shown efficacy in biliary tract cancers, but responses are seen only in a minority of patients. Here, we studied the roles of anti-PD1 and anti-CTLA-4 immune checkpoint blockade (ICB) therapies when combined with gemcitabine/cisplatin and the mechanisms of treatment benefit in orthotopic murine ICC models. We evaluated the effects of the combined treatments on ICC vasculature and immune microenvironment using flow cytometry analysis, immunofluorescence, imaging mass cytometry, RNA-sequencing, qPCR, and in vivo T-cell depletion and CD8+ T-cell transfer using orthotopic ICC models and transgenic mice. Combining gemcitabine/cisplatin with anti-PD1 and anti-CTLA-4 antibodies led to substantial survival benefits and reduction of morbidity in two aggressive ICC models, which were ICB-resistant. Gemcitabine/cisplatin treatment increased the frequency of tumor-infiltrating lymphocytes and normalized the ICC vessels, and when combined with dual CTLA-4/PD1 blockade, increased the number of activated CD8+Cxcr3+IFN-{gamma}+ T-cells. Depletion of CD8+ but not CD4+ T-cells compromised efficacy. Conversely, CD8+ T-cell transfer from Cxcr3-/- versus Cxcr3+/+ mice into Rag1-/- immunodeficient mice restored the anti-tumor effect of gemcitabine/cisplatin/ICB combination therapy. Finally, rational scheduling of the ICBs (anti-CTLA-4 "priming") with chemotherapy and anti-PD1 therapy achieved equivalent efficacy with continuous dosing while reducing overall drug exposure. In summary, gemcitabine/cisplatin chemotherapy normalizes vessel structure, increases activated T-cell infiltration, and enhances anti-PD1/CTLA-4 immunotherapy efficacy in aggressive murine ICC. This combination approach should be clinically tested to overcome resistance to current therapies in ICC patients. One Sentence SummaryImmune microenvironment reprogramming by chemotherapy and priming using CTLA-4 blockade render ICCs responsive to anti-PD-1 immunotherapy.

cancer biology↗

bioRxiv2022

Integrated transcriptome and lineage analyses reveal novel catecholaminergic cardiomyocytes contributing to the cardiac conduction system in murine heart

Cardiac conduction system (CCS) morphogenesis is essential for correct heart function yet is incompletely understood. Here we established the transcriptional landscape of cell types populating the developing heart by integrating single-cell RNA sequencing and spatial enhanced resolution omics-sequencing (Stereo-seq). Stereo-seq provided a spatiotemporal transcriptomic cell fate map of the murine heart with a panoramic field of view and in situ cellular resolution of the CCS. This led to the identification of a previously unrecognized cardiomyocyte population expressing dopamine beta-hydroxylase (Dbh+-CMs), which is closely associated with the CCS in transcriptomic analyses. To confirm this finding, genetic fate mapping by using DbhCre/Rosa26-tdTomato reporter mouse line was performed with Stereo-seq, RNAscope, and immunohistology. We revealed that Dbh+-derived CMs first emerged in the sinus venosus at E12.5, then populated the atrial and ventricular CCS components at E14.5, with increasing abundance towards perinatal stages. Further tracing by using DbhCFP reporter and DbhCreERT/Rosa26-tdTomato inducible reporter, we confirmed that Dbh+-CMs are mostly abundant in the AVN and ventricular CCS and this persists in the adult heart. By using DbhCre/Rosa26-tdTomato/Cx40-eGFP compound reporter line, we validated a clear co-localization of tdTomato and eGFP signals in both left and right ventricular Purkinje fibre networks. Finally, electrophysiological optogenetic study using cell-type specific Channelrhodopsin2 (ChR2) expression further elucidated that Dbh+-derived CMs form a functional part of the ventricular CCS and display similar photostimulation-induced electrophysiological characteristics to Cx40CreERT/ChR2-tdTomato CCS components. Thus, by utilizing advanced transcriptomic, mouse genetic, and optogenetic functional analyses, our study provides new insights into mammalian CCS development and heterogeneity by revealing novel Dbh+-CMs. HighlightsO_LIStereo-seq provided a spatiotemporal transcriptomic cell fate map of the murine heart with a panoramic field of view and in situ cellular resolution of the CCS. C_LIO_LIEstablished the transcriptional landscape of cell types populating the developing murine heart. C_LIO_LIRevealed previously unreported catecholaminergic cardiomyocyte populations contributing to the developing and mature murine cardiac conduction system. C_LI

cell biology↗

bioRxiv2022

Inflammasome targeting with an NLRP3 agonist therapy is feasible but ineffective in murine hepatocellular carcinoma models with liver damage

Co-inhibition of programmed cell death receptor-1 (PD-1) and vascular endothelial growth factor receptor (VEGFR) pathway has shown efficacy in hepatocellular carcinoma (HCC). NLRP3 is a component of the inflammasome involved in the initiation, development, and progression of multiple cancers. We examined whether adding an NLRP3 agonist to dual PD-1/VEGFR inhibitors is feasible and can address treatment resistance in orthotopic HCC in mice with underlying liver damage. Mice with established tumors were treated with an NLRP3 agonist alone, combination of anti-VEGFR2 or the multikinase inhibitor regorafenib with anti-PD1 antibodies, or their combination. In all models tested, NLRP3 agonist therapy showed acceptable toxicity but no effect on tumor growth delay, disease morbidity, or survival. Pharmacodynamic analyses confirmed the effects of NLRP3 agonist therapy on inflammasome, evidenced by a significant elevation in plasma levels of pro-inflammatory cytokines such as IL-1{beta}. However, these changes were not detectable in tumor tissues, where we detected increased expression of immunosuppressive markers IL-6, KC/GRO, CCL9, and IL-18, and immune checkpoint molecules (PD1, PD-L1, and CTLA-4) after NLRP3 agonist therapy. Thus, modulation of the inflammasome with a novel NLRP3 agonist was feasible in mice with orthotopic HCC and liver damage but did not enhance efficacy when combined with anti-PD1/VEGFR therapies.

immunology↗

bioRxiv2020

The wheat 55K SNP-based exploration of loci for spikelet number per spike from a tetraploid wheat (Triticum turgidum L.) recombinant inbred line population derived from a Chinese landrace Ailanmai and a wild emmer accession

The spikelet number per spike (SNS) is a primary factor determining wheat yield. Common wheat breeding reduces the genetic diversity among elite germplasm resources, leading to a detrimental effect on future wheat production. It is, therefore, necessary to explore new genetic resources for SNS to increase wheat yield. A tetraploid landrace Ailanmai x wild emmer wheat recombinant inbred line (RIL) population was used to construct a genetic map using the wheat 55K single nucleotide polymorphism (SNP) array. The linkage map containing 1150 bin markers with a total genetic distance of 2411.8 cM was obtained. Based on phenotypic data from eight environments and best linear unbiased prediction (BLUP) values, five quantitative trait loci (QTL) for SNS were identified, explaining 6.71-29.40% of the phenotypic variation. Two of them, QSns.sau-AM-2B.3 and QSns.sau-AM-3B.2, were detected as the major and novel QTL. Their effects were further validated in two additional F2 populations using tightly linked Kompetitive Allele-Specific PCR (KASP) markers. Potential candidate genes within the physical intervals of corresponding QTL were predicted to participate in inflorescence development and spikelet formation. Genetic associations between SNS and other agronomic traits were also detected and analyzed. This study demonstrates the feasibility of wheat 55K SNP array developed for common wheat in genetic mapping of tetraploid population and shows the potential application of wheat related species in wheat improvement programs.

genetics↗