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Biology subjects

Wang, Z. P.

Publications and source records attributed to Wang, Z. P..

5 recordsLinked to original sources

CCT2 expression marks a translation-activated state in sporadic ALS motor neurons and is associated with functional decline

Sporadic disease accounts for about 90% of amyotrophic lateral sclerosis (ALS) cases, and its biological heterogeneity is a major contributor to the failure of trials that enroll patients under a single diagnosis. Because sporadic ALS lacks a shared genetic anchor, identifying biological signals is critical for effective patient stratification. We analyzed induced pluripotent stem cell derived motor neurons from 619 AnswerALS participants using transcriptomics, proteomics, and whole-genome sequencing and identified CCT2 as the first single-gene marker of a molecular state within sporadic ALS, providing a measurable basis for trial enrollment according to biology. We first anchored the analysis in known ALS genotypes. C9orf72 and SOD1 motor neurons did not converge on a common signature but retained genotype-specific differences that bulk postmortem tissue compresses. Scoring 391 sporadic patients along three transcriptomic axes (bioenergetic stress, cell cycle, and inflammation) resolved three states. One state was marked by CCT2, a TRiC chaperonin subunit, which distinguished it from the quiescent state with an area under the curve of 0.892. CCT2 was also elevated at the protein level and associated with the rate of ALSFRS-R decline, although this association weakened after adjustment for culture composition. Upstream regulator analysis placed this state downstream of MYC and mTORC1 activation. No germline test across 360 whole genomes explained these states. Validation using Target ALS data showed that the relationship between CCT2 and the cell cycle program was also present in postmortem cortex enriched for layer 5b projection neurons.

bioinformatics↗

EcoXAI: Autonomous Agentic Ecosystem for Explainable Artificial Intelligence and Biomedical Discovery

Motivation: As biomedical datasets and knowledge graphs continue to grow in size, complexity, and heterogeneity, navigating and extracting actionable insights from them presents a major bottleneck for researchers. There is a clear need for autonomous analytical solutions that can utilize recent advancements in agentic AI such as agent harnessing and loop engineering without introducing hallucination or workflow fragmentation. Researchers, regardless of technical expertise, need tools that streamline complex data analysis and deliver meaningful, actionable insights grounded in both data and established biomedical knowledge. EcoXAI addresses this by introducing a modular, customizable, containerized multi-agent system that structures analysis into explicit pipeline execution stages, lowering the computational barrier for clinical and translational researchers. Result: EcoXAI replaces monolithic AI text interfaces with an autonomous execution-driven framework with specialized bioinformatics agents for delivering proactive, data-driven insights grounded in established biological knowledge. Unlike purely LLM-driven or less integrated AI solutions prone to hallucinations or biologically implausible outcomes, EcoXAI's multi-agent framework, which leverages modern agentic management and explicit knowledge graph integration, provides greater transparency and verifiability in its reasoning. In our use case in drug repurposing for Alzheimer's Disease, EcoXAI evaluated 103 drug candidates and identified 79 novel candidates whose predictive models exceeded a randomized baseline, including the CCR5 antagonist Maraviroc, whose generated hypothesis was subsequently supported by the literature. These results demonstrate the potential of knowledge graph-grounded AI agents to accelerate hypothesis-driven biomedical research.

bioinformatics↗

Ectopic engraftment of nociceptive neurons derived from hPSCs for pain relief and joint homeostasis

Chronic pain arises from the interplay of inflammatory signals that activate and sensitize nociceptors within injured tissues. Most analgesics fail clinically due to their mono-targeted mechanisms. Here, we apply human pluripotent stem cell-derived nociceptive neurons (hPSC-NNs) as therapeutic agents for osteoarthritis, targeting both pain and joint degeneration. We generated sensory neurons from hPSCs and identified CD200 as a nociceptor marker. Transcriptomic and functional profiling revealed that CD200highhPSC-NNs closely resemble human nociceptors, expressing pain-relevant receptors and ion channels. Strikingly, ectopic transplantation of CD200highhPSC-NNs into the knee joint of osteoarthritic mice reduced pain and promoted bone and cartilage repair, whereas CD200low cells exhibited no benefit. Mechanistically, human and mouse proteomics suggest that CD200highhPSC-NNs act as decoys by sequestering inflammatory ligands while secreting reparative factors in joint tissues. These findings uncover a fundamental role of nociceptors in tissue repair, providing a multi-targeted, disease-modifying strategy for OA and chronic pain. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/694733v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@15f0948org.highwire.dtl.DTLVardef@5a59bforg.highwire.dtl.DTLVardef@1ba4439org.highwire.dtl.DTLVardef@1d518d1_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIhPSC-derived nociceptors (hPSC-NNs) as Decoy Engraftment for Cellular Interception and Repair (DECIR) when transplanted into the knee joint, extending beyond conventional regenerative strategies C_LIO_LICD200 serves as a clinically actionable surface marker for the purification of hPSC-NNs C_LIO_LIEctopic grafting of CD200high hPSC-NNs delivers dual benefits, alleviating pain and modulating the neuro-immune environment within joint tissues C_LIO_LIProteomic analyses reveal that CD200highhPSC-NNs sequester inflammatory mediators and secrete reparative factors to support joint homeostasis C_LI

neuroscience↗

An Integrative Study to Investigate Sex-Specific Biomarkers in Bladder Cancer Patients

Bladder cancer shows distinct sex-related patterns, with male patients experiencing significantly higher incidence and female patients facing worse survival outcomes. In this paper, we aimed to address the lack of understanding of the biological mechanisms responsible for this sex-based divergence through an integrative analysis using bladder cancer data from TCGA and GTEx. Our study analyzed various bladder cancer data types, including genomic mutation data, gene expression data, and clinical data. We conducted an in-depth study of protein-protein interactions, pathway analysis, survival analysis, and immune cell correlations. Notably, we discovered that the androgen receptor (AR) related pathways were unique to male hub genes, while the Wnt signaling pathway was unique to female hub genes. Additionally, we identified 14 hub genes with significant sex-biased survival rates, including known DLGAP5, SOX2, LAMA2, and COL5A2, as well as new discoveries of male-specific markers ERCC5, NID1, and ANK2, and female-specific RAD51C, COL22A1 and COL5A2. Furthermore, we identified four male hub genes--DAXX, IKBKB, PDGFRA, and PPARG--that overlapped with immune-related genes. The expression of these genes exhibited differential interactions with immune cells between males and females. These insights could pave the way for more personalized and effective therapeutic interventions tailored to male and female patients.

bioinformatics↗

Using GPT-4 to write a scientific review article: a pilot evaluation study

GPT-4, as the most advanced version of OpenAIs large language models, has attracted widespread attention, rapidly becoming an indispensable AI tool across various areas. This includes its exploration by scientists for diverse applications. Our study focused on assessing GPT-4s capabilities in generating text, tables, and diagrams for biomedical review papers. We also assessed the consistency in text generation by GPT-4, along with potential plagiarism issues when employing this model for the composition of scientific review papers. Based on the results, we suggest the development of enhanced functionalities in ChatGPT, aiming to meet the needs of the scientific community more effectively. This includes enhancements in uploaded document processing for reference materials, a deeper grasp of intricate biomedical concepts, more precise and efficient information distillation for table generation, and a further refined model specifically tailored for scientific diagram creation.

bioinformatics↗