Publications by authors named "Shijia Zhu"

Article Synopsis
  • * The STIE algorithm enhances spatial transcriptome analysis by aligning it with histology images and recovering missing data from significant gaps, enabling detailed single-cell-level insights and improved clustering.
  • * STIE effectively captures cell-type-specific gene expression and reveals crucial information on cell interactions and resolution characteristics that surpasses existing methods, proving to be a more accurate tool for transcriptomic analysis.
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Over recent years, as digitalization and intelligence in oil wellbore have increased, so have the stricter requirements for wireless communication technology in terms of distance, accuracy, and portability. As a result, it's necessary to rely on more advanced and efficient wireless communication technologies to meet the industry's needs. However, traditional communication technologies such as cables and optical fibers have inherent shortcomings in construction, data interpretation, and cost.

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This study presents the initial sequencing and characterization of the complete mitochondrial genome (mitogenome) of , making the first comprehensive exploration of the mitogenome in the . Utilizing next-generation sequencing techniques, we identified a circular DNA molecule spanning 15,307 bp. The mitogenome comprises 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes, and a primary non-coding region.

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Article Synopsis
  • - Current spot-based spatial transcriptomics struggles to accurately profile single-cell transcriptomes because fixed-size spots often overlap multiple cells, leading to an inherent limitation in achieving real single-cell resolution despite improvements in spot size and computational techniques.
  • - The proposed STIE algorithm enhances transcriptomic analysis by aligning spatial data with histology images based on nuclear morphology, allowing recovery of missing cells in areas where spots overlap and facilitating true single-cell resolution and analysis at a whole-slide scale.
  • - STIE not only improves understanding of gene expression variations specific to cell types but also reveals insights into cellular morphology's role in cell typing and the nuances of cell type localization that existing methods fail to capture, outperforming conventional approaches.
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Unlabelled: Signaling rewiring allows tumors to survive therapy. Here we show that the decrease of the master regulator microphthalmia transcription factor (MITF) in lethal prostate cancer unleashes eukaryotic initiation factor 3B (eIF3B)-dependent translation reprogramming of key mRNAs conferring resistance to androgen deprivation therapy (ADT) and promoting immune evasion. Mechanistically, MITF represses through direct promoter binding eIF3B, which in turn regulates the translation of specific mRNAs.

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Somatic mutations in nonmalignant tissues accumulate with age and injury, but whether these mutations are adaptive on the cellular or organismal levels is unclear. To interrogate genes in human metabolic disease, we performed lineage tracing in mice harboring somatic mosaicism subjected to nonalcoholic steatohepatitis (NASH). Proof-of-concept studies with mosaic loss of Mboat7, a membrane lipid acyltransferase, showed that increased steatosis accelerated clonal disappearance.

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Article Synopsis
  • Somatic mutations accumulate in non-cancerous tissues with age, and their impact on metabolism in diseases like NASH is being researched in mice.
  • The study, termed MOSAICS, traced mutations in known NASH genes and identified that some mutations help reduce harmful effects of fat accumulation in the liver.
  • Key findings showed that specific gene deletions provided protection against NASH, highlighting pathways crucial for managing metabolic diseases.
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Hepatocellular carcinoma (HCC) is a leading cause of death among cirrhotic patients, for which chemopreventive strategies are lacking. Recently, we developed a simple human cell-based system modeling a clinical prognostic liver signature (PLS) predicting liver disease progression and HCC risk. In a previous study, we applied our cell-based system for drug discovery and identified captopril, an approved angiotensin converting enzyme (ACE) inhibitor, as a candidate compound for HCC chemoprevention.

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Prediction of hepatocellular carcinoma (HCC) risk is an urgent unmet need in patients with nonalcoholic fatty liver disease (NAFLD). In cohorts of 409 patients with NAFLD from multiple global regions, we defined and validated hepatic transcriptome and serum secretome signatures predictive of long-term HCC risk in patients with NAFLD. A 133-gene signature, prognostic liver signature (PLS)-NAFLD, predicted incident HCC over up to 15 years of longitudinal observation.

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Background & Aims: During liver fibrosis, tissue repair mechanisms replace necrotic tissue with highly stabilized extracellular matrix proteins. Extracellular matrix stabilization influences the speed of tissue recovery. Here, we studied the expression and function of peroxidasin (PXDN), a peroxidase that uses hydrogen peroxide to cross-link collagen IV during liver fibrosis progression and regression.

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Background & Aims: There is a major unmet need to assess the prognostic impact of antifibrotics in clinical trials because of the slow rate of liver fibrosis progression. We aimed to develop a surrogate biomarker to predict future fibrosis progression.

Methods: A fibrosis progression signature (FPS) was defined to predict fibrosis progression within 5 years in patients with hepatitis C virus and nonalcoholic fatty liver disease (NAFLD) with no to minimal fibrosis at baseline (n = 421) and was validated in an independent NAFLD cohort (n = 78).

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Article Synopsis
  • Chronic liver disease and hepatocellular carcinoma (HCC) pose significant health risks with few effective treatments, largely due to the absence of suitable experimental models for research.
  • The study introduces a human liver cell-based model that accurately reflects a clinical prognostic liver signature (PLS), which helps predict the progression of liver disease to HCC.
  • By validating the PLS with animal models and patient samples, researchers identify nizatidine, an H2 receptor blocker, as a promising treatment for advanced liver disease and as a preventive measure against HCC, revealing new therapeutic targets through advanced analysis techniques.
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Since the discovery of microRNAs (miRNAs) as a class of important regulatory molecules, miRNAs are involved in the occurrence and development of tumors. In this paper, we aimed to identify the role of miR-1274a in non-small cell lung cancer (NSCLC). The miR-1274a expression levels in four NSCLC cells and tissues from 125 patients were determined by qRT-PCR assays.

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Background: Accurate non-invasive prediction of long-term hepatocellular carcinoma (HCC) risk in advanced liver fibrosis is urgently needed for cost-effective HCC screening; however, this currently remains an unmet need.

Methods: A serum-protein-based prognostic liver secretome signature (PLSec) was bioinformatically derived from previously validated hepatic transcriptome signatures and optimized in 79 patients with advanced liver fibrosis. We independently validated PLSec for HCC risk in 331 cirrhosis patients with mixed etiologies (validation set 1 [V1]) and thereafter developed a score with clinical prognostic variables.

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Despite several technical challenges, human induced pluripotent stem cell (hiPSC)-derived organoids enable biologically and clinically relevant functional study of physiology and disease. In a recent Cell Systems article, Velazquez et al. report a novel strategy to identify regulators of multilineage organoid maturation by reverse-engineering from the global transcriptome of human tissues.

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Background: Gene expression regulators identified in transcriptome profiling experiments may serve as ideal targets for genetic manipulations in farm animals.

Results: In this study, we developed a gene expression profile of 76,000+ unique transcripts for 224 porcine samples from 28 tissues collected from 32 animals using Super deepSAGE technology. Excellent sequencing depth was achieved for each multiplexed library, and replicated samples from the same tissues clustered together, demonstrating the high quality of Super deepSAGE data.

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Murine models of chronic alcohol consumption are frequently used to investigate alcoholic liver injury and define new therapeutic targets. Lieber-DeCarli diet (LD) and Meadows-Cook diet (MC) are the most accepted models of chronic alcohol consumption. It is unclear how similar these models are at the cellular, immunologic, and transcriptome levels.

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NRXN1 undergoes extensive alternative splicing, and non-recurrent heterozygous deletions in NRXN1 are strongly associated with neuropsychiatric disorders. We establish that human induced pluripotent stem cell (hiPSC)-derived neurons well represent the diversity of NRXN1α alternative splicing observed in the human brain, cataloguing 123 high-confidence in-frame human NRXN1α isoforms. Patient-derived NRXN1 hiPSC-neurons show a greater than twofold reduction in half of the wild-type NRXN1α isoforms and express dozens of novel isoforms from the mutant allele.

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Clostridioides (formerly Clostridium) difficile is a leading cause of healthcare-associated infections. Although considerable progress has been made in the understanding of its genome, the epigenome of C. difficile and its functional impact has not been systematically explored.

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Prognostic biomarkers are vital in the management of progressive chronic diseases such as liver cirrhosis, affecting 1-2% of the global population and causing over 1 million deaths every year. Despite numerous candidate biomarkers in literature, the costly and lengthy process of validation hampers their clinical translation. Existing omics databases are not suitable for validation due to the ignorance of critical factors, i.

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Introduction: Big-data-driven drug development resources and methodologies have been evolving with ever-expanding data from large-scale biological experiments, clinical trials, and medical records from participants in data collection initiatives. The enrichment of biological- and clinical-context-specific large-scale data has enabled computational inference more relevant to real-world biomedical research, particularly identification of therapeutic targets and drugs for specific diseases and clinical scenarios.

Areas Covered: Here we overview recent progresses made in the fields: new big-data-driven approach to therapeutic target discovery, candidate drug prioritization, inference of clinical toxicity, and machine-learning methods in drug discovery.

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Summary: level data of GWAS becomes increasingly important in post-GWAS data mining. Here, we present GIGSEA (Genotype Imputed Gene Set Enrichment Analysis), a novel method that uses GWAS summary statistics and eQTL to infer differential gene expression and interrogate gene set enrichment for the trait-associated SNPs. By incorporating empirical eQTL of the disease relevant tissue, GIGSEA naturally accounts for factors such as gene size, gene boundary, SNP distal regulation and multiple-marker regulation.

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N6-Methyladenine (mdA) has been discovered as a novel form of DNA methylation prevalent in eukaryotes; however, methods for high-resolution mapping of mdA events are still lacking. Single-molecule real-time (SMRT) sequencing has enabled the detection of mdA events at single-nucleotide resolution in prokaryotic genomes, but its application to detecting mdA in eukaryotic genomes has not been rigorously examined. Herein, we identified unique characteristics of eukaryotic mdA methylomes that fundamentally differ from those of prokaryotes.

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