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Biomedical subjects

Lu Zhang

Publications and source records attributed to Lu Zhang.

7 recordsLinked to original sources

TNF-NF-κB signaling mediates immune-biomineralization crosstalk during shell repair under ocean acidification in Mytilus edulis.

Ocean acidification (OA) impairs biomineralization in bivalves, but its effects on immune-biomineralization crosstalk during shell repair remain unknown. Here, we exposed adult Mytilus edulis bearing standardized shell perforations to three pH levels (8.1, 7.9, and 7.7) for up to 40 days. OA slowed early repair and caused microstructural disorganization and an approximately 87% reduction of compressive strength at pH 7.7, yet the damaged area appeared largely closed by day 15, suggesting a decoupling between morphological closure and functional recovery. In addition, transcriptomic profiling of hemocytes and mantle tissue, based on an average of 6.5 Gb of clean reads per sample mapped to the M. edulis reference genome (NCBI Assembly GCF_000511035.1), revealed that these shell-level defects were accompanied by coordinated immune and metabolic reprogramming. Hemocytes, the primary immune effector cells of bivalves, exhibited pH- and time-dependent shifts with moderate acidification (pH 7.9) promoting inflammatory transcripts, whereas severe acidification (pH 7.7) suppressed these signals while upregulating stress-associated pathways; both treatments consistently downregulated lysosomal proteases and NF-κB negative regulators. The mantle, a primarily mineralizing organ, paradoxically upregulated immune-related genes while suppressing oxidative phosphorylation and extracellular matrix pathways. This tissue-level imbalance, with hemocytes recruited but functionally constrained and mantle metabolically suppressed yet immunologically activated, points to TNF-NF-κB pathway modulation as a key mediator of shell repair under acidification. Our findings demonstrate that visible shell closure masks underlying structural and mechanical failure, and that immune regulation, rather than simple suppression or activation, critically shapes the repair outcome. These results advocate for multifunctional indicators beyond closure area to assess shell integrity in acidified marine environments.

Animals

Metagenomic-based quantification of Pseudomonas aeruginosa burden links microbiome collapse to mortality in severe community-acquired pneumonia.

BACKGROUND: Severe community-acquired pneumonia (sCAP) remains a major cause of mortality in critically ill patients, Pseudomonas aeruginosa (P. aeruginosa) is a frequent pathogen associated with poor prognosis in this population. While metagenomic next-generation sequencing (mNGS) is widely used for pathogen detection, its value in quantifying pathogen abundance and linking it to lung microbiome alterations remains unclear. OBJECTIVES: This study investigated the association between P. aeruginosa abundance quantified by mNGS and lung microbiome alterations and clinical outcomes in sCAP patients. METHODS: This multicenter retrospective study included 130 patients with sCAP caused by P. aeruginosa from five hospitals (September 2021-June 2025). Patients were stratified into low, medium, and high abundance groups according to mNGS-derived reads per ten million (RPTM) values of P. aeruginosa. Lung microbiome diversity and community structure were analyzed, and differences between groups were assessed using appropriate statistical methods. The association between P. aeruginosa abundance and clinical outcomes was evaluated using correlation analysis, sankey diagram, receiver operating characteristic curve, grey zone analysis and logistic regression. RESULTS: A total of 130 patients with sCAP due to P. aeruginosa were stratified into low, medium, and high abundance groups based on mNGS-derived RPTM value. Microbial diversity decreased progressively with increasing abundance, and community structures differed significantly among groups (all P&#x2009;<&#x2009;0.05). P. aeruginosa became increasingly dominant, accounting for up to 95.99% of the microbiota in the high abundance group. Higher P. aeruginosa abundance was associated with increased disease severity, including longer mechanical ventilation, prolonged hospital stay, and higher 28-day mortality. Sankey diagram showed a progressive decline in treatment effectiveness and an increase in mortality with increasing P. aeruginosa abundance. P. aeruginosa_RPTM showed moderate predictive value for mortality (AUC&#x2009;=&#x2009;0.761, Sens&#x2009;=&#x2009;69.40%, Spec&#x2009;=&#x2009;75.30%, cutoff: 41122, grey zone: 2287-220339) and remained independently associated with 28-day mortality in multivariable analysis [2.219 (1.509 to 3.262), P&#x2009;<&#x2009;0.001]. CONCLUSION: In patients with sCAP, higher P. aeruginosa_RPTM measured by mNGS was associated with reduced lung microbiome diversity and unfavorable clinical outcomes. RPTM-based risk stratification may help identify patients at increased risk of poor prognosis.

Humans

Whole-genome evolutionary dynamics of human parainfluenza virus type 3 in Shanghai, China, 2016-2024.

&#x2022; Fifty whole-genome sequencing revealed co-circulating HPIV-3 C3 sub-lineages C3f and C3a in Shanghai, China. &#x2022; Whole-genome phylogeny dated the HPIV-3 tMRCA to &#x223c;1925.6 and revealed two post-1990 demographic expansions. &#x2022; Recombination signals detected in the HN gene and other regions may lead to discordance in partial-gene phylogenies. &#x2022; The L gene showed the highest variability and harbored the largest number of putative positively selected sites.

Letter

stDyer-image improves clustering analysis of spatially resolved transcriptomics and proteomics with morphological images.

MOTIVATION: Spatially resolved transcriptomics (SRT) and spatially resolved proteomics (SRP) data enable the study of gene expression and protein abundances within their precise spatial and cellular contexts in tissues. Certain SRT and SRP technologies also capture corresponding morphology images, adding another layer of valuable information. However, few existing methods developed for SRT data effectively leverage these supplementary images to enhance clustering performance. RESULTS: Here, we introduce stDyer-image, an end-to-end deep learning framework designed for clustering for SRT and SRP datasets with images. Unlike existing methods that utilize images to complement gene expression data, stDyer-image directly links image features to cluster labels. This approach draws inspiration from pathologists, who can visually identify specific cell types or tumor regions from morphological images without relying on gene expression or protein abundances. Benchmarks against state-of-the-art tools demonstrate that stDyer-image achieves superior performance in clustering. Moreover, it is capable of handling large-scale datasets across diverse technologies, making it a versatile and powerful tool for spatial omics analysis. AVAILABILITY AND IMPLEMENTATION: The source code of stDyer-image and detailed tutorials are available at https://github.com/ericcombiolab/stDyer-image.

Proteomics

Depth-dependent multi-kingdom microbial interactions and biogeochemical cycling genes in eutrophic shallow lake sediments.

Microorganisms are pivotal to lake ecosystem biogeochemical cycles, yet existing research often focuses on single microbial kingdoms or surface sediments, neglecting multi-kingdom interactions and depth-resolved dynamics. To address these gaps, we used metagenomic sequencing to characterize microbial communities and their functional associations across overlying water and 0-45 cm sediments in four shallow lakes of the middle Yangtze River basin, China. Despite increasing bacterial and fungal diversity with depth, the 0-9 cm surface sediments exhibited the strongest multi-kingdom network connectivity and the greatest microbial stability. Functional genes exhibited clear depth-dependent patterns: nitrogen cycling genes, including those involved in dissimilatory nitrate reduction to ammonium, were most enriched in the upper 0-9 cm of sediment; methane cycling genes were positively correlated with depth; phosphorus cycling genes and some sulfur cycling genes, such as assimilatory sulphate reduction, declined with depth. Sediment microbial assembly was dominated by deterministic processes, in which the vertical distribution of functional genes was primarily dictated by heavy metals and conventional environmental indicators. These findings highlight depth-specific multi-kingdom microbial interactions and their associations with biogeochemical cycling, advancing lacustrine microbial ecology understanding and providing references for lake conservation under environmental change.

Lakes

Reprogramming neuroblastoma by diet-enhanced polyamine depletion.

Neuroblastoma is a highly lethal childhood tumour derived from differentiation-arrested neural crest cells1,2. Like all cancers, its growth is fuelled by metabolites obtained from either circulation or local biosynthesis3,4. Neuroblastomas depend on local polyamine biosynthesis, and the inhibitor difluoromethylornithine has&#xa0;shown clinical activity5. Here we show that such inhibition can be augmented by dietary restriction of upstream amino acid substrates, leading to disruption of oncogenic protein translation, tumour differentiation and profound survival gains in the Th-MYCN mouse model. Specifically, an arginine- and proline-free diet decreases the amount of the polyamine precursor ornithine and enhances tumour polyamine depletion by difluoromethylornithine. This polyamine depletion causes ribosome stalling, unexpectedly specifically at codons with adenosine in the third position. Such codons are selectively enriched in cell cycle genes and low in neuronal differentiation genes. Thus, impaired translation of these codons, induced by combined dietary and pharmacological intervention, favours a pro-differentiation proteome. These results suggest that the genes of specific cellular programmes have evolved hallmark codon usage preferences that enable coherent translational rewiring in response to metabolic stresses, and that this process can be targeted to activate differentiation of paediatric cancers.

Animals

Clinical and Multiorgan Proteomics Characteristics of the Diverse Fatal Phase in Super Elderly Patients With SARS-CoV-2 Infection: A Descriptive Study.

This study aims to identify the risk factors associated with clinical outcomes and the proteomic changes in organs related to fatal SARS-CoV-2 infection within the super-elderly population. This retrospective analysis included all elderly individuals with COVID-19 admitted to the Second Medical Center of PLA General Hospital from December 2022 to January 2023. The follow-up period ended on March 30, 2023. During this time, epidemiological, demographic, laboratory, and outcome data were analyzed descriptively. Proteomic sequencing was performed on super-elderly patients who died from COVID-19 at different stages of the disease. A total of 352 elderly COVID-19 patients, with a mean age of 89.84&#x2009;&#xb1;&#x2009;8.54 years, were included in this study. During a median follow-up period of 98 days, 79 patients died. Deceased patients were older and more likely to have cardiovascular and cerebrovascular diseases, with a lower prevalence of lipid-lowering therapy. The number of deaths in the acute and post-acute phases were 34 and 45, respectively. Proteomics data suggest that the immune systems of patients who died in the acute phase underwent a more rapid and severe onslaught. Patients in the post-acute phase showed higher levels of viral genome replication and a more robust immune response. However, the over-activation of the immune system led to systemic organ dysfunction. Effective management of comorbidities may improve the prognosis of COVID-19 in super-elderly patients. The continuous replication of the SARS-CoV-2 virus and its subsequent impact on the immune system are critical determinants of survival time in this demographic.

Humans