Biomedical subjects

Su Wang

Publications and source records attributed to Su Wang.

3 recordsLinked to original sources

PubMed2025

Genome-Wide Identification, Phylogenetic Analysis, and Expression Pattern of Polyamine Biosynthesis Gene Family in Pepper.

Polyamines (PAs), including putrescine, spermidine, spermine, and thermospermine, play essential roles in plant growth, development, and responses to stress. However, the structure and function of PA biosynthetic genes in pepper remain poorly characterized. This study aimed to identify PA biosynthesis genes in the pepper genome using bioinformatics approaches and to assess their expression under various stress conditions. A total of 16 PA biosynthesis-related genes were identified, representing members of the arginine decarboxylase (ADC), ornithine decarboxylase (ODC), agmatine iminohydrolase (AIH), N-carbamoylputrescine amidohydrolase (CPA), S-adenosylmethionine decarboxylase (SAMDC), spermidine synthase (SPDS), spermine synthase (SPMS), and ACAULIS5 (ACL5) gene families. These genes encode proteins with an average molecular weight of approximately 40 kDa, primarily localized in the mitochondria and cytoplasm. Promoter analysis revealed multiple cis-acting elements associated with stress and phytohormone responsiveness. Gene expression was induced by various abiotic stresses, including saline-alkaline, drought, heat, cold, and hydrogen peroxide, as well as by phytohormones such as abscisic acid, ethylene, salicylic acid, auxin, and gibberellin. Overall, this study provides a comprehensive analysis of PA biosynthesis genes in pepper and highlights their potential roles in stress adaptation and hormone signalling, offering a foundation for further exploration of PA-mediated stress tolerance mechanisms.

Capsicum↗

PubMed2025

Association of cancers with the occurrence and 28-day mortality of sepsis: a mendelian randomization and mediator analysis.

Observational studies have indicated an association between cancer and the occurrence of sepsis, with an increased risk of mortality in cancer-related sepsis. However, whether a causal relationship exists between the two remains unknown. Summary statistics of thirteen cancers from the largest available genome-wide association studies (GWAS) of GWAS catalog and FinnGen biobank were extracted for the MR analysis. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. Univariable, multivariable, and reverse MR analyses were employed to explore potential associations between cancers and sepsis and its 28-day mortality. Moreover, a two-step mediation MR analysis was performed to investigate independent positive causal relationships between cancers and sepsis and its 28-day mortality. In univariable Mendelian randomization (MR) analysis, significant causal relationships were found between genetically predicted lung cancer (OR = 1.17, 95% CI = 1.08-1.26, adjusted p = 0.001), squamous cell lung carcinoma (OR = 1.10, 95% CI = 1.02-1.18, adjusted p = 0.042), lung adenocarcinoma (OR = 1.12, 95% CI = 1.03-1.21, adjusted p = 0.032), small cell lung carcinoma (OR = 1.07, 95% CI = 1.02-1.12, adjusted p = 0.031), and sepsis. Subsequent multivariable MR analysis revealed that these three types of lung cancer were independently associated with the risk of sepsis. Additionally, a causal relationship was found between lung cancer and 28-day mortality from sepsis, while no causal link was observed between non-solid tumors and the onset or death of sepsis. Reverse MR analysis did not indicate a potential for sepsis to trigger the onset of cancers. Furthermore, TRAIL was found to have promotive effects on the occurrence and mortality of sepsis. Lung cancer causally correlates with increased sepsis occurrence and 28-day mortality, as evidenced by Mendelian Randomization analysis. Genetic predispositions enhance this risk, underscoring the potential of genetic profiling to guide early, precise sepsis interventions in these patients.

Humans↗

PubMed2024

Expression profile of long noncoding RNAs and comprehensive analysis of lncRNA-cisTF-DGE regulation in condyloma acuminatum.

OBJECTIVE: To identify differentially expressed long noncoding RNAs (lncRNAs) in condyloma acuminatum (CA) and to explore their probable regulatory mechanisms by establishing coexpression networks. METHODS: High-throughput RNA sequencing was performed to assess genome-wide lncRNA expression in CA and paired adjacent mucosal tissue. The expression of candidate lncRNAs and their target genes in larger CA specimens was validated using real-time quantitative reverse transcriptase polymerase chain reaction (RT‒qPCR). Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used for the functional enrichment analysis of these candidate lncRNAs and differential mRNAs. The coexpressed mRNAs of the candidate lncRNAs, calculated by Pearson's correlation coefficient, were also analysed using GO and KEGG analysis. In addition, the interactions among differentially expressed lncRNAs (DElncRNAs)-cis-regulatory transcription factors (cisTFs)-differentially expressed genes (DEGs) were analysed and their network was constructed. RESULTS: A total of 546 lncRNAs and 2553 mRNAs were found to be differentially expressed in CA compared to the paired control. Functional enrichment analysis revealed that the DEGs coexpressed with DElncRNAs were enriched in the terms of cell adhesion and keratinocyte differentiation, and the pathways of ECM-receptor interaction, local adhesion, PI3K/AKT and TGF-ß signaling. We further constructed the network among DElncRNAs-cisTFs-DEGs and found that these 95 DEGs were mainly enriched in GO terms of epithelial development, regulation of transcription or gene expression. Furthermore, the expression of 3 pairs of DElncRNAs and cisTFs, EVX1-AS and HOXA13, HOXA11-AS and EVX1, and DLX6-AS and DLX5, was validated with a larger number of specimens using RT‒qPCR. CONCLUSION: CA has a specific lncRNA profile, and the differentially expressed lncRNAs play regulatory roles in mRNA expression through cis-acting TFs, which provides insight into their regulatory networks. It will be useful to understand the pathogenesis of CA to provide new directions for the prevention, clinical treatment and efficacy evaluation of CA.

RNA, Long Noncoding↗