PubMed Health⌕ Search

Biomedical subjects

Li Xu

Publications and source records attributed to Li Xu.

7 recordsLinked to original sources
PubMed2026

Transcription factor NtELF3 promotes the polyphenol accumulation by targeting NtFLS-1 and NtCHIL-2 genes in tobacco.

Tobacco (Nicotiana tabacum L.) is an important economic crop, from which polyphenols are crucial for regulating its growth and development as well as shaping its quality. However, few genes associated with polyphenol accumulation have been cloned from tobacco, and the molecular mechanisms underlying this process remain poorly understood. Here, we found that the tobacco transcription factor EARLY FLOWERING 3 (NtELF3), which is highly expressed in tobacco leaves, positively regulates the accumulation of chlorogenic acid, neochlorogenic acid, cryptochlorogenic acid, rutin, scopoletin, and total polyphenols in tobacco middle leaves. The metabolomic and transcriptomic analyses of middle leaves showed that a total of 177 differentially accumulated metabolites and 7409 differentially expressed genes (DEGs) were identified in ntelf3-1 mutant versus wild type, respectively. Further investigation identified that 17 DEGs were involved in phenylpropanoid metabolic and flavonoid metabolic processes. Combined analysis indicated that the phenylpropanoid and flavonoid biosynthesis pathways were also co-enriched in kyoto encyclopedia of genes and genomes enrichment analysis. Molecular biology experiment demonstrated that NtELF3 directly binds to the promoters of NtFLS-1 and NtCHIL-2 that are both associated with phenylpropanoid and flavonoid biosynthesis, and promotes their expression. Taken together, our results not only provide new theoretical support for in-depth understanding of the regulatory mechanisms underlying polyphenol accumulation in tobacco, but also offer excellent genes and germplasm resources for tobacco quality breeding.

NtCHIL↗
PubMed2026

The association of 25-hydroxyvitamin D deficiency with neuroinflammation and prognosis in HIV-negative cryptococcal meningitis.

BACKGROUND: Cryptococcal meningitis (CM) in HIV-negative individuals is increasing, yet the role of vitamin D remains unclear. This study investigates serum 25-hydroxyvitamin D [25(OH)D] levels and their clinical implications in HIV-negative CM patients. METHODS: We conducted a retrospective case-control study of 93 HIV-negative CM patients and 191 healthy controls (HCs). Serum 25(OH)D levels, cerebrospinal fluid (CSF) fungal burden, cytokine profiles, the incidence of postinfectious inflammatory response syndrome (PIIRS), and one-year mortality were assessed. Bivariate logistic regression models identified predictors of mortality. RESULTS: CM patients had significantly lower serum 25(OH)D levels than HCs (18.33 vs. 23.69&#xa0;ng/mL, p&#xa0;<&#xa0;0.001), with a higher rate of deficiency (<20&#xa0;ng/mL) in the CM group (59.14% vs. 34.03%, p&#xa0;<&#xa0;0.001). Lower 25(OH)D levels were associated with elevated CSF levels of IL-6 and IL-8 (p&#xa0;<&#xa0;0.05). Deficiency was linked to increased PIIRS incidence (43.64% vs. 21.05%, p&#xa0;=&#xa0;0.028). Bivariate logistic regression showed a protective trend for 25(OH)D levels (OR 0.939, 95% CI 0.877-1.006, p&#xa0;=&#xa0;0.075), although deficiency was not associated with higher mortality. CONCLUSIONS: Serum 25(OH)D deficiency is prevalent in HIV-negative CM patients and linked to neuroinflammation and increased risk of PIIRS. Serum 25(OH)D levels may serve as a useful prognostic marker, although further research is needed.

Humans↗
PubMed2026

Bioinformatic analysis reveals the potential association of ESRP1 with the splicing of cytoskeleton-associated genes in doxorubicin-resistant MCF7 breast cancer cells.

BACKGROUND: Breast cancer remains one of the most prevalent malignancies among women, with doxorubicin resistance posing a significant challenge that undermines treatment success and survival outcomes. Aberrant alternative splicing (AS), driven by dysregulation or mutations in splicing factors (SFs), is implicated in cancer initiation, progression, and drug resistance. This study aims to investigate the association of the epithelial cell-specific splicing factor ESRP1 with doxorubicin resistance in breast cancer, focusing on how ESRP1 deficiency correlates with AS changes that promote chemoresistance. METHODS: We analyzed RNA-sequencing (RNA-seq) data from doxorubicin-resistant (MCF7-DR) and parental (MCF7) breast cancer cell lines to identify enhanced alternative splicing events (ASEs) and changes in ESRP1 expression; we further leveraged The Cancer Genome Atlas (TCGA)-BRCA cohort to construct an SF-RASE correlation network for screening core SFs (including ESRP1). An integrative analysis combining crosslinking immunoprecipitation (CLIP-seq) data and The Cancer Genome Atlas (TCGA) database was performed to validate ESRP1 binding targets and assess the association between ESRP1-related splicing and cytoskeleton organization. RESULTS: We observed extensive AS changes and significantly downregulated ESRP1 expression in MCF7-DR cells. Integrative analysis identified 61 high-confidence ASEs that correlate with ESRP1 expression. Further bioinformatic integration suggests that ESRP1 expression is associated with the splicing patterns of SPTBN1, MAP2K7, FGFR3, and CYB561A3-four genes involved in cytoskeleton organization-though direct experimental verification to confirm a causal regulatory relationship between ESRP1 and the splicing of these genes is still pending. CONCLUSIONS: Our findings suggest that ESRP1 expression is closely associated with doxorubicin resistance in breast cancer cells, with concomitant alterations in key ASEs linked to cytoskeletal remodeling that correlate with ESRP1. Exploring the ESRP1-related splicing network may offer new strategies to overcome chemoresistance and improve patient outcomes. However, the small cell line sample size (n&#x2009;=&#x2009;2 per group) constrains the robustness of ASE and SF-ASE correlation findings, and these results should be interpreted with caution and require further validation with larger sample cohorts.

Alternative splicing↗
PubMed2026

A single-nucleus and spatial transcriptomic atlas of poplar leaves reveals the regulation of leaf polarity and cuticle deposition.

Leaf adaxial-abaxial polarity is fundamental for plant morphogenesis and environmental adaptation through asymmetric cell differentiation. Emerging evidence reveals dorsoventral metabolic gradients act downstream of transcriptional networks to fine-tune cellular specialization. While conserved transcription factors (e.g., HD-ZIP III and KANADI) establish initial polarity, the molecular networks driving position-specific cellular differentiation and their integration with metabolic adaptation remain unclear. Leveraging single-nucleus and spatial transcriptomics, we resolve major cell classes (mesophyll, epidermal, and vascular-associated) and their adaxial-abaxial subtypes, revealing dorsoventral polarity in transcriptional profiles and metabolic pathways. Adaxial cells are enriched in phenylpropanoid/flavonoid biosynthesis, while abaxial cells show preferential activation of stress and hormone signaling. Notably, we identify MYC2 as a key regulator of adaxial cuticle biosynthesis, binding to promoters of lipid biosynthetic and transport genes (e.g., CER10 and LTPG1) and promoting cuticle thickening. Our study uncovers how positional identity shapes transcriptional and metabolic polarity in leaves, with MYC2 emerging as a central regulator coordinating organ-specific adaptations. These findings provide insights into the spatial regulation of plant development and stress resilience, offering potential strategies for engineering stress-tolerant woody crops.

Plant Leaves↗
PubMed2026

A machine learning-based predictive model for radiosensitivity in nasopharyngeal carcinoma utilizing serum proteomics.

BACKGROUND: Nasopharyngeal carcinoma (NPC) remains highly sensitive to radiotherapy; however, radioresistance in a subset of patients leads to local recurrence and distant metastasis. Serum proteomics provides a minimally invasive approach to capturing dynamic physiological changes, and machine learning enables efficient construction of predictive models. This study aimed to develop and validate a serum proteomics&#x2013;based machine-learning model for predicting radiotherapy sensitivity in nasopharyngeal carcinoma (NPC). METHODS: Pretreatment serum samples from newly diagnosed NPC patients were analyzed using SELDI-TOF-MS. Differentially expressed proteins between radiosensitive and radioresistant groups were identified using limma. GO and KEGG analyses were performed to explore functional enrichment. Twelve machine-learning algorithms were used to construct predictive models, and the top-performing models were optimized through feature selection. A Random Forest model with seven features was identified as the optimal model. External validation was performed using an independent cohort with ELISA-quantified protein levels. Model performance was assessed using Receiver operating characteristic curve (ROC), calibration analysis, decision curve analysis (DCA), and 10-fold cross-validation. SHapley Additive exPlanations (SHAP) analysis was applied for model interpretability, and the final model was deployed via a ShinyAPP. RESULTS: A total of 96 differentially expressed proteins were identified, which involved multiple function and signaling pathways. The Random Forest model demonstrated the best predictive performance, achieving an area under the curve (AUC) of 0.963 in the training set and 0.975 in the validation set. Cross-validation yielded an average AUC of 0.965. DCA indicated high clinical utility across a broad threshold range, and calibration curves showed good model agreement. Seven proteins (PLXND1, GSR, PGD, PTPRC, OR2T29, ACTG2, CHAD) were selected as final features. SHAP analysis provided global and individual-level interpretability. A web-based tool was developed to facilitate clinical application. CONCLUSION: This study establishes a robust serum proteomics&#x2013;based machine-learning model capable of accurately predicting radiotherapy sensitivity in NPC. The model offers clinical interpretability and practical implementation, supporting personalized radiotherapy decision-making.

Humans↗
PubMed2024

Angiopoietin-like protein 8 directs DNA damage responses towards apoptosis by stabilizing PARP1-DNA condensates.

Upon genotoxic stresses, cells employ various DNA damage responses (DDRs), including DNA damage repair or apoptosis, to safeguard genome integrity. However, the determinants among different DDRs choices are largely unknown. Here, we report angiopoietin-like protein 8 (ANGPTL8), a secreted regulator of lipid metabolism, localizes to the nucleus and acts as a dynamic switch that directs DDRs towards apoptosis rather than DNA repair after genotoxin exposure. ANGPTL8 deficiency alleviates DNA damage and apoptosis in cells exposed to genotoxins, as well as in the liver or kidney of mice injured by hepatic ischemia/reperfusion or cisplatin treatment. Mechanistically, ANGPTL8 physically interacts with Poly (ADP-ribose) polymerase 1 (PARP1), in a PARylation-independent manner, and reduces the fluidity of PARP1-DNA condensates, thereby enhancing the pro-apoptotic accumulation of PARP1 and PAR chains on DNA lesions. However, the transcription of ANGPTL8 is gradually decreased following genotoxin treatment, partly due to downregulation of CCAAT enhancer binding protein alpha (CEBPA), presumably to avoid further cytotoxicity. Together, we provide new insights by which genotoxic stress induced DDRs are channeled to suicidal apoptosis to safeguard genome integrity.

Animals↗
PubMed2022

Kr&#xfc;ppel-like factor 5 promotes the progression of oral squamous cell carcinoma via the baculoviral IAP repeat containing 5 gene.

BACKGROUND: Kr&#xfc;ppel-like factor 5 (KLF5) is highly expressed in a variety of tumors, and our study aimed to investigate the role of KLF5 in oral squamous cell carcinoma (OSCC). METHODS: To explore the differential expression of KLF5, next-generation sequencing (NGS) and further analyses were conducted in paired premalignant and tumor tissues and adjacent normal mucosa. We then analyzed the mRNA expression data from The Cancer Genome Atlas (TCGA) and performed gene set enrichment analysis (GSEA) to predict the function of KLF5. Small interfering RNA (siRNA) targeting KLF5 was used to knock down its expression in cells and further evaluate the changes in cell apoptosis, proliferation, and migration. We predicted whether baculoviral inhibitor of apoptosis protein (IAP) repeat containing 5 (BIRC5) was the potential target gene of KLF5 via the NCBI and JASPAR databases. Furthermore, we analyzed BIRC5 expression after KLF5 knockdown and explored its function in athymic BALB/c nude mice. RESULTS: KLF5 expression in clinical samples gradually increased from normal mucosa tissues to premalignant and then to OSCC tissues. Analysis of TCGA data and GSEA also suggested that KLF5 was expressed at higher levels in OSCC and involved apoptosis and the protein 53 (P53), transforming growth factor-&#x3b2; (TGF-&#x3b2;), and wingless/integrated (Wnt) signaling pathways. Cell apoptosis was promoted, whereas proliferation and migration were inhibited after KLF5 knockdown. Furthermore, we found KLF5 transcription binding sites on the BIRC5 promoter and BIRC5 expression was inhibited after suppressing KLF5 in vitro and in vivo. CONCLUSIONS: Our findings indicate that KLF5 promotes the development of OSCC via BIRC5, and could be a potential diagnostic and therapeutic target for OSCC.

Kr&#xfc;ppel-like factor 5 (KLF5)↗