Influence of mainland China’s industrial structure evolution on the development of Cross-Strait trade: the grey relational analysis (2011–2020)

Because of the complex and special political relationship between Mainland China and Taiwan. Cross-Strait trade is influenced by many variables, there has been a view that trade relations between Mainland China and Taiwan are more influenced by political factors. However, between the Cross-Strait, the trade volume has generally shown an upward development trend, especially since 2001. Therefore, the political factors can hardly explain the facts, and economic factors, especially industrial structure factors in Mainland China play an important role in Cross-Strait trade. Based on the small sample data since 2001, this study employed Grey Relational Analysis （GRA） method to verify the evolution of Mainland China’s industrial structure and Cross-Strait trade. Based on the results show that the evolution of Mainland China’s industrial structure strongly impacts the development of Cross- Strait trade. The tertiary industry has the strongest correlation with Cross-Strait trade, followed by the secondary and primary industries. Furthermore, the evolution of the mainland’s industrial structure will expand as well as accelerate the imbalance of Cross-Strait trade

Attenuation of RNA polymerase II pausing mitigates BRCA1-associated R-loop accumulation and tumorigenesis.

Most BRCA1-associated breast tumours are basal-like yet originate from luminal progenitors. BRCA1 is best known for its functions in double-strand break repair and resolution of DNA replication stress. However, it is unclear whether loss of these ubiquitously important functions fully explains the cell lineage-specific tumorigenesis. In vitro studies implicate BRCA1 in elimination of R-loops, DNA-RNA hybrid structures involved in transcription and genetic instability. Here we show that R-loops accumulate preferentially in breast luminal epithelial cells, not in basal epithelial or stromal cells, of BRCA1 mutation carriers. Furthermore, R-loops are enriched at the 5' end of those genes with promoter-proximal RNA polymerase II (Pol II) pausing. Genetic ablation of Cobra1, which encodes a Pol II-pausing and BRCA1-binding protein, ameliorates R-loop accumulation and reduces tumorigenesis in Brca1-knockout mouse mammary epithelium. Our studies show that Pol II pausing is an important contributor to BRCA1-associated R-loop accumulation and breast cancer development

3-D modeling and molecular dynamics simulation of interleukin-22 from the So-iny mullet, Liza haematocheila

Background: Interleukin-22 (IL-22) plays an important role in the regulation of immune responses. However, little is known about its function or structure in fish. Results: The IL-22 gene was first cloned from So-iny mullet ( Liza haematocheila ), one of commercially important fish species in China. Then, 3-D structure model of the mullet IL-22 was constructed by comparative modeling method using human IL-22 (1M4R) as template, and a 5 ns molecular dynamics (MD) was studied. The open reading frame (ORF) of mullet IL-22 cDNA was 555 bp, encoding 184 amino acids. The mullet IL-22 shared higher identities with the other fish IL-22 homologs and possessed a conserved IL-10 signature motif at its C-terminal. The mullet IL-22 model possessed six conserved helix structure. PROCHECK, SAVES and Molprobity server analysis confirmed that this model threaded well with human IL-22. Strikingly, analysis with CastP, cons-PPISP server suggested that the cysteines in mullet IL-22 might not be involved in the forming of disulfide bond for structural stabilization, but related to protein-protein interactions. Conclusions: The structure of IL-22 in So-iny mullet (Liza haematocheila) was constructed using comparative modeling method which provide more information for studying the function of fish IL-22

Identification of immune infiltration and cuproptosis-related molecular clusters in tuberculosis

BackgroundTuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb) infection. Cuproptosis is a novel cell death mechanism correlated with various diseases. This study sought to elucidate the role of cuproptosis-related genes (CRGs) in TB.MethodsBased on the GSE83456 dataset, we analyzed the expression profiles of CRGs and immune cell infiltration in TB. Based on CRGs, the molecular clusters and related immune cell infiltration were explored using 92 TB samples. The Weighted Gene Co-expression Network Analysis (WGCNA) algorithm was utilized to identify the co-expression modules and cluster-specific differentially expressed genes. Subsequently, the optimal machine learning model was determined by comparing the performance of the random forest (RF), support vector machine (SVM), generalized linear model (GLM), and eXtreme Gradient Boosting (XGB). The predictive performance of the machine learning model was assessed by generating calibration curves and decision curve analysis and validated in an external dataset.Results11 CRGs were identified as differentially expressed cuproptosis genes. Significant differences in immune cells were observed in TB patients. Two cuproptosis-related molecular clusters expressed genes were identified. Distinct clusters were identified based on the differential expression of CRGs and immune cells. Besides, significant differences in biological functions and pathway activities were observed between the two clusters. A nomogram was generated to facilitate clinical implementation. Next, calibration curves were generated, and decision curve analysis was conducted to validate the accuracy of our model in predicting TB subtypes. XGB machine learning model yielded the best performance in distinguishing TB patients with different clusters. The top five genes from the XGB model were selected as predictor genes. The XGB model exhibited satisfactory performance during validation in an external dataset. Further analysis revealed that these five model-related genes were significantly associated with latent and active TB.ConclusionOur study provided hitherto undocumented evidence of the relationship between cuproptosis and TB and established an optimal machine learning model to evaluate the TB subtypes and latent and active TB patients

Identifying early blood glucose trajectories in sepsis linked to distinct long-term outcomes: a K-means clustering study with external validation

BackgroundBlood glucose (BG) dysregulation, including hyperglycemia, hypoglycemia and increased glycemic variability (GV), is common in septic patients and potentially associated with poor clinical outcomes. However, the prognostic value of early BG trajectories remains unclear. We intend to investigate the association between the early dynamic trajectory of BG and 1-year mortality among sepsis patients.MethodsThis retrospective study comprises a derivation cohort of sepsis patients admitted to the First Affiliated Hospital of Sun Yat-sen University (FAH-SYSU) from January 2018 to December 2023, and an external validation cohort of 10,874 sepsis patients from the Medical Information Mart for Intensive Care (MIMIC) IV database. Distinct clusters were demarcated using K-means clustering based on the BG trajectory within the first 48 hours after ICU admission, while the optimal number of clusters was determined by a consensus of quantitative metrics and the elbow plot. Kaplan-Meier survival curves and multivariable Cox proportional hazards regression models were used to assess the association between these identified clusters and 1-year mortality.ResultsAmong 3,655 sepsis patients from the FAH-SYSU dataset, we identified 5 distinct clusters of BG trajectories, which were significantly associated with 1-year mortality risk. In the full Cox regression model, patients with “low-stable” and “moderate-stable” trajectories had the lowest 1-year mortality risk (P = 0.077). Conversely, patients with a “high-stable” trajectory (HR: 1.61, 95% CI: 1.35-1.92, P < 0.001) and those exhibiting unstable trends had significantly higher mortality risks (“high-decreasing”, HR: 1.38, 95% CI: 1.16-1.65, P < 0.001; “moderate-increasing”, HR: 1.37, 95% CI: 1.18-1.60, P < 0.001). External validation found consistent clusters with similar mortality trends. Restricted cubic spline analysis demonstrated a U-shaped association for mean glucose levels and a J-shaped relationship for GV linked to 1-year mortality risks, while an optimal glycemic range of 122 to 160 mg/dL and GV less than 0.18 indicated improved survival.ConclusionEarly BG trajectory patterns are independently associated with long-term mortality in sepsis patients. Incorporating dynamic BG measurements into clinical practice may improve risk stratification and guide individualized glucose management strategies

Attenuation of RNA polymerase II pausing mitigates BRCA1-associated R-loop accumulation and tumorigenesis

Most BRCA1-associated breast tumours are basal-like yet originate from luminal progenitors. BRCA1 is best known for its functions in double-strand break repair and resolution of DNA replication stress. However, it is unclear whether loss of these ubiquitously important functions fully explains the cell lineage-specific tumorigenesis. In vitro studies implicate BRCA1 in elimination of R-loops, DNA-RNA hybrid structures involved in transcription and genetic instability. Here we show that R-loops accumulate preferentially in breast luminal epithelial cells, not in basal epithelial or stromal cells, of BRCA1 mutation carriers. Furthermore, R-loops are enriched at the 50 end of those genes with promoter-proximal RNA polymerase II (Pol II) pausing. Genetic ablation of Cobra1, which encodes a Pol II-pausing and BRCA1-binding protein, ameliorates R-loop accumulation and reduces tumorigenesis in Brca1-knockout mouse mammary epithelium. Our studies show that Pol II pausing is an important contributor to BRCA1-associated R-loop accumulation and breast cancer development

Mortality among People Living with HIV and AIDS in China: Implications for Enhancing Linkage.

To assess the patterns and predictors of AIDS-related mortality and identify its correlates among adult people living with HIV/AIDS (PLWHA) in China, a retrospective record-based cohort study was conducted among 18 years or older PLWHA, who had at least one follow up reported to the national database between January-1989 and June-2012. Cumulative Incidence Function was used to calculate AIDS-related mortality rate. Gray's test was used to determine the variation in cumulative incidence across strata. The Fine and Gray model was used to measure the burden of cumulative incidence of AIDS-related mortality and strength of its association with potential correlates. Among 375,629 patients, 107,634 died during study period, of which 54,759 (50.87%) deaths were AIDS-related. Cumulative mortality rates of AIDS-related death at one, two, five, 10 and 15 years post-diagnosis were 5.7%, 8.2%, 14.3%, 22.9% and 30.9%, respectively. Among PLWHA, male gender, ethnic minority and having AIDS were associated with significantly higher mortality. Further, homosexual transmission, being on ART and increasing CD4-testing frequency were associated with lower mortality. To reduce mortality among PLWHA, efficient interventions targeting males, ethnic minority, heterosexually infected and AIDS patients should be combined with immunologic monitoring, enhancement of coverage of HIV-testing and ART