Background: s/Aims: The critical view of safety (CVS) prevents bile duct injury, but severe inflammation hinders its achievement.This study evaluated the parkland grading scale (PGS) as a real-time intraoperative predictor of CVS attainment in a Southeast Asian population, establishing standardized clinical data for future artificial intelligence applications. Methods: This prospective observational study (January–June 2025) included 88 consecutive patients undergoing laparoscopic cholecystectomy by a single surgeon. PGS was assessed upon initial laparoscopic inspection. We analyzed correlations between PGS, CVS attainment (Strasberg’s criteria), operative time, and bail-out procedures using Spearman’s correlation and multivariate logistic regression. Results: Severe inflammation (PGS grade 4–5) was observed in 31.8% of patients. PGS exhibited a strong negative correlation with CVS score (p = −0.652; p < 0.001) and strong positive correlations with operative time and blood loss. A PGS threshold of 4 accurately predicted CVS failure (area under the curve = 0.863). Bail-out procedures were necessary in 11 cases (12.5%), all occurring in the PGS ≥ 4 group. Advanced age and diabetes mellitus were independent risk factors for CVS failure. Conclusions The PGS serves as a precise intraoperative early warning system. A score ≥ 4 indicates a significant risk of CVS failure, prompting safer bail-out strategies. Additionally, this study provides a standardized dataset vital for training future autonomous surgical risk assessment models.

Objective Exploring genetic differences among geographic strains of Anopheles sinensis in China. Methods Based on the mitochondrial cytochrome oxidase subunit I(COⅠ )and ribosomal the second internal transcribed spacer(ITS2), genetic distance analyses were conducted on An. sinensis samples collected nationwide. Results Genetic differentiation was observed within An. sinensis geographic strains, primarily reflected in the genetic distances of COⅠ sequences, with some distances between samples exceeding those between closely related species. However, ITS2 sequences showed relatively low levels of differentiation within geographic strains. No significant separation was observed, and gene exchange exhibited a random pattern among geographic strains. Conclusions Significant differences in genetic distance were observed among An. sinensis samples, along with evidence of interspecific continuity among sibling species. For the identification of closely related species using wild-collected Anopheles mosquitoes samples, reliance solely on commonly used barcodes such as COⅠ and ITS2 may be insufficient. Additional molecular markers, including COⅡ and D3 gene fragments, should also be considered. Caution should be exercised when using COⅠ genes to identify cryptic species, especially within Anopheles mosquitoes.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

OBJECTIVE: To investigate the molecular mechanism and explore blood transfusion strategies for a proband exhibiting the JK (a-b-) phenotype and anti-JK³ high frequency antigen antibody and her eight family members. METHODS: The Kidd blood phenotype and irregular antibodies in a family were identified by serologic tests. Exon 4-11 and intron region of SLC14A1 gene were sequenced by Sanger method. RESULTS: The combination of the gene JK*B (c.499A>G,c.512G>A,c.588A>G) and gene JK*B (c.342-1G>A,588A>G) in this family were considered to result in the JK (a-b-) phenotype in two members. The members carrying gene JK*A(c.130G>A,588A>G) all present serological JK^a+W. Members carrying gene JK*B (c.499A>G,c.588A>G) all present serological JK^b+W, which has not been previously reported to cause antigenic weakening. The proband with JK (a-b-) phenotype produced anti-JK³ antibodies, the hospital formulated a number of blood preparation strategies for the patient and she was discharged after recovery. CONCLUSION In this study, the molecular mechanism of JK (a-b-) in this family was identified, the transfusion strategy of rare blood group was established in our institution preliminary, and the necessity of establishing a rare blood group bank was revealed in this region. It is suggested that JK*B (c.499A>G,c.588A>G) may be a new genetic pattern leading to the weakening of Kidd antigenicity, which lays a foundation for the study of population genetics.
Humans ; Blood Transfusion ; Female ; Kidd Blood-Group System/genetics* ; Phenotype ; Pedigree

BACKGROUND: The association of systemic inflammatory response index (SIRI) with prognosis of coronary artery disease (CAD) patients has never been investigated in a large sample with long-term follow-up. This study aimed to explore the association of SIRI with all-cause and cause-specific mortality in a nationally representative sample of CAD patients from United States. METHODS: A total of 3386 participants with CAD from the National Health and Nutrition Examination Survey (NHANES) 1999-2018 were included in this study. Cox proportional hazards model, restricted cubic spline (RCS), and receiver operating characteristic curve (ROC) were performed to investigate the association of SIRI with all-cause and cause-specific mortality. Piece-wise linear regression and sensitivity analyses were also performed. RESULTS: During a median follow-up of 7.7 years, 1454 all-cause mortality occurred. After adjusting for confounding factors, higher lnSIRI was significantly associated with higher risk of all-cause (HR = 1.16, 95% CI: 1.09-1.23) and CVD mortality (HR = 1.17, 95% CI: 1.05-1.30) but not cancer mortality (HR = 1.17, 95% CI: 0.99-1.38). The associations of SIRI with all-cause and CVD mortality were detected as J-shaped with threshold values of 1.05935 and 1.122946 for SIRI, respectively. ROC curves showed that lnSIRI had robust predictive effect both in short and long terms. CONCLUSIONS SIRI was independently associated with all-cause and CVD mortality, and the dose-response relationship was J-shaped. SIRI might serve as a valid predictor for all-cause and CVD mortality both in the short and long terms.

OBJECTIVE: To describe survival trends and global patterns of esophageal cancer (EC) using survival data from population-based cancer registries. METHODS: We systematically searched PubMed, EMBASE, Web of Science, SEER, and SinoMed databases for articles published up to 31 December 2023. Eligible EC survival estimates were evaluated according to country or region, period, sex, age group, pathology, and disease stage. RESULTS: After 2010, Jordan exhibited the highest age-standardized 5-year relative survival rates (RSRs)/net survival rates (NSRs) at 41.1% between 2010 and 2014, while India had the lowest, at 4.1%. Survival rates generally improved with diagnostic age across most countries, with significant increases in South Korea and China, of 12.7% and 10.5% between 2000 and 2017, respectively. Survival was higher among women compared to men, ranging from 0.4%-10.9%. Survival rates for adenocarcinoma and squamous cell carcinoma were similar, differing by about 4%. In China, the highest age-standardized RSRs/NSRs was 33.4% between 2015 and 2017. Meanwhile, the lowest was 5.3%, in Qidong (Jiangsu province) between 1992-1996. CONCLUSION Global EC survival rates have improved significantly in recent decades, but substantial geographical, sex, and age disparities still exist. In Asia, squamous cell carcinoma demonstrated superior survival rates compared to adenocarcinoma, while the opposite trend was observed in Western countries. Future research should clarify the prognostic factors influencing EC survival and tailor prevention and screening strategies to the changing EC survival patterns.
Humans ; Esophageal Neoplasms/mortality* ; Registries ; Male ; Female ; Survival Analysis ; Middle Aged ; Survival Rate ; Aged ; Global Health

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.