Objective To explore the causal relationships between 13 micronutrients (copper, selenium, zinc, calcium, folate, iron, magnesium, vitamin A, vitamin B6, vitamin B12, vitamin C, vitamin D, and vitamin E) and risk of tuberculosis (TB) through a two-sample Mendelian randomization (MR) study. Methods The Genome-Wide Association Study (GWAS) data about micronutrients and TB were obtained from the IEU Open GWAS and FinnGen Biobank, and Bayesian Weighted Mendelian Randomization (BWMR) and Inverse Variance Weighted (IVW) methods were employed to explore the causal relationship between micronutrients and risk of TB. The robustness and reliability of the results were assessed through horizontal pleiotropy tests, heterogeneity tests, and leave-one-out sensitivity analyses. Results The BWMR results indicated that iron (OR = 0.40, 95% CI : 0.20- 0.79, P = 0.008) and vitamin C (OR = 0.42, 95% CI : 0.20 - 0.87, P = 0.019) were protective factors against TB infection, while no causal relationships were found between other micronutrients with TB infection. The IVW method produced consistent results with BWMR. The results for other micronutrients were robust and reliable (P > 0.05), except for calcium-related Instrumental Variables (IVs), which exhibited heterogeneity (P < 0.05). Conclusion Iron and vitamin C may play a protective role in reducing the risk of TB, whereas the remaining micronutrients show no significant causal relationship with TB.

Objective:To investigate the current status of standardized residency training (SRT) teaching activities at Zhongshan Hospital affiliated to Fudan University, and to explore optimization strategies.Methods:We collected behavioral data from the SRT course selection platform and resident questionnaire survey data throughout 2024. Descriptive analysis, chi-square test, Mann-Whitney U test, and multivariable logistic regression analysis were performed. Results:A total of 170 teaching sessions were conducted in 2024, with interactive practice-based sessions accounting for 42.35% and lecture-based sessions accounting for 47.06%. According to 536 questionnaires, residents' overall satisfaction with teaching activities scored 87.83 points (high satisfaction, ≥85 points; moderate satisfaction, <85 points). The proportion of high satisfaction with interactive practice-based sessions was significantly higher than that with lecture-based sessions (82.81% vs. 75.46%, P=0.034). The enrollment for weekday evening courses filled up significantly faster than that for weekday daytime courses [4 (2, 6) seconds vs. 12 (8, 15) seconds, P<0.001]. Interactive practice-based sessions [odds ratio ( OR)=1.6, 95% CI=1.1-2.3, P=0.018] and weekday evening sessions ( OR=1.4, 95% CI=1.0-2.0, P=0.048) significantly improved resident satisfaction. Conclusions:Optimizing course formats and scheduling can enhance the quality of SRT teaching activities.

Due to its high sensitivity and non-destructive nature, Raman spectroscopy has become an essential analytical tool in biopharmaceutical analysis and drug development. Despite of the computational demands, data requirements, or ethical considerations, artificial intelligence (AI) and particularly deep learning algorithms has further advanced Raman spectroscopy by enhancing data processing, feature extraction, and model optimization, which not only improves the accuracy and efficiency of Raman spectroscopy detection, but also greatly expands its range of application. AI-guided Raman spectroscopy has numerous applications in biomedicine, including characterizing drug structures, analyzing drug forms, controlling drug quality, identifying components, and studying drug-biomolecule interactions. AI-guided Raman spectroscopy has also revolutionized biomedical research and clinical diagnostics, particularly in disease early diagnosis and treatment optimization. Therefore, AI methods are crucial to advancing Raman spectroscopy in biopharmaceutical research and clinical diagnostics, offering new perspectives and tools for disease treatment and pharmaceutical process control. In summary, integrating AI and Raman spectroscopy in biomedicine has significantly improved analytical capabilities, offering innovative approaches for research and clinical applications.

Objective: To explore the clinical manifestations and treatment plans of chronic recurrent parotitis (CRP), and to provide a reference for the clinical diagnosis and treatment of CRP. Methods: Approval was obtained from the hospital’s Medical Ethics Committee, and a retrospective analysis and summary of the clinical features, imaging characteristics, diagnosis, and treatment of 41 CRP patients with complete data were performed. Results: Among the 41 patients with CRP, 14 were male and 27 were female, with a male-to-female ratio of approximately 1:2 (14/27). The age at first-time onset ranged from 3 to 23 years, with a median age of 6 years, and there were 38 patients (92.7%, 38/41) with the first onset age of under 18 years old. The age of the first visit to our hospital ranged from 4 to 72 years old, with an average age of (41.0 ± 17.3) years; the disease duration was 0.5 to 66 years, with an average of 35.0 ± 16.1 years. Twenty-five cases had bilateral parotid gland involvement (61.0%, 25/41). The clinical manifestations of CRP are repeated swelling of one or both parotid glands, along with discomfort, and this may be accompanied by mild edema or skin flushing and pus or jelly-like secretions at the duct openings. The typical manifestations of parotid angiography are: the dominant duct and branch ducts of the parotid gland do not have specific dilation or narrowing, and the peripheral ducts show characteristic “punctate, spherical, or cavitary” dilation and delayed emptying. Of the cases, 34 had abnormal enlargement of the main duct orifice (82.9%, 34/41), and 37 presented with abnormal anterior displacement of the accessory glands (90.2%, 37/41). The treatment plan of “antibiotic perfusion + aspiration and removal of obstruction (or aspiration after obstruction dissolution)+ postprandia massage along the direction of the parotid duct (from posterior to anterior) with multiple courses for consolidation”achieved favorable outcomes. The mean follow-up period of this group was(71.1+21.9)months, and no recurrence was observed during the follow-up period. Conclusion CRP is more prevalent in young females and frequently presents with bilateral involvement. Congenital anatomical defects, such as abnormal enlargement of the main duct orifice and abnormal anterior displacement of the accessory glands, are important predisposing factors. The multi-course comprehensive therapy centered on antibiotic infusion, removal and dissolution of obstructions, and post-prandial massage along the direction of the parotid duct has significant therapeutic effects and deserves clinical application.

Objective To construct a quality control model for cervical liquid-based thin cell smears using two different artificial intelligence(AI)techniques and to compare the total use of the two methods to improve the level of quality control of cervical liquid-based thin cell smears through the assistance of hybrid AI.Methods In this study,105 cervical liquid-based thin cell smear samples were used.Convolutional neural network(CNN)algorithm and Transformer network algorithm were used as specific AI algorithms in the AI model.The labeled features included the number of cells in the slice,excessive red blood cells,excessive inflammatory cells,and air bubbles.The smear samples were pre-processed and digitized by smear,followed by image segmentation and feature extraction.Using the labeled feature data,machine learning models were trained and optimized.Statistical AI and physician QC results were analyzed by calculating KAPPA index,sensitivity,specificity,area under the curve(AUC),and other indexes for AI QC results.Results CNN algorithm QC results in normal smear,inflammatory background and bloody background were significantly different from the expert review QC results(P＜0.001).Transformer algorithm QC results were similar to the expert review results,with no statistical difference(P＞0.05).General practitioner QC results were statistically different from the expert review QC results in normal smear detection rate and bloody background(P＜0.001).CNN algorithm Kappa value was 0.567,which had medium consistency with expert review results.Transformer algorithm Kappa value was 0.890,with the best consistency with expert review results.General practitioner Kappa value was 0.675,which had better consistency with expert review results.Using the expert review results as a reference standard,the predictive efficacy of the Transformer algorithm and the general practitioners' QC results was evaluated,and the predictive efficacy of the Transformer algorithm was higher than that of the general practitioners in detecting hemorrhagic backgrounds and normal smears(inflammatory backgrounds:AUC=1.000;normal smears:AUC=0.768)(hemorrhagic backgrounds:AUC=0.849;normal smears:AUC=0.849;normal smear:AUC=0.500).Conclusion In this study,we found that the Transformer algorithm was effective in improving the quality control of cervical liquid-based thin-layer cell smears by assisting doctors to perform smear quality control scoring and improving the efficiency and accuracy of smear sample quality control.It can be used as a new quality control method for cervical cancer cytological screening and has potential clinical applications.

Objective:To analyze the impact of different intrauterine intervention methods and types of complications on fetal prognosis in cases of giant placental chorioangioma (CA), and determine the indications for various treatment methods by analyzing cases of adverse outcomes.Methods:Relevant articles were retrieved from China National Knowledge Infrastructure, VIP Database, Wanfang Database, and Yiigle using the keywords "placental chorioangioma" and "fetal edema" or "anemia" or "cardiomegaly" or "polyhydramnios," and from PubMed, Embase, and UpToDate databases using the keywords "placental chorionic angioma or chorioangioma" and "fetal edema" or "anemia" or "polyhydramnios" or "hyperdynamic circulation" up to June 30th 2023. The size of the angiomas, fetal complications, intrauterine intervention methods, gestational weeks at intervention, and pregnancy outcomes were analyzed. Fetal and neonatal deaths were defined as adverse outcomes. Statistical analysis was performed using an independent sample t-test, rank-sum test, or Chi-square test (continuity correction Chi-square test or Pearson Chi-square test). Results:(1) A total of 582 articles were retrieved, and 51 articles were finally included, comprising 65 cases. Based on the intrauterine intervention methods, these cases were divided into the symptomatic treatment group (17 cases) and the etiological treatment group (48 cases). There were no statistically significant differences between the two groups in the maximum diameter of the angiomas, the gestational weeks at intervention, or the gestational weeks at delivery. (2) The incidence of adverse outcomes was 3/17 in the symptomatic treatment group and 27.1% (13/48) in the etiological treatment group, with no statistically significant difference. In the etiological treatment group, the incidence of adverse outcomes in cases with fetal edema was 45.4% (10/22), which was significantly higher than the 11.5% (3/26) in cases without fetal edema, and the difference was statistically significant ( χ 2=6.94, P=0.008). (3) An analysis of 13 cases with adverse outcomes revealed that nine cases had highly vascularized chorioangiomas and/or blood supply vessels located close to the umbilical cord insertion point on the placenta, and nine were complicated by fetal edema. The incidence of adverse outcomes for fetoscopic laser coagulation/bipolar coagulation, radiofrequency or microwave ablation, bioglue embolization, anhydrous alcohol ablation, and microcoil embolization were 4/19, 3/4, 1/8, 2/9, and 3/6, respectively. Conclusions:Intrauterine treatment of CA should be individualized. Bioglue embolization may be the first-line treatment; Fetoscopic laser coagulation can be applied to cases where the blood supply vessels are small and superficial;Interstitial laser ablation and radiofrequency ablation can be used for branch-type CA when the main blood supply vessels are located within the hemangioma; Anhydrous alcohol ablation is contraindicated due to its risk of fetal circulation entry; Microcoil embolization has the risk of incomplete occlusion, which should be used with caution.

Objective:To conduct a cost-utility analysis of Tuberculosis Preventive Treatment(TPT)strategies for Latent Tuberculosis Infection(LTBI)individuals,providing a scientific basis for the implementation of TPT strategies and fund allocation.Methods:Based on a simulated population of 100 000 LTBI individuals,a decision tree-Markov Model was constructed to compare the cost-utility of six TPT strategies over 20 years.Results:Compared with no treatment,3HP-SAT,3HP-DOT,3HR-SAT,3HR-DOT and Vaccae could prevent 91.08％,94.15％,83.49％,87.18％and 53.13％of ATB cases,respectively,and avoid 3.55％,3.70％,3.30％,3.43％,and 2.06％of LTBI individuals from dying of ATB.Except for Vaccae,other schemes could reduce costs and improve QALYs,being absolutely dominant strategies,while Vaccae was a relatively dominant strategy.3HP under DOT was more cost-utility than that under SAT.Sensitivity analysis showed that the utility value of curing ATB was the only parameter affecting the ICUR result,and the model result was stable and reliable.When the WTP threshold was greater than 41 608.54 yuan/QALY,3HP-DOT was better than 3HP-SAT;otherwise,3HP-SAT was the optimal strategy.Conclusion:TPT for LTBI individuals has high cost-utility value.Clarifying the advantages of short-course therapy helps promote the implementation of TPT strategies and contributes to achieving the goal of"ending tuberculosis".

Objective To explore and analyze the application effect of the digital information management mode of nurs-ing"teaching-training-clinical"work in operating room teaching.Methods 100 nursing students who interned in the operating room of Gaozhou Hospital of Traditional Chinese Medicine from April 2023 to February 2024 were selected as the research sub-jects.They were divided into an observation group(digital information management mode of"teaching-training-clinical"work)and a control group(traditional teaching mode)by random number table method,with 50 students in each group.The teaching effects of the two groups were compared.Results The theoretical and practical scores and core competency scores of the obser-vation group after teaching were significantly higher than those of the control group.The observation group had higher satisfaction with the teaching plan,teaching content,teaching methods,teaching achievements,and teaching ability,and the comparison was statistically significant(P＜0.05).The long-term teaching results of the observation group,including theoretical and practical assessment results and core competency assessment results,were higher than those of the control group(P＜0.05).Conclusion The digital information management mode of"teaching-training-clinical"work can improve the teaching quality of operating room teaching and enhance the working ability of nursing students.

Objective To construct a quality control model for cervical liquid-based thin cell smears using two different artificial intelligence(AI)techniques and to compare the total use of the two methods to improve the level of quality control of cervical liquid-based thin cell smears through the assistance of hybrid AI.Methods In this study,105 cervical liquid-based thin cell smear samples were used.Convolutional neural network(CNN)algorithm and Transformer network algorithm were used as specific AI algorithms in the AI model.The labeled features included the number of cells in the slice,excessive red blood cells,excessive inflammatory cells,and air bubbles.The smear samples were pre-processed and digitized by smear,followed by image segmentation and feature extraction.Using the labeled feature data,machine learning models were trained and optimized.Statistical AI and physician QC results were analyzed by calculating KAPPA index,sensitivity,specificity,area under the curve(AUC),and other indexes for AI QC results.Results CNN algorithm QC results in normal smear,inflammatory background and bloody background were significantly different from the expert review QC results(P＜0.001).Transformer algorithm QC results were similar to the expert review results,with no statistical difference(P＞0.05).General practitioner QC results were statistically different from the expert review QC results in normal smear detection rate and bloody background(P＜0.001).CNN algorithm Kappa value was 0.567,which had medium consistency with expert review results.Transformer algorithm Kappa value was 0.890,with the best consistency with expert review results.General practitioner Kappa value was 0.675,which had better consistency with expert review results.Using the expert review results as a reference standard,the predictive efficacy of the Transformer algorithm and the general practitioners' QC results was evaluated,and the predictive efficacy of the Transformer algorithm was higher than that of the general practitioners in detecting hemorrhagic backgrounds and normal smears(inflammatory backgrounds:AUC=1.000;normal smears:AUC=0.768)(hemorrhagic backgrounds:AUC=0.849;normal smears:AUC=0.849;normal smear:AUC=0.500).Conclusion In this study,we found that the Transformer algorithm was effective in improving the quality control of cervical liquid-based thin-layer cell smears by assisting doctors to perform smear quality control scoring and improving the efficiency and accuracy of smear sample quality control.It can be used as a new quality control method for cervical cancer cytological screening and has potential clinical applications.

Objective To explore and analyze the application effect of the digital information management mode of nurs-ing"teaching-training-clinical"work in operating room teaching.Methods 100 nursing students who interned in the operating room of Gaozhou Hospital of Traditional Chinese Medicine from April 2023 to February 2024 were selected as the research sub-jects.They were divided into an observation group(digital information management mode of"teaching-training-clinical"work)and a control group(traditional teaching mode)by random number table method,with 50 students in each group.The teaching effects of the two groups were compared.Results The theoretical and practical scores and core competency scores of the obser-vation group after teaching were significantly higher than those of the control group.The observation group had higher satisfaction with the teaching plan,teaching content,teaching methods,teaching achievements,and teaching ability,and the comparison was statistically significant(P＜0.05).The long-term teaching results of the observation group,including theoretical and practical assessment results and core competency assessment results,were higher than those of the control group(P＜0.05).Conclusion The digital information management mode of"teaching-training-clinical"work can improve the teaching quality of operating room teaching and enhance the working ability of nursing students.