Objective By conducting a statistical analysis of self-paid health examination items among individuals at a public medical institution in Xinjiang in 2023,this study aims to understand the preferences of different demographic groups re-garding health examination items.Methods Data from self-paid health examinations in 2023 were collected and analyzed using statistical methods such as chi-square tests and binary logistic regression to examine the frequency of selection,differences,and influencing factors of health examination items among different demographic groups.Results ① The total number of research subjects was 11,228,including 5,205 males and 6,023 females,with ages ranging from 18 to 94 years old.② The frequency of choosing examination items for males ranked from highest to lowest in the top 5 were thyroid B-ultrasound,prostate and bladder B-ultrasound,color Doppler echocardiography,spiral CT of the lungs,and glycosylated hemoglobin determination.For females,the frequency of choosing examination items ranked from highest to lowest in the top 5 were thyroid B-ultrasound,breast B-ultra-sound,vaginal B-ultrasound,vaginal discharge routine test combination,and spiral CT of the lungs.③ Older individuals were more likely to choose color Doppler echocardiography,spiral CT of the lungs,and glycosylated hemoglobin determination.Youn-ger individuals were more likely to choose thyroid B-ultrasound,13-carbon urea breath test;those with lower educational attain-ment were more likely to choose thyroid B-ultrasound,color Doppler echocardiography,spiral CT of the lungs,glycosylated hemo-globin,and 13-carbon urea breath test;those with fewer physical examinations were more likely to choose thyroid B-ultrasound,color Doppler echocardiography,spiral CT of the lungs,and 13-carbon urea breath test.Conclusion By analyzing the prefer-ences and influencing factors of health examination items among different demographic groups,targeted plans can be proposed to assist medical institutions in designing more appropriate health examination packages tailored to diverse populations.

Objective:To investigate the predictive value of machine learning-based CT radiomics model for radioresistance in patients with esophageal squamous cell carcinoma (ESCC).Methods:Clinical data of 185 patients with ESCC treated with radical radiotherapy in the First Affiliated Hospital of Anhui Medical University from December 2015 to July 2022 were retrospectively analyzed, and all patients were randomly divided into a training set ( n=129) and a validation set ( n=56) at a ratio of 7 : 3. The radiomics parameters of the primary lesion of esophageal cancer and the surrounding 5 cm region in the patients' CT arterial phase images were extracted, and 6 machine learning methods were used to screen the optimal radiomics model to obtain the optimal radiomics score (Radscore). Independent prognostic predictors of radioresistance in ESCC were obtained by univariate and multivariate logistic regression analyses, which was used as the basis for constructing the nomogram. The predictive performance of different models was compared by the area under the receiver operating characteristic (ROC) curve (AUC). The predictive efficacy and clinical value of the combined model were evaluated using calibration curve, decision curve analysis and clinical impact curve, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Results:The combined intratumoral and peritumoral radiomics model based on naive Bayesian classifier yielded the optimal prediction performance, with AUC of 0.859 and 0.936 in the training set and validation set, respectively. Multivariate logistic regression analysis showed that Radscore and T stage were the independent prognostic predictors of radioresistance in ESCC patients, and the AUC of the combined model constructed based on these predictors in the training and validation sets were 0.942 and 0.959, respectively. Calibration curve, decision curve analysis and clinical impact curve, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) all indicated higher clinical benefit and more consistent predictive efficacy of the combined model.Conclusions:Machine learning-based CT radiomics model is useful for the prediction of radioresistance in ESCC. The nomogram of radiomics and clinical parameters can further improve the prediction accuracy and provide novel reference for individualized treatment of patients with ESCC.

Objective:To explore the predictive value of models based on clinical parameters, deep learning radiomics (DLR) from CT images, and traditional handcrafted radiomics (HCR) in assessing pathological complete response (pCR) after neoadjuvant radiotherapy combined with medical therapy in patients with esophageal cancer.Methods:A retrospective study was conducted on 130 patients with locally advanced esophageal cancer who underwent neoadjuvant radiotherapy combined with medical therapy followed by surgery at the First Affiliated Hospital of the University of Science and Technology of China from August 1, 2018, to August 31, 2024. Patients were randomly divided into a training set ( n=91) and a validation set ( n=39) at a ratio of 7:3. Logistic regression analysis was performed to identify clinical independent risk factors associated with pCR. DLR and HCR features were extracted from the tumor and the 5 mm peritumoral region on planning CT images. Features for modeling were selected using t-test, Mann-Whitney U test or Fisher exact probability method, least absolute shrinkage and selection operator (LASSO) regression to calculate the radiomics score (Rad-score). A nomogram was then constructed by integrating the clinical risk factors. The predictive performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA) to assess clinical benefits. Results:Multivariate logistic regression analysis identified body weight ( OR=1.101, 95% CI: 1.029-1.177, P=0.005) and lymph node positivity ( OR=0.100, 95% CI: 0.014-0.727, P=0.023) as independent predictors of pCR. The peritumoral DLR-HCR model showed superior predictive performance, with AUCs of 0.870 (95% CI: 0.799-0.942) in the training set and 0.866 (95% CI: 0.750-0.982) in the validation set. The combined model incorporating clinical parameters achieved the best performance, with AUCs of 0.903 (95% CI: 0.845-0.962) and 0.888 (95% CI: 0.782-0.994) in the training and validation sets, respectively. Conclusions:The combined model integrating peritumoral DLR-HCR features with clinical parameters provides excellent predictive value for pCR after neoadjuvant radiotherapy combined with medical therapy in esophageal cancer and offers valuable guidance for personalized treatment strategies.

Objective:To analyze the epidemiological characteristics and injury patterns of eye trauma in children and adolescents in China.Methods:A multicenter cross-sectional, retrospective, observational study. Based on the Chinese Eye Trauma Registry database, 189 patients (189 eyes) aged 0-18 years (13.4%, 189/1 412) of 1 412 patients (1 435 eyes) with eye trauma who were hospitalized from January to December 2023 were included in the study. Patients were recruited from 23 tertiary general hospitals or ophthalmology specialty hospitals located in 17 provincial-level administrative regions across six major geographical areas in China (North China, East China, South China, Central China, Northwest China, and Southwest China). The analysis focused on population characteristics, epidemiological features, injury patterns, and visual outcomes of children from different geographical regions and age groups. Among the 189 eyes, 95 eyes underwent secondary surgery. A total of 23 eyes were excluded due to non-cooperation during examination, no light perception, or only light perception. Ultimately, 72 eyes were included in the statistical analysis. Of these, 36 eyes had follow-up data and were used to observe postoperative visual outcomes.Results:Among 189 patients, 143 were males (75.7%, 143/189) and 46 were females (24.3%, 46/189). Age 8.73 (1-18) years old. The gender composition of all age groups was mainly male. The geographical distribution showed that East China had the largest number of cases, 55 (29.1%, 55/189). There were 70 cases (37.0%, 70/189) in 7-10 years old. The type analysis of eye trauma showed that in 189 eyes, mechanical ocular trauma accounted for 130 eyes, of which 105 (80.8%, 105/130) eyes had open globe injuries and 25 (19.2%, 25/130) eyes had closed globe injuries. 122 eyes received emergency surgery within 24 h after injury (accounts for 83.6% of emergency surgical cases, 122/146). In 36 eyes with complete follow-up data, the initial visual acuity distribution was: blind 23 eyes (63.9%), low visual acuity 6 eyes (16.7%), visual acuity ≥0.3 in 7 eyes (19.4%). At the last follow-up, visual acuity improved in 12 eyes (33.3%) with blindness, 8 eyes (22.2%) with low visual acuity, and 16 eyes (44.4%) with visual acuity ≥ 0.3. The final visual outcome showed that the disability rate was 22.2% (8/36) and the blindness rate was 33.3% (12/36).Conclusions:Children and adolescents account for 13.4% of the hospitalized patients with eye trauma in the same period, and there is a significant gender difference (male accounted for 75.7%). There are obvious age-specific distribution rules in the causes, locations and clinical features of eye trauma in children and adolescents of different ages.

The Blow-Fill-Seal(BFS)technology is a highly automated aseptic manufacturing process that significantly reduces contamination risks by integrating container blowing,filling,and sealing operations.First,this article introduced the core technical features of BFS equipment and its advantages in aseptic production,followed by a comparative analysis of regulatory requirements for BFS technology across different jurisdictions.Finally,in light of pharmaceutical industry trends,it explored the future development prospects of BFS technology in intelligent manufacturing and high-barrier material applications,while examining its potential value in personalized medicine and specialized drug production.

AIM:To investigate the effect and mechanism of Shen-Huang granule(SHG)on Aβ25-35-induced ferroptosis in HT22 cells.METHODS:An in vitro model of Alzheimer disease(AD)was established by treating HT22 cells with Aβ25-35.The cells were divided into the following groups:control group,model group(Aβ25-35 group),ferroptosis inhibitor ferrostatin-1(Fer-1)group,low-dose SHG(SHG-L)group,and high-dose SHG(SHG-H)group.Cell viability was assessed using the Cell Counting Kit-8(CCK-8)assay.Ultrastructural changes in each group were observed via trans-mission electron microscopy.The intracellular levels of reactive oxygen species(ROS)were measured by flow cytometry.Iron deposition and lipid peroxidation levels were evaluated by examining Fe2+,total superoxide dismutase(SOD),and malondialdehyde(MDA)levels.Western blot analysis was employed to detect the protein expression of cyclooxygenase 2(TfR1),ferritin heavy chain 1(FTH1),nuclear factor E2-related factor 2(Nrf2),and heme oxygenase-1(HO-1).RE-SULTS:Compared to the control group,the model group exhibited mitochondrial shrinkage,increased membrane densi-ty,and decreased cristae.Levels of ROS,Fe2+,and MDA were significantly elevated,while SOD levels were markedly re-duced.The protein expression of SLC7A11,GPX4,FTH1,Nrf2,and HO-1 was significantly down-regulated,whereas the expression of COX2 and TfR1 was significantly up-regulated.In comparison to the model group,the morphology and structure of mitochondria improved in the Fer-1,low-dose SHG,and high-dose SHG groups.ROS,Fe2+,and MDA levels decreased while SOD levels increased.Furthermore,the expression of SLC7A11,GPX4,FTH1,Nrf2,and HO-1 was sig-nificantly up-regulated,while COX2 and TfR1 expression was significantly down-regulated.CONCLUSION:Shen-Huang granule can inhibit Aβ25-35-induced ferroptosis in HT22 cells,and the underlying mechanism may involve the Nrf2/HO-1/GPX4 signaling pathway.

Objective:To systematically search and summarize high-quality evidence-based evidence on the prevention and management of refeeding syndrome in patients with anorexia nervosa, and to provide a basis for preventive management of patients at high risk.Methods:A computerized search was conducted for evidence on the prevention and management of refeeding syndrome in patients with anorexia nervosa in relevant domestic and international databases and professional team websites, including clinical decision-making, guidelines, expert consensus, evidence summaries and systematic evaluations, and randomized controls. The search timeframe was from database construction to August 2024. Two researchers trained in systematic evidence-based knowledge independently performed literature screening, quality assessment, and extraction and summarization of evidence according to inclusion and exclusion criteria.Results:A total of 15 publications were included, which contained 4 guidelines, 3 expert consensus, 3 clinical decision-making, 3 systematic evaluations, and 2 randomized control trials. Thirty-one pieces of evidence for the prevention and management of refeeding syndrome were summarized in seven areas: treatment team, risk factors, risk assessment, preventive measures, clinical diagnosis, management measures, and patient safety.Conclusions:The best evidence summarized in this study for the prevention and management of refeeding syndrome in anorexia nervosa provides an evidence-based basis for practitioners to implement refeeding syndrome prevention and management measures.

The Blow-Fill-Seal(BFS)technology is a highly automated aseptic manufacturing process that significantly reduces contamination risks by integrating container blowing,filling,and sealing operations.First,this article introduced the core technical features of BFS equipment and its advantages in aseptic production,followed by a comparative analysis of regulatory requirements for BFS technology across different jurisdictions.Finally,in light of pharmaceutical industry trends,it explored the future development prospects of BFS technology in intelligent manufacturing and high-barrier material applications,while examining its potential value in personalized medicine and specialized drug production.

Objective By conducting a statistical analysis of self-paid health examination items among individuals at a public medical institution in Xinjiang in 2023,this study aims to understand the preferences of different demographic groups re-garding health examination items.Methods Data from self-paid health examinations in 2023 were collected and analyzed using statistical methods such as chi-square tests and binary logistic regression to examine the frequency of selection,differences,and influencing factors of health examination items among different demographic groups.Results ① The total number of research subjects was 11,228,including 5,205 males and 6,023 females,with ages ranging from 18 to 94 years old.② The frequency of choosing examination items for males ranked from highest to lowest in the top 5 were thyroid B-ultrasound,prostate and bladder B-ultrasound,color Doppler echocardiography,spiral CT of the lungs,and glycosylated hemoglobin determination.For females,the frequency of choosing examination items ranked from highest to lowest in the top 5 were thyroid B-ultrasound,breast B-ultra-sound,vaginal B-ultrasound,vaginal discharge routine test combination,and spiral CT of the lungs.③ Older individuals were more likely to choose color Doppler echocardiography,spiral CT of the lungs,and glycosylated hemoglobin determination.Youn-ger individuals were more likely to choose thyroid B-ultrasound,13-carbon urea breath test;those with lower educational attain-ment were more likely to choose thyroid B-ultrasound,color Doppler echocardiography,spiral CT of the lungs,glycosylated hemo-globin,and 13-carbon urea breath test;those with fewer physical examinations were more likely to choose thyroid B-ultrasound,color Doppler echocardiography,spiral CT of the lungs,and 13-carbon urea breath test.Conclusion By analyzing the prefer-ences and influencing factors of health examination items among different demographic groups,targeted plans can be proposed to assist medical institutions in designing more appropriate health examination packages tailored to diverse populations.

Objective:To systematically search and summarize high-quality evidence-based evidence on the prevention and management of refeeding syndrome in patients with anorexia nervosa, and to provide a basis for preventive management of patients at high risk.Methods:A computerized search was conducted for evidence on the prevention and management of refeeding syndrome in patients with anorexia nervosa in relevant domestic and international databases and professional team websites, including clinical decision-making, guidelines, expert consensus, evidence summaries and systematic evaluations, and randomized controls. The search timeframe was from database construction to August 2024. Two researchers trained in systematic evidence-based knowledge independently performed literature screening, quality assessment, and extraction and summarization of evidence according to inclusion and exclusion criteria.Results:A total of 15 publications were included, which contained 4 guidelines, 3 expert consensus, 3 clinical decision-making, 3 systematic evaluations, and 2 randomized control trials. Thirty-one pieces of evidence for the prevention and management of refeeding syndrome were summarized in seven areas: treatment team, risk factors, risk assessment, preventive measures, clinical diagnosis, management measures, and patient safety.Conclusions:The best evidence summarized in this study for the prevention and management of refeeding syndrome in anorexia nervosa provides an evidence-based basis for practitioners to implement refeeding syndrome prevention and management measures.