Addressing the enduring challenge of evaluating traditional Chinese medicines (TCMs), the integrated evidence chain-based effectiveness evaluation of TCMs (Eff-iEC) has emerged. This paper explored its capacity through a demonstration study that evaluated the effectiveness evidence of six commonly used anti-hepatic fibrosis Chinese patent medicines (CPMs), including Biejiajian Pill (BP), Dahuang Zhechong Pill (DZP), Biejia Ruangan Compound (BRC), Fuzheng Huayu Capsule (FHC), Anluo Huaxian Pill (AHP), and Heluo Shugan Capsule (HSC), using both Eff-iEC and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The recognition of these CPMs within the TCM academic community was also assessed through their inclusion in relevant medical documents. Results showed that the evidence of BRC and FHC received higher assessments in both Eff-iEC and GRADE system, while the assessments for others varied. Analysis of community recognition revealed that Eff-iEC more accurately reflects the clinical value of these CPMs, exhibiting superior evaluative capabilities. By breaking through the conventional pattern of TCMs effectiveness evaluation, Eff-iEC offers a novel epistemology that better aligns with the clinical realities and reasoning of TCMs, providing a coherent methodology for clinical decision-making, new drug evaluations, and health policy formulation.

Gastric carcinoma(GC),a highly prevalent malignant tumor globally,often progresses to advanced stages by the time of diagnosis due to its insidious clinical presentation,thereby significantly reducing therapeutic effectiveness and patient quality of life.Accurate screening and histopathological characterization of early gastric cancer(EGC)are essential for developing individualized treatment approaches.Although endoscopic techniques remain the gold standard for early GC detection,their diagnostic accuracy is largely dependent on the operator's skill,a challenge that current artificial intelligence(AI)-assisted innovations aim to address by stan-dardizing diagnostic procedures.Deep learning(DL)-based computer vision systems have demonstrated remarkable performance in identifying subtle EGC features,not only improving lesion detection sensitivity but also enabling automated assessment of key pathological indicators.These technological advances offer objective,visualized diag-nostic support for clinical decision-making.This review provides a systematic overview of recent developments in DL applications for endoscopic image analysis of EGC and evaluates their potential for clinical integration.

Objective:To establish reference ranges for left and right ventricular structure and function parameters using cardiovascular magnetic resonance (CMR) in healthy Tibetan natives residing at ultra-high altitudes, and analyze their influencing factors.Methods:This prospective study enrolled Tibetan healthy volunteers who underwent CMR examinations between September 2021 and August 2022. Participants were stratified into four age groups: 20-29, 30-39, 40-49, and 50-59 years. CMR-derived parameters included left ventricular ejection fraction (LVEF), right ventricular ejection fraction (RVEF), left/right ventricular end-diastolic volumes (LVEDV/RVEDV), left/right ventricular end-systolic volumes (LVESV/RVESV), and end-diastolic left ventricular mass (LVM at ED). Normally distributed data were compared between genders using independent samples t-test and among age groups using ANOVA. Non-normally distributed data were analyzed with Kruskal-Wallis test. Linear regression assessed relationships between parameters and gender, age, residential altitude, body surface area (BSA), and body mass index (BMI). Results:The study included 66 volunteers (27 males, 39 females), distributed as follows: 21 (20-29 years), 15 (30-39 years), 15 (40-49 years), and 15 (50-59 years). Reference values were: LVEF (62.6±5.7)%, RVEF (55.0±7.1)%, BSA-indexed LVEDV (60.6±12.1)ml/m2, RVEDV (65.5±14.8)ml/m2, LVESV (22.7±5.9)ml/m2, RVESV (29.6±8.1)ml/m2, and LVM at ED (39.1±8.0)g/m2. Gender and age significantly affected RVEF, RVESV, and LVM at ED ( P<0.05). Multivariate regression revealed:Gender independently predicted RVEF ( β=-5.556, P=0.003), RVESV ( β=5.421, P=0.007), and LVM at ED ( β=8.338, P<0.001). Age negatively influenced RVESV ( β=-0.202, P=0.019). BSA positively correlated with LVM at ED ( β=19.980, P=0.041). No significant associations were found with residential altitude or BMI ( P>0.05). Conclusion:This study establishes preliminary reference ranges for ventricular parameters in Tibetan ultra-high altitude natives, with gender, age, and BSA identified as key determinants of cardiac structural/functional indices.

Objective To investigate the achievement of early fluid resuscitation targets and factors influencing 28-day outcomes in patients with sepsis.Methods A retrospective cohort analysis was conducted.A total of 164 patients with sepsis admitted to the First Affiliated Hospital of Xinjiang Medical University between January 2022 and January 2024 were enrolled.Patients were divided into survival and death groups based on 28-day survival status,with both groups receiving early fluid resuscitation.Comparisons were made between groups for general characteristics[gender,age,body mass index(BMI),infection site,comorbidities],primary indicators[central venous pressure(CVP),mean arterial pressure(MAP),urine output],and secondary indicators[blood lactate acid(Lac),procalcitonin(PCT),heart rate,sequential organ failure assessment(SOFA)on intensive care unit(ICU)admission day,Glasgow coma scale(GCS),duration and dose of vasoactive medication use].Univariate analysis identified variables associated with prognosis,followed by multivariate Logistic regression to select independent risk factors.Receiver operator characteristic(ROC curve)were plotted to assess predictive performance of each risk factor for the 28-day prognosis of patients with sepsis.Results This study included 164 patients.The primary infection sites were mainly the lungs,abdominal cavity,and urinary system,accounting for 42.7%(70/164),38.4%(63/164),and 9.1%(15/164)respectively.The survival group comprised 141 patients,while the the death group included 23 patients.No statistically significant differences existed between groups in gender,BMI,infection site(soft tissue infection vs.others),underlying diseases,MAP,urine output(all P>0.05).Compared to the survival group,the death group showed significantly higher age,pulmonary infection rate,Lac levels,vasoactive drug duration/dose,heart rate,and SOFA scores,while the rates of abdominal,and urinary tract infection,as well as CVP,PCT,and GCS scores were significantly lower(all P<0.05).The achievement rates of early fluid resuscitation parameters:MAP target achievement was highest at 78.7%(129/164),followed by urine output compliance at 78.0%(128/164),while CVP compliance was the lowest at 39.0%(64/164).The overall compliance rate was 21.3%(35/164).Univariate analysis showed that age,pulmonary infection,Lac levels,duration and dose of vasoactive drugs,heart rate,PCT,GCS score,and SOFA score were all risk factors affecting the 28-day prognosis of patients with sepsis(all P<0.05).Multivariate Logistic regression analysis showed Lac levels,and pulmonary infection were independent risk factors affecting 28-day prognosis of patients with sepsis[odds ratio(OR)were 0.801,3.966,0.812,95%confidence interval(95%CI)were 0.711-0.903,1.149-13.696,0.674-0.979 respectively,P values were<0.001,0.029,0.029 respectively].ROC curve analysis demonstrated that age,Lac levels,and pulmonary infection all possessed predictive value for 28-day outcomes(all P<0.05).Age exhibited the highest predictive value with an AUC of 0.922.At the optimal cut-off of 76.6 years,sensitivity reached 95.7%and specificity 80.9%.Conclusion The overall achievement rate of early fluid resuscation in sepsis patients was low,with age,Lac levels,and pulmonary infection being major factors influencing poor prognosis.

Gastric carcinoma(GC),a highly prevalent malignant tumor globally,often progresses to advanced stages by the time of diagnosis due to its insidious clinical presentation,thereby significantly reducing therapeutic effectiveness and patient quality of life.Accurate screening and histopathological characterization of early gastric cancer(EGC)are essential for developing individualized treatment approaches.Although endoscopic techniques remain the gold standard for early GC detection,their diagnostic accuracy is largely dependent on the operator's skill,a challenge that current artificial intelligence(AI)-assisted innovations aim to address by stan-dardizing diagnostic procedures.Deep learning(DL)-based computer vision systems have demonstrated remarkable performance in identifying subtle EGC features,not only improving lesion detection sensitivity but also enabling automated assessment of key pathological indicators.These technological advances offer objective,visualized diag-nostic support for clinical decision-making.This review provides a systematic overview of recent developments in DL applications for endoscopic image analysis of EGC and evaluates their potential for clinical integration.

Objective To investigate the achievement of early fluid resuscitation targets and factors influencing 28-day outcomes in patients with sepsis.Methods A retrospective cohort analysis was conducted.A total of 164 patients with sepsis admitted to the First Affiliated Hospital of Xinjiang Medical University between January 2022 and January 2024 were enrolled.Patients were divided into survival and death groups based on 28-day survival status,with both groups receiving early fluid resuscitation.Comparisons were made between groups for general characteristics[gender,age,body mass index(BMI),infection site,comorbidities],primary indicators[central venous pressure(CVP),mean arterial pressure(MAP),urine output],and secondary indicators[blood lactate acid(Lac),procalcitonin(PCT),heart rate,sequential organ failure assessment(SOFA)on intensive care unit(ICU)admission day,Glasgow coma scale(GCS),duration and dose of vasoactive medication use].Univariate analysis identified variables associated with prognosis,followed by multivariate Logistic regression to select independent risk factors.Receiver operator characteristic(ROC curve)were plotted to assess predictive performance of each risk factor for the 28-day prognosis of patients with sepsis.Results This study included 164 patients.The primary infection sites were mainly the lungs,abdominal cavity,and urinary system,accounting for 42.7%(70/164),38.4%(63/164),and 9.1%(15/164)respectively.The survival group comprised 141 patients,while the the death group included 23 patients.No statistically significant differences existed between groups in gender,BMI,infection site(soft tissue infection vs.others),underlying diseases,MAP,urine output(all P>0.05).Compared to the survival group,the death group showed significantly higher age,pulmonary infection rate,Lac levels,vasoactive drug duration/dose,heart rate,and SOFA scores,while the rates of abdominal,and urinary tract infection,as well as CVP,PCT,and GCS scores were significantly lower(all P<0.05).The achievement rates of early fluid resuscitation parameters:MAP target achievement was highest at 78.7%(129/164),followed by urine output compliance at 78.0%(128/164),while CVP compliance was the lowest at 39.0%(64/164).The overall compliance rate was 21.3%(35/164).Univariate analysis showed that age,pulmonary infection,Lac levels,duration and dose of vasoactive drugs,heart rate,PCT,GCS score,and SOFA score were all risk factors affecting the 28-day prognosis of patients with sepsis(all P<0.05).Multivariate Logistic regression analysis showed Lac levels,and pulmonary infection were independent risk factors affecting 28-day prognosis of patients with sepsis[odds ratio(OR)were 0.801,3.966,0.812,95%confidence interval(95%CI)were 0.711-0.903,1.149-13.696,0.674-0.979 respectively,P values were<0.001,0.029,0.029 respectively].ROC curve analysis demonstrated that age,Lac levels,and pulmonary infection all possessed predictive value for 28-day outcomes(all P<0.05).Age exhibited the highest predictive value with an AUC of 0.922.At the optimal cut-off of 76.6 years,sensitivity reached 95.7%and specificity 80.9%.Conclusion The overall achievement rate of early fluid resuscation in sepsis patients was low,with age,Lac levels,and pulmonary infection being major factors influencing poor prognosis.

Objective:To establish reference ranges for left and right ventricular structure and function parameters using cardiovascular magnetic resonance (CMR) in healthy Tibetan natives residing at ultra-high altitudes, and analyze their influencing factors.Methods:This prospective study enrolled Tibetan healthy volunteers who underwent CMR examinations between September 2021 and August 2022. Participants were stratified into four age groups: 20-29, 30-39, 40-49, and 50-59 years. CMR-derived parameters included left ventricular ejection fraction (LVEF), right ventricular ejection fraction (RVEF), left/right ventricular end-diastolic volumes (LVEDV/RVEDV), left/right ventricular end-systolic volumes (LVESV/RVESV), and end-diastolic left ventricular mass (LVM at ED). Normally distributed data were compared between genders using independent samples t-test and among age groups using ANOVA. Non-normally distributed data were analyzed with Kruskal-Wallis test. Linear regression assessed relationships between parameters and gender, age, residential altitude, body surface area (BSA), and body mass index (BMI). Results:The study included 66 volunteers (27 males, 39 females), distributed as follows: 21 (20-29 years), 15 (30-39 years), 15 (40-49 years), and 15 (50-59 years). Reference values were: LVEF (62.6±5.7)%, RVEF (55.0±7.1)%, BSA-indexed LVEDV (60.6±12.1)ml/m2, RVEDV (65.5±14.8)ml/m2, LVESV (22.7±5.9)ml/m2, RVESV (29.6±8.1)ml/m2, and LVM at ED (39.1±8.0)g/m2. Gender and age significantly affected RVEF, RVESV, and LVM at ED ( P<0.05). Multivariate regression revealed:Gender independently predicted RVEF ( β=-5.556, P=0.003), RVESV ( β=5.421, P=0.007), and LVM at ED ( β=8.338, P<0.001). Age negatively influenced RVESV ( β=-0.202, P=0.019). BSA positively correlated with LVM at ED ( β=19.980, P=0.041). No significant associations were found with residential altitude or BMI ( P>0.05). Conclusion:This study establishes preliminary reference ranges for ventricular parameters in Tibetan ultra-high altitude natives, with gender, age, and BSA identified as key determinants of cardiac structural/functional indices.

OBJECTIVES: To achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China. METHODS: We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS). RESULTS: The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1,000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1,000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease. CONCLUSIONS The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy.

Objective To evaluate the application value of the three-point localization method in improving the quality and efficiency of four-chamber view acquisition in cardiac magnetic resonance(CMR)imaging.Methods A total of 215 patients who underwent four-chamber view in CMR imaging from January 2022 to October 2023 were retrospectively enrolled and divided into two groups.The control group(n=109)received traditional localization method while the study group(n=106)received three-point localization method.The image quality of mitral valve,tricuspid valve and cruciform structure in four-chamber view images were assessed by two radiologists using a Likert 4-piont scale.The time-consumption from scout imaging to the finish of four-chamber view imaging was recorded.Constituent data and numeral data were compared by Chi-square test and two-sample t test,respectively.Kappa test was used to analyze the inter-observer consistency.Results There were no significant inter-group differences in gender,age,disease profile,or the radiographers'experience.The mean quality scores of the mitral valve,tricuspid valve and cruciform structure in the control group and the study group were 3.44±0.64 and 3.63±0.49(P=0.023),3.43±0.67 and 3.53±0.60(P=0.202),3.71±0.49 and 3.83±0.35(P=0.047),respectively.The image quality score was higher in the study group than in the control group,with the differences in mitral valve and cruciform structure reaching statistical significance.The time-consumption for obtaining four-chamber view for the control group and the study group was 11.67±3.49 minutes and 7.212±1.83 minutes,respectively,with statistically significant differences(P＜0.001).Conclusion Compared with the traditional localization method,the three-point localization method provides better image quality in four-chamber view imaging with shortened imaging time.