ObjectiveTo develop a community-family management model for older adults with mild cognitive impairment (MCI) and to formulate detailed application specifications, and to fully leverage the initiative of communities and families under limited resource conditions, for achieving community-based early detection and early intervention for older adults with MCI. MethodsA systematic literature review was conducted to identify pertinent publications. Corpus-based research methodologies were employed to extract, refine, integrate and synthesize management elements, thereby establishing the specific content and service processes for each stage of the management model. Utilizing the 5W2H analytical framework, essential elements such as management stakeholders, target populations, content and methods for each stage were delineated. The model and its application guidelines were finalized through expert consultation and demonstration. ResultsAn expert evaluation of the management model yielded mean scores of 4.84, 4.32 and 4.84 for acceptability, feasibility and systematicity, respectively. By integrating the identified core elements with expert ratings and feedback, the final iteration of the community-family management model for older adults with MCI was formulated. This model comprised of five stages: screening and identification, comprehensive assessment, intervention planning, monitoring and referral pathways to ensure implementation, and enhanced support for communities, family members and caregivers. Additionally, it included 18 specific application guidelines. ConclusionThe proposed management model may theoretically help delay cognitive decline, improve cognitive function and potentially promote reversal from MCI to normal cognition. It may also enhance the awareness and coping capacity of older adults and their families, strengthen community healthcare professionals' ability to early identify and manage MCI.

OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling） and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting degree and generalization ability （mean absolute error＝4.28 min， R 2 ＝0.882）. The comprehensive satisfaction scores of pharmacists and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and （88.61±2.08） in the new system， respectively （ P ＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’ dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup experience.

ObjectiveTo develop and validate a nomogram for predicting the risk of concurrent cognitive impairment in older adults with heart disease. MethodsSelf-reported data from 2 673 respondents in the 2020 China Health and Retirement Longitudinal Study were analyzed. The participants were randomly divided into a training set (n = 1 871) and a validation set (n = 802). Heart disease status was determined using a self-report questionnaire. Logistic regression analysis was performed to identify predictors, and a nomogram for predicting the risk of concurrent cognitive impairment in older adults with heart disease was developed using R software. Bootstrap resampling was used for internal validation, and model performance was further evaluated in the randomly split validation set. The predictive performance of the model was assessed using the area under the receiver operating characteristic curve (AUC) and calibration curves.. ResultsA total of 2 673 older adults with heart disease were included, out of whom 315 participants in the training set had cognitive impairment. Lasso regression analysis identified age, education level, place of residence, instrumental activities of daily living and depression as predictors of concurrent cognitive impairment. A prediction model incorporating these five variables was constructed. The AUC were 0.827 (95%CI 0.804 to 0.850) in the training set and 0.847 (95%CI 0.812 to 0.882) in the validation set. The Hosmer-Lemeshow test yielded P = 0.154 and P = 0.716 in the training and validation sets, respectively. Calibration curves showed good agreement between predicted and observed probabilities. Decision curve analysis indicated that the model provided favorable net benefit and predictive performance. ConclusionThe nomogram may provide a useful reference for risk screening and early intervention for cognitive impairment in older adults with heart disease.

OBJECTIVE To construct a multimodal similarity model for Chinese drug names and design optimized display names，compare the potential confusion risk of display names of the same drug catalogue in different scenarios，so as to provide a quantitative basis for the management of drug display names.METHODS A total of 1 221 drug entries were extracted from the drug dictionary of a tertiary grade A hospital，forming 744 810 drug pairs. “Five rules” were summarized based on the confusion characteristics of candidate confusable drug pairs under the currently used in-hospital display names （Scenario 1） and standard display names （Scenario 2），to generate optimized display names （Scenario 3）. A multimodal similarity model integrating Pinyin，glyph，character sequence and rendered visual features was constructed. The same threshold （total similarity S total ≥0.70） was adopted to screen candidate confusable drug pairs. Confusion risk grading and transition，confusion characteristic labeling，confusion network clustering and residual cluster analysis were carried out. The naming mechanism of optimized display names was investigated through display morphology indicators and rule ablation，and the robustness of the comparison results among the three scenarios was evaluated through similarity threshold and fusion weight sensitivity analysis.RESULTS The numbers of candidate confusable drug pairs in the three scenarios were 156，269 and 83 respectively，among which the number of pairs at high risk and above was 109， 215 and 64 respectively. Compared with Scenario 1，Scenario 3 reduced the number of candidate confusable drug pairs by 46.8%，and the number of those at high risk or above decreased by 41.3%. Display morphology analysis showed that Scenario 3 had the lowest average ink density （0.057 3） and the largest average number of structural slots （2.99）. Rule ablation analysis showed that after disabling the rule of manufacturer characteristic abbreviation prompts，the number of candidate confusable drug pairs increased the most （+74 pairs），while disabling structured naming alone resulted in a net decrease of 9 pairs. The residual clusters mainly involved drugs with the same active ingredient but different specifications or subtypes，as well as series products from the same manufacturer with similar main name stems. Under the threshold setting of 0.60 to 0.80 with a step size of 0.025 and 11 different weight configurations （including the baseline value），the number of candidate confusable drug pairs always maintained the ranking of Scenario 3＜Scenario 1＜Scenario 2.CONCLUSIONS The multimodal similarity model can be used for quantitative screening of potential confusion of Chinese drug display names，and the ranking of the number of candidate confusable drug pairs among scenarios remains stable within the set parameter range. The optimized display names based on the “five rules” can reduce the number of candidate confusable drug pairs， and the number of those at high risk or above in the hospital’s drug catalogue，but their impact on actual identification behavior and clinical medication safety still needs further verification.

ObjectiveTo establish preliminary diagnostic criteria for spleen and kidney deficiency syndrome in ischemic stroke patients and provide a basis for standardized diagnosis and treatment of ischemic stroke. MethodsRelevant literature on the diagnostic criteria for spleen and kidney deficiency syndrome in ischemic stroke patients was retrieved， and data were mined and extracted to form an item pool. Based on the formation of the item pool， this study used the Delphi method to initiate two rounds of questionnaire surveys with selected experts to complete the initial screening of items and the discrimination of symptom importance. A prospective clinical investigation method was adopted to collect clinical information from patients， and statistical analysis methods and data mining techniques were comprehensively used to determine their primary and secondary symptoms. Based on the clear main and secondary symptoms identified， combined with expert group discussions， the study established preliminary diagnostic criteria for spleen and kidney deficiency syndrome in ischemic stroke patients. ResultsA total of 25 relevant syndrome differentiation standards were included. After splitting， standardizing， and screening the items， the study established a pool of 48 items. The first round of questionnaire survey consulted 30 experts， with both the positive coefficient of experts and the effectiveness rate of the questionnaire reaching 100%. The Kendall's coefficient of concordance was 0.359. According to the item screening criteria， 26 items were retained in this round of questionnaire survey. A total of 176 cases were collected through clinical information investigation， including 94 cases with spleen and kidney deficiency syndrome and 82 cases without spleen and kidney deficiency syndrome. The statistical results were as follows： ① Descriptive statistics： The main symptoms with a frequency of ≥ 30% included mental fatigue and lack of strength， weakness of the lower back and knees， etc. The secondary symptoms with a frequency of ≥ 10% and ≤ 30% were lassitude and disinclination to talk， shortness of breath， etc. ② Binary logistic regression analysis： The main symptoms with an odds ratio （OR） value of ≥ 3 were mental fatigue and lack of strength， weakness of the lower back and knees， etc. The secondary symptoms with an OR value of ≥ 1 and ≤ 3 were lassitude and disinclination to talk， shortness of breath， etc. Artificial neural network： The main symptoms with a weight value（W_ij）of ≥ 0.5 and < 1 were mental fatigue and lack of strength， lassitude and disinclination to talk， etc. The secondary symptoms with W_ij of ≥ 0.3 and < 0.5 were shortness of breath， flaccid limbs， etc. In the second round of questionnaire survey， a total of 37 experts were consulted， with both the positive coefficient of experts and the effectiveness rate of the questionnaire reaching 100%. The Kendall's coefficient of concordance was 0.237. According to the criteria to determine primary and secondary symptoms based on the Delphi method， the main symptoms included in this round of the questionnaire were mental fatigue and lack of strength， lassitude and disinclination to talk， etc.， and the secondary symptoms were shortness of breath， dizziness， etc. ConclusionThe main symptoms of spleen and kidney deficiency syndrome in ischemic stroke patients are mental fatigue and lack of strength， weakness of the lower back and knees， loose stool， pale and edematous tongue texture possibly with tooth marks， and deep and thready pulse or weak pulse. The secondary symptoms include shortness of breath， dizziness， tinnitus and deafness， decreased appetite or postprandial abdominal distension， pale complexion， frequent micturition at night， dull tongue texture， and white and slippery tongue coating. The preliminarily established diagnostic criteria for spleen and kidney deficiency syndrome in ischemic stroke patients can provide a standardized and objective basis， thereby better guiding clinical diagnosis and treatment of ischemic stroke.

Objective:To characterize the vaginal flora of pregnant women during the second trimester using full-length 16S rRNA sequencing.Methods:A total of 142 pregnant women were systematically sampled from a pregnancy cohort. Vaginal swabs were collected for full-length 16S rRNA gene sequencing，and bioinformatics analysis was performed to characterize the vaginal microbiota and identify associated influencing factors.Results:Among the 142 pregnant women，the most frequently detected species were Lactobacillus iners（83.10%，118/142）and Lactobacillus crispatus（49.30%，70/142）. The majority of samples（90.85%，129/142）were classified as Lactobacillus-dominant vagitypes，with the Lactobacillus iners vagitype accounting for 48.59%（69/142）and the Lactobacillus crispatus vagitype accounting for 38.73%（55/142）. The vaginal microbiota was clustered into five community state types（CSTs）：Ⅰa，Ⅰb，Ⅲa，Ⅲb，and Ⅳ. The most prevalent CSTs were Lactobacillus iners-dominated CST-Ⅲ（51.41%，73/142）and Lactobacillus crispatus-dominated CST-Ⅰ（24.65%，35/142）. No samples were classified as CST-Ⅱ or CST-Ⅴ. A significant negative correlation was observed between Lactobacill and vaginosis-associated bacteria. Age，alcohol consumption，smoking，and vaginal treatments showed significant associations or trends toward significance with various Alpha diversity indices. Vaginal douching was associated with CST clustering，while obstetric history（primiparity，previous miscarriage history）was associated with vagitype classification. However，no significant associations were identified between maternal baseline characteristics and Beta diversity indices. Conclusions:Full-length 16S rRNA gene sequencing reveals that the vaginal microbiota of pregnant women is dominated by Lactobacillus iners and Lactobacillus crispatus. Maternal age，lifestyle factors such as smoking and alcohol consumption，and obstetric history are significantly associated with variations in vaginal microbiota composition.

Objective:To investigate the association between adiponectin-related copy number variation (CNV) region (CNVR) and gestational diabetes mellitus (GDM).Methods:Pregnant women who had prenatal screening in Anqing Municipal Hospital, Anhui Province, from February 2018 to December 2020 were surveyed for baseline information collection, and blood samples were collected. The outcome information was obtained by post pregnancy follow-up. Latex-enhanced immunoturbidimetry and ASA-CHIA chip were used to detect serum adiponectin levels and CNV of pregnant women, respectively. After genotyping, CNV data were processed with software PennCNV 1.0.5 following standard quality control procedure. CNVR were identified and integrated by using software R 4.3.3. Then the associations between CNVR and adiponectin was evaluated, and gene annotation and over-representation analysis were conducted. The log-binomial regression model was used to adjust relevant covariates and analyze the association between adiponectin-related CNVR and GDM.Results:The detection rate of GDM was 9.54% (176/1 845) in the pregnant women. The genotyping information of 1 840 people (99.73%) passed quality evaluation. A total of 33 878 CNVs were identified, and 1 449 CNVRs were obtained after integration. After the false discovery rate method correction, CNVR_132 (CHR2: 47611743-47635062), CNVR_254 (CHR3: 10182703-10183872), CNVR_691 (CHR7: 150637053-150834539) and CNVR_1101 (CHR14: 104248431-104830620) were correlated with adiponectin levels (all P<0.05). Over- representation analysis showed that the molecular function of ribonucleotide binding [Gene Ontology (GO): 0032553] was significantly enriched based on the GO database. The log-binomial regression model, adjusting age, pre-pregnancy BMI, history of miscarriage, smoking history, and family history of diabetes, indicated that CNVR_132 (CHR2: 47611743-47635062) and CNVR_1101 (CHR14: 104248431-104830620) were not statistically associated with the risk for GDM (both P>0.05). However, CNVR_254 (CHR3: 10182703-10183872, a RR=1.83, 95% CI: 1.15-2.91) and CNVR_691 (CHR7: 150637053-150834539, a RR=1.73, 95% CI: 1.23-2.43) might be associated with an increased risk for GDM (all P<0.05). Conclusion:Adiponectin-related CNVR_254 (CHR3: 10182703-10183872) and CNVR_691 (CHR7: 150637053-150834539) might be risk factors for the incidence of GDM.

Crohn's disease (CD) is a refractory and recurrent chronic inflammatory bowel disease with an unclear etiology. In addition to intestinal symptoms, the disease is often accompanied by various extraintestinal manifestations. Studies have found that abnormalities in central nervous system activity in CD patients are closely related to the brain-gut axis, which may be one of the reasons for the high incidence of adverse emotions such as anxiety and depression. Functional magnetic resonance imaging (fMRI) has been widely used in the field of neurogastroenterology due to its non-invasiveness, high spatial resolution, and whole-brain coverage. This article reviews the application and progress of fMRI in CD brain functional study, aiming to comprehensively analyze and integrate the impact of the disease on brain function and provide a reference for clinical diagnosis, treatment, and future research.

Objective:To explore the relationship between urinary cadmium levels and thyroid hormone levels in people aged 40-89 years old in selected areas of China.Methods:Based on the "Investigation of the Impact of Soil Quality of Agricultural Land on Human Health in Typical Areas" project from October 2019 to August 2020, a multi-stage stratified random sampling method was used to include 6 588 middle-aged and older adults aged 40-89. Demographic characteristics, dietary frequency and disease status were collected through the questionnaire and physical examination. Urinary cadmium and urinary creatinine were detected by random midstream urine. Fasting venous blood was collected for the detection of Triiodothyronine (T3) and Thyroxine (T4). The linear mixed effects model was used to explore the association of urine cadmium levels with thyroid hormone levels. Its dose-response relationship was explored by using the restricted cubic spline.Results:The age of the subjects was (63.48±12.18) years, with males accounting for 51.28%. The M ( Q 1,Q 3) of urinary cadmium level, T3 and T4 was 2.48 (1.36, 4.42) μg/g·creatinine, (1.96±0.51) nmol/L and (113.75±29.11) nmol/L, respectively. The linear mixed effects model showed that the changes of T3 and T4 were 0.027 (0.009, 0.044) nmol/L and 2.019 (1.084, 2.953) nmol/L for each one-unit increase (natural logarithm transformed) of urinary cadmium. The restricted cubic spline showed that there was a positive nonlinear association between urinary cadmium and T3 as well as T4 (all Pnonlinear<0.05). Conclusion:In selected areas of China, the urinary cadmium level of middle-aged and older adults aged 40-89 years is positively associated with T3 and T4.

Objective:To investigate the prevalence and risk factors of overweight and obesity among Chinese children aged 3-18 years from 11 provinces, antonomous regions, or municipalities.Methods:This national cross-sectional community health survey utilized a multistage stratified cluster-random sampling method to recruit 193 997 nationally representative participants from 11 provinces, autonomous regions, or municipalities between January 2017 and December 2019. All participants underwent physical examinations, and their caregivers completed questionnaires assessing participants′ dietary, lifestyle, familial, and perinatal information. Multilevel multinomial logistic regression models were employed to identify the potential risk factors.Results:The cohort comprised 193 997 children (102 178 boys, 91 819 girls),aged (10±4) years. Overall prevalence rates were 30 574(15.8%)overweight children and 17 217(8.9%) obesity children. Boys exhibited higher overweight and obesity rates than girls (17.0% (17 368/102 178) vs. 14.4% (13 206/102 178), 11.3% (11 553/91 819) vs. 6.2% (5 664/91 819), χ2=249.12,1 578.69,both P<0.001). The detection rates of obesity in Tanner stage 2 and 3 were the highest in boys and girls, with 13.4%(2 231/16 665) and 8.6%(880/10 221) respectively. Risk factors for obesity included parental overweight (paternal OR=2.34 and maternal OR=2.29), annual household income of 100 000-200 000 yuan (compared with<100 000 yuan, OR=1.04), higher paternal education (compared with below high school,high school and a college education OR=1.09,1.14), birth weight >4.0 kg (≤5 and>5 years old OR=1.74, 1.44,respectively), and western food consumption≥1 time/month (compared with<1, 1-2, 3-4,>4 times/month OR=1.36, 1.30, 1.67(≤5 years), 1.19, 1.16, 1.15 (>5 years), respectively) (all P<0.05). Conversely, coarse grain intake≥1 times/week (compared with<1 times/week, every day, 3-4, 1-2 times/week OR=0.74, 0.80, 0.71 (≤5 years), 0.75, 0.87, 0.90(>5 years), respectively, all P<0.05) was associated with reduced obesity risk. Conclusions:Obesity epidemiology in children demonstrates significant heterogeneity across age, gender, geographic regions, and pubertal stages. It is necessary to establish a personalized prevention and control strategy.