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.

Background China is a major coal producer and consumer country in the world. Coal workers' pneumoconiosis (CWP) is a primary factor endangering the occupational health of coal miners. Research on the disease burden of CWP and its changing trend is significant for disease prevention & control and associated policies. Objective To analyze the disease burden of CWP in China from 1990 to 2021 and its changing trend, and predict the disease burden from 2022 to 2035. Methods Using the Global Burden of Disease Study (GBD) database of 2021, numbers ofincident cases, prevalent cases, deaths, and disability-adjusted life years (DALYs) as well as crude and age-standardized rates of CWP in China were retrieved. Linear regression model was used to calculate the estimated annual percentage change (EAPC) of the age-standardized rates. Joinpoint regression model was used to analyze the temporal trend of disease burden and the disease burden of different sexes and age groups, and Bayesian age-period-cohort (BAPC) model was used to forecast the trend of CWP disease burden. Results In 1990, the incident, prevalent, and deaths cases of CWP in China were 3266, 18872, and 1561, respectively, and the DALYs of CWP were 44614.718 person-years. In 2021, the incident, prevalent, and deaths cases of CWP were 3446, 23975, and 1229, respectively, and the DALYs of CWP were 29610.754 person-years. From 1990 to 2021, the age-standardized incidence, prevalence, mortality, and DALYs rates of CWP in China all showed a downward trend, with the EAPCs of −3.121%, −2.532%, −4.018%, and −4.268%, respectively. The disease burden of CWP in China was mainly concentrated in the male population. The annual average percent change analysis indicated that each standardized rate showed a fluctuating downward trend in different periods. The BAPC model showed that from 2022 to 2035, the age-standardized rates of CWP in China would continue to decline steadily. In 2035, the age-standardized incidence, prevalence, mortality, and DALYs rates of CWP would be reduced to 0.10 per 100000, 0.74 per 100000, 0.03 per 100000, and 0.74 per 100000, respectively. Conclusion The disease burden contributed by CWP in China generally show a downward trend from 1990 to 2021, and it is expected that the age-standardized rates will continue to decline steadily from 2022 to 2035.

BACKGROUND: The global rise in diabetes prevalence is a pressing concern. Despite initiatives like "The Healthy Beijing Action 2020-2030" advocating for increased awareness, treatment, and control, the specific situation in Beijing remains unexplored. This study aimed to analyze the trends in diabetes prevalence, awareness, treatment, and control among Beijing adults. METHODS: Through a stratified multistage probability cluster sampling method, a series of representative cross-sectional surveys were conducted in Beijing from 2005 to 2022, targeting adults aged 18-79 years. A face-to-face questionnaire, along with body measurements and laboratory tests, were administered to 111,943 participants. Data from all survey were age- and/or gender-standardized based on the 2020 Beijing census population. Annual percentage rate change (APC) or average annual percentage rate change (AAPC) was calculated to determine prevalence trends over time. Complex sampling logistic regression models were employed to explore the relationship between various characteristics and diabetes. RESULTS: From 2005 to 2022, the total prevalence of diabetes among Beijing adults aged 18-79 years increased from 9.6% (95% CI: 8.8-10.4%) to 13.9% (95% CI: 13.1-14.7%), with an APC/AAPC of 2.1% (95% CI: 1.1-3.2%, P <0.05). Significant increases were observed among adults aged 18-39 years and rural residents. Undiagnosed diabetes rose from 3.5% (95% CI: 3.2-4.0%) to 7.2% (95% CI: 6.6-7.9%) with an APC/AAPC of 4.1% (95% CI: 0.5-7.3%, P <0.05). However, diabetes awareness and treatment rates showed annual declines of 1.4% (95% CI: -3.0% to -0.2%, P <0.05) and 1.3% (95% CI: -2.6% to -0.2%, P <0.05), respectively. The diabetes control rate decreased from 21.5% to 19.1%, although not statistically significant (APC/AAPC = -1.5%, 95% CI: -5.6% to 1.9%). Overweight and obesity were identified as risk factors for diabetes, with ORs of 1.65 (95% CI: 1.38-1.98) and 2.48 (95% CI: 2.07-2.99), respectively. CONCLUSIONS The prevalence of diabetes in Beijing has significantly increased between 2005 and 2022, particularly among young adults and rural residents. Meanwhile, there has been a concerning decrease in diabetes awareness and treatment rates, while control rates have remained stagnant. Regular blood glucose testing, especially among adults aged 18-59 years, should be warranted. Furthermore, being male, elderly, overweight, or obese was associated with higher diabetes risk, suggesting the needs for targeted management strategies.
Humans ; Adult ; Middle Aged ; Male ; Female ; Aged ; Adolescent ; Young Adult ; Cross-Sectional Studies ; Diabetes Mellitus/epidemiology* ; Beijing/epidemiology* ; Prevalence ; China/epidemiology* ; Surveys and Questionnaires

The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

OBJECTIVE: To investigate the accuracy and safety of pedicle screw placement using 3D-printed auxiliary guides in scoliosis correction surgery for adolescents. METHODS: A retrospective analysis was conducted on the clinical data of 51 patients who underwent posterior scoliosis correction surgery from January 2020 to March 2023. Among them, there were 35 cases of adolescent idiopathic scoliosis and 16 cases of congenital scoliosis. The patients were divided into two groups based on the auxiliary tool used:the 3D-printed auxiliary guide screw placement group (3D printing group) and the free-hand screw placement group (free-hand group, without auxiliary tools). The 3D printing group included 32 patients (12 males and 20 females) with an average age of (12.59±2.60) years;the free-hand group included 19 patients (7 males and 12 females) with an average age of (14.58±3.53) years. The two groups were compared in terms of screw placement accuracy and safety, spinal correction rate, intraoperative blood loss, number of intraoperative fluoroscopies, operation time, hospital stay, and preoperative and last follow-up scores of the Scoliosis Research Society-22 (SRS-22) questionnaire. RESULTS: A total of 707 pedicle screws were placed in the two groups, with 441 screws in the 3D printing group and 266 screws in the free-hand group. All patients in both groups successfully completed the surgery. There was a statistically significant difference in operation time between the two groups (P<0.05). The screw placement accuracy rate of the 3D printing group was 95.46% (421/441), among which the Grade A placement rate was 89.34% (394/441);the screw placement accuracy rate of the free-hand group was 86.47% (230/266), with a Grade A placement rate of 73.31% (195/266). There were statistically significant differences in the accuracy of Grade A, B, and C screw placements between the two groups (P<0.05), while no statistically significant differences were observed in intraoperative blood loss, number of fluoroscopies, correction rate, or hospital stay (P>0.05). In the SRS-22 questionnaire scores, the scores of functional status and activity ability, self-image, mental status, and pain of patients in each group at the last follow-up were significantly improved compared with those before surgery (P<0.05), but there were no statistically significant differences in all scores between the two groups (P>0.05). CONCLUSION In scoliosis correction surgery, compared with traditional free-hand screw placement, the use of 3D-printed auxiliary guides for screw placement significantly improves the accuracy and safety of screw placement and shortens the operation time.
Humans ; Male ; Scoliosis/surgery* ; Female ; Adolescent ; Printing, Three-Dimensional ; Retrospective Studies ; Pedicle Screws ; Child

OBJECTIVE: The aim of this study is to investigate the risk factors of prognosis in patients with early-onset prostate cancer treated without surgery. A nomogram will be constructed and validated to predict overall survival (OS) of patients with early-onset prostate cancer treated without surgery. METHODS: The clinical data was obtained from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) database on prostate cancer patients aged 18－55 years who were treated without surgery between 2010 and 2015. The clinical data set was divided into training set and validation set according to 7∶3 ratio, including age, race, marital status, Gleason score, prostate specific antigen (PSA) and other 8 factors. And significant variables were screened by univariate Cox regression analysis. Multivariate Cox regression analysis was used to identify the influence factors. Stepwise regression method was used to select the most influential factors on the total OS, and R software was used to build a nomogram model. The accuracy and prediction ability of the model were verified by drawing receiver operating characteristic (ROC) and Calibration Plot. The clinical benefit of the model was evaluated by decision curve analysis (DCA). RESULTS: A total of 8 212 patients who met the criteria were randomly assigned to the training set (n=5 752) or validation set (n=2 460), with no statistical difference between the two groups (all P>0.05). Six factors were identified through univariate and multivariate Cox regression analysis including marital status, N stage, M stage, radiotherapy, PSA and Gleason score, which were most closely associated with the OS of prostate cancer patients, and a column graph model was constructed based on these factors. The Consistency index (C-index) of the model in the training set and the verification set were 0.802 and 0.794, respectively. And the apparent diffusion coefficient (AUC) was 0.851, 0.855 and 0.855 for training sets 1, 3 and 5 years, and 0.694, 0.860 and 0.832 for verification sets 1, 3 and 5 years. The calibration chart showed a good agreement between the predicted and actual values of the model. In the analysis of decision curve, the model showed good clinical application value. CONCLUSION The prediction model based on marital status, radiotherapy, M stage, N stage, PSA and Gleason score for early-onset prostate cancer patients without surgical treatment has certain reference value which is expected to become an effective tool for clinicians to treat in future prospective studies on large and multi-center samples.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Middle Aged ; Nomograms ; SEER Program ; Prognosis ; Adult ; Prostate-Specific Antigen ; Risk Factors ; Proportional Hazards Models ; Neoplasm Grading ; ROC Curve

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

BACKGROUND: Diabetes mellitus with nonalcoholic fatty liver disease (DM-NAFLD) represents a complex metabolic syndrome with significant clinical challenges. This study explores the therapeutic potential and underlying mechanisms of umbilical cord-derived mesenchymal stem cells (UCMSCs)-derived extracellular vesicles (EVs) in DM-NAFLD. METHODS: UCMSCs-EVs were isolated and characterized. DM-NAFLD mouse model was developed through highenergy diet and streptozotocin injection. Additionally, primary mouse hepatocytes were exposed to high glucose to simulate cellular conditions. Hepatic tissue damage, body weight changes, lipid levels, glucose and insulin homeostasis, and hepatic lipid accumulation were evaluated. The interaction between UCMSCs-EVs and hepatocytes was assessed, focusing on the localization and function of circ-Tulp4. The study also investigated the expression of circularRNA TUBlike protein 4 (circ-Tulp4), heterogeneous nuclear ribonucleoprotein C (HNRNPC), abhydrolase domain containing 6 (ABHD6), cleaved Caspase-1, NLR family pyrin domain containing 3 (NLRP3) and cleaved N-terminal gasdermin D (GSDMD-N). The binding of circ-Tulp4 to lysine demethylase 6B (KDM6B) and the subsequent epigenetic regulation of ABHD6 by H3K27me3 were analyzed. RESULTS: Circ-Tulp4 was reduced, while HNRNPC and ABHD6 were elevated in DM-NAFLD models. UCMSCs-EVs attenuated hepatic steatosis and inhibited the NLRP3/cleaved Caspase-1/GSDMD-N pathway. EVs delivered circ-Tulp4 into hepatocytes, thereby restoring circ-Tulp4 expression. Elevated circ-Tulp4 enhanced the recruitment of H3K27me3 to the HNRNPC promoter through interaction with KDM6B, thus suppressing HNRNPC and ABHD6. Overexpression of HNRNPC or ABHD6 counteracted the protective effects of UCMSCs-EVs, exacerbating pyroptosis and hepatic steatosis in DM-NAFLD. CONCLUSION UCMSCs-EVs deliver circ-Tulp4 into hepatocytes, where circ-Tulp4 inhibits the HNRNPC/ABHD6 axis, thereby reducing pyroptosis and alleviating DM-NAFLD. These findings provide a novel therapeutic avenue for targeting DM-NAFLD through modulation of cell pyroptosis.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.