Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Objective:To investigate the effect of neoadjuvant chemotherapy on the safety of laparoscopic D 2 radical resection and prognosis of patients with locally advanced gastric cancer. Methods:The propensity score matching and retrospective cohort study was conducted. The clinicopathological data of 351 patients with locally advanced gastric cancer who underwent laparos-copic D 2 radical resection in the Second Affiliated Hospital of Air Force Medical University from December 2016 to December 2021 were collected. There were 256 males and 95 females, aged (58±9)years. Of the 351 patients, 124 cases undergoing neoadjuvant chemotherapy were divided into the neoadjuvant chemotherapy group, 227 patients undergoing postoperative adjuvant chemotherapy were divided into the adjuvant chemotherapy group. Observation indicators: (1) propensity score matching and comparison of general data of patients between the two groups after matching; (2) effect evaluation of neoadjuvant chemotherapy; (3) intraoperative and postoperative situations; (4) postoperative histopathological examinations; (5) follow-up. Propensity score matching was done by the 1∶1 nearest neighbor matching method. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the t test. Measure-ment data with skewed distribution were represented as M(range) or M( Q1, Q3), and comparison between groups was conducted using the rank sum test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. The Kaplan-Meier method was used to draw survival curves, and the Log-Rank test was used for survival analysis. Results:(1) Propensity score matching conditions and comparison of general data of patients between the two groups of patients after matching. Of 351 patients, 154 cases were successfully matched, including 77 cases in the neoadjuvant chemotherapy group and 77 cases in the adjuvant chemotherapy group. The elimination of gender, age, preoperative body mass index, clinical T staging and clinical N staging confounding bias ensured comparability between the two groups after propensity score matching. (2) Effect evaluation of neoadjuvant chemotherapy. Of the 77 patients receiving neoadjuvant chemotherapy, none of patient achieved complete response, 26 patients achieved partial response, 46 patients showed stable disease, 5 patients had progression of disease, showing the objective response rate as 33.8%(26/77) and the disease control rate as 93.5%(72/77). There were 15 males and 11 females sensitive to neoadjuvant chemotherapy, while 46 males and 5 females not sensitive, showing a significant difference between them ( χ2=11.05, P<0.05). (3) Intra-operative and postoperative situations. The operation time, volume of intraoperative blood loss, cases with intraoperative blood transfusion, time to postoperative first flatus, time to postoperative first liquid food intake, duration of postoperative hospital stay, cases with postoperative immediate complications, cost of hospital stay were (308±71)minutes, 100(range, 20?600)mL, 5, 3.0(range, 2.0?10.0)days, 4.0(range, 2.0?12.0)days, 9.0(range, 4.0?31.0)days, 7, 7.96(7.37,8.58) ten thousand yuan in patients of the neoadjuvant chemotherapy group, versus (296±67)minutes, 100(range, 20?500)mL, 4, 3.5(range, 1.0?14.0)days, 4.0(range, 2.0?15.0)days, 8.0(range, 5.0?45.0)days, 11, 8.18(7.52,9.19) ten thousand yuan in patients of the adjuvant chemotherapy group, showing no signifi-cant difference in the above indicators between the two groups ( t=1.13, Z=?0.37, χ2=0.12, Z=?1.26, ?0.33, ?0.70, χ2=1.01, Z=?1.04, P>0.05). (4) Postoperative histopathological examinations. Results of postoperative histopatho-logical examinations showed that all 154 patients achieving R 0 resection. Cases with pathological T staging as stage T1, stage T2, stage T3, stage T4, cases with pathological N staging as stage N0, stage N1, stage N2, stage N3, number of positive lymph nodes, cases with human epidermal growth factor receptor 2 (negative, positive) were 3, 7, 5, 62, 27, 19, 19, 12, 1(range, 0?28), 59, 18 in patients of the neoadjuvant chemotherapy group, versus 0, 0, 2, 75, 17, 15, 21, 24, 3(range, 0?31), 44, 33 in patients of the adjuvant chemotherapy group, showing significant differences in the above indicators between the two groups ( Z=?3.39, ?2.55, ?3.12, χ2=6.60, P<0.05). (5) Follow-up. Of the 154 patients, 143 patients were followed up for 37(range, 5?69)months. The 3-year overall survival rate and 3-year disease-free survival rate was 72.1% and 70.0%, respectively, in patients of the neoadjuvant chemotherapy group, versus 74.8% and 76.6% in patients of the adjuvant chemo-therapy group, showing no significant difference in the above indicators between the two groups ( χ2=0.14, 0.60, P>0.05). Conclusions:Compared to postoperative adjuvant chemotherapy, neoadjuvant chemotherapy does not bring additional surgical risks, but can reduce the tumor stage of patients who underwent laparoscopic D 2 radical resection for locally advanced gastric cancer. However, it does not show any advantage in improving survival of patients.

Sclerostin, a protein secreted from osteocytes, negatively regulates the WNT signaling pathway by binding to the LRP5/6 co-receptors and further inhibits bone formation and promotes bone resorption. Sclerostin contributes to musculoskeletal system-related diseases, making it a promising therapeutic target for the treatment of WNT-related bone diseases. Additionally, emerging evidence indicates that sclerostin contributes to the development of cancers, obesity, and diabetes, suggesting that it may be a promising therapeutic target for these diseases. Notably, cardiovascular diseases are related to the protective role of sclerostin. In this review, we summarize three distinct types of inhibitors targeting sclerostin, monoclonal antibodies, aptamers, and small-molecule inhibitors, from which monoclonal antibodies have been developed. As the first-in-class sclerostin inhibitor approved by the U.S. FDA, the monoclonal antibody romosozumab has demonstrated excellent effectiveness in the treatment of postmenopausal osteoporosis; however, it conferred high cardiovascular risk in clinical trials. Furthermore, romosozumab could only be administered by injection, which may cause compliance issues for patients who prefer oral therapy. Considering these above safety and compliance concerns, we therefore present relevant discussion and offer perspectives on the development of next-generation sclerostin inhibitors by following several ways, such as concomitant medication, artificial intelligence-based strategy, druggable modification, and bispecific inhibitors strategy.