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 gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

In the era of intelligence and individualization, gastric cancer surgery is under-going multidimensional advancements. The authors focus on the cutting-edge progress and future challenges of artificial intelligence (AI) in the diagnosis and decision-making, treatment and drug development, as well as postoperative rehabilitation in gastric cancer surgery. In terms of diagnosis, AI integrates imaging, liquid biopsy, pathology, and multimodal technologies to enhance diagnostic comprehensiveness and accuracy. Regarding decision-making, AI assists in formulating personalized treatment plans, conducting risk assessments, and predicting prognoses. In the treatment domain, AI facilitates the advancement of individualized surgical approaches, supports postoperative follow-up, and aids in physician education and training. In drug development, the introduction of virtual cell models and AlphaFold has improved the efficiency and accuracy of mechanistic and clinical research. For postoperative rehabilitation guidance, AI provides personalized recommendations to optimize treatment outcomes.AI holds great promise in gastric cancer surgery across diagnosis and decision-making, treatment and drug development, and postoperative rehabilitation. However, current AI technologies face challenges such as data sharing and privacy protection, multicenter research and model generalization, human-machine collaboration, interpretability, ethical considerations, sustaina-bility, and widespread adoption. Addressing these challenges will require collective efforts to fully leverage AI′s advantages in gastric cancer diagnosis and treatment.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To investigate the factors influencing the persistence of prostate specific antigen(PSA) following radical prostatectomy, and to develop and validate a predictive model for PSA persistence.Methods:Clinical data from 1 828 patients who underwent radical prostatectomy at Shanghai Changhai Hospital between January 2015 and December 2023 were retrospectively analyzed. Of these, 1 295 patients from January 2015 to April 2021 comprised the modeling group, while 533 patients from May 2021 to December 2023 formed the validation group. Additionally, 109 patients who underwent radical surgery at the Third Affiliated Hospital of Naval Medical University between March and December 2023 were included as an external validation group. Patients with incomplete clinical information, serum PSA levels exceeding 100 ng/ml, or those who received preoperative neoadjuvant therapy were excluded. Ultimately, 1 003, 369, and 86 patients were included in the modeling, validation, and external validation groups, respectively. The modeling group had serum PSA of 19.29 (8.43, 23.73) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 191, 673, 123, and 16 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 460, 466, and 77 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 363, 486, and 154 patients, respectively. The validation group had serum PSA of 12.80 (6.82, 14.40) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 40, 289, 37, and 3 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 218, 145, and 6 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 140, 184, and 45 patients, respectively. The external validation group had serum PSA of 12.84 (7.11, 12.97) ng/ml; the clinical stages were distributed as T 1, T 2 and T 3 in 9, 68, and 9 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 58, 27, and 1 patient, respectively; and the secondary Gleason scores were 3, 4, and 5 in 28, 50, and 8 patients, respectively. Logistic regression analysis was used to identify independent risk factors for PSA persistence after radical prostatectomy in the modeling group and a prediction model was constructed. The predictive performance of the model was analyzed using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve, the calibration curve, and the clinical decision curve. The predictive performance of the model was verified by the ROC curve in the validation group and the external validation group. Results:The incidence of persistent PSA after surgery in the modeling group, validation group, and external validation group was 8.97% (90/1 003), 7.32% (27/369), and 17.4% (15/86), respectively. In the modeling group, univariate and multivariate logistic regression analysis revealed that serum PSA, percentage of positive needle cores, primary Gleason score on biopsy, and secondary Gleason score on biopsy were independent risk factors for PSA persistence ( P<0.05), and a prediction model was constructed based on these factors. The AUC value of this model was 0.790 (95% CI 0.745-0.835). Calibration curve and clinical decision curve analyses showed that the model's predicted probabilities aligned well with actual risks within the 0-40% prediction interval, providing clinical benefit. The AUC values of the ROC curves in the validation group and external validation group were 0.808 (95% CI 0.719-0.897) and 0.822 (95% CI 0.714-0.929), respectively, indicating that the model had good predictive performance. Conclusions:The predictive model for PSA persistence, constructed based on serum PSA, percentage of positive needle cores, primary and secondary Gleason score on biopsy, demonstrated good clinical predictive performance, exhibiting high accuracy in both internal and cross-center validation.

Objective:To investigate the current status of occupational stress among electronic manufacturing workers in Qingdao and analyze its effect on depressive symptoms and anxiety symptoms.Methods:From July to September 2022, a cluster random sampling method was employed to select frontline workers from 14 electronic manufacturing enterprises in Qingdao as the study subjects. A total of 1134 questionnaires were distributed, with 1000 valid questionnaires collected, yielding an effective response rate of 88.18%. The Core Occupational Stress Scale (COSS), the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7) were adopted to assess occupational stress, depressive symptoms, and anxiety symptoms, respectively. Binary logistic regression was employed to analyze influencing factors of occupational stress and its effects on depressive and anxiety symptoms.Results:The detection rates of occupational stress, depressive symptoms, and anxiety symptoms were 15.1% (15/1000), 7.9% (79/1000), and 13.8% (138/1000), respectively. The influencing factor analysis of occupational stress revealed that female gender ( OR=0.621, 95% CI: 0.434-0.890) and weekly working hours of 45-48 hours ( OR=0.537, 95% CI: 0.309-0.935) were protective factors ( P<0.05), while weekly working hours ≥55 hours ( OR=2.176, 95% CI: 1.290-3.670) and shift work ( OR=2.038, 95% CI: 1.412-2.940) were risk factors ( P<0.05). Spearman correlation analysis showed that the COSS score was positively related with the PHQ-9 score and the GAD-7 score ( rs=0.438, 0.289, P<0.01). Workers judged with occupational stress had 3.596 times (95% CI: 2.181-5.931, P<0.001) and 3.121 times (95% CI: 2.046-4.761, P<0.001) higher risks of detecting depressive and anxiety symptoms compared to those without occupational stress. Conclusion:Electronic manufacturing workers in Qingdao experience a certain level of occupational stress, which may increase the risk of developing depressive and anxiety symptoms. Enterprises should implement appropriate interventions to promote workers' mental health.

Objective:To investigate the factors influencing the persistence of prostate specific antigen(PSA) following radical prostatectomy, and to develop and validate a predictive model for PSA persistence.Methods:Clinical data from 1 828 patients who underwent radical prostatectomy at Shanghai Changhai Hospital between January 2015 and December 2023 were retrospectively analyzed. Of these, 1 295 patients from January 2015 to April 2021 comprised the modeling group, while 533 patients from May 2021 to December 2023 formed the validation group. Additionally, 109 patients who underwent radical surgery at the Third Affiliated Hospital of Naval Medical University between March and December 2023 were included as an external validation group. Patients with incomplete clinical information, serum PSA levels exceeding 100 ng/ml, or those who received preoperative neoadjuvant therapy were excluded. Ultimately, 1 003, 369, and 86 patients were included in the modeling, validation, and external validation groups, respectively. The modeling group had serum PSA of 19.29 (8.43, 23.73) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 191, 673, 123, and 16 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 460, 466, and 77 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 363, 486, and 154 patients, respectively. The validation group had serum PSA of 12.80 (6.82, 14.40) ng/ml; the clinical stages were distributed as T 1, T 2, T 3, and T 4 in 40, 289, 37, and 3 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 218, 145, and 6 patients, respectively; and the secondary Gleason scores were 3, 4, and 5 in 140, 184, and 45 patients, respectively. The external validation group had serum PSA of 12.84 (7.11, 12.97) ng/ml; the clinical stages were distributed as T 1, T 2 and T 3 in 9, 68, and 9 patients, respectively; the primary Gleason scores of biopsy were 3, 4, and 5 in 58, 27, and 1 patient, respectively; and the secondary Gleason scores were 3, 4, and 5 in 28, 50, and 8 patients, respectively. Logistic regression analysis was used to identify independent risk factors for PSA persistence after radical prostatectomy in the modeling group and a prediction model was constructed. The predictive performance of the model was analyzed using the area under the curve (AUC) of the receiver operating characteristics (ROC) curve, the calibration curve, and the clinical decision curve. The predictive performance of the model was verified by the ROC curve in the validation group and the external validation group. Results:The incidence of persistent PSA after surgery in the modeling group, validation group, and external validation group was 8.97% (90/1 003), 7.32% (27/369), and 17.4% (15/86), respectively. In the modeling group, univariate and multivariate logistic regression analysis revealed that serum PSA, percentage of positive needle cores, primary Gleason score on biopsy, and secondary Gleason score on biopsy were independent risk factors for PSA persistence ( P<0.05), and a prediction model was constructed based on these factors. The AUC value of this model was 0.790 (95% CI 0.745-0.835). Calibration curve and clinical decision curve analyses showed that the model's predicted probabilities aligned well with actual risks within the 0-40% prediction interval, providing clinical benefit. The AUC values of the ROC curves in the validation group and external validation group were 0.808 (95% CI 0.719-0.897) and 0.822 (95% CI 0.714-0.929), respectively, indicating that the model had good predictive performance. Conclusions:The predictive model for PSA persistence, constructed based on serum PSA, percentage of positive needle cores, primary and secondary Gleason score on biopsy, demonstrated good clinical predictive performance, exhibiting high accuracy in both internal and cross-center validation.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

The paper introduces Professor JI Laixi's academic thought and clinical experience in treatment of primary open angle glaucoma with "nape-eight-needle" acupotomy. Professor JI Laixi believes that the key pathogenesis lies in "occlusion of xuanfu (subtle orifices) within the eyes and obstruction of meridian pathways". Using the unblocking principle of treatment, taking meridian theory of traditional acupuncture as the core and based on the anatomical principles of structural acupuncture, Professor JI has proposed his academic thought, "treating eye diseases from the nape". In treatment, "nape-eight-needle" acupotomy is adopted, combined with filiform needle acupuncture. It is the advantageous compound therapeutic method, aiming to open xuanfu, restore brain-eye meridian connectivity, harmonize body, qi and mind through systemic regulation, address both the causative factors and symptoms and prevent from blindness. This therapeutic approach provides a new idea for clinical treatment of primary open angle glaucoma.
Humans ; Acupuncture Therapy/history* ; Glaucoma, Open-Angle/therapy* ; Male ; Meridians ; Female ; Acupuncture Points ; Middle Aged ; Aged