Objective To explore the impact of wearable devices in assisting disease monitoring on heart-focused anxiety in patients with tachyarrhythmias. Methods A cross-sectional study design was conducted. 305 patients with tachyarrhythmias who attended the department of cardiology of Zhongshan Hospital, Fudan University in Shanghai from July 2025 to December 2025 were enrolled as the research subjects, and clinical data of patients were collected. Univariate analysis and multiple stepwise regression analysis were used to analyze the impact of wearable devices in assisting disease monitoring on patients’ heart-focused anxiety. Results The mean score of heart-focused anxiety in the 305 patients with tachyarrhythmias was 33.16±9.70. Among them, 104(34.10%) patients used wearable devices in assisting disease monitoring. The results of univariate analysis and multiple stepwise regression showed that the use of wearable devices in assisting disease monitoring was an influencing factor for heart-focused anxiety (P＜0.05), and the patients who used wearable devices in assisting disease monitoring had a significantly lower level of heart-focused anxiety (P＜0.05). Conclusions The use of wearable devices in assisting disease monitoring is associated with a lower level of heart-focused anxiety in patients with tachyarrhythmias. Medical staff can guide patients to rationally use wearable devices in assisting disease monitoring on the basis of evaluating their needs and device operation capabilities.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Previous studies have shown that the diversity and composition of intestinal microbiota are related to the effect of tumor immunotherapy,but the mechanism of intestinal microbiota affecting tumor immunotherapy resistance has rarely been sum-marized.This article not only expounds the current clinical sta-tus of tumor immunotherapy resistance,but also summarizes the correlation and regulatory mechanism between the composition and homeostasis of intestinal microbiota and drug resistance to different types of tumor immunotherapy,so as to provide a refer-ence for the study of potential targets for improving tumor immu-notherapy resistance based on intestinal microbiota.

AIM To study the chemical constituents from salt-processed Litchi Semen and their antioxidant activities.METHODS The 85％ethanol extract from salt-processed Litchi Semen was isolated and purified by silica gel,Sephadex LH-20,MCI,ODS and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.DPPH and ABTS+free radical scavenging method were used to evaluate their antioxidant activities.RESULTS Fifteen compounds were isolated and identified as dehydrocostuslactone(1),ananosmoside A(2),funingensin A(3),(2S)-pinocembrin-7-O-(6-O-α-L-rhamnopyranosyl-β-D-glucopyranoside)(4),liquiritienin(5),quercetin(6),rutin(7),isorhamnetin-3-O-β-rutinoside(8),procyanidin A2(9),procyanidin A1(10),ethyl protocatechuate(11),5-hydroxymethylfurfural(12),di(2-ethyl-hexyl)phthalate(13),nicotinamide(14),(10E,15Z)-9,12,13-trihydroxyoctadeca-10,15-dienoic acid(15).Compounds 6-7,9-10 exhibited scavenging activities against DPPH radicals with IC50 values of(12.929±1.232),(14.104±0.946),(10.417±1.736),(6.944±0.030)μmol/L,respectively.Compounds 6-10 exhibited scavenging activities against ABTS+radicals with IC50 values of(21.952±0.577),(25.683±0.625),(22.970±1.336),(20.210±1.435),(18.725±0.324)μmol/L,respectively.CONCLUSION Compounds 1,5,14-15 are isolated from Litchi genus for the first time.Compounds 6-7,9-10 have strong in vitro antioxidant activities.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Previous studies have shown that the diversity and composition of intestinal microbiota are related to the effect of tumor immunotherapy,but the mechanism of intestinal microbiota affecting tumor immunotherapy resistance has rarely been sum-marized.This article not only expounds the current clinical sta-tus of tumor immunotherapy resistance,but also summarizes the correlation and regulatory mechanism between the composition and homeostasis of intestinal microbiota and drug resistance to different types of tumor immunotherapy,so as to provide a refer-ence for the study of potential targets for improving tumor immu-notherapy resistance based on intestinal microbiota.

Objective:To explore the role positioning and job responsibilities of integrated care managers in China, with a view to providing reference for policy formulation and career development.Methods:The qualitative study was conducted. From December 2023 to July 2024, 18 frontline workers and managers working in integrated care in two hospitals, two community health service centers and seven elderly care institutions in Beijing were selected by purposive sampling method to conduct semi-structured interviews. Colaizzi 7-step analysis was used to analyze the data.Results:A total of six core roles and seven responsibilities of the integrated care managers were identified, including the role of the comprehensive assessor and the responsibility of conducting comprehensive health assessments, the role of the team collaborator and the responsibility of organizing interdisciplinary discussions, decision-making and collaboration, the role of the case manager and the responsibility of developing and implementing integrated care plans, the role of the resource integrator and the responsibility of coordinating and integrating resources, the role of the service controller and the responsibility of supervising and optimizing care services, the role of professional leader and communicator and the responsibility of promoting team building and development, and the responsibility of leading professional innovation and growth.Conclusions:As an emerging complex professional talent to cope with population aging, clarifying their roles and responsibilities is of great significance in realizing the goal of healthy aging and building an integrated healthcare service system in China. Integrated care managers should be based on personalized, multi-level, and whole-process care service needs, flexibly adapt to diversified role changes, and stimulate their own intrinsic motivation and innovation ability to provide high-quality care services.

Objective:To understand the usability evaluation indicators for intelligent caregiving robots in elderly care from the perspectives of stakeholders, and provide a reference for constructing a usability evaluation indicator system for these robots.Methods:This study was a qualitative study. From November 2023 to May 2024, purposive sampling was used to select eight intelligent robot developers from three engineering universities and one medical technology company, seven intelligent product usage managers from three elderly care institutions in Beijing, and seven elderly users who have used intelligent caregiving robots at Xuanwu Hospital of Capital Medical University. Semi-structured interviews were conducted with these participants. The content analysis method was employed to organize and analyze the interview data, and themes were extracted.Results:A total of four themes and eleven sub-themes were identified: safety and reliability (mechanical safety, sensory safety, privacy safety) , performance (effectiveness, fault tolerance, intelligence) , user experience (learnability, ease of use, comfort) , and cost-effectiveness (cost-performance ratio, usage cost) .Conclusions:The usability evaluation indicators for intelligent caregiving robots in elderly care, extracted from multiple perspectives, provide a reference for constructing a scientific, reasonable, and comprehensive usability evaluation indicator system for intelligent caregiving robots in elderly care.

Objective:To explore the impact of community environment on the functional ability in the elderly based on a person-environment fit perspective.Methods:The descriptive qualitative research method was used. Applying the purposive sampling method, elderly people attending two community health centers and their subordinate health stations in Beijing were selected as respondents from January to May 2024. An interview outline was developed based on the person-environment fit theory, and semi-structured interviews were used to collect information. Thematic analysis was used for data analysis.Results:A total of 16 community elderly people were interviewed, and four themes were finalized, including multidimensional compensation of the environment for individual competence (accessible and convenient environments compensate for declining motor abilities, supportive physical environments compensate for declining vision and vitality, social support compensates for declining cognitive abilities, and age-friendly environments enhancing a sense of belonging and security) , congruence of personal preferences with the community environment (diversity of activities to meet individualized needs, environmental stability to ensure a sense of control over life, age-friendly digital environments to meet the digital needs of the elderly) , personal influencing factors of the perceived environment (length of residence, personal health status, personal social relations) , and coping styles with person-environment mismatches (enhancement of individual capabilities, use of assistive devices for self-empowerment, proactive home age-friendly adaptation, self-psychological adjustment) .Conclusions:Community healthcare workers should emphasize the role of the environment and give full consideration to the individual characteristics, needs and preferences of the elderly people, and pay special attention to the elderly people who have a poor perception of the environment and encourage them to take positive coping styles to adapt to the environment.

AIM To study the chemical constituents from ethyl acetate fraction of Balanophora harlandii Hook.f.and their tyrosinase inhibitory activity.METHODS Separation and purification were performed using silica gel,MCI,ODS,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The monophenolase inhibitory activity was determined by the tyrosinase-catalyzed oxidation of L-tyrosine.RESULTS Twenty-four compounds were isolated and identified as sesamin(1),methyl caffeate(2),quercetin(3),5,7-dihydroxychromanone(4),methyl 3,4-dihydroxybenzoate(5),esculetin(6),kaempferol(7),naringenin(8),pyrogallic acid(9),pinosylvin(10),methyl propionate(11),caffeic acid(12),saccharinol(13),ferulic acid(14),trans-p-hydroxycinnamic acid(15),cinnamic acid(16),vanillic acid(17),vanillin(18),4-hydroxyacetophenone(19),4-hydroxybenzaldehyde(20),apigenin(21),(-)-isolariciresinol(22),(-)-secoisolariciresinol(23)and meso-2,3-di(3′,4′-methylenedioxybenzyl)butane-1,4-diol(24).The IC50 values of compounds 3,5,7,8,19,and 20 ranged from(0.246 5±0.028 3)to(1.278 2±0.021 3)mmol/L.CONCLUSION Compounds 1-9、11、15、17-21、24 are isolated from this plant for the first time,and 1,6,9,17-19,24 are first isolated from genus Balanophora.Compounds 3、5、7、8、19 and 20 have tyrosinase inhibitory activity.