Objective To analyze the urban drinking water quality and its influencing factors in Anhui Province from 2014 to 2022, and to provide a scientific basis for water quality improvement and protection. Methods The data were collected, saved and monitored according to the Standard Test Method for Drinking Water (GB/T5750-2006) and evaluated according to the Hygienic Standard for Drinking Water (GB 5749-2006). Results A total of 20 941 samples were collected, and the overall qualified rate was 84.26%. The qualified rate of urban drinking water increased from 76.9% in 2014 to 93.3% in 2022, and the qualified rate of water quality was on the rise (χ²=544.43, P＜0.01). From 2014 to 2022, the qualified rate of water quality in dry season was higher than that in wet season (χ²=35.98, P<0.001), the qualified rate of surface water was higher than that of ground water (χ²=4440.8, P<0.001), and the qualified rate of peripheral tap water was higher than that of factory water (χ²=145.1, P<0.001). Among all kinds of disinfection methods, chlorination disinfection had the highest qualified rate (χ²=1483.8, P<0.001). The qualified rate of water quality increased with the increase of the scale of water plant. Among the inspected indicators, the main unqualified indicators were chlorine dioxide (7.72%), fluoride (7.41%), free residual chlorine (3.90%), and total bacterial count (2.13%). Conclusion The passing rate of urban drinking water quality in Anhui Province is on an upward trend, and the quality of urban drinking water has improved. However, it is still important to pay attention to the problem of excessive microorganism and fluoride in water, and the quality of drinking water varies from place to place.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

Objective: To investigate the prevalence of sleep quality among the elderly in nursing homes in Changning District, Shanghai Municipality, so as to provide insights into prevention and intervention strategies for improving sleep quality and overall quality of life for the elderly. Methods: The elderly from 25 nursing homes in Changning District were selected using a two-stage sampling method. Basic information including gender, age and types of medication were collected. Sleep quality was assessed using the Athens Insomnia Scale, and depressive symptoms were measured using the Geriatric Depression Scale. Factors affecting sleep quality among the elderly in nursing homes were analyzed using a multivariable logistic regression model. Results: A total of 739 participants were surveyed, including 516 males (69.82%) and 223 females (30.18%). The majority of participants were aged 80 to <90 years (478, 64.68%). Among them, 432 participants (58.46%) had normal sleep, 144 (19.49%) had suspected insomnia, and 163 (22.06%) had insomnia. Multivariable logistic regression analysis showed that older age (OR=1.030, 95%CI: 1.005-1.055), more medication types (OR=1.971, 95%CI: 1.381-2.812), frequent nighttime bathroom visits (OR=2.921, 95%CI: 1.853-4.605) and depressive symptoms (OR=3.295, 95%CI: 2.440-4.449) were associated with a higher risk of insomnia among the elderly in nursing homes. Conclusions Insomnia was reported in 22.06% of the elderly in nursing homes in Changning District. Age, the number of medication types, frequency of nighttime bathroom visits, and depressive symptoms are the main influencing factors for their sleep quality.

Objective To investigate the prevalence and risk factors of cognitive impairment in the nursing home population in Changning District, Shanghai. Methods In this study, random cluster sampling method was used to select 570 elderly people from 5 nursing homes in Changning District. Multivariate logistic regression was used to analyze the risk factors influencing cognitive function. Results The total prevalence of cognitive impairment in Changning nursing home population was 22.5%. The prevalence rates of ≤80 and >80 age groups were 16.8% and 23.9%, respectively, and the prevalence rates of men and women were 19.2% and 23.9%, respectively. Multivariate analysis showed that age ≥ 80 years old (OR=1.839, 95% CI: 1.045~3.235), no habit of reading book or newspaper (OR=2.087, 95%CI: 1.282~3.398), limitation of daily activity ability (OR=1.577, 95% CI: 1.023~2.431), and having depressive symptoms (OR=2.809, 95% CI: 1.840~4.288) were all influencing factors for cognitive impairment. Conclusion More than one fifth of elderly people in nursing homes in Changning District have symptoms of cognitive impairment. It is necessary to carry out routine cognitive assessment and appropriate cognitive intervention for the nursing home population to reduce the health and economic losses caused by cognitive impairment.

Liver metastases (LMs) are common in lung cancer. Despite substantial advances in diagnosis and treatment, the survival rate of patients with LM remains low as the immune-suppressive microenvironment of the liver allows tumor cells to evade the immune system. The impact of LMs on the outcomes of immune checkpoint inhibitors in patients with solid tumors has been the main focus of recent translational and clinical research. Growing evidence indicates that the hepatic microenvironment delivers paracrine and autocrine signals from non-parenchymal and parenchymal cells. Overall, these microenvironments create pre- and post-metastatic conditions for the progression of LMs. Herein, we reviewed the epidemiology, physiology, pathology and immunology, of LMs associated with non-small cell lung cancer and the role and potential targets of the liver microenvironment in LM in each phase of metastasis. Additionally, we reviewed the current treatment strategies and challenges that should be overcome in preclinical and clinical investigations. These approaches target liver elements as the basis for future clinical trials, including combinatorial interventions reported to resolve hepatic immune suppression, such as immunotherapy plus chemotherapy, immunotherapy plus radiotherapy, immunotherapy plus anti-angiogenesis therapy, and surgical resection.

Objective: To examine the association of hypertension onset age with diabetes, so as to provide insights into reducing the the risk of cardiovascular events. Methods: Permanent residents aged 35 to 75 years were selected through the program of early screening and comprehensive intervention for the high-risk cardiovascular disease population in Changning District and Baoshan District, Shanghai Municipality from 2016 to 2020. Demographic information, disease history, hypertension onset age, blood pressure and fasting blood glucose were collected through questionnaire surveys, physical examination and laboratory tests. The residents were divided into four groups based on the onset age of hypertension: <45, 45-<55, 55-<65 and ≥65 years old, and the residents with normal blood pressure were selected as control. The association of hypertension onset age with prediabetes and diabetes were identified using a multivariable logistic regression model. Results: A total of 25 228 residents were recruited, including 8 753 males (34.70%) and 16 475 females (65.30%). The prevalence of hypertension was 43.80%. There were 1 779, 3 274, 3 781 and 2 217 cases with hypertension onset age of <45, 45-<55, 55-<65 and ≥65 years old, respectively, and 14 177 residents with normal blood pressure. The prevalence of prediabetes and diabetes were 24.01% and 11.29%, respectively. Multivariable logistic regression analysis showed that after adjusting for confounding factors such as gender, marital status and educational level, compared with the normal blood pressure group, the risk of prediabetes was higher in the hypertension onset age groups of <45 (OR=1.345, 95%CI: 1.164-1.553), 45-<55 (OR=1.365, 95%CI: 1.212-1.536) and 55-<65 years old (OR=1.376, 95%CI: 1.239-1.527), and the risk of diabetes was higher in the hypertension onset age groups of <45 (OR=2.302, 95%CI: 1.906-2.775), 45-<55 (OR=2.349, 95%CI: 2.016-2.734), 55-<65 (OR=1.909, 95%CI: 1.667-2.184) and ≥65 years old (OR=1.315, 95%CI: 1.131-1.526). Conclusion There are statistically significant associations between hypertension onset age with prediabetes and diabetes.

Objective To investigate the current situation of home environment safety of the elderly in Changning District, identify the risk factors related to the fall of the home environment of the elderly, and take targeted rectification measures, so as to create a safer environment for the elderly. Methods A phased random sampling method was used to select 201 elderly households from 10 streets in Changning District. Community doctors conducted on-the-spot investigation and assessment to collect information, and Epidata3.1 was used to input data and SAS 9.2 was used for statistical analysis. Results The incidence of falls in the past year was 19.90%, and the score of environmental risk factors/the number of environmental risk factors in each family ranged from 0 to 25, with an average of 9 items (standard deviation of 4.71). The results of multivariate logistic regression analysis show that the high level of falling environment (the number of falling risk factors in home environment ≥12) is still an independent risk factor for falls of the elderly, except for the influence of age and the number of drugs taken (OR=3.835, 95% CI:1.718-8.561). Conclusion The environmental risk factors causing falls are common in the home environment of the elderly in the community. It is necessary to focus on improving the home environment, reducing the risk of falls for the elderly, and creating a safe and comfortable home environment for the elderly.

Objectives:To analyze the status and temporal changes of disability-adjusted life year (DALY) for stomach and colorectal cancers among registered permanent residents in Changning District of Shanghai Municipality, and provide scientific basis for the prevention and treatment of stomach and colorectal cancers in this district.Methods:Using the cancer registration data of stomach and colorectal cancers from 2002 to 2019, we estimated the indices such as the DALYs, the DALY crude rates, the age-standardized DALY rates, etc. Then we used the Joinpoint regression model to calculate the average annual percent change (AAPC) and annual percent change (APC) to explore the temporal variations in different periods.Results:The DALYs of stomach and colorectal cancers in Changning District from 2002 to 2019 were 55 931 person years and 65 252 person years, respectively. The crude rates of DALY were 512.16/10 5 and 597.51/10 5, respectively. We observed a higher disease burden in men than in women, and the peak rate of DALY in stomach cancer was in the 75-79 years age group, while in colorectal cancer the rate was in the 85-years-or-older age group. Joinpoint regression analysis showed that from 2002 to 2019, the age-standardized DALY rate of stomach cancer showed a downward trend (AAPC=-3.86%, P＜0.05), while the trend of colorectal cancer was not statistically significant(AAPC=-0.08%, P＞0.05). However, the trends in the age-standardized DALY rates of colorectal cancer were different between males and females, with males showing an upward trend (AAPC=1.24%, P＜0.05) and females showing a downward trend (AAPC=-1.67%, P＜0.05). Conclusions:The DALY of stomach and colorectal cancers in Changning District of Shanghai showed a decreasing trend. Males and the middle-aged and elderly populations are still the key targets for disease prevention and control in this district.

Objective To build a dataset encompassing a large number of stained tongue coating images and process it using deep learning to automatically recognize stained tongue coating images. Methods A total of 1 001 images of stained tongue coating from healthy students at Hunan University of Chinese Medicine and 1 007 images of pathological(non-stained)tongue coat-ing from hospitalized patients at The First Hospital of Hunan University of Chinese Medicine with lung cancer,diabetes,and hypertension were collected.The tongue images were randomi-zed into the training,validation,and testing datasets in a 7:2:1 ratio.A deep learning model was constructed using the ResNet50 for recognizing stained tongue coating in the training and validation datasets.The training period was 90 epochs.The model's performance was evaluated by its accuracy,loss curve,recall,F1 score,confusion matrix,receiver operating characteristic(ROC)curve,and precision-recall(PR)curve in the tasks of predicting stained tongue coating images in the testing dataset.The accuracy of the deep learning model was compared with that of attending physicians of traditional Chinese medicine(TCM). Results The training results showed that after 90 epochs,the model presented an excellent classification performance.The loss curve and accuracy were stable,showing no signs of overfitting.The model achieved an accuracy,recall,and F1 score of 92%,91%,and 92%,re-spectively.The confusion matrix revealed an accuracy of 92%for the model and 69%for TCM practitioners.The areas under the ROC and PR curves were 0.97 and 0.95,respectively. Conclusion The deep learning model constructed using ResNet50 can effectively recognize stained coating images with greater accuracy than visual inspection of TCM practitioners.This model has the potential to assist doctors in identifying false tongue coating and prevent-ing misdiagnosis.

Objective To explore the value of intravoxel incoherent motion(IVIM)parameters in the diagnosis of ipsilateral thalamic diaschisis(ITD)after unilateral supratentorial cerebral infarction via combination of arterial spin labeling(ASL)and IVIM.Methods A total of 111 patients with cerebral infarction were selected,including 61 patients in the acute stage(＞6 h-3 d),50 patients in the subacute stage(＞3 d-11 d).All patients were subjected to MRI examination,and the diffusion weighted imaging(DWI),ASL,and IVIM image data were uploaded to the GE workstation.The regions of interest(ROI)in the bilateral thalamus were selected,and the cerebral blood flow(CBF),D*,D,and f values were measured,and the asymmetry index(AI)was calculated.ITD was diagnosed according to AI＞10％,and all patients were divided into ITD-positive and ITD-negative groups.The differences of each parameter between the two groups and their relationship with AI were analyzed.Results In acute stage and subacute stage cerebral infarction,the CBF,D*and D values of ipsilateral thalamus were lower than those of contralateral thalamus,while the f value was higher than those of contralateral thalamus.There was no statistical significance in D*,D and f values between ITD-positive and ITD-negative groups after acute stage cerebral infarction(P＞0.05).There were significant differences in CBF,apparent diffusion coefficient(ADC),D and f values in ITD-positive group after subacute stage cerebral infarction(P＜0.05),but no significant differences in D*value of ITD-positive group and CBF,D*,D,f values of ITD-negative group(P＞0.05).AI-D*,AI-D and AI-ADC in subacute stage were positively correlated with AI-CBF,while AI-f was negatively correlated with AI-CBF.The area under the curve(AUC)of AI-D and AI-f in subacute stage were 0.749 and 0.699,respectively.Conclusion The combination of ASL and IVIM has confirmed the phenomenon of ITD after unilateral supratentorial cerebral infarction,with high diagnostic efficacy of quantitative parameters D value and f value.It can non-invasively evaluate the thalamic microstructural and perfusion changes in the early stage after cerebral infarction.