ObjectiveTo investigate the effects and underlying mechanisms of polydatin in delaying the progression of colitis-associated colorectal cancer （CAC） by constructing an azoxymethane （AOM）/dextran sulfate sodium （DSS）-induced CAC mouse model and conducting in vitro experiments. MethodsFifty-four male C57BL/6J mice were randomly divided into normal， model， and polydatin groups （0.045 g·kg^-1）. The CAC mouse model was established using AOM/DSS， and samples were collected at 4， 7， and 10 weeks. Body weight change rate， disease activity index （DAI）， and tumor formation were assessed. Hematoxylin-eosin （HE） staining was used to observe pathological injury in intestinal tissues. Immunohistochemistry （IHC） was performed to detect zonula occludens-1 （ZO-1） expression in colonic tissues， and Western blot was used to detect the expression of E-cadherin， N-cadherin， and Vimentin in colonic epithelial cells. Real-time PCR was used to measure mRNA expression of interleukin-17A （IL-17A）， Wnt3a， β-catenin， T cell factor 1 （Tcf1）， E-cadherin， N-cadherin， and Vimentin in colonic tissues. Flow cytometry was used to analyze the proportion of CD8⁺T cells and the expression of exhaustion-related molecules in tumors. Human colon cancer DLD-1 cells were cultured in a polydatin-containing medium， and wound healing assays were performed to observe migration changes. Real-time PCR was used to detect mRNA expression of interleukin-17 receptor A （IL-17RA）， Wnt3a， β-catenin， Tcf1， E-cadherin， N-cadherin， and Vimentin in DLD-1 cells. ResultsCompared with the normal group， the model group at all three time points showed significantly decreased body weight change rate （P<0.01）， significantly shortened colon length （P<0.01）， and markedly increased DAI scores （P<0.01）. HE staining revealed significant inflammatory cell infiltration in the submucosa of the colon in the model group， accompanied by epithelial dysplasia. ZO-1 expression in colonic tissues was significantly reduced （P<0.01）. The mRNA expression of the pro-inflammatory factor IL-17A and key molecules of the Wnt/β-catenin pathway （Wnt3a， β-catenin， Tcf1） was significantly elevated （P<0.05）. The mRNA and protein expression of epithelial-mesenchymal transition （EMT） markers N-cadherin and Vimentin was significantly upregulated （P<0.05）， while E-cadherin expression was significantly downregulated （P<0.05）. The proportion of tumor-infiltrating CD8⁺T cells expressing immunosuppressive molecules （TIM-3， LAG-3， PD-1） was significantly increased （P<0.05）. Compared with the model group， the polydatin group showed significant improvement in body weight and DAI score （P<0.01）， as well as recovery of colon length and tissue injury. ZO-1 expression in colonic tissue was significantly increased （P<0.01）， while IL-17A， Wnt3a， β-catenin， Tcf1， N-cadherin， and Vimentin expression levels were significantly decreased （P<0.05）， and E-cadherin expression was significantly increased （P<0.01）. Tumor-infiltrating CD8⁺ T cells expressing immunosuppressive molecules were significantly reduced （P<0.05）. In vitro experiments showed that polydatin significantly inhibited migration of DLD-1 cells （P<0.01） and reversed the upregulation of IL-17RA， Wnt3a， β-catenin， N-cadherin， and Vimentin mRNA， as well as the downregulation of E-cadherin mRNA （P<0.05）. ConclusionPolydatin inhibits IL-17A secretion and IL-17RA expression， improves the immune microenvironment， blocks activation of the Wnt/β-catenin signaling pathway， suppresses EMT markers （N-cadherin and Vimentin）， and restores tight junction protein expression in intestinal epithelial cells， thereby delaying the progression from colitis to colorectal cancer in mice.

BackgroundModified electroconvulsive therapy （MECT） is a common front-line strategy widely used in psychiatric practice， and the optimal first stimulus dosage in MECT is usually estimated clinically based on the factors influencing the patient's initial seizure threshold （IST）. However， previous studies on the influencing factors of IST have mostly suffered from limitations such as small sample sizes and single-dimensional research perspectives. ObjectiveTo explore the factors influencing IST in MECT for patients with mental disorders， so as to provide references for stimulus dosing strategies in MECT for the patients. MethodsA retrospective study was used to include 1 446 inpatients fulfilling the diagnostic criteria for any specific mental disorder listed in the ICD-10 and receiving MECT at Shandong Daizhuang Hospital from January 1， 2021 to August 1， 2023. Their general and clinical data were collected， including IST， psychiatric diagnostic categories， gender， ethnicity， age， body weight， body mass index （BMI）， course of disease， family history of psychiatric disorders， first episode status， use of antiepileptic drugs the day before treatment， use of benzodiazepines the day before treatment， and previous MECT treatment history. Pearson correlation analysis was utilized to test the correlation of IST with age， height， body weight， BMI， and course of disease， and stepwise multivariate linear regression analysis was performed to identify the factors affecting IST. ResultsIST yielded statistical difference among patients in terms of gender， first episode status， use of antiepileptic drugs the day before treatment， and use of benzodiazepines the day before treatment （t=2.256， -3.059， -2.136， -3.006， P<0.05 or 0.01）. IST in patients of different ages and psychiatric diagnostic categories also demonstrated statistical difference （F=913.120， 6.212， P<0.01）. Within young population， IST varied significantly based on the psychiatric diagnostic categories （F=2.986， P<0.05）. Correlation analysis indicated that IST was positively correlated with age， body weight， BMI and course of disease （r=0.886， 0.055， 0.184， 0.456， P<0.05 or 0.01）， and negatively correlated with height （r=-0.183， P<0.01）. Stepwise multivariate linear regression analysis revealed that age， gender， and body weight were influencing factors of IST （β=0.888， -0.049， -0.035， P<0.01）. ConclusionsAge， gender and body weight may be factors influencing IST in MECT for patients with mental disorders. ［Funded by Key R&D Plan Projects of Jining City in 2024 (number, 2024YXNS202）］

ObjectiveTo analyze the epidemiological characteristics of long COVID and to investigate its main influencing factors by examining individuals infected with SARS-CoV-2 between March and June 2022 in two communities in Shanghai, to lay the foundation for further research on the mechanism and clinical treatment of long COVID, and to provide the basis for the development of inexpensive, convenient, and feasible prevention and intervention strategies. MethodsA cross-sectional study was conducted, enrolling 6 410 individuals infected with SARS-CoV-2. Data were collected through a questionnaire survey. The incidence and common symptoms of long COVID were analyzed, along with their associations with demographic characteristics, medical history, and behavioral factors. A logistic regression model was used to identify the major factors associated with the development of long COVID symptoms. ResultsThe overall incidence rate of long COVID among the study population was 13.9%. The most commonly reported symptoms included fatigue (65.1%), attention disorders (23.1%), and cough (16.9%). The analysis showed that having underlying chronic diseases (OR=2.580, 95%CI: 2.165‒3.074), a history of allergies (OR=1.418, 95%CI: 1.003‒1.971), current smoking (OR=1.461, 95%CI: 1.013‒2.079), ever smoking (OR=2.462, 95%CI: 1.687‒3.551), a greater number of symptoms during the acute phase [1 symptom (OR=1.778, 95%CI: 1.459‒2.162), 2 symptoms (OR=2.749, 95%CI: 2.209‒3.409), ≥3 symptoms (OR=7.792, 95%CI: 6.333‒9.593)] and aggravated symptoms during the acute phase (OR=1.082, 95%CI: 1.070‒1.094) were factors associated with a higher risk of developing long COVID symptoms. Additionally, individuals who had consumed alcohol in the past year (OR=1.914, 95%CI: 1.344‒2.684) were more prone to objective long COVID symptoms. Among individuals under 50 years of age, females (OR=1.427, 95%CI: 1.052‒1.943) were more likely to develop objective long COVID symptoms. ConclusionThis study has identified the diversity of long COVID symptoms, which involve multiple organs and systems, including fatigue, attention disorders, cough, and joint pain. It has also revealed associations between long COVID and various demographic factors (e.g., age, gender), personal medical history (e.g., underlying chronic diseases, history of allergies), acute-phase characteristics (e.g., number and severity of symptoms), and behavioral factors (e.g., smoking, alcohol consumption). These findings highlight the need for further research and ongoing surveillance of long COVID and may inform the development of more targeted health management strategies for specific populations.

Objective: To investigate the characteristics of malignant tumor incidence and mortality in cancer registration areas of Zhejiang Province in 2021. Methods: Based on the 2021 cancer registration data from 22 national cancer registries in Zhejiang Province, the crude incidence, crude mortality, and cumulative rate for 0 to 74 years were calculated. Age standardized was performed using the age composition of the standard population from the Fifth National Population Census in 2000 and Segi's world standard population. The incidence and mortality characteristics of malignant tumor in different genders, urban/rural areas and ages were described. The order of crude incidence and mortality of malignant tumor were analyzed. Results: In 2021, there were 116 639 new malignant tumor cases in Zhejiang Province. The crude, Chinese population standardized, and world population-standardized incidences were 530.93/100 000, 304.83/100 000, and 288.20/100 000, respectively. The cumulative incidence for 0 to 74 years was 31.92%. There were 40 475 death cases. The crude, Chinese population-standardized, and world population-standardized mortalities were 184.24/100 000, 79.40/100 000, and 78.97/100 000, respectively. The cumulative mortality for 0 to 74 years was 8.37%. The Chinese population-standardized incidence for males and females were 286.34/100 000 and 323.45/100 000, respectively, and the Chinese population-standardized mortality were 106.25/100 000 and 54.17/100 000, respectively. The Chinese population-standardized incidence for urban and rural were 316.85/100 000 and 285.11/100 000, respectively, and the Chinese population-standardized mortality were 75.59/100 000 and 85.48/100 000, respectively. The crude incidence and crude mortality of malignant tumor both increased with age, peaking in the groups aged 80-<80 and ≥85 years at 1 845.06/100 000 and 1 656.88/100 000, respectively. The top ten malignant tumors with the highest crude incidence were, in descending order: lung cancer, thyroid cancer, breast cancer, prostate cancer, colorectal cancer, gastric cancer, liver cancer, cervical cancer, lymphoma, and brain tumors. These accounted for 80.34% of all new malignant tumor cases. The top ten malignant tumors with the highest crude mortality were, in descending order: lung cancer, liver cancer, colorectal cancer, gastric cancer, pancreatic cancer, prostate cancer, breast cancer, esophageal cancer, lymphoma, and gallbladder cancer. These accounted for 82.26% of all malignant tumor deaths. Conclusions In 2021, the cancer registration areas of Zhejiang Province were characterized by a relatively high malignant tumor incidence and a comparatively low mortality compared to national data. Males and the elderly emerged as key populations for targeted prevention and control. It is recommended to enhance screening, early diagnosis, and early treatment for lung cancer, thyroid cancer, prostate cancer, breast cancer, and gastric cancer malignancies.

ObjectiveTo analyze the epidemiological characteristics and influencing factors of SARS-CoV-2 reinfection by conducting follow-up investigations among community residents who experienced their first SARS-CoV-2 infection between March and June 2022, so as to provide a scientific basis for predicting future epidemic trends and adjusting prevention and control strategies. MethodsA cohort study was conducted in Xuhui District, Shanghai. A total of 1 208 individuals with a documented primary SARS-CoV-2 infection between March and June 2022 were enrolled and followed-up longitudinally. Data were collected using structured questionnaire surveys to assess the reinfection rate, incidence density, and clinical manifestations of SARS-CoV-2 reinfection. A logistic regression model was used to analyze the influencing factors of SARS-CoV-2 reinfection. ResultsA total of 497 SARS-CoV-2 reinfection cases were observed among the 1 208 research subjects, with a reinfection rate of 41.14% and an incidence density of 0.63 cases per 1 000 person-days. The cumulative reinfection rates at 6, 9, 12, 15, and 18 months following the initial infection were 0.08%, 15.31%, 19.04%, 33.53%, and 38.25%, respectively. Compared with the primary infection, reinfection was more likely to be symptomatic, with a greater severity of fever, dry cough, sore throat, and runny nose. Being female, younger age, and symptom duration ≥7 days during the primary infection were identified as influencing factors for SARS-CoV-2 reinfection, while a higher socioeconomic status can reduce the risk of SARS-CoV-2 reinfection. ConclusionSARS-CoV-2 reinfection is relatively common and often symptomatic. Age, gender, income level, and the duration of symptoms during the primary infection are identified as infuencing factors for SARS-CoV-2 reinfection. Continuous monitoring of reinfection in the population is recommended, along with the development of effective strategies to mitigate the impact of reinfection.

BACKGROUND: Lung adenocarcinoma (LUAD) is the predominant subtype of non-small cell lung cancer (NSCLC). Damage-specific DNA binding protein 1 (DDB1), as a core protein of the CUL4-DDB1 ubiquitin ligase complex, is involved in the regulation of DNA damage repair, epigenetic modification, and cell cycle checkpoint activation. While the involvement of DDB1 in tumour progression through DNA repair and RNA transcriptional regulation has been reported, its expression and role in LUAD remain to be elucidated. This study aims to investigate the expression and role of DDB1 in LUAD. METHODS: The expression, clinicopathological features and prognosis of DDB1 in LUAD were analysed using databases such as UALCAN, Kaplan-Meier Plotter and GEPIA; The interaction network and enriched functional pathways were constructed by GeneMANIA and Metascape; the correlation between DDB1 and immune cells by combining with TISIDB infiltration was evaluated, and the clustering results of cell subtypes and the expression of DDB1 in different immune cell subpopulations were analysed by single-cell sequencing; finally, tissue microarrays were used to further verify the expression and prognostic value of DDB1 in LUAD. RESULTS: The mRNA and protein expression of DDB1 in LUAD tissues were significantly higher than those in normal tissues (P<0.01), and the high expression correlated with later clinical stage (P<0.001), lymph node metastasis (P<0.001) and poor prognosis (P<0.001). Functional enrichment showed that DDB1 was involved in DNA repair and RNA transcriptional regulation, and TISIDB evaluation revealed that DDB1 was negatively correlated with the expression level of immune cells, suggesting the potential regulation of the immune microenvironment. Single cell analysis showed that DDB1 was mainly expressed in T cells, alveolar macrophages and dendritic cells. Tissue microarrays confirmed that overall survival was shorter in the DDB1 high expression group (P<0.001), and Cox multifactorial analysis showed that DDB1 was an independent predictor of LUAD prognosis. CONCLUSIONS DDB1 is highly expressed in LUAD, which is associated with poor prognosis, and is closely related to tumor immune cell infiltration, and is involved in tumourigenesis and development through DNA repair and RNA transcriptional regulation. DDB1 can be used as a potential prognostic marker and therapeutic target for LUAD.
Humans ; Adenocarcinoma of Lung/immunology* ; DNA-Binding Proteins/metabolism* ; Lung Neoplasms/diagnosis* ; Gene Expression Regulation, Neoplastic ; Prognosis ; Male ; Female ; Middle Aged

OBJECTIVE: To evaluate the effect of palliative care on drug use, medical service utilization and medical expenditure of patients with advanced cancer. METHODS: A cohort of patients including pal-liative care and standard care was constructed using the medical records of the patients in Peking University Cancer Hospital from 2018 to 2020, and coarsened exact matching was used to match the two groups of patients. The average monthly opioid consumption, hospitalization rate, intensive care unit (ICU) rate and operation rate, and the average monthly total cost were selected to evaluate drug use, medical service utilization and medical expenditure. Chi-square test and Wilcoxon signed rank test were used to compare the differences between the two groups before and after exposure and the change in the palliative care group. The net impact of palliative care on the patients was calculated using the difference-in-differences analysis. RESULTS: In this study, 180 patients in the palliative care group and 3 101 patients in the stan-dard care group were finally included in the matching, and the matching effect of the two groups was good (L₁ < 0.1). Before and after exposure, the average monthly opioid consumption in the palliative care group was significantly higher than that in the standard care group (Before exposure: 0.3 DDD/person-month vs. 0.1 DDD/person-month, P < 0.01; After exposure: 0.7 DDD/person-month vs. 0.1 DDD/person-month, P < 0.01; DDD refers to defined daily dose), palliative care significantly increased the average monthly opioid consumption in the patients (0.3 DDD/person-month, P < 0.01). The hospitalization rate (48.9% vs. 74.3%, P < 0.01) and operation rate (3.9% vs. 8.8%, P < 0.01) of the patients in palliative care group were significantly lower than those in standard care group, and the ICU rate became similar between the two groups (1.1% vs. 1.6%, P=0.634). Palliative care significantly reduced the patients ' hospitalization rate (-25.6%, P < 0.01), ICU rate (-4.9%, P < 0.01) and operation rate (-14.5%, P < 0.01). Before and after exposure, the average monthly total costs of pal-liative care group were slightly higher than those of standard care group (Before exposure: 20 092.3 yuan vs. 19 132.8 yuan, P=0.725; After exposure: 9 719.8 yuan vs. 8 818.8 yuan, P=0.165). Palliative care increased the average monthly total cost by 2 208.8 yuan, but it was not statistically significant (P=0.316). CONCLUSION Palliative care can increase the opioid consumption in advanced cancer patients, reduce the rates of hospitalization, ICU and surgery, but has no significant effect on medical expenditure.
Humans ; Palliative Care/economics* ; Neoplasms/drug therapy* ; Analgesics, Opioid/economics* ; Male ; Female ; Middle Aged ; Aged ; Hospitalization/economics* ; Intensive Care Units/statistics & numerical data* ; Health Expenditures/statistics & numerical data* ; Adult ; Drug Utilization/statistics & numerical data* ; Patient Acceptance of Health Care/statistics & numerical data*

The pharmaceutical industry faces challenges in quality digitization for complex multi-stage processes, especially in small-sample systems. Here, an intelligent quality prediction and diagnostic (IQPD) framework was developed and applied to Tong Ren Tang's Niuhuang Qingxin Pills, utilizing four years of data collected from four production units, covering the entire process from raw materials to finished products. In this framework, a novel path-enhanced double ensemble quality prediction model (PeDGAT) is proposed, which combines a graph attention network and path information to encode inter-unit long-range and sequential dependencies. Additionally, the double ensemble strategy enhances model stability in small samples. Compared to global traditional models, PeDGAT achieves state-of-the-art results, with an average improvement of 13.18% and 87.67% in prediction accuracy and stability on three indicators. Additionally, a more in-depth diagnostic model leveraging grey correlation analysis and expert knowledge reduces reliance on large samples, offering a panoramic view of attribute relationships across units and improving process transparency. Finally, the IQPD framework integrates into a Human-Cyber-Physical system, enabling faster decision-making and real-time quality adjustments for Tong Ren Tang's Niuhuang Qingxin Pills, a product with annual sales exceeding 100 million CNY. This facilitates the transition from experience-driven to data-driven manufacturing.

Liver being substantial Yin and functional Yang maintain normal function of Qi， blood and meridians. In clinical practice， it is often found that pan-vascular lesions with atherosclerosis as the predominant pathological change often co-occur with metabolic dysfunction-associated fatty liver disease（MAFLD）. MAFLD leads to increased risk and worse prognosis for many pan-vascular diseases， including cardiovascular disease. Dysregulation of energy homeostasis disrupts the hepatic homeostasis of body use， and representative drugs to improve metabolism， such as metformin， sodium-glucose co-transporter 2 inhibitors， and glucagon-like peptide-1 agonists， not only have a clear cardiovascular benefit， potential improvement of MAFLD has also been demonstrated. The liver stores blood and the heart pumps blood， and liver diseases affect the heart， that's why the unsmoothness of vessels appears. So the treatment should from the standpoint of liver， restoring liver function， soothing the liver and nourishing heart， activating blood and dredging meridian. It is of great significance to explore in depth the pathogenesis and treatment of pan-vascular lesions caused by MAFLD， and to restore the energy homeostasis by adjusting the balance of liver Yin and Yang.

ObjectiveTo explore the correlation between the blood stasis score of coronary heart disease（CAD） and mild cognitive impairment（MCI）， as well as the changes in plasma metabolic profile of blood stasis in patients with CAD combined with MCI（CADMCI） through a cross-sectional study， and further explore the impact of different degrees of blood stasis on the plasma metabolite profile of CADMCI patients. MethodsAccording to the diagnostic criteria of CAD and CAD blood stasis， patients hospitalized in Xiyuan Hospital of China Academy of Chinese Medical Sciences from October 2022 to October 2023 were continuously included. According to the Montreal Cognitive Assessment（MoCA） scale score， the enrolled patients were divided into CADMCI blood stasis group and CAD blood stasis group. The association between blood stasis score and MCI was analyzed by multivariate Logistic regression model. The receiver operating characteristic（ROC） curve was drawn， and the area under the curve（AUC） was calculated to evaluate the sensitivity and specificity of the model. According to the blood stasis score， the first 30 patients in the CADMCI blood stasis group and CAD blood stasis group were divided into mild blood stasis and severe blood stasis. Ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS） was used to detect plasma metabolites in each group of patients. The differential metabolites were screened according to variable importance in the projection（VIP） value≥1， fold change（FC）<0.67 or >1.5， and P<0.05. ROC curve analysis was further used to evaluate the discriminatory efficiency of the screened differential metabolites for each group of samples. ResultsA total of 266 CAD patients were included in this study. Multivariate Logistic regression analysis showed that the CAD blood stasis score was significantly correlated with MCI［odds ratio（OR）=1.619， 95% confidence interval（CI） 1.223-2.142， P<0.001， ROC curve AUC was 0.615（95% CI 0.547-0.683， P=0.001）］， indicating that the CAD blood stasis score has a certain predictive value for MCI. Plasma non-targeted metabolomics analysis showed that the main differential metabolites between CAD blood stasis and CADMCI blood stasis were lipid metabolites， among which phosphatidylcholine［20∶4（5Z， 8Z， 11Z， 14Z）/P-18∶1（11Z）］ had the best discriminatory efficiency（ROC curve AUC=0.867， 95% CI 0.754-0.942）. Further analysis of the differential metabolites between mild and severe blood stasis showed that lipid metabolites were also the main differential metabolites between mild and severe blood stasis. Among them， 1α，25-dihydroxy-2β-（2-hydroxyethoxy） vitamin D₃ had the best efficacy in distinguishing mild and severe CAD blood stasis（AUC=0.813， 95% CI 0.649-0.951）， and phosphatidylcholine 34∶2 had the best efficacy in distinguishing mild and severe CADMCI blood stasis（AUC=0.819， 95% CI 0.640-0.941）. ConclusionThere is a significant correlation between CAD blood stasis score and MCI. Phosphatidylcholine metabolites play an important role in the pathogenesis of CADMCI blood stasis and severe blood stasis. The CAD blood stasis score combined with the detection of phosphatidylcholine metabolites can provide a reference for the development of early and efficient identification strategies for CADMCI.