Objective To explore the visiting behavior and health management strategy of patients with cardiovascular disease (CVD) and the industry management strategies under the family doctor contract service model. Methods A total of 351 patients with CVD from January 2022 to January 2025 were included in the case investigation by random sampling. Taking the number of visits in community health service institutions/total number of visits ≥90% as high compliance, the influencing factors of the visiting behavior of CVD patients were analyzed. Results Finally, 344 valid questionnaires were collected, with an effective recovery rate of 98.01%. The study subjects were categorized into high compliance group (271 cases) and low compliance group (73 cases). The scores of policy cognition understanding, institutional trust and medical service understanding in the high compliance group were higher compared with those in the low compliance group (P<0.05). There was no significant difference in the understanding of medical expenses between the two groups (P>0.05). Multivariate logistic regression model analysis revealed that CVD duration [OR (95% CI): 1.72 (1.21-2.44)], policy cognition understanding [OR (95% CI): 2.16 (1.20-3.89)] and institutional trust [OR (95% CI): 1.88 (1.08-3.25)] were independently associated with medical treatment behavior in CVD patients (P<0.05). Conclusion Enhancing the policy cognition understanding and institutional trust of CVD patients on family doctor contract service can promote patients to seek medical treatment and promote the high-quality development of family doctor contract service.

Lung cancer remains one of the leading causes of cancer-related morbidity and mortality worldwide, and its treatment continues to face major challenges such as therapeutic resistance and tumor recurrence. Pyroptosis, a newly characterized form of programmed cell death, induces tumor cell death through gasdermin-mediated membrane pore formation and is accompanied by the release of inflammatory mediators, thereby playing complex roles in lung cancer initiation, progression, and modulation of the tumor microenvironment. Active components and herbal formulas derived from traditional Chinese medicine can modulate pyroptosis-related signaling pathways through multi-target mechanisms, showing potential advantages in inducing lung cancer cell death, inhibiting proliferation and migration, and reversing chemoresistance. This review systematically summarizes relevant studies from domestic and international sources, focusing on the molecular mechanisms of pyroptosis, its roles in lung cancer development and tumor microenvironment remodeling, and the current research progress on traditional Chinese medicine-based interventions targeting pyroptosis, with the aim of providing references for the prevention and treatment of lung cancer using traditional Chinese medicine.

ObjectiveTo compare female C57BL/6J and BALB/c mice models of ulcerative colitis (UC) induced by dextran sulfate sodium salt (DSS), providing a reference for selecting female animal models in studies of innovative drugs for UC treatment. MethodsA total of 48 female mice aged 6–8 weeks, including 24 C57BL/6J and 24 BALB/c mice, were divided into four groups: control group, UC-3d group (2.5% DSS drinking for 3 days), UC-7d group (2.5% DSS drinking for 7 days), and UC-withdrawal group (2.5% DSS drinking for 7 days followed by 3 days of pure water replacement), with 6 mice in each group. Body weight, fecal occult blood, and stool characteristics were recorded daily, and disease activity index (DAI) scores were calculated. At the end of DSS induction, mice were gavaged with fluorescein isothiocyanate (FITC)-labeled dextran solution before tissue collection. Four hours later, under deep anesthesia induced by inhalation of 4% isoflurane, blood samples were collected from the retro-orbital venous plexus, and euthanasia was performed by cervical dislocation. The colon was then separated immediately, and its length from the anus to the ileocecal junction was measured. Colon tissues were fixed, embedded, and sectioned, and they were evaluated using hematoxylin-eosin (HE) staining and alcian blue-periodic acid-Schiff (AB-PAS) staining to comprehensively assess the degree of colonic inflammation. The spleen was also collected and weighed, and the spleen coefficient was calculated. Serum FITC fluorescence intensity and D-lactic acid concentration were measured to evaluate intestinal permeability and barrier injury. The grooming duration, the number of buried marbles, the time spent in the center of the open field, and the total distance traveled were measured to evaluate anxiety/depression-like behaviors in mice. ResultsFecal occult blood appeared in both C57BL/6J and BALB/c mice after 3 days of ad libitum access to DSS. Compared with the control group, there was no significant change in the weight loss rate of female BALB/c mice in the UC-7d and UC-withdrawal groups (P > 0.05), but the DAI score increased (P < 0.01). Conversely, both the weight loss rate and DAI score increased for female C57BL/6J mice in the UC-7d and UC-withdrawal groups (P < 0.01). In female C57BL/6J mice, both the UC-7d and UC-withdrawal groups had higher spleen coefficients than the control group (P < 0.05). Additionally, in these groups, colon length was significantly reduced (P < 0.01), FITC fluorescence intensity in serum was markedly increased (P < 0.01), obvious inflammatory reaction areas appeared in the colon, and the goblet cells and acidic mucus layer were damaged. In contrast, in female BALB/c mice, no significant differences were observed in colon length, serum FITC fluorescence intensity, or D-lactic acid concentration between the UC-7d and UC-withdrawal groups compared with the control group (P > 0.05). Only a few inflammatory cells and damaged goblet cells were observed in the colonic mucosal layer, and no other obvious pathological changes were detected. In addition, female C57BL/6J mice in the UC-7d group showed a significantly reduced total distance in the open field and fewer buried marbles (P < 0.05), indicating depression-like behavior, as well as prolonged grooming duration (P < 0.05), indicating anxiety-like behavior. ConclusionFemale BALB/c mice are not sensitive to 2.5% DSS and do not show typical colonic pathological changes of UC. In contrast, ad libitum access to 2.5% DSS for 7 days successfully induces typical UC pathological symptoms and colonic pathological changes in female C57BL/6J mice. These changes persist for 3 days after DSS withdrawal, and the mice also exhibit symptoms of anxiety/depression. The results suggest that this model can be used for research on the pathogenesis and therapeutic drugs of UC.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

BackgroundCurrent studies on the relationship between depressive symptoms and the risks of stroke and all-cause mortality mostly focus on the elderly population or high-risk groups with chronic diseases. The long-term impact of depressive symptoms in young and middle-aged people on the risks of stroke and all-cause mortality still lacks systematic assessment， and the relevant evidence is insufficient. ObjectiveTo explore the association between depressive symptoms and the risks of stroke and all-cause mortality in young and middle-aged adults， thereby expanding the risk evidence in this age group and providing epidemiological basis for early identification of high-risk individuals and the development of targeted intervention strategies. MethodsBased on data from the National Health and Nutrition Examination Survey （NHANES） database （2009–2018）， a total of 14 947 young and middle-aged respondents aged 18 to 64 were included as the research subjects. Logistic regression and restricted cubic spline （RCS） models were employed to examine the association between depressive symptoms and stroke. Cox proportional hazards model， RCS model， and Kaplan-Meier （K-M） survival curves were used to clarify the relationship between depressive symptoms and all-cause mortality risk. To verify the robustness of main findings， sensitivity analysis was conducted stratified by gender， hypertension， diabetes， hyperlipidemia， body mass index （BMI）， and age. ResultsLogistic regression analysis revealed that compared with the non-depressed group， the risk of stroke in the mild depression group increased by 53.50% （OR=1.535， 95% CI： 1.147–2.053）， while the moderate-to-severe depression group showed the highest risk with a 132.90% increase （OR=2.329， 95% CI： 1.733–3.129）. RCS analysis indicated an approximately linear dose-response relationship between PHQ-9 score and the risk of stroke （P_{for non-linearity}=0.089）， with stroke risk increasing as PHQ-9 scores rose. As the PHQ-9 score increased， the risk of stroke also showed an upward trend. Cox regression analysis demonstrated that compared with the non-depressed group， the risk of all-cause mortality in the mild depression group increased by 48.80% （HR=1.488， 95% CI： 1.164–1.902）， and the moderate-to-severe depression group had a 70.60% increased risk （HR=1.706， 95% CI： 1.310–2.221）. RCS analysis showed a linear dose-response relationship between PHQ-9 scores and all-cause mortality risk （P_{for non-linearity}=0.440）. K-M curves indicated that as the severity of depressive symptoms increases， the risk of all-cause mortality gradually rises （P<0.05）. Sensitivity analysis confirmed that the associations between depression symptoms and risks of stroke and all-cause mortality were not modified by gender， hypertension， diabetes， hyperlipidemia， BMI， or age， demonstrating robust findings. ConclusionAmong the young and middle-aged population， both mild and moderate-to-severe depression were associated with increased risks of stroke and all-cause mortality， with the moderate-to-severe depression group showed more pronounced risk elevations. A positive dose-response relationship was observed between depressive symptoms and these risks.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Objective:To observe the clinical efficacy and safety of Jianpi Bushen Jiedu Prescription combined with 5-fluorouracil (5-FU)-based chemotherapy and targeted therapy for the treatment of advanced colorectal cancer patients with liver and kidney yin deficiency combined with spleen deficiency pattern.Methods:A randomized controlled trial was conducted. A total of 72 hospitalized patients with advanced colorectal cancer treated at the Department of Oncology, Nanjing Hospital of Traditional Chinese Medicine Affiliated to Nanjing University of Chinese Medicine from October 2022 to January 2024 were enrolled as study subjects. Using a random number table method, they were allocated into two groups, with 36 patients in each group. The control group received the mFOLFOX6/FOLFIRI combined with bevacizumab regimen, while the treatment group was administered additional oral Jianpi Bushen Jiedu Prescription on the basis of the control group. Two weeks was a cycle in both groups, with a total of 6 cycles of treatment. Serum levels of carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), and carbohydrate antigen 724 (CA724) were detected using electrochemiluminescence; the Karnofsky Performance Status (KPS) scale was utilized to evaluate patients' functional status; vital signs were continuously monitored, and adverse reactions were recorded. The short-term efficacy and TCM syndrome efficacy of patients were evaluated.Results:The treatment group demonstrated higher objective response rate (ORR) [31.25% (10/32) vs. 21.88% (7/32), χ2=0.72] and disease control rate (DCR) [84.38% (27/32) vs. 71.88% (23/32), χ2=1.46] compared to the control group, without statistical significance ( P>0.05). Post-treatment levels of CEA [4.09 (3.31,8.57) μg/L vs. 10.07 (4.55,22.35) μg/L, Z=-2.10] and CA72-4 [4.54 (2.04,10.99) mU/L vs. 9.48 (4.34,18.95) mU/L, Z=-2.52] in the treatment group were significantly lower than those in the control group ( P<0.05). The total effective rate of TCM syndrome was significantly higher in the treatment group [78.13% (25/32)] compared with the control group [50.00% (16/32)], with statistical significance ( χ2=5.50, P=0.019). Post-treatment KPS scores in the treatment group [80.0 (80.0, 80.0) vs. 70.0 (62.5, 80.0), Z=-2.76] were significantly higher compared with the control group ( P<0.01). During the treatment period, the treatment group showed statistical significance compared with the control group in the incidence of hemoglobin decrease ( χ2=4.66), leukopenia decrease ( χ2=4.27), and peripheral neuropathy ( χ2=3.93), with statistical significance ( P<0.05). Conclusion:The addition of Jianpi Bushen Jiedu Prescription to 5-FU-based chemotherapy combined with targeted therapy demonstrates significant clinical benefits in advanced colorectal cancer patients, including reducing tumor marker levels, alleviating clinical symptoms, improving quality of life, and mitigating treatment-related toxicities, with a good safety.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.