Objective To explore the risk factors of progression to dementia within 2 years in patients with recent subcortical small infarction (RSSI) complicated with cognitive dysfunction. Methods A total of 340 patients with RSSI complicated with cognitive dysfunction who were treated in the hospital and completed 2-year follow-up were selected from February 2021 to February 2025. According to whether the patients progressed to dementia, they were classified into dementia group (n=105) and non-dementia group (n=235). The clinical data were compared between both groups, and the independent risk factors were screened by Logistic regression analysis. Results Multivariate logistic regression analysis suggested that history of hypertension (OR=1.919), history of diabetes mellitus (OR=1.597), multiple infarctions (OR=1.455), severe white matter lesions (OR=1.595), no cognitive function training (OR=1.923), increased infarct size (OR=1.069), reduced MMSE score (OR=0.945) and increased levels of NfL (OR=1.049) and IL-6 (OR=1.038) were independent risk factors for the progression to dementia (all P<0.05). Conclusion The progression to dementia in patients with recent subcortical small infarction and cognitive dysfunction is affected by multiple factors. In clinical practice, the integration of vascular risk factors, imaging features, cognitive assessment and serum biomarkers (NfL, IL-6) helps to construct an early risk prediction model and implement targeted interventions for high-risk groups.

ObjectiveTo investigate the therapeutic efficacy of Danggui Shaoyaosan （DSS） on renal injury in db/db mice and its impact on endoplasmic reticulum stress （ERS） in renal tissues. MethodsThirty 8-week-old male db/db mice and six db/m mice were acclimated for one week， after which urinary microalbumin and blood glucose levels were monitored to establish a diabetic kidney disease （DKD） model. The model mice were randomly divided into a model group， an irbesartan group， and three DSS treatment groups with different doses （16.77， 33.54， and 67.08 g·kg^-1·d^-1）. A normal group was set as control. Each group was intragastrically administered with the corresponding drugs or saline for 8 weeks. After the intervention， general conditions were observed. Serum cystatin C （Cys-C）， 24-hour urinary total protein （24 h-UTP）， 24-hour urinary microalbumin （24 h-UMA）， urinary creatinine （Ucr）， and urea nitrogen （UUN） were measured. Transmission electron microscopy （TEM） was used to observe glomerular basement membrane （GBM） and ultrastructural changes of the endoplasmic reticulum （ER） in glomerular endothelial cells. Western blot， real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）， and immunohistochemistry were used to analyze renal tissue structure and the expression of GRP78， CHOP， and related markers. ResultsCompared with the normal group， the mice in the model group showed curled posture， sluggish response， poor fur condition， increased levels of Cys-C， 24 h-UTP， 24 h-UMA， and UUN （P<0.05）， while Ucr decreased （P<0.05）. The GBM was significantly thickened， with podocyte and foot process fusion. The protein expressions of GRP78， CHOP， and ATF6 were significantly upregulated （P<0.05）， the mRNA levels of GRP78 and CHOP increased （P<0.05）， and immunohistochemistry showed an enhanced GRP78 signal （P<0.05）. After treatment， the mice exhibited improved behavior， normalized GBM and podocyte structure， improved ER morphology and markedly better biochemical indicators. Western blot， Real-time PCR， and immunohistochemistry indicated that the ERS-related markers were downregulated in the DSS treatment groups （P<0.05）， suggesting alleviated ERS and improved renal function. ConclusionDSS can effectively ameliorate renal pathological damage in db/db mice， possibly by regulating ERS in glomerular endothelial cells， although the underlying signaling mechanisms require further investigation.

OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Objective: To investigate the correlation between color parameters (L^*, a^*, b^*, Eab^*) and the contents of reducing sugars, total polysaccharides, total oligosaccharides, as well as four saccharides (fructose, glucose, sucrose, and kestose) during the nine cycles of steaming and sun-drying processing of Polygonatum kingianum, and to preliminarily explore the optimal processing duration.
Methods: The color changes were objectively evaluated using a colorimeter. The anthrone-sulfuric acid method was employed to determine total polysaccharides and oligosaccharides. The 3,5-dinitrosalicylic acid (DNS) colorimetric method was used to measure total reducing sugar content. High-performance liquid chromatography coupled with charged aerosol detection (HPLC-CAD) was applied for quantitative analysis of fructose, glucose, sucrose, and kestose. Multivariate statistical analysis was conducted to assess samples from different processing stages.
Results: Significant variations in color and component contents were observed across processing stages. The herbal pieces progressively darkened with increased processing cycles: brightness (L^*) and total color difference (Eab^*) initially decreased then stabilized, while a^* (red-green) and b^* (yellow-blue) values first increased then declined. Total polysaccharides and oligosaccharides showed overall decreasing trends, whereas reducing sugars initially increased before stabilizing. Fructose and glucose levels rose continuously, while sucrose and kestose decreased progressively, becoming undetectable after five cycles.
Conclusion: The chromatic alteration and saccharide composition of P. kingianum showed significant correlation with processing duration. Both total color difference (Eab^*) and reducing sugar content stabilized after four processing cycles (12 hours), suggesting that four cycles of steaming and sun-drying may represent the optimal processing duration.

Objective: To investigate the correlation between the color parameters (L^*, a^*, b^*, Eab^* values) of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques and the contents of 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucopyranoside, emodin, physcion, emodin-8-O-β-D-glucopyranoside, physcion-8-O-β-D-glucopyranoside.
Methods: The L^*, a^*, b^* and Eab^* values of Polygoni Multiflori Radix Praeparata powder prepared by different processing techniques were determined by spectrophotometer, and the contents of the five components were determined by high performance liquid chromatography. Secondly, SPSS 26.0 software and Simca 14.1 software were used to analyze the correlation.
Results: Through the hierarchical cluster analysis (HCA), it was found that the steamed samples and black bean steamed samples could be obviously divided into two categories: raw products and processed products. The processed products could be further divided into 2-8 h and 12-48 h. Pearson correlation analysis showed that the content of stilbene glycoside was significantly positively correlated with L^*, a^* and b^* values (P<0.01). The a^* value was significantly positively correlated with the content of emodin and physcion (P<0.01). Emodin-8-O-β-D-glucoside was positively correlated with L^* value and b^* value, while physcion-8-O-β-D-glucoside was negatively correlated with a^* value. Partial least squares discriminant analysis (PLS) showed that 2,3,5,4’-tetrahydroxystilbene-2-O-β-D-glucoside (VIP=1.69) and emodin-8-O-β-D-glucoside (VIP=1.06) were the key variables affecting chromaticity characteristics (P<0.01).
Conclusion: The three processes of steaming, black bean steaming and black bean stewing are consistent in composition transformation and chromaticity variation, and stilbene glycoside can be used as a specific index component to characterize the processed color. Chromatic parameters can effectively reflect the processing progression and serve as quality monitoring indicators during production.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Effective symptom management can alleviate the physical and psychological distress experienced by patients with cancer, improve quality of life, and contribute to treatment adherence and improve clinical outcomes. However, most existing guidelines are developed for healthcare professionals, and patients and the public have limited access to standardized and comprehensible guidance on symptom management. To address this gap and to facilitate effective communication and shared decision-making, this study proposes the development of a patient version of the cancer symptom management guideline. The development process will adhere to the methodological framework recommended by the Guidelines International Network and the World Health Organization. The GRADE approach will be employed to assess the certainty of evidence and to formulate recommendations. In addition, the process will be informed by the Appraisal of Guidelines for Research and Evaluation Ⅱ (AGREE Ⅱ) instrument and the Reporting Items for Practice Guidelines in Healthcare-Public or Patient Versions of Guidelines (RIGHT-PVG). This protocol outlines the establishment of the guideline working group, the identification and prioritization of key questions, evidence retrieval and appraisal, and the formulation of recommendations, with the aim of ensuring methodological rigor and transparency in the development of the patient guideline and providing methodological reference for similar guideline initiatives.

To address the constrains imposed by insufficient hydrogen peroxide (H2O2) and high glutathione (GSH) expression in tumor cells on the efficacy of chemodynamic therapy (CDT), zeolitic imidazolate framework-8 (ZIF-8) loaded with disulfiram (DSF) and 3-amino-1,2,4-triazole (3-AT) was synthesized via a one-pot approach. Subsequently, hyaluronic acid (HA)-modified cupric peroxide (CuO2) was in-situ grown on its surface through biomineralization to construct a multifunctional copper-based nanozyme ADZCH (3-AT/DSF@ZIF-8@CuO2-HA). This nanoplatform disrupts the intratumoral H2O2 homeostasis, depletes GSH, and synchronously delivers DSF and Cu2+ via cascade catalysis, thereby enhancing CDT and sensitizing tumors to DSF-based chemotherapy. The results of physicochemical characterization indicated that ADZCH presented a uniform core-shell structure with favorable dispersibility. Its particle size and Zeta potential were 196.5 nm and −19.5 mV, respectively. It possessed a microporous structure with a specific surface area of 81.8600 m2/g, and demonstrated efficient loading capacity for DSF and 3-AT, achieving drug loading efficiencies of 5.91% and 45.07%, respectively. Moreover, ADZCH can continuously and slowly release drugs in an acidic environment and maintain good stability under diverse physiological conditions. In vitro functional assays verified that ADZCH catalytically generated H2O2 and hydroxyl radicals while concurrently depleting GSH in a concentration- and incubation time-dependent manner. Cellular uptake experiments showed that HA modification significantly improved the uptake of nanoparticles by 4T1 cells. Cytotoxicity tests showed that 80 μg/mL ADZCH had a significant cytotoxic effect on 4T1 cells but no significant toxicity on L929 cells. DCFH-DA probe detection indicated that ADZCH could significantly induce intracellular reactive oxygen species (ROS) generation, thereby enhancing CDT efficacy. Live/dead staining experiments showed that ADZCH efficiently induced apoptosis, with the proportion of dead cells reaching 94.74%, demonstrating its promising potential for anti-tumor applications.This study provides new research ideas and experimental basis for overcoming the tumor microenvironment barrier and enhancing the anti-tumor effect of CDT combined with chemotherapy.

Objective:To describe the current status of responsive caregiving behavior of infant mothers,to analyze their influencing factors and pathways using the information-motivation-behavioral skills(IMB)model,and to provide a basis for further interventions related to responsive caregiving be-haviors and comprehensive promotion of early childhood development.Methods:This study was a cross-sectional survey using convenience sampling.Questionnaires were used to collect basic information about mothers and their infants,as well as data on mothers' responsive caregiving behavior,knowledge of re-sponsive caregiving,social support,and parenting self-efficacy.Multivariate linear regression models were employed to analyze the influencing factors of responsive caregiving behavior,and structural equa-tion modeling was used to analyze the pathways of these influencing factors.The criterion for inadequate responsive caregiving is defined as scores not exceeding the lower quartile(P25)of the total score.Results:Among 510 mothers of aged 0-12 months infants in Weifang City,the average score for respon-sive caregiving behavior was 16.41±3.99.The proportion of inadequate responsive caregiving was 25.7％.Mothers in the insufficient responsive caregiving group had lower scores in knowledge(7.70±1.41),social support(57.92±15.16),and parenting self-efficacy(30.36±6.48)compared with those in the sufficient group,with statistically significant differences(P＜0.001).Logistic regres-sion analysis indicated that the influencing factors for responsive caregiving included the level of know-ledge about responsive parenting[adjusted OR(aOR)=0.795,95％CI:0.566-0.838],social support(aOR=0.979,95％CI:0.961-0.996),and parenting self-efficacy(aOR=0.894,95％CI:0.857-0.932).Structural equation modeling revealed that knowledge of responsive caregiving(β=0.089,P=0.031),social support(β=0.153,P=0.001),and parenting self-efficacy(β=0.296,P＜0.001)were directly related to responsive caregiving behavior.Additionally,knowledge of responsive caregiving indirectly affected responsive caregiving behavior through parenting self-efficacy(β=0.095,P=0.014),and social support indirectly affected responsive caregiving behavior through parenting self-efficacy(β=0.497,P＜0.001).Conclusion:The current level of responsive caregiving behavior among mothers of 0-1-year-old infants in Weifang City is not satisfactory.Future development of responsive care-giving interventions should focus on providing caregivers with relevant knowledge of responsive caregiving based on their needs.Additionally,it is essential to offer social support from multiple aspects to enhance caregivers' parenting self-efficacy,thereby promoting improvements in responsive caregiving behavior.

Objective:To analyze the association between healthcare workers mental health,institu-tional supplies and facilities,inter-organizational coordination during infectious disease outbreaks,and the healthcare institution resilience.Methods:An online questionnaire survey was conducted among the healthcare workforce from 146 institutions in Beijing from January 13,2023 to February 9,2023,and a total of 1 434 eligible respondents were included.The sample comprised 408 responses from tertiary hos-pitals,117 from secondary hospitals,and 909 from primary care institutions.The resilience indicator for healthcare institutions was defined as the degree to which medical services met patient demands,with in-fluencing factors including physical factors,such as material shortages and facility space adaptation or ex-pansion,organizational factors such as information sharing and patient referral,and psychological factors were evaluated using job satisfaction(extrinsic satisfaction,intrinsic satisfaction),burnout(emotional exhaustion,depersonalization,reduced personal accomplishment),and depression status.Ordered mul-ticlassification Logistic regression was used to examine the impact of various factors on the degree to which healthcare services met patient needs;additionally,demographic factors that might influence institutional resilience were controlled.Results:During the emergency response phase,93％of hospitals maintained the capacity to meet patient needs,though tertiary hospitals demonstrated significantly higher rates of service inadequacy(21.05％).Material shortages were reported across all institutions,with tertiary hos-pitals experiencing more frequent multi-item shortages.Inter-institutional collaboration patterns revealed substantial variation:87.50％of primary care facilities,42.86％of secondary hospitals,and 31.58％of tertiary hospitals.Healthcare workers across all levels reported mild depressive symptoms and moderate-to-severe burnout levels.Regression analysis showed high satisfaction(overall satisfaction β=0.04,ex-trinsic satisfaction β=0.06,and intrinsic satisfaction β=0.08),low degree of job burnout(emotional exhaustion β=-0.04,depersonalization β=-0.07 and reduced personal accomplishment β=0.01),low degree of depression(β=-0.06)were significantly associated with higher healthcare institution re-silience.In addition,material shortages were significantly associated with lower resilience,and renova-tion and expansion of treatment spaces,and information sharing,were all associated with higher resilience.Demographic factors(age,gender,marital status,educational background,etc.)had no sig-nificant impact on resilience.Conclusion:Mental health status significantly influences healthcare institu-tion resilience.As human resources constitute the core asset of healthcare institutions,strategic optimiza-tion of workforce allocation and psychological support interventions can effectively strengthen resilience.Moreover,healthcare institution resilience is positively impacted by orderly material supply chains,timely resource distribution,and adaptive reconfiguration of clinical spaces.Finally,facilitating information sharing also enhances institutional resilience.