ObjectiveTo investigate the effects of Huanglian Jiedutang （HLJDT） on cognitive function in mice with ischemic stroke （IS） and to elucidate whether its neuroprotective effects are mediated by inhibition of the nuclear factor-κB （NF-κB） signaling pathway and subsequent suppression of NF-κB-regulated neuronal apoptosis. MethodsAn IS model was established using middle cerebral artery occlusion （MCAO）. Sixty C57BL/6J mice were randomly assigned to five groups （n =12 per group）， i.e.， sham operation， model， HLJDT low-dose （3.9 g·kg^-1·d^-1）， HLJDT high-dose （7.8 g·kg^-1·d^-1）， and Ginkgo biloba extract （GBE， 31.2 mg·kg^-1·d^-1）. Post-operatively， neurological deficit scores （Longa score）， cerebral infarct volume assessed by 2，3，5-triphenyltetrazolium chloride （TTC） staining， and brain water content were evaluated. Learning and memory were assessed using new object recognition （NOR） and fear conditioning （FC） tests. Hippocampal pathology was examined via hematoxylin and eosin （HE） staining. Immunofluorescence detected expression of glial fibrillary acidic protein （GFAP， astrocyte marker）， cellular oncogene Fos （c-Fos， neuronal activation marker）， and glutamate decarboxylase 65 （GAD65）. Western blot measured nuclear factor-κB inhibitor protein α （IκBα）， phosphorylated IκBα （p-IκBα）， NF-κB p65， phosphorylated NF-κB p65 （p-NF-κB p65）， ionic calcium binding adapter molecule 1 （Iba-1）， tumor necrosis factor （TNF）-α， interleukin （IL）-1β， and apoptosis-related proteins， such as cleaved cysteinyl aspartate-specific protease 3 （Caspase-3）， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. Real-time quantitative PCR （Real-time PCR） was used to assess mRNA levels of Iba-1， TNF-α， IL-1β， NF-κB p65， cleaved Caspase-3， Bax， and Bcl-2. ResultsCompared with the sham group， the model group exhibited significantly increased neurological deficit scores， brain water content， and cerebral infarct volume （P<0.01）. Hippocampal CA1 neurons were disorganized， showing nuclear pyknosis and karyolysis. NOR exploration time and FC freezing time were significantly reduced （P<0.01）. GFAP and c-Fos expression were increased， while GAD65 expression was decreased （P<0.01）. Cleaved Caspase-3 and Bax were upregulated， Bcl-2 was downregulated， and the Bax/Bcl-2 ratio was elevated （P<0.01）. Expression levels of p-IκBα， p-NF-κB p65， IL-1β， TNF-α， and Iba-1 were significantly increased （P<0.01）. Compared with the model group， HLJDT high-dose， low-dose， and GBE groups showed significant improvements in all parameters （P<0.01）. Among them， the HLJDT high-dose group showed the most pronounced neuronal structural recovery and superior performance in NOR and FC tests （P<0.01）. In this group， GFAP and c-Fos decreased， GAD65 increased （P<0.01）， apoptosis-related protein expression was reversed， and NF-κB signaling and related inflammatory factor expression were suppressed （P<0.01）. ConclusionHLJDT ameliorates cognitive dysfunction in mice after IS， potentially by inhibiting the NF-κB signaling pathway， thereby reducing neuroinflammation and hippocampal neuronal apoptosis.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.

Purpose To evaluate the diagnostic value of 18F-fluorodeoxyglucose(18F-FDG)PET/CT in differentiating primary lung cancer(PLC)from metastatic pulmonary breast cancer in breast cancer patients with solitary pulmonary lesion(SPL).Materials and Methods This retrospective analysis included 58 breast cancer patients with SPL in the Cancer Hospital of the Chinese Academy of Medical Sciences from January 2015 to August 2024.All patients had pathologically confirmed breast cancer with SPL and underwent PET/CT scans,including 36 cases of PLC and 22 cases of metastatic pulmonary breast cancer.Differences in clinical pathological features,high resolution CT morphological,and PET metabolic characteristics were analyzed.Multivariate Logistic regression was utilized to investigate independent predictive factors for SPL diagnosis.Results Statistically significant differences were observed between lesion density,nodule-lung interface,bubble sign,vascular convergence sign and pleural indentation sign(χ2=9.420,7.000,8.487,all P<0.05).PET/CT metabolic analysis revealed a significant difference in maximum standardized uptake value(SUVmax)between the two groups(Z=4.613,P<0.001).Multivariate analysis showed that bubble sign,pleural indentation sign and lower SUVmax were independent predictors for PLC.With an SUVmax threshold of 2.5,the area under the receiver operating curve(AUC)was 0.862,with a sensitivity of 90.9%,specificity of 77.8%and an accuracy of 82.8%.Combined analysis of high resolution CT and SUVmax demonstrated the highest diagnostic efficacy,with an area under the curve of 0.937,sensitivity of 90.9%,specificity of 94.4%and accuracy of 93.1%.Conclusion The presence of bubble sign,pleural indentation and SUVmax<2.5 suggests a high likelihood of PLC.Combined high resolution CT imaging features and PET metabolic characteristics significantly improve diagnostic accuracy for SPLs in breast cancer patients.

Objective:To investigate the diagnostic value of D-dimer (D-D) testing combined with multi-slice spiral CT pulmonary angiography (MSCTPA) in patients with pulmonary embolism (PE) based on the modified Geneva score.Methods:This study adopted a prospective design. Ninety-six patients with suspected pulmonary embolism (PE) who received treatment at Jinhua Hospital of Traditional Chinese Medicine, Zhejiang Chinese Medical University, from January to December 2024, were included in this study. The modified Geneva score was used to assess the clinical probability and severity of PE in these patients. Based on their modified Geneva scores, the patients were divided into high-risk, moderate-risk, and low-risk groups. All patients underwent both MSCTPA and D-D testing. The diagnostic value of D-D testing and MSCTPA, both individually and in combination, for PE among patients with different modified Geneva scores was evaluated.Results:Clinical diagnosis confirmed PE in 55 of the 96 suspected cases, with a positivity rate of 57.29% (55/96). According to the revised Geneva score, the high-risk group had the highest PE positivity rate (91.67%, 11/12), followed by the moderate-risk group (59.70%, 40/67) and the low-risk group (23.53%, 4/17). In the moderate-risk group, MSCTPA showed a significantly higher positive confirmation rate than negative confirmation rate ( χ2 = 12.32, P < 0.001), with a positive predictive value of 73.91% (34/46), a negative predictive value of 71.43% (15/21), specificity of 55.56% (15/27), sensitivity of 85.00% (34/40), and accuracy of 73.13% (49/67). D-D testing in the moderate-risk group also demonstrated a higher positive confirmation rate ( χ2 = 9.04, P < 0.05), with a positive predictive value of 72.73% (32/44), negative predictive value of 65.22% (15/23), specificity of 55.56% (15/27), sensitivity of 80.00% (32/40), and accuracy of 70.15% (47/67). The combination of D-D testing and MSCTPA significantly increased the positive confirmation rate for patients in the moderate-risk group compared with the negative confirmation rate ( χ2 = 28.78, P < 0.001). D-D testing combined with MSCTPA showed a positive predictive value of 83.72% (36/43), a negative predictive value of 83.33% (20/24), specificity of 74.07% (20/27), sensitivity of 90.00% (36/40), and accuracy of 83.58% (56/67) for patients in the moderate-risk group. Conclusions:D-D testing combined with MSCTPA demonstrates high diagnostic value for PE in patients assessed by the revised Geneva score, particularly for patients who are at moderate risk for PE.

Objective To analyse and explore whether there is a causal association without confounding factors between malignant haematological diseases and frailty based on a bidirectional Mendelian randomisation(MR)analysis,and to provide a theoretical basis for clinical management of the frailty associated with malignant haematological diseases.Methods In December 2023,the IEU OpenGWAS database(https://gwas.mrcieu.ac.uk/)was searched to acquire the datasets in genome-wide association studies(GWAS)derived from non-overlapping multi-ethnic populations based on Mendelian Randomisation(MR)analysis.The bidirectional causal association was verified utilising the two-sample MR approach.Single nucleotide polymorphisms(SNPs)of the frailty index(FI)(n=175,226),haematological malignancies(n=212,453),multiple myeloma/malignant plasmacytoma(n=218,792),and follicular lymphoma(n=181,278)were used as the study instruments.Results The analysis with the statistic inverse variance weighted method(IVW)showed that haematological malignancies(OR=1.00,95%CI:0.98-1.00,P=0.797),multiple myeloma/malignant plasma cell tumours(OR=1.00,95%CI 0.99～1.01,P=0.982),and follicular lymphoma(OR=1.00,95%CI:0.99～1.01,P=0.314)were not causally associated with genetically predicted FI.Similarly,FI was not significantly or causally correlated with haematological malignancies(OR=0.89,95%CI:0.25～3.12,P=0.861),multiple myeloma/malignant plasma cell tumours(OR=0.52,95%CI:0.00～3.13,P=0.473),and follicular lymphoma(OR=1.06,95%CI:0.00～5.19,P=0.944).Conclusion No causal relationship between the malignant haematological diseases and frailty was found in this study.It suggests that other factors might exist to cause the malignant haematological frailty.

Plant-derived bioactive peptides have become a research hotspot in the fields of food and medicine due to their high source safety,easy absorption and utilization by the human body,and potential edible and medicinal value.Bioactive peptides can be classified into antihypertensive,hypoglycemic,hypolipidemic,anticancer,antioxidant,antimicrobial,and anti-inflammatory peptides according to their functions.Among these,antihypertensive,hypoglycemic,and hypolipidemic peptides are collectively referred to as cardiovascular active peptides,which can be used for the treatment and prevention of cardiovascular diseases and have an important role in the development of modem biomedicine.This review focused on the preparation methods,separation,purification,and identification techniques of bioactive peptides,as well as their mechanisms of action and applications in regulating cardiovascular diseases,aiming to provide a reference for further development and application of plant-derived cardiovascular peptides.

The enhancement of cultural development in public Traditional Chinese Medicine(TCM)hospitals serves as a crucial foundation for maintaining TCM-centered healthcare delivery,preserving institutional public welfare values,and advancing the inheritance and innovation of TCM practices.This study examines practical strategies for hospital cultural development through an integrated approach encompassing ideological cultivation via party building initiatives,core value system development,thera-peutic environment optimization,clinical behavior standardization,and healthcare service quality enhancement.The framework further incorporates targeted efforts in TCM cultural promotion,research innovation grounded in TCM principles,and international dissemination of TCM culture.

Objective:To evaluate the effect of sex factors on rewarming in patients with mild hypothermia undergoing lithotripsy for urolithiasis.Methods:In this prospective study, 100 American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ patients, aged 18-60 yr, with a body mass index of 18-30 kg/m 2, scheduled for elective lithotripsy for urolithiasis, were divided into 2 groups ( n=50 each) based on sex: male group (group M) and female group (group F). The rewarming measures were as follows: the room was preheated, maintaining a constant temperature of 22-24 ℃, all the patients were covered with medical heating blanket under their bodies, and the inflatable heating apparatus was placed on the surface quilt, and the air supply was placed near the lower limbs of the patients. The parameters were set as follows: temperature 40 ℃, strong wind. If the patients complained of heat, the temperature parameter settings were changed, and the quilt was removed when necessary. If the patients complained of cold, blood transfusion and infusion heating instrument were added, medical heating blanket was turned on, or an anther quilt was used. Body temperature and the number of patients with successful rewarming were recorded on admission to post-anesthesia care unit (T 0) and at 10, 30, 45 and 60 min after rewarming (T 1-4), and at 1, 3 and 5 h after returning to the ward (T 5-7). The comfort scores were assessed while measuring body temperature at T 0 and T 4, and the occurrence of shivering, hypertension, hypotension and arrhythmias was observed. Results:Compared with group F, the body temperature was significantly increased at T 3 and T 4, the success rate of rewarming and incidence of shivering were increased at T 3 ( P<0.05), and no significant change was found in the incidence of hypertension, hypotension and arrhythmias in group M ( P<0.05). Conclusions:Sex factors affect rewarming outcomes in patients with mild hypothermia undergoing lithotripsy for urolithiasis. Females exhibit a slower rewarming rate and less shivering than males.

Objective Based on Network pharmacology to explore the mechanism of Compound Danshen Dripping Pills in treating Psycho-cardiological disease.Methods To obtain the validated targets of the complete formulation of Compound Danshen Dripping Pills,data were sourced from databases including China National Knowledge Infrastructure,Wanfang,VIP,and PubMed.Additionally,genes associated with Psycho-cardiological disease were retrieved from the Genecards database.Utilizing the Digital Intelligence Traditional Chinese Medicine Innovation Platform,network proximity was calculated for the obtained targets and genes.The potential targets of Compound Danshen Dripping Pills in the treatment of Psycho-cardiological disease conduct enrichment analysis,trace the source of medicinal materials and effective components absorbed into the blood.Results Obtained 192 targets for the Compound Danshen Dripping Pills,1137 genes for Psycho-cardiological disease,and the network proximity calculation showed a significant correlation between the two(Z-score=-6.5282).The enrichment analysis of the 95 potential targets predominantly reveals their association with several key pathways,including AGE-RAGE signaling in diabetic complications,Lipid and atherosclerosis,fluid shear stress and atherosclerosis,the HIF-1 signaling pathway,TNF signaling.The traceability analysis indicates that 80 targets are associated with three distinct medicinal materials,10 targets are linked to two medicinal materials,and 5 targets are connected to a single medicinal material.95 targets are mainly related to 17 effective blood components such as salvianolic acid B,tanshinone ⅡA,and salvianolic acid A.The top 16 key genes were obtained by sorting the targets based on the Betweenness values corresponding to the blood components.The enrichment analysis of the key gene indicated that the treatment of Psycho-cardiological disease with Compound Danshen Dripping Pills is associated with the positive regulation of smooth muscle cell proliferation and the hypoxia response.Additionally,it is linked to the AGE-RAGE signaling pathway in diabetic complications,fluid shear stress and atherosclerosis,the relaxin signaling pathway,lipid and atherosclerosis,and the TNF signaling pathway,etc.Conclusion The Compound Danshen Dripping Pills may improve Psycho-cardiological disease by regulating inflammatory response,oxidative stress,myocardial ischemia,neuroprotection,and neurotoxicity inhibition through components such as salvianolic acid B,tanshinone ⅡA,tanshinone Ⅰ,salvianolic acid A,protocatechuic acid,etc.

Purpose To explore the value of machine learning models based on synthetic MRI,dynamic contrast-enhanced MRI(DCE-MRI)and diffusion weighted imaging(DWI)parameters in identifying molecular subtypes of breast cancer.Materials and Methods A retrospective analysis was conducted on the data of 292 patients who underwent synthetic MRI,DCE-MRI and DWI examinations from September 2020 to September 2024 in Ningxia Medical University General Hospital before surgery and were pathologically confirmed to have breast cancer postoperatively.Patients were randomly divided into training and test sets using a ratio of 7:3.Multiple parameters were obtained from the synthetic MRI,DCE-MRI and DWI images.Variance analysis were used to screen the characteristic parameters among molecular subtype groups.Five machine learning models were established based on the selected characteristic parameters,and receiver operating characteristic curves were plotted to calculate the area under the curve among the molecular subtype groups.Results The support vector machine model exhibited the highest overall performance,with an area under the curve of 0.972,accuracy of 82.5％,specificity of 94.76％and sensitivity of 82.14％in the test set.This model's area under the curve values for differentiating luminal A,luminal B,human epidermal growth factor receptor-2 overexpression,and triple-negative groups in the training set were 0.979,0.925,0.971 and 0.982,respectively;in the test set,the area under the curve values were 0.973,0.873,0.956 and 0.955,respectively.Conclusion Machine learning models based on multimodal MRI parameters can assist clinicians in preoperatively determining the molecular subtypes of breast cancer and the support vector machine model shows relatively high comprehensive performance.