Objective To explore the correlation between nutritional status and frailty in elderly patients with cardiovascular disease (CVD), and to provide suggestions for the prevention of frailty occurrence in elderly patients with CVD. Methods A retrospective study was conducted on 357 elderly CVD patients who were admitted to the Third Affiliated Hospital of Chengdu Medical College from May 2024 to July 2024. These patients were divided into a frailty group and a non-frailty group based on the presence or absence of frailty. Data on the patients' nutritional status indicators [body mass index (BMI), weight loss, calf circumference, albumin, and grip strength], general demographic and clinical data, laboratory and physiological indicators, and functional and activity indicators were collected. The influencing factors of frailty and the correlation between nutritional status indicators and frailty were analyzed. Results Among the 357 patients, 69 cases (19.33%) were detected with frailty, while 288 (80.67%) were without frailty. Multivariate logistic regression analysis revealed that age (OR=1.120, 95% CI: 1.023–1.225) and weight loss (OR=2.776, 95% CI: 1.145–6.732) were risk factors influencing the occurrence of frailty in elderly CVD patients (P<0.05), while grip strength (OR=0.902, 95% CI: 0.831–0.980), albumin level (OR=0.892, 95% CI: 0.806–0.988), and calf circumference (OR=0.900, 95% CI: 0.829–0.978) were protective factors of frailty occurrence in elderly CVD patients (P<0.05). Conclusion The incidence rate of frailty is relatively high in elderly patients with CVD. Age and weight loss are independent risk factors for frailty, while high grip strength level, high albumin level, and large calf circumference are independent protective factors of frailty.

Objective To analyze the characteristic influencing factors for enlarged perivascular spaces(EPVS)in different regions of acute ischemic stroke(AIS)patients and explore their un-derlying pathogenesis.Methods A total of 172 AIS patients admitted to our department from September 2020 to September 2023 were consecutively enrolled.According to the distribution of EPVS,they were divided into basal ganglia EPVS group(n=103)and non-basal ganglia EPVS group(n=69),as well as centrum semiovale EPVS group(n=77)and non-centrum semiovale EPVS group(n=95).General information,NIHSS score at onset,TOAST classification,fasting blood glucose,liver function,coagulation function,and homocysteine(Hcy)level were collected in all the patients.Multivariate logistic regression analysis was used to identify independent influen-cing factors for EPVS in different regions.Results The basal ganglia EPVS group had significant-ly advanced age and larger proportion of hypertension than the non-basal ganglia EPVS group,while the centrum semiovale EPVS group had smaller proportion of hyperhomocysteinemia,and larger ratios of smoking and alcohol consumption,higher alanine aminotransferase(ALT)level,and longer thrombin time than the non-centrum semiovale EPVS group(P＜0.05,P＜0.01).Mul-tivariate logistic regression analysis showed that hypertension(OR=2.093,95％CI:1.045-4.192,P=0.037)and age(OR=1.071,95％CI:1.016-1.130,P=0.011)were independent influ-encing factors for basal ganglia EPVS,while alcohol consumption(OR=2.418,95％CI:1.097-5.330,P=0.029)and thrombin time(OR=1.593,95％CI:1.129-2.249,P=0.008)were inde-pendent influencing factors for centrum semiovale EPVS.Conclusion EPVS in different regions of AIS patients are associated with distinct risk factors.Age and hypertension are primary influen-cing factors for basal ganglia EPVS,while alcohol consumption and prolonged thrombin time are significant factors for centrum semiovale EPVS.

Objective:To address the critical issue of missing dynamic border molding information in edentulous direct digital impression technology, this study explores innovative digital solutions and conducts preliminary application validation.Methods:Based on the myostatic line theory, a methodology was established: intraoral scanner (IOS) high-frequency video was utilized to dynamically capture functional molding data of soft tissues, integrated with a self-developed mobility gradient recognition algorithm to achieve dynamic threshold segmentation between the muscle dynamic zone and myostatic zone, termed "optical digital molding technology". Ten edentulous patients with well-fitting complete dentures, treated at the Department of Prosthodontics, Peking University School and Hospital of Stomatology from January 2024 to December 2024, were enrolled. The standard deviation between the muscle static line (generated by mobility gradient algorithm with thresholds of 0.3-0.7 mm) and the denture border curve was analyzed to optimize the dynamic threshold, followed by single-case clinical validation.Results:Among the mobility thresholds of 0.3-0.7 mm, the 0.5 mm threshold yielded the smallest standard deviation between the myostatic line and denture border. Clinical validation demonstrated that dentures designed with this threshold exhibited no displacement during dynamic functional tests, with marginal sealing meeting clinical standards.Conclusions:The optical digital border molding technique for edentulous soft tissue boundaries translates the myostatic line theory into quantifiable parameters for the first time. Based on data from 10 cases, a mobility threshold of 0.5 mm is recommended for clinical application.

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.

This paper systematically reviews the application progress of machine learning in perioperative transfusion medicine, focusing on its significant achievements in identifying transfusion risk factors, accurately predicting transfusion requirements, and enabling dynamic monitoring with real-time feedback. It also examines the methodologies, performance metrics, and clinical significance of constructing machine learning models across various surgical specialties, including orthopaedics, cardiac surgery, trauma, and obstetrics. The review further analyzes major challenges currently facing the field, including data bias, model overfitting and interpretability issues, alongside privacy and ethical concerns. Finally, it outlines future directions, highlighting how multimodal data fusion, deep learning applications, multicentre validation, and interdisciplinary collaboration are poised to significant potential for advancing the clinical translation of intelligent transfusion models, achieve personalized precision transfusion management, and enhance patient safety and therapeutic outcomes.

Objective To explore the symptom clusters in renal transplant recipients and con-struct a concurrent symptom network to identify core symptoms.Methods A total of 343 patients with followed up after renal transplantation were selected as the study subjects.A general information questionnaire and the Chinese version of the Modified Transplant Symptom Occurrence and Symptom Distress Scale were employed to analyze the occurrence of symptoms in patients.In this study,only symptoms with an incidence rate greater than 20％and Spearman correlation coefficient greater than 0.40 between symptom severity and total score were retained.Exploratory factor analysis was used to extract symptom clusters with a factor loading of ≥0.45 as the criterion.The R language was utilized to construct symptom network,based on which core symptoms and bridge symptoms were identified.Results A total of 5 symptom clusters were extracted in this study:the neuro-gastrointestinal symp-tom cluster,the mood-related symptom cluster,the hormone-related symptom cluster,the energy de-ficiency symptom cluster and the vision-related symptom cluster.The core symptoms were anxiety(rs=1.75),mood swings(rs=1.50)and muscle weakness(rs=1.27).The top three symptoms in terms of bridge strength were muscle weakness(rb=0.87),lack of vitality(rb=0.66)and fa-tigue(rb=0.65).Conclusion Multiple symptoms are presented in patients after renal transplanta-tion.Based on the results of symptom network analysis,clinicians can strengthen the assessment of core symptoms and bridge symptoms to develop precise intervention strategies and improve the effectiveness of symptom management.

Traditional Chinese medicine （TCM） has unique advantages in alleviating the symptoms of diabetic kidney disease （DKD） and slowing its progression. However， traditional clinical trials often use the occurrence of end-stage renal disease as the end point， requiring long-term follow-up， which increases trial complexity and costs， thereby limiting the feasibility of TCM clinical studies. This paper suggested that in clinical trials of TCM for DKD， both the estimated glomerular filtration rate （eGFR） change rate （≥30%） and eGFR slope can serve as potential surrogate outcome measures. If the intervention course is short （＜1 year）， the eGFR change rate （≥30%） is recommended as a surrogate outcome measure， whereas in long-term interventional studies （≥1 year）， the eGFR slope may be more appropriate. Furthermore， based on biochemical indicators such as eGFR slope and urinary albumin-to-creatinine ratio （UACR） change rate， integrating TCM symptom evaluation， TCM syndrome evaluation， and quality of life scales can help develop internationally recognized patient-reported outcome measures （PROMs） for TCM clinical trials， which will be a key step in enhancing the evaluation system for the effectiveness of TCM in treating DKD.

Perimenopause raises the risk and incidence of depression, whereas the underlying molecular mechanism remains unclear. Disturbed glucose regulation has been widely documented in depressive disorders, which renders the brain susceptible to various stresses such as estrogen depletion. However, whether and how glucose dysfunction regulates depression-like behaviors and neuronal damage in perimenopausal transition remains unexplored. Here, a prominent depressive phenotype was found in perimenopausal mice induced by the ovarian toxin 4-vinylcyclohexene diepoxide (VCD). The VCD depression susceptible group (VCD^SS) and the VCD depression resilient group (VCD^RES) were determined using a ROC-based behavioral screening approach. We found that the hippocampus, a crucial region linked to depression, had hyperglycemia and mitochondrial abnormalities. Interestingly, oral administration of the SGLT2 inhibitor empagliflozin (EMPA) and intrahippocampal glucose infusion suggest a close relationship between hyperglycemia in the hippocampus and the susceptibility to depression. We verified that cytochrome c oxidase 7c (COX7C) downregulation is a potential cause of the high glucose-induced neuronal injury using proteomic screening and biochemical validations. High glucose causes COX7C to be ubiquitinated in a S-phase kinase associated protein 1 (SKP1)-dependent manner. According to these results, SKP1/COX7C represents a unique therapeutic target and a novel molecular route for treating perimenopausal depression.

BACKGROUND:Flap transplantation technique is a commonly used surgical procedure for the treatment of severe tissue defects,but postoperative flap necrosis is easily triggered by ischemia-reperfusion injury.Therefore,it is still an important research topic to improve the survival rate of transplanted flaps. OBJECTIVE:To review the pathogenesis and latest treatment progress of flap ischemia-reperfusion injury. METHODS:CNKI,WanFang Database and PubMed database were searched for relevant literature published from 2014 to 2024.The search terms used were"flap,ischemia-reperfusion injury,inflammatory response,oxidative stress,Ca2+overload,apoptosis,mesenchymal stem cells,platelet-rich plasma,signaling pathways,shock wave,pretreatment"in Chinese and English.After elimination of irrelevant literature,poor quality and obsolete literature,77 documents were finally included for review. RESULTS AND CONCLUSION:Flap ischemia/reperfusion injury may be related to pathological factors such as inflammatory response,oxidative stress response,Ca2+overload,and apoptosis,which can cause apoptosis of vascular endothelial cells,vascular damage and microcirculation disorders in the flap,and eventually lead to flap necrosis.Studies have found that mesenchymal stem cell transplantation,platelet-rich plasma,signaling pathway modulators,shock waves,and pretreatment can alleviate flap ischemia/reperfusion injuries from different aspects and to varying degrees,and reduce the necrosis rate and necrosis area of the grafted flap.Although there are many therapeutic methods for skin flap ischemia/reperfusion injury,a unified and effective therapeutic method has not yet been developed in the clinic,and the advantages and disadvantages of various therapeutic methods have not yet been compared.Most of the studies remain in the stage of animal experiments,rarely involving clinical observations.Therefore,a lot of research is required in the future to gradually move from animal experiments to the clinic in order to better serve the clinic.

Cancer is one of the major diseases of high morbidity and mortality worldwide,and its therapeutic approaches are facing great challenges.Immunotherapy,especially the activation of innate immunity represented by the cGAS-STING signaling pathway,is the current research hotspot in tumor immunotherapy.Activation of innate immune response by gas therapy is the latest development in tumor therapeutic approaches,especially the use of gas signaling molecules(NOx CO,H2S and SO2)to activate the cGAS-STING signaling pathway to induce intrinsic immunity of the organism,which leads to anti-tumor immunotherapy.Although intrinsic immunity activated by gas signaling molecules plays an important role in tumor immunotherapy,few reviews have been reported on its association with the cGAS-STING signaling mechanism.In this paper,we will comprehensively describe how gas signaling molecules damage the mitochondrial matrix and DNA damage through oxidative/nitrosative stress,thereby activating the cGAS-STING signaling pathway and triggering the innate immune cascade,aiming to summarize the process of activation of anti-tumor immune effects by gas signaling molecules,and to provide more references for the gas therapies in the future anti-tumor immunity research.