Ophiopogon japonicus, a precious medicinal plant endemic to Zhejiang Province. Its tuberous roots are rich in bioactive components such as flavonoids, possessing anti-inflammatory, antioxidant, and immunomodulatory properties. To elucidate the impact of cadmium (Cd) stress on the accumulation and biosynthetic pathway of flavonoids in O. japonicus, this study exposed O. japonicus to different concentrations of Cd stress and explored the changes through integrated transcriptomics and metabolomics analysis. The results demonstrated that Cd stress (1 mg/L and 10 mg/L) significantly increased the content of flavonoids in O. japonicus in a concentration-dependent manner. The metabolomics analysis revealed a total of 110 flavonoids including flavones, flavanols, flavonols, flavone and flavonol derivatives, flavanones, isoflavonoids, chalcones and dihydrochalcones, and anthocyanins in O. japonicus, among which flavones, flavonols, flavone and flavonol derivatives, and anthocyanins increased under Cd stress. The transcriptomics analysis identified several key flavonoid biosynthesis-associated genes with up-regulated expression under Cd stress, including 14 genes encoding 4-coumarate CoA ligase (4CL), 2 genes encoding chalcone isomerase (CHI), and 14 genes encoding phenylalanine ammonia lyase (PAL). The gene-metabolite regulatory network indicated significant positive correlations of 4CL (Cluster-21637.5012, Cluster-21637.90648, and Cluster-21637.62637) and CHI (Cluster-21637.111909 and Cluster-21637.123300) with flavonoid metabolites, suggesting that these genes promoted the synthesis of specific flavonoid metabolites, which led to the accumulation of total flavonoids under Cd stress. These findings provide theoretical support for the cultivation and utilization of medicinal plants in Cd-contaminated environments and offered new perspectives for studying plant responses to heavy metal stress.
Cadmium/toxicity* ; Flavonoids/biosynthesis* ; Metabolomics ; Ophiopogon/drug effects* ; Stress, Physiological ; Transcriptome ; Gene Expression Profiling ; Gene Expression Regulation, Plant

Objective To analyze the acupoint selection law of acupuncture and moxibustion for pediatric cerebral palsy based on data mining techniques.Methods Clinical research literature about acupuncture and moxibustion for the treatment of pediatric cerebral palsy was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed,Web of Science,Embase and Cochrane Library from the establishment of the databases to April 1,2024.Excel 2021 was used to establish a database of prescription acupoints.The frequency of use of acupoints,attributed to the meridians,parts and specific acupoints were under statistically analysis,and SPSS Modeler 18.0 and SPSS Statistics 27.0 were used to conduct the association rules analysis,factor analysis and clustering analysis of acupoints.Results A total of 579 articles were included,579 prescriptions were extracted,containing 245 acupoints with the frequency of 6 422 times.The high-frequency acupoints were Zusanli,Baihui,Hegu,Sanyinjiao and Quchi,etc.The commonly used meridians were Governor Vessel,gall bladder meridian,stomach meridian,large intestine meridian and bladder meridian;mostly used acupoints were in the lower limbs,head and neck,upper limbs,waist and back.The association rules analysis showed that the top combinations were"Hegu-Quchi","Zusanli-Quchi","Zusanli-Quchi-Hegu","Hegu-Quchi-Zusanli";clustering analysis showed that 6 valid clusters were extracted;factor analysis extracted 7 valid common factors.Conclusion Acupuncture and moxibustion treatment for pediatric cerebral palsy is based on the principle of strengthening the brain,improving intelligence and tonifying the five zang organs,reflecting the principle of matching acupoints far and near.The core combination of acupoints is"Zusanli-Quchi-Hegu".

Objective To observe the value of venous phase CT radiomics combined with clinical features for predicting breast cancer susceptibility gene(BRCA)mutation in patients with epithelial ovarian cancer(EOC).Methods A total of 111 EOC patients diagnosed by surgical pathology and BRCA detection were retrospectively enrolled and divided into training set(n=90,35 BRCA mutations[+]and 55 BRCA mutations[-])and test set(n=21,8 BRCA mutations[+]and 13 BRCA mutations[-])at the ratio of 8∶2.Clinical and CT data were analyzed using univariate and multivariate logistic regression(LR)to screen independent predictors of BRCA mutations in EOC patients,and then a clinical model was established.Based on venous phase CT,the best radiomics features of EOC lesions were extracted and screened,radiomics score(Radscore)was calculated.Machine learning(ML)models were established using random forest(RF),support vector machine(SVM)and LR,respectively,and the optimal ML model was screened.Finally a combined model was constructed based on Radscore and independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Human epididymis protein 4 was the independent predictor of BRCA mutation in EOC patients,and the area under the curve(AUC)of clinical model was 0.648 and 0.742 in training and test sets,respectively.AUC of RF,SVM and LR model was 0.726,0.763 and 0.860 in training set,0.708,0.750 and 0.700 in test set,respectively,and SVM model was the optimal ML model.AUC of combined model was 0.819 and 0.783 in training and test set,respectively,which in training set was higher than that of clinical model(P=0.022).No significant difference of AUC was found by pairwise comparison of other models in both training and test set(all P＞0.05).Decision curve analysis showed that when the threshold was larger than 0.15,the clinical value of combined model was higher than that of clinical and SVM models.Conclusion Venous phase CT radiomics combined with clinical features could effectively predict BRCA mutation in EOC patients.

Objective To translate self-care in spinal cord injuries inventory(SC-SCII)into Chinese and evaluate its reliability and validity,therefore to provide medical staff with a tool for evaluation of self-care behaviour of patients.Methods Brislin translation model was adopted for forward translation,back-translation,cultural adaptation and pilot testing in the development of Chinese version of SC-SCII.Convenience sampling was used to recruit 207 patients with spinal cord injury(SCI)from three Tier-IIIA hospitals in Xi'an between January 2024 and March 2025 for the purpose of assessing the reliability and validity of the translated inventory.Results A total of 202 patients completed the study.The finalised Chinese version of SC-SCII encompassed 4 dimensions with a total of 35 items,with the same structure as the original SC-SCII.Scale-level content validity index was 0.948,and the item-level content validity indices ranged from 0.912 to 1.000.Four common factors were extracted by exploratory factor analysis:self-care maintenance(12 items),self-care monitoring(8 items),self-care management(8 items)and self-care self-efficacy(7 items),cumulatively accounting for 61.402%of the total variance.The overall Cronbach's α coefficient was 0.820 and the Cronbach's α coefficients of the four dimensions were 0.935,0.905,0.921 and 0.892,respectively.The split-half reliability was 0.798,and the two-week retest reliability was 0.875.No statistically significant difference was observed between the original and sinicised scales(paired t-test,P>0.05),indicating a high cross-time stability of the sinicised scale.Conclusion The Chinese version of SC-SCII demonstrates a good reliability and validity,making it a suitable tool in evaluation of self-care abilities in SCI patients.

Depression, one of the most prevalent mental health disorders, has emerged as a critical focus in medical and neurobiological research, as well as a major challenge for global public health. The immune-inflammatory hypothesis has been confirmed to play a pivotal role in the pathogenesis and pathophysiology of depression, though its precise mechanisms remain to be fully elucidated. This article reviews the effects of key inflammatory factors, including tumor necrosis factor-α, interleukin-1β, interleukin-6, and Toll-like receptors on depression. Additionally, it summarizes the effects of immune-inflammatory pathway invovled in the pathogenesis of depression, along with scientific clues related to inflammatory factors in this pathway. Findings from this review will provide new insights for antidepressant development and serve as a reference for evaluating the clinical efficacy of antidepressants.

Objective To translate self-care in spinal cord injuries inventory(SC-SCII)into Chinese and evaluate its reliability and validity,therefore to provide medical staff with a tool for evaluation of self-care behaviour of patients.Methods Brislin translation model was adopted for forward translation,back-translation,cultural adaptation and pilot testing in the development of Chinese version of SC-SCII.Convenience sampling was used to recruit 207 patients with spinal cord injury(SCI)from three Tier-IIIA hospitals in Xi'an between January 2024 and March 2025 for the purpose of assessing the reliability and validity of the translated inventory.Results A total of 202 patients completed the study.The finalised Chinese version of SC-SCII encompassed 4 dimensions with a total of 35 items,with the same structure as the original SC-SCII.Scale-level content validity index was 0.948,and the item-level content validity indices ranged from 0.912 to 1.000.Four common factors were extracted by exploratory factor analysis:self-care maintenance(12 items),self-care monitoring(8 items),self-care management(8 items)and self-care self-efficacy(7 items),cumulatively accounting for 61.402%of the total variance.The overall Cronbach's α coefficient was 0.820 and the Cronbach's α coefficients of the four dimensions were 0.935,0.905,0.921 and 0.892,respectively.The split-half reliability was 0.798,and the two-week retest reliability was 0.875.No statistically significant difference was observed between the original and sinicised scales(paired t-test,P>0.05),indicating a high cross-time stability of the sinicised scale.Conclusion The Chinese version of SC-SCII demonstrates a good reliability and validity,making it a suitable tool in evaluation of self-care abilities in SCI patients.

Objective To analyze the acupoint selection law of acupuncture and moxibustion for pediatric cerebral palsy based on data mining techniques.Methods Clinical research literature about acupuncture and moxibustion for the treatment of pediatric cerebral palsy was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed,Web of Science,Embase and Cochrane Library from the establishment of the databases to April 1,2024.Excel 2021 was used to establish a database of prescription acupoints.The frequency of use of acupoints,attributed to the meridians,parts and specific acupoints were under statistically analysis,and SPSS Modeler 18.0 and SPSS Statistics 27.0 were used to conduct the association rules analysis,factor analysis and clustering analysis of acupoints.Results A total of 579 articles were included,579 prescriptions were extracted,containing 245 acupoints with the frequency of 6 422 times.The high-frequency acupoints were Zusanli,Baihui,Hegu,Sanyinjiao and Quchi,etc.The commonly used meridians were Governor Vessel,gall bladder meridian,stomach meridian,large intestine meridian and bladder meridian;mostly used acupoints were in the lower limbs,head and neck,upper limbs,waist and back.The association rules analysis showed that the top combinations were"Hegu-Quchi","Zusanli-Quchi","Zusanli-Quchi-Hegu","Hegu-Quchi-Zusanli";clustering analysis showed that 6 valid clusters were extracted;factor analysis extracted 7 valid common factors.Conclusion Acupuncture and moxibustion treatment for pediatric cerebral palsy is based on the principle of strengthening the brain,improving intelligence and tonifying the five zang organs,reflecting the principle of matching acupoints far and near.The core combination of acupoints is"Zusanli-Quchi-Hegu".

Depression, one of the most prevalent mental health disorders, has emerged as a critical focus in medical and neurobiological research, as well as a major challenge for global public health. The immune-inflammatory hypothesis has been confirmed to play a pivotal role in the pathogenesis and pathophysiology of depression, though its precise mechanisms remain to be fully elucidated. This article reviews the effects of key inflammatory factors, including tumor necrosis factor-α, interleukin-1β, interleukin-6, and Toll-like receptors on depression. Additionally, it summarizes the effects of immune-inflammatory pathway invovled in the pathogenesis of depression, along with scientific clues related to inflammatory factors in this pathway. Findings from this review will provide new insights for antidepressant development and serve as a reference for evaluating the clinical efficacy of antidepressants.

Objective To observe the value of venous phase CT radiomics combined with clinical features for predicting breast cancer susceptibility gene(BRCA)mutation in patients with epithelial ovarian cancer(EOC).Methods A total of 111 EOC patients diagnosed by surgical pathology and BRCA detection were retrospectively enrolled and divided into training set(n=90,35 BRCA mutations[+]and 55 BRCA mutations[-])and test set(n=21,8 BRCA mutations[+]and 13 BRCA mutations[-])at the ratio of 8∶2.Clinical and CT data were analyzed using univariate and multivariate logistic regression(LR)to screen independent predictors of BRCA mutations in EOC patients,and then a clinical model was established.Based on venous phase CT,the best radiomics features of EOC lesions were extracted and screened,radiomics score(Radscore)was calculated.Machine learning(ML)models were established using random forest(RF),support vector machine(SVM)and LR,respectively,and the optimal ML model was screened.Finally a combined model was constructed based on Radscore and independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Human epididymis protein 4 was the independent predictor of BRCA mutation in EOC patients,and the area under the curve(AUC)of clinical model was 0.648 and 0.742 in training and test sets,respectively.AUC of RF,SVM and LR model was 0.726,0.763 and 0.860 in training set,0.708,0.750 and 0.700 in test set,respectively,and SVM model was the optimal ML model.AUC of combined model was 0.819 and 0.783 in training and test set,respectively,which in training set was higher than that of clinical model(P=0.022).No significant difference of AUC was found by pairwise comparison of other models in both training and test set(all P＞0.05).Decision curve analysis showed that when the threshold was larger than 0.15,the clinical value of combined model was higher than that of clinical and SVM models.Conclusion Venous phase CT radiomics combined with clinical features could effectively predict BRCA mutation in EOC patients.