Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial inflammation, joint destruction, and functional impairment. Angiogenesis plays a key role in the pathological progression of RA with dysfunction of endothelial cells to promote synovial inflammation, sustain pannus formation, subsequently leading to joint damage. Colquhounia Root Tablets (CRT), a Chinese patent drug, has shown a satisfying clinical efficacy in treating RA, while the underlying mechanism by which CRT inhibits RA-associated angiogenesis remains unclear. In this study, we applied a research approach combining transcriptomic data analysis, bio-network mapping, and in vivo and in vitro experiments to explore the molecular mechanisms of CRT in suppressing angiogenesis in RA. Animal welfare and experimental procedures follow the regulations of the Animal Ethics Committee of Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences (ratification number: IBTCMCACMS21-2307-06). Network analysis identified that key genes such as nucleotide-binding oligomerization domain-containing protein 2 (NOD2), SMAD family member 3 (SMAD3), and vascular endothelial growth factor A (VEGFA) significantly enriched in pathways related to NOD-like receptor signaling and VEGF signaling, indicating that CRT may inhibit angiogenesis by regulating vascular endothelial cell function with modulating angiogenesis-related pathways. In vivo data showed that CRT significantly reduced the positive expression of CD31 and VEGF in the ankle joint of adjuvant-induced arthritis (AIA) rats. In vitro data further confirmed that CRT effectively inhibited VEGF-induced migration, invasion, and tube formation in HUVECs, while significantly reduced the expression of angiogenesis-related factors VEGF/CD31/Ang-1, as well as the positive expression of VEGF and CD31 in HUVECs. Furthermore, CRT markedly decreased the protein expression of NOD2, VEGFA, and SMAD3. In conclusion, these findings indicate that CRT may inhibit the RA-related angiogenesis by targeting the NOD2/SMAD3/VEGF signaling axis to improve endothelial cell function, enriching the scientific connotation of CRT in inhibiting pathological angiogenesis in RA and also offer new insights for clinical prevention and treatment of RA.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To investigate the effects of joint function screening and correction on intervention efficacy of prevention and assessment score of training injuries in new recruits.Methods A randomized controlled study was conducted on 265 new recruits subjected from two organizational units of an army unit with cluster sampling.Based on entire organizational unit,the participants were randomly divided into a control group(n=132)and an experimental group(n=133).The experimental group received joint function screening and corrective movement training,which was subsequently applied in the new recruit training,while the control group underwent training according to conventional methods.Joint function were collected before and after training.The demographic data,assessment score of training,and incidence of training injuries were collected through the participant's own organizational unit.Receiver operating characteristic(ROC)curve was plotted to evaluate the efficacy of joint function screening in predicting training injuries,and binary logistic regression and general linear regression analyses were applied to verify the correlation of joint function screening score with training injuries and assessment score of training.Results After new training,the score of joint function screening was significantly higher in the experimental group than the control group(16.62±1.87 vs 14.92±2.58,P<0.001).And the score was obviously increased in the experimental group(16.62±1.87 vs 12.82±1.98,P<0.001)and the control group(14.92±2.58 vs 12.95±1.81,P<0.001)when compared with the corresponding score before training.The area under the ROC curve(AUC)of joint function screening in predicting training injuries was 0.762(95%CI:0.694～0.830),indicating good predictive efficacy.During the new training process,the incidence of training injuries in the experimental group(13.53%)was significantly lower than that in the control group(24.24%,Chi-square=4.963,P=0.026).Binary logistic regression analysis showed that the pre-training assessment score of joint function screening was an important influencing factor for training injuries in new recruits(OR=0.552,95%CI:0.413～0.660,P<0.001).The experimental group obtained notably higher mean assessment score than the control group[733.00(716.00,752.75)vs 728.79(710.46,744.28),P=0.027].Linear regression analysis revealed a correlation between post-training score of joint function screening and the assessment score of newly trained personnel(P<0.001).Conclusion Joint function screening and correction for newly trained personnel can effectively prevent training-related injuries during the new training period,and correcting joint function through training can effectively improve the assessment score of newly trained personnel.

The zebrafish model has attracted much attention due to its strong reproductive ability, short research cycle, and ease of maintenance. It has always been an important vertebrate model system, often used to carry out human disease research. Its motor behavior features have the advantages of being simpler, more intuitive, and quantifiable. In recent years, it has received widespread attention in the study of traditional Chinese medicine(TCM)for the treatment of sleep disorders, neurodegenerative diseases, fatigue, epilepsy, and other diseases. This paper reviews the characteristics of zebrafish motor behavior and its applications in the pharmacodynamic verification and mechanism research of TCM extracts, active ingredients, and TCM compounds, as well as in active ingredient screening and safety evaluation. The paper also analyzes its advantages and disadvantages, with the aim of improving the breadth and depth of zebrafish and its motor behavior applications in the field of TCM research.
Zebrafish/physiology* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/therapeutic use* ; Disease Models, Animal ; Drug Evaluation, Preclinical/methods* ; Animals ; Sleep Wake Disorders/physiopathology* ; Epilepsy/physiopathology* ; Neurodegenerative Diseases/physiopathology* ; Fatigue/physiopathology* ; Behavior, Animal/physiology* ; Motor Activity/physiology*

OBJECTIVE: Burning solid cooking fuel contributes to household air pollution and is associated with frailty. However, how solid cooking fuel use contributes to the development of frailty has not been well illustrated. METHODS: This study recruited 8,947 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study, 2011-2018. Group-based trajectory modeling was employed to identify frailty trajectories. Multinomial logistic regression was used to assess the association between solid cooking fuel use and frailty trajectories. Population-attributable fractions were used to estimate the frailty burden from solid fuel use. RESULTS: We identified three frailty trajectories: low-stable ( n = 5,789), moderate-increasing ( n = 2,603), and fast-increasing ( n = 555). Solid fuel use was associated with higher odds of being in the moderate-increasing ( OR: 1.24, 95% CI: 1.08-1.42) and fast-increasing ( OR: 1.48, 95% CI: 1.14-1.92) trajectories. These associations were strengthened by longer solid fuel use ( P for trend < 0.001). Switching to clean fuel significantly reduced the risk of being in these trajectories compared with persistent solid fuel users. Without solid fuel, 8% of moderate- and 19% of fast-increasing trajectories demonstrated frailty development like the low-stable group. CONCLUSION Solid cooking fuel use is associated with frailty trajectories in middle-aged and older Chinese populations.
Humans ; China/epidemiology* ; Cooking ; Male ; Female ; Middle Aged ; Aged ; Air Pollution, Indoor/adverse effects* ; Frailty/etiology* ; Longitudinal Studies ; Cohort Studies

OBJECTIVE: To assess the value of the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) score combined with PSA density (PSAD) in the diagnosis of clinically significant prostate cancer (CSPCa) in the PSA grey zone by MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy. METHODS: This retrospective study included 327 male patients with total PSA (tPSA) levels of 4-10 μg/L undergoing MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy in our hospital between January 2021 and December 2023. According to the pathological results, we divided the patients into a CSPCa (n = 44) and a non-CSPCa group (n = 283), collected their clinical and imaging data, and subjected them to statistical analysis. RESULTS: The age, tPSA level, PSAD and PI-RADS score were significantly higher, while the free PSA (fPSA) level, f/tPSA ratio and prostate volume remarkably lower in the CSPCa than in the non-CSPCa group (P<0.05). The areas under the curve (AUCs) of PSAD, PI-RADS score and their combination were 0.772, 0.730 and 0.801, with sensitivities of 63.63%, 70.45% and 72.73%, and specificities of 84.10%, 75.62% and 83.75%, respectively (P<0.01). With PSAD 0.2 μg/(ml·cm3) as the best cut-off value and based on the PI-RADS scores, the patients were divided into two groups for analysis. In the patients with PI-RADS scores 2 and 5, the AUCs were 0.534 and 0.643, with sensitivities of 16.67% and 63.64%, and specificities of 85.14% and 64.29%, with no statistically significant differences (P= 0.784, P= 0.228), and in those with PI-RADS scores 3 and 4, the AUCs were 0.794 and 0.843, with sensitivities of 57.14% and 80.00%, and specificities of 87.14% and 81.82%, with statistically significant differences (P= 0.009, P<0.001). CONCLUSION PI-RADS v2.1 score combined with PSAD can effectively improve the diagnostic efficiency of CSPCa in the PSA grey zone by MRI-TRUS cognitive fusion-guided transperineal targeted prostate biopsy and serve as a guide for selection of prostate biopsy.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Retrospective Studies ; Prostate-Specific Antigen ; Magnetic Resonance Imaging ; Image-Guided Biopsy ; Prostate/pathology* ; Aged ; Middle Aged

[This corrects the article DOI: 10.1016/j.apsb.2022.03.002.].

Objective To explore the value of MRI subtraction technique(ST)for evaluating the efficacy of systemic therapy for advanced hepatocellular carcinoma(HCC)and predicting prognosis after combining with surgery.Methods Totally 35 patients with 39 HCC lesions who received systemic therapy+radical resection were retrospectively collected.Based on preoperative MRI,tumor activity ratio(recorded as tumor activityST)was obtained with ST,while tumor activity value(recorded as tumor activitypathology)was obtained through postoperative pathology,and their correlation was analyzed.The patients were regularly followed up after surgery,and the survival data were recorded.Receiver operating characteristic(ROC)curve was drawn to evaluate the efficacy of tumor activityST for predicting patients'survival status.Then the patients were divided into survival benefit group and no survival benefit group according to the cut-off value,and survival analysis was conducted.Results Tumor activityST was positively correlated with tumor activitypathology(r=0.900,P＜0.001).The median follow-up time was 32.93 months,during which 8 patients died,and the median survival time was 29.9 months.The area under the curve(AUC)of tumor activityST for predicting patients'survival status was 0.67,and the cut-off value was 0.36.Thirty patients with tumor activityST＜0.36 were enrolled in survival benefit group,while 5 patients≥0.36 were collected in no survival benefit group.The overall survival in survival benefit group was longer than that in no survival benefit group(P＜0.001).Conclusion MRI ST could be used to non-invasively evaluate the efficacy of systemic therapy for advanced HCC and predict prognosis after combining with surgery.

Objective To explore the predictive efficacy of several multimodal MRI-based machine learning models for the promoter methylation states of O6-methylguanine-DNA methyltransferase(MGMT)of glioblastoma muliforme(GBM)patients in terms of the GBM heterogeneity and the complexity of the tumor microenvironment.Methods Firstly,the multimodal MRI images of 317 GBM patients from The University of Pennsylvania Glioblastoma(UPENN-GBM)dataset were pre-processed,with four sequences involved in including T1-weighted imaging(T1WI)sequence,T1-weighted contrast-enhanced imaging(T1CE)sequence,T2-weighted imaging(T2WI)sequence and fluid-attenuated inversion recovery(FLAIR)sequence,and the radiomics features were extracted for two regions of interest(ROIs)such as the tumor core region and the tumor edema region.Secondly,the data of the 317 GBM patients were randomly divided into a training set(254 cases)and a test set(63 cases),which underwent normalization with Z-scores and feature selection and dimensionality reduction with Lasso regression.Finally,three models were established respectively with particle swarm optimization-support vector machine(PSO-SVM),C-support vector classification(C-SVC)and adaptive boosting(adaptive boosting(Adaboost)algorithms,and the predictive efficacy of the three models for glioblastoma multiforme MGMT promoter methylation states were evaluated in terms of accuracy and AUC.Results The Adaboost model based on T2WI sequence and radiomics features of the tumor core region had the highest predictive efficacy with accuracy and AUC values of 67％and 0.74,respectively,higher than those of other combinations of sequences,models and regions of interest.Conclusion The multimodal MRI-based machine learning models can be used for the prediction of glioblastoma multiforme MGMT promoter methylation states,which provides powerful support for personalized treatment and prognostic assessment of GBM.[Chinese Medical Equipment Journal,2025,46(6):7-13]