Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications (ASMs), a condition known as pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy remains an intractable issue in the clinic. Its early prediction is important for prevention and diagnosis. However, it still lacks effective predictors and approaches. Here, a classical model of pharmacoresistant temporal lobe epilepsy (TLE) was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats. Ictal electroencephalograms (EEGs) recorded before phenytoin treatment were analyzed. Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats, a convolutional neural network predictive model was constructed to predict pharmacoresistance, and achieved 78% prediction accuracy. We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power, which was verified in seizure EEGs from pharmacoresistant TLE patients. Prospectively, therapies targeting the subiculum in those predicted as "pharmacoresistant" individual rats significantly reduced the subsequent occurrence of pharmacoresistance. These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model. This may be of translational importance for the precise management of pharmacoresistant TLE.
Epilepsy, Temporal Lobe/diagnosis* ; Animals ; Drug Resistant Epilepsy/drug therapy* ; Electroencephalography/methods* ; Rats ; Anticonvulsants/pharmacology* ; Neural Networks, Computer ; Male ; Humans ; Phenytoin/pharmacology* ; Adult ; Disease Models, Animal ; Female ; Rats, Sprague-Dawley ; Young Adult ; Convolutional Neural Networks

Ovarian cancer is the most lethal malignancy affecting the female reproductive system. Pharmacological inhibitors targeting CDK4/6 have demonstrated promising efficacy across various cancer types. However, their clinical benefits in ovarian cancer patients fall short of expectations, with only a subset of patients experiencing these advantageous effects. This study aims to provide further clinical and biological evidence for antineoplastic effects of a CDK4/6 inhibitor (TQB4616) in ovarian cancer and explore underlying mechanisms involved. Patient-derived ovarian cancer organoid models were established to evaluate the effectiveness of TQB3616. Potential key genes related to TQB3616 sensitivity were identified through RNA-seq analysis, and TRIM4 was selected as a candidate gene for further investigation. Subsequently, co-immunoprecipitation and GST pull-down assays confirmed that TRIM4 binds to hnRNPDL and promotes its ubiquitination through RING and B-box domains. RIP assay demonstrated that hnRNPDL binded to CDKN2C isoform 2 and suppressed its expression by alternative splicing. Finally, in vivo studies confirmed that the addition of siTRIM4 significantly improved the effectiveness of TQB3616. Overall, our findings suggest that TRIM4 modulates ubiquitin-mediated degradation of hnRNPDL and weakens sensitivity to CDK4/6 inhibitors in ovarian cancer treatment. TRIM4 may serve as a valuable biomarker for predicting sensitivity to CDK4/6 inhibitors in ovarian cancer.
Humans ; Female ; Ovarian Neoplasms/pathology* ; Animals ; Tripartite Motif Proteins/genetics* ; Mice ; Cyclin-Dependent Kinase 4/antagonists & inhibitors* ; Cell Line, Tumor ; Cyclin-Dependent Kinase 6/antagonists & inhibitors* ; Protein Kinase Inhibitors/pharmacology* ; Ubiquitin/metabolism* ; Xenograft Model Antitumor Assays ; Ubiquitination ; Antineoplastic Agents/pharmacology*

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Resistant ovary syndrome(ROS)and premature ovarian insufficiency(POI)fall under the cat-egory of hypogonadotropic amenorrhea,sharing similar clinical features that often pose challenges in differentiation.ROS can be easily misdiagnosed as POI,which presents a significant obstacle to subsequent treatment.Therefore,it is crucial for patients with fertility requirements to have a clear understanding of the etiology,clinical features,and diagnostic criteria of ROS and POI in order to establish an early diagnosis and develop an appropriate treatment plan.This article provides a systematic and comprehensive discussion on the research progress regarding the eti-ology and pathogenesis,clinical features and diagnosis,as well as individualized management of ROS and POI.The aim is to offer reference for clinicians in achieving early clarification of diagnoses,avoiding misdiagnosis or mistreatment,while assisting patients in improving symptoms and realizing their fertility aspirations through person-alized management.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Resistant ovary syndrome(ROS)and premature ovarian insufficiency(POI)fall under the cat-egory of hypogonadotropic amenorrhea,sharing similar clinical features that often pose challenges in differentiation.ROS can be easily misdiagnosed as POI,which presents a significant obstacle to subsequent treatment.Therefore,it is crucial for patients with fertility requirements to have a clear understanding of the etiology,clinical features,and diagnostic criteria of ROS and POI in order to establish an early diagnosis and develop an appropriate treatment plan.This article provides a systematic and comprehensive discussion on the research progress regarding the eti-ology and pathogenesis,clinical features and diagnosis,as well as individualized management of ROS and POI.The aim is to offer reference for clinicians in achieving early clarification of diagnoses,avoiding misdiagnosis or mistreatment,while assisting patients in improving symptoms and realizing their fertility aspirations through person-alized management.

Osteoporosis （OP） is a systemic metabolic bone disease characterized by bone microstructure degeneration and bone mass loss， which has a high prevalence and disability rate. Effective prevention and treatment of OP is a major difficulty in the medical community. The nature of OP is that multiple pathological factors lead to the imbalance of human bone homeostasis maintained by osteoblasts and osteoclasts. Ferroptosis is a non-apoptotic cell death pathway， and its fundamental cause is cell damage caused by iron accumulation and lipid peroxidation. Studies have shown that ferroptosis is involved in and affects the occurrence and development of OP， which leads to OP by mediating the imbalance of bone homeostasis. Ferroptosis is an adjustable form of programmed cell death. The intervention of ferroptosis can regulate the damage degree and death process of osteoblasts and osteoclasts， which is beneficial to maintain bone homeostasis， slow down the development process of OP， improve the clinical symptoms of patients， reduce the risk of disability， and improve their quality of life. However， there are few studies on ferroptosis in OP. Traditional Chinese medicine （TCM） is a medical treasure with unique characteristics and great application value in China. It has been widely used in China and has a long history. It has the multi-target and multi-pathway advantages in the treatment of OP， with high safety， few toxic and side effects， and low treatment cost， and has a significant effect in clinical application. The intervention of TCM in ferroptosis to regulate bone homeostasis may be a new direction for the prevention and treatment of OP in the future. This article summarized the regulatory mechanisms related to ferroptosis， discussed the role of ferroptosis in bone homeostasis， and reviewed the current status and progress of active ingredients in TCM compounds and monomers in the regulation of OP through ferroptosis， so as to provide a theoretical basis for the participation of TCM in the prevention and treatment of OP in the future.

Objective:To establish a scoring system for preoperative prediction of the malignant potential of gastric stromal tumors based on gastroscopic and endoscopic ultrasound features, along with validation.Methods:A total of 286 patients who were treated in Jiangsu Province Hospital of Chinese Medicine from January 1, 2017 to December 31, 2023 and diagnosed as having gastric stromal tumors by postoperative pathology were enrolled in the modeling group. According to National Institutes of Health classification system, 227 very-low/low-risk patients were classified into the low malignant potential (LMP) group, and the 59 intermediate/high-risk patients into the high malignant potential (HMP) group. LASSO regression analysis was performed to identify predictive factors for HMP gastric stromal tumors, and a nomogram prediction model was developed. Internal validation using the Bootstrap method was performed on the modeling group, and external validation was performed on data from 85 patients who were treated and diagnosed as having gastric stromal tumors by postoperative pathology in Taizhou People's Hospital from January 1, 2021 to December 31, 2023. The receiver operator characteristic (ROC) curves, calibration curves, and decision curve analyses were employed in both the modeling and external validation groups.Results:Tumor size (coef=0.755), tumor shape (coef=0.015), tumor location (coef=0.008), growth pattern (coef=-0.026), cystic change (coef=0.685), and surface unceration change (coef=-0.545) were the independent predictive factors for HMP gastric stromal tumors. The nomogram-based prediction model constructed using these factors achieved an area under the ROC curve of 0.959 (95% CI: 0.898-0.903) in the modeling group and 0.959 (95% CI: 0.857-1.000) in the external validation group. The model demonstrated good accuracy (0.917) and a Kappa value of 0.737 in internal validation. Calibration curve and decision curve analyses indicated strong calibration and high net benefit in both the modeling and the external validation groups. Conclusion:Tumor size, tumor shape, tumor location, growth pattern, cystic change, and surface ulceration change are independent predictive factors for HMP gastric stromal tumors. The nomogram model developed based on these factors offers effective and convenient visualization for clinicians to predict the malignant potential of gastric stromal tumors preoperatively.

Objective To compare the effect of palliative mitral valve surgeries and medication therapies for secondary non-ischemic mitral regurgitation. Methods The clinical data of patients with non-ischemic functional mitral regurgitation treated in our hospital between 2009 and 2019 were retrospectively analyzed. Patients with a left ventricular ejection fraction (LVEF)＜40% underwent a dobutamine stress test, and a positive result was determined when the LVEF improved by more than 15% compared to the baseline value. Positive patients were divided into a surgery group and a medication group. The surgery group underwent surgical mitral valve repair or replacement, while the medication group received simple medication treatment. Follow-up on survival and cardiac function status through outpatient or telephone visits every six months after surgery, and patients underwent cardiac ultrasound examination one year after surgery. The main research endpoint was a composite endpoint of all-cause death, heart failure readmission, and heart transplantation, and the differences in cardiac function and cardiac ultrasound parameters between the two groups were compared. Results Ultimately 41 patients were collected, including 28 males and 13 females with an average age of 55.5±11.1 years. Twenty-five patients were in the surgery group and sixteen patients in the medication group. The median follow-up time was 16 months, ranging 1-96 months. The occurrence of all-cause death in the surgery group was lower than that in the medication group (HR=0.124, 95%CI 0.024-0.641, P=0.034). The difference between the two groups was not statistically significant in the composite endpoint (HR=0.499, 95%CI 0.523-1.631, P=0.229). The New York Heart Association (NYHA) grade of the surgery group was better (NYHA Ⅰ-Ⅱ accounted for 68.0% in the surgury group and 18.8% in the medication group, P<0.01) as well as the grade of mitral valve regurgitation (87.5% of the patients in the medication group had moderate or above regurgitation at follow-up, while all the patients in the surgery group had moderate below regurgitation, P<0.01). There was no statistical difference in preoperative and follow-up changes in echocardiograph parameters between the two groups (P＞0.05). Conclusion For non-ischemic functional mitral regurgitation, if the cardiac systolic function is well reserved, mitral valve surgery can improve survival and quality of life compare to simple medication therapy.