This research study focuses on addressing the limitations of current neuropathic pain (NP) treatments by developing a novel dual-target modulator, E0199, targeting both Na_V1.7, Na_V1.8, and Na_V1.9 and K_V7 channels, a crucial regulator in controlling NP symptoms. The objective of the study was to synthesize a compound capable of modulating these channels to alleviate NP. Through an experimental design involving both in vitro and in vivo methods, E0199 was tested for its efficacy on ion channels and its therapeutic potential in a chronic constriction injury (CCI) mouse model. The results demonstrated that E0199 significantly inhibited Na_V1.7, Na_V1.8, and Na_V1.9 channels with a particularly low half maximal inhibitory concentration (IC₅₀) for Na_V1.9 by promoting sodium channel inactivation, and also effectively increased K_V7.2/7.3, K_V7.2, and K_V7.5 channels, excluding K_V7.1 by promoting potassium channel activation. This dual action significantly reduced the excitability of dorsal root ganglion neurons and alleviated pain hypersensitivity in mice at low doses, indicating a potent analgesic effect without affecting heart and skeletal muscle ion channels critically. The safety of E0199 was supported by neurobehavioral evaluations. Conclusively, E0199 represents a ground-breaking approach in NP treatment, showcasing the potential of dual-target small-molecule compounds in providing a more effective and safe therapeutic option for NP. This study introduces a promising direction for the future development of NP therapeutics.

Cardiotoxicity is a critical issue in drug development that poses serious health risks, including potentially fatal arrhythmias. The human ether-à-go-go related gene (hERG) potassium channel, as one of the primary targets of cardiotoxicity, has garnered widespread attention. Traditional cardiotoxicity testing methods are expensive and time-consuming, making computational virtual screening a suitable alternative. In this study, we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds, with the aim of improving prediction accuracy and efficiency. We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms, including Gaussian naive Bayes (NB), random forest (RF), support vector machine (SVM), K-nearest neighbors (KNN), eXtreme gradient boosting (XGBoost), and Transformer models, to build predictive models. Our models demonstrated advanced predictive performance. The best machine learning model, XGBoost Morgan, achieved an accuracy (ACC) value of 0.84, and the deep learning model, Transformer_Morgan, achieved the best ACC value of 0.85, showing a high ability to distinguish between toxic and non-toxic compounds. On an external independent validation set, it achieved the best area under the curve (AUC) value of 0.93, surpassing ADMETlab3.0, Cardpred, and CardioDPi. In addition, we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods, such as voting and stacking, provided slight improvements in model stability. Furthermore, the SHapley Additive exPlanations (SHAP) explanations revealed the relationship between benzene rings, fluorine-containing groups, NH groups, oxygen in ether groups, and cardiotoxicity, highlighting the importance of these features. This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment. Using computational methods, this study facilitates a more efficient drug development process, reduces costs, and improves the safety of new drug candidates, ultimately benefiting medical and public health.

Objective:To investigate the risk factors of skin adverse events associated with immune checkpoint inhibitor (ICI) therapy in patients with urologic neoplasms, and establish a predictive model.Methods:A single-center retrospective case-control study enrolled 91 advanced urologic neoplasms patients who received ICI therapy at the Department of Urology, Beijing Friendship Hospital, Capital Medical University from January 2020 to June 2025. Patients were divided into the skin lesion group ( n=44) and the control group ( n=47). Patients in the skin lesion group experienced related skin adverse events during ICI treatment, while patients in the control group did not experience such events during ICI treatment. The general data and laboratory indicators were compared between the two groups. The normally distributed measurement data were expressed as mean±standard deviation ( ± s), and the independent sample t-test was used for comparison between groups; the non-normally distributed measurement data were expressed as the median (interquartile range) [ M ( Q1, Q3)], and the Kruskal-Wallis test was used for comparison between groups. The count data were expressed as the number of cases and percentages, and the Chi-test was used for comparison between groups. First, a univariate analysis was conducted on the influencing factors of skin adverse events in patients with urologic neoplasms after ICI treatment. Then, the indicators with statistically significant differences in the univariate analysis were further included in the multivariate Logistic regression model to screen the independent risk factors for predicting skin adverse events. The R software was used to incorporate the factors with significant differences from multivariate analysis into the prediction model and construct a Nomogram. The calibration curve was utilized to evaluate the consistency between predicted values and actual observed results. Meanwhile, the discrimination of the model was verified by the receiver operating characteristic (ROC) curve and the area under the curve (AUC), so as to comprehensively verify the reliability and clinical application value of the prediction model. Results:The results of univariate analysis showed that there were statistically significant differences between the skin lesion group and the control group in terms of the proportion of other immune responses, serum albumin level, absolute eosinophil count, and C-reactive protein (CRP) levels ( P<0.05). These factors were included in multivariate Logistic regression, which identified elevated absolute eosinophil count and elevated CRP as the independent risk factors for related skin adverse events in patients with urologic neoplasms after ICI treatment. A predictive nomogram was built based on these factors. The calibration curve showed high consistency between predicted and actual probabilities, and ROC analysis confirmed the combined model had high predictive value (AUC=0.883, P<0.001). Conclusions:Elevated absolute eosinophil count and elevated CRP level are independent predictors of immune-related skin adverse events in urologic neoplasms patients after ICI treatment. The prediction model constructed based on these two factors facilitates early clinical screening and identification of high-risk patients.

Cardiotoxicity is a critical issue in drug development that poses serious health risks,including potentially fatal arrhythmias.The human ether-à-go-go related gene(hERG)potassium channel,as one of the pri-mary targets of cardiotoxicity,has garnered widespread attention.Traditional cardiotoxicity testing methods are expensive and time-consuming,making computational virtual screening a suitable alter-native.In this study,we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds,with the aim of improving prediction accuracy and efficiency.We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms,including Gaussian naive Bayes(NB),random forest(RF),support vector machine(SVM),K-nearest neighbors(KNN),eXtreme gradient boosting(XGBoost),and Trans-former models,to build predictive models.Our models demonstrated advanced predictive performance.The best machine learning model,XGBoost Morgan,achieved an accuracy(ACC)value of 0.84,and the deep learning model,Transformer_Morgan,achieved the best ACC value of 0.85,showing a high ability to distinguish between toxic and non-toxic compounds.On an external independent validation set,it achieved the best area under the curve(AUC)value of 0.93,surpassing ADMETlab3.0,Cardpred,and CardioDPi.In addition,we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods,such as voting and stacking,provided slight improvements in model stability.Furthermore,the SHapley Additive exPlanations(SHAP)explanations revealed the relationship between benzene rings,fluorine-containing groups,NH groups,oxygen in ether groups,and cardiotoxicity,highlighting the importance of these features.This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment.Using computational methods,this study facilitates a more efficient drug development process,reduces costs,and improves the safety of new drug candidates,ultimately benefiting medical and public health.

This research study focuses on addressing the limitations of current neuropathic pain(NP)treatments by developing a novel dual-target modulator,E0199,targeting both Nav1.7,Nay1.8,and Nay1.9 and Kv7 channels,a crucial regulator in controlling NP symptoms.The objective of the study was to synthesize a compound capable of modulating these channels to alleviate NP.Through an experimental design involving both in vitro and in vivo methods,E0199 was tested for its efficacy on ion channels and its therapeutic potential in a chronic constriction injury(CCI)mouse model.The results demonstrated that E0199 significantly inhibited Nav1.7,Nav1.8,and Nav1.9 channels with a particularly low half maximal inhibitory concentration(ICs0)for Nay1.9 by promoting sodium channel inactivation,and also effectively increased Kv7.2/73,Kv7.2,and Kv7.5 channels,excluding Kv7.1 by promoting potassium channel acti-vation.This dual action significantly reduced the excitability of dorsal root ganglion neurons and alle-viated pain hypersensitivity in mice at low doses,indicating a potent analgesic effect without affecting heart and skeletal muscle ion channels critically.The safety of E0199 was supported by neurobehavioral evaluations.Conclusively,E0199 represents a ground-breaking approach in NP treatment,showcasing the potential of dual-target small-molecule compounds in providing a more effective and safe thera-peutic option for NP.This study introduces a promising direction for the future development of NP therapeutics.

Although blood banks based on human blood can provide blood transfusions for the wounded timely and effec-tively,scientific research has never given up on finding new blood sources due to the restrictions of human blood sources.With the application of transgenic technology and the successful breeding of gene-edited pigs,gene-edited pig blood as a po-tential source of clinical transfusion has attracted wide attention.Now there are preclinical studies showing the feasibility of transfusing gene-edited pig red blood cells into primates.This paper discusses the related research and future development of xenogeneic transfusion of porcine red blood cells by gene editing.

Objective:To explore the risk factors for recurrence of intussusception in children after successful ultrasound-guided saline enema reduction.Methods:The clinical and follow up data of 355 hospitalized children with intussusception at the First Affiliated Hospital of Zhengzhou University from Feb 2018 to Feb 2023 were reviewed.Patients were divided into two groups by recurrence develped and the differences were compared, Data with significant differences were incorporated into multi-factor logistic analysis.Results:The overall recurrence rate was 15.8% (56/355). By univariate variable analysis model, there were statistically significant differences between the two groups in age, previous intussusception history, vomiting, maximum diameter of concentric circles shown by ultrasound, and concurrent bowel organic diseases (lead points) (all P<0.05). In multivariate Logistic regression model, age, previous intussusception history, maximum diameter of concentric circles, and lead points were independent risk factors for recurrent intussusception after saline enema.The optimal cut-off values for age and maximum diameter of concentric circles were 2 years and 33.5 mm, respectively, according to ROC curve analysis. Conclusion:Age older than 2 years, previous intussusception history, maximum diameter of concentric circles longer than 33.5 mm, and lead points are independent risk factors for recurrence after saline enema.

Limb dismemberment injuries are common in clinical practice,and safe and effective protection of the dismembered limb is the key to successful limb replantation.Normothermic machine perfusion has made significant breakthrough in the field of organ transplantation,which may maintain the active function of organs and tissues for a long period of time and prolong the preservation time.These findings have been validated in large animal models and clinical trials.Meantime,this technology is expected to provide novel reference for the preservation and functional recovery of severed limbs.Therefore,this paper reviews the problems of static cold preservation in the preservation of disarticulated limbs,the development history of mechanical perfusion,the current status of clinical application of ambient mechanical perfusion of disarticulated limbs as well as the problems to be solved,and looks forward to the direction of its development and the prospect of its clinical application,with a view to promoting the wide application of this technology in the clinic.

Objective Based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF/MS),the potential biomarkers and metabolic mechanisms of adult calcium oxalate urolithiasis were identified to guide the diagnosis and treatment of calcium oxalate lithiasis.Methods Blood samples of 36 patients diagnosed with bilateral upper urinary tract calcium oxalate stones and 36 healthy controls admitted to our hospital during Oct.2017 and Jul.2018 were collected.Metabolic fingerprints were analyzed with UPLC-Q-TOF/MS.The multivariate data were analyzed with principal component analysis(PCA)and orthogonal partial least squares discriminant analysis(OPLS-DA).Potential biological markers were identified by comparing human metabolome datasets.Finally,the metabolic pathways of the identified compounds were analyzed and the metabolic network map was constructed.Results PCA and OPLS-DA showed significant differences in blood metabolites between patients and healthy controls,and identified 29 blood-related metabolites,including linoleic acid,citric acid,uric acid and so on.The most relevant blood metabolic pathways were bile acid synthesis pathway,fatty acid biosynthesis pathway,glycerophospholipid metabolism pathway,sphingolipid metabolism pathway and purine metabolism pathway.Conclusion Blood metabolomics analysis based on the UPLC-Q-TOF/MS platform identified 29 potential blood biomarkers of adult calcium oxalate urolithiasis,and purine and lipid metabolism may be related to the genesis of calcium oxalate stones.

Objective To summarize the experience and practical value of living donor kidney harvesting in Bama miniature pigs with six gene modified. Methods The left kidney of Bama miniature pigs with six gene modified was obtained by living donor kidney harvesting technique. First, the ureter was occluded, and then the inferior vena cava and abdominal aorta were freed. During the harvesting process, the ureter, renal vein and renal artery were exposed and freed in sequence. The vascular forceps were used at the abdominal aorta and inferior vena cava, and the renal artery and vein were immediately perfused with 4℃ renal preservation solution, and stored in ice normal saline for subsequent transplantation. Simultaneously, the donor abdominal aorta and inferior vena cava gap were sutured. The operation time, blood loss, warm and cold ischemia time, postoperative complications and the survival of donors and recipients were recorded. Results The left kidney of the genetically modified pig was successfully harvested. Intraoperative bleeding was 5 mL, warm ischemia time was 45 s, and cold ischemia time was 2.5 h. Neither donor nor recipient pig received blood transfusion, and urinary function of the kidney transplanted into the recipient was recovered. The donor survived for more than 8 months after the left kidney was resected. Conclusions Living donor kidney harvesting is safe and reliable in genetically modified pigs. Branch blood vessels could be processed during kidney harvesting, which shortens the process of kidney repair and the time of cold ischemia. Living donor kidney harvesting contributes to subsequent survival of donors and other scientific researches.