OBJECTIVE To provide guidance for the individualized use of antiepileptic drugs （AEDs） in patients with epilepsy or bipolar affective disorder.METHODS Clinical data of patients with epilepsy or bipolar affective disorder who received AEDs treatment and underwent therapeutic drug monitoring （TDM） at Xi’an International Medical Center Hospital from January 2023 to December 2025 were retrospectively collected. The baseline information， characteristics of AEDs utilization， implementation status of TDM and laboratory parameters were summarized. Spearman correlation analysis， univariate analysis and multivariate linear regression analysis were performed to identify the independent influencing factors for blood concentrations of AEDs.RESULTS A total of 1 572 patients were enrolled， including 660 males and 912 females. The majority were aged ≥60 years （30.15%）； 71.76% of patients were on monotherapy with AEDs， with valproic acid being the most commonly prescribed （51.97%）； combination therapy was predominantly a two-drug regimen （26.21%）， while three-drug regimens were rare （2.04%）. A total of 2 901 blood samples for TDM were collected， with the highest number of samples for valproic acid and levetiracetam （1 987 and 684 samples， respectively）. TDM for all five drugs was primarily conducted once； among which， the blood concentrations attainment rates exceeded 50% for patients taking valproic acid and levetiracetam， while the median blood concentrations for patients taking lamotrigine， oxcarbazepine， and carbamazepine were all below the lower limit of the therapeutic reference range. Based on the results of Spearman correlation analysis， univariate analysis， and multivariate linear regression analysis， patient gender， platelet count （PLT）， alanine transaminase （ALT）， aspartate transaminase （AST）， and total bilirubin （TBil） were found to be independent factors influencing blood concentration of valproic acid （unstandardized coefficients were －6.770 7， －0.078 6， －0.099 4， 0.083 2， －0.578 9， P ＜0.05）， while age and creatinine （CRE） were found to be independent factors influencing blood concentration of levetiracetam （unstandardized coefficients were 0.108 7， 0.047 8， P ＜0.05）.CONCLUSIONS Female gender and elevated AST levels are risk factors for increased blood concentration of valproic acid， while elevated PLT， ALT and TBil levels are associated with decreased blood concentration of valproic acid. Patients of advanced age and those with renal insufficiency bear a relatively high risk of in vivo levetiracetam accumulation.

Objective To explore the incidence and prognosis of citrin deficiency in Maoming,and to understand mutation types and frequency of SLC25A13 gene.Methods A total of 88 322 newborns born in Maoming from April 2022 to January 2025 were selected as research subjects.These specimens were screened using tandem mass spectrometry.Newborns with elevated citrulline levels or suspected clinical symptoms of citrin deficiency were recalled immediately for further genetic confirmation,and treated confirmed cases were followed up.Results Among 88 322 newborns,53 cases were positive for citrulline by tandem mass spectrometry,43 cases were recalled with positive initial screening,23 cases were still positive for citrulline after re-examination.Finally,1 case of neonatal intrahepatic cholestasis caused by citrin deficiency(NICCD)was clinically diagnosed,and 10 cases were diagnosed with SLC25A13 gene,of which 1 case was false negative.Therefore,the total positive predictive value was 18.87％(10/53),and the prevalence rate of NICCD in Maoming was 1/8029(11/88 322).A total of 5 mutation sites were detected in 10 neonates with NICCD gene diagnosis,and the top 3 mutation sites in the order of proportion were:c.852-855delTATG accounted for 65.0％(13/20),c.615+5G>A accounted for 15.0％(3/20),IVS16ins3kb accounted for 10.0％(2/20).Among the 11 cases,1 case refused treatment and died of liver failure,while the remaining 10 cases were developing well after standardized treatment.Conclusion The incidence of neonatal citrin deficiency in Maoming is significantly higher than in other areas.Tandem mass spectrometry enables rapid early detection of citrin deficiency,though false-negative results may occur in individual cases.Combining genetic sequencing can improve diagnostic accuracy,and achieve precise management of inherited metabolic diseases.

Objective To explore the incidence and prognosis of citrin deficiency in Maoming,and to understand mutation types and frequency of SLC25A13 gene.Methods A total of 88 322 newborns born in Maoming from April 2022 to January 2025 were selected as research subjects.These specimens were screened using tandem mass spectrometry.Newborns with elevated citrulline levels or suspected clinical symptoms of citrin deficiency were recalled immediately for further genetic confirmation,and treated confirmed cases were followed up.Results Among 88 322 newborns,53 cases were positive for citrulline by tandem mass spectrometry,43 cases were recalled with positive initial screening,23 cases were still positive for citrulline after re-examination.Finally,1 case of neonatal intrahepatic cholestasis caused by citrin deficiency(NICCD)was clinically diagnosed,and 10 cases were diagnosed with SLC25A13 gene,of which 1 case was false negative.Therefore,the total positive predictive value was 18.87％(10/53),and the prevalence rate of NICCD in Maoming was 1/8029(11/88 322).A total of 5 mutation sites were detected in 10 neonates with NICCD gene diagnosis,and the top 3 mutation sites in the order of proportion were:c.852-855delTATG accounted for 65.0％(13/20),c.615+5G>A accounted for 15.0％(3/20),IVS16ins3kb accounted for 10.0％(2/20).Among the 11 cases,1 case refused treatment and died of liver failure,while the remaining 10 cases were developing well after standardized treatment.Conclusion The incidence of neonatal citrin deficiency in Maoming is significantly higher than in other areas.Tandem mass spectrometry enables rapid early detection of citrin deficiency,though false-negative results may occur in individual cases.Combining genetic sequencing can improve diagnostic accuracy,and achieve precise management of inherited metabolic diseases.

Objective:To evaluate the impact of postoperative radiotherapy (RT) and associated risk factors on the prognosis of patients undergoing postmastectomy breast reconstruction (PMBR) for breast cancer.Methods:A retrospective analysis was conducted on 1593 breast cancer patients who underwent PMBR at Tianjin Medical University Cancer Institute & Hospital between January 2010 and October 2023. Patients were divided into an RT group ( n = 351) and a non-RT group ( n =1242) based on whether postoperative radiotherapy was administered. The primary endpoints were overall survival (OS) and progression-free survival (PFS), and the secondary endpoint was the incidence of revision surgery. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were used for pairing. Continuous variables were compared between the two groups using the independent samples t-tests, while categorical variables were compared using chi-square tests, and survival analysis was performed using the Kaplan-Meier method. Cox proportional hazards model was used to analyze survival influencing factors, and include propensity factors with P<0.2 in univariate analysis into multivariate analysis. Results:In the RT group, there were 3 deaths (0.9%) and 21 cases of disease progression (6.0%); in the non-RT group, 7 patients died (0.56%) and 40 experienced disease progression (3.22%). The median OS was 20.1 months (range: 0.1-164.9), and the median PFS was 19.5 months (range: 0.1-160.9). Pregnancy-associated breast cancer and higher N stage were identified as significant risk factors for OS, while neoadjuvant therapy, absence of adjuvant chemotherapy or endocrine therapy, and higher T stage were significant risk factors affecting patients' PFS. Radiotherapy significantly reduced the survival risk for PMBR patients with pregnancy-associated breast cancer or those receiving neoadjuvant therapy ( P=0.019, 0.027). Compared with other reconstruction methods, implant-based reconstruction was associated with a lower incidence of postmastectomy revision surgery(10.5% vs. 17.0%, P<0.001). Even after radiotherapy, the revision surgery incidence for implant-based reconstruction remained lower than that of other methods (12.2% vs. 14.2%, P=0.591). Compared with other reconstruction types, expander-based reconstruction was associated with an increased incidence of revision surgery (31.9% vs. 10.9%, P<0.001). Conclusions:Postmastectomy radiotherapy can reduce survival risk in PMBR patients with pregnancy-associated breast cancer or who received neoadjuvant therapy, showing positive effects on OS and PFS in high-risk patients. Pregnancy, higher T/N stage, and specific treatment strategies are critical factors influencing the prognosis of PMBR patients. Implant-based reconstruction is associated with a lower incidence of revision surgery, which remains low even after RT, whereas expander-based reconstruction may increase the long-term risk of revision surgery.

A medical image segmentation network (RPR-MLP) based on multi-scale convolution and parallel reverse attention is presented. In the encoder,Res2net modules and tokenized multi-layer perceptron modules are used as the backbone structure to extract multi-scale information and enhance the diversity of semantic features. Meanwhile,the accuracy of semantic information extraction in the decoder is improved through parallel partial decoder. Additionally,reverse attention module re-emphasizes the focus on important regions for further improving the accuracy of segmentation results. The proposed method achieves Dice scores of 0.8967 and 0.8762 on the Kvasir and ISIC 2018 public datasets,respectively,demonstrating its effectiveness and generalization ability in medical image segmentation. Furthermore,when applied to the lung tumor CT image dataset (LungCancer dataset) collected in the study,the proposed network has Dice score,IoU and F1 score of 0.7278,58.83％and 67.85％,respectively,outperforming baseline network (UNeXt) and common CNN (U-Net,AttU-Net,U-Net++and PraNet) by 0.0301-0.0578、3.16％-4.70％,and 6.72％-18.53％,respectively. The study confirms the effectiveness and generalization ability of RPR-MLP network on different datasets,providing important technical support for lung tumor image segmentation.

Myocardial infarction is a serious type of myocardial ischemic disease. Traditional treatments can only alleviate clinical symptoms and cannot repair damaged myocardium. In this review, the application progress of chitosan-based composite scaffolds in myocardial repair and regeneration after myocardial infarction was reviewed. Combining chitosan with polymers, such as natural proteins and natural polysaccharides can mimic the properties of natural myocardial tissue, reducing ventricular wall stress while increasing biological activity and promoting the retention, repair or regeneration of myocardial cells. Combining chitosan with synthetic polymers and nanomaterials can promote the repair and regeneration of myocardial cells, improve the electrophysiological function of the infarcted area and resynchronise cardiac contraction.

OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

Objective:To evaluate the impact of postoperative radiotherapy (RT) and associated risk factors on the prognosis of patients undergoing postmastectomy breast reconstruction (PMBR) for breast cancer.Methods:A retrospective analysis was conducted on 1593 breast cancer patients who underwent PMBR at Tianjin Medical University Cancer Institute & Hospital between January 2010 and October 2023. Patients were divided into an RT group ( n = 351) and a non-RT group ( n =1242) based on whether postoperative radiotherapy was administered. The primary endpoints were overall survival (OS) and progression-free survival (PFS), and the secondary endpoint was the incidence of revision surgery. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were used for pairing. Continuous variables were compared between the two groups using the independent samples t-tests, while categorical variables were compared using chi-square tests, and survival analysis was performed using the Kaplan-Meier method. Cox proportional hazards model was used to analyze survival influencing factors, and include propensity factors with P<0.2 in univariate analysis into multivariate analysis. Results:In the RT group, there were 3 deaths (0.9%) and 21 cases of disease progression (6.0%); in the non-RT group, 7 patients died (0.56%) and 40 experienced disease progression (3.22%). The median OS was 20.1 months (range: 0.1-164.9), and the median PFS was 19.5 months (range: 0.1-160.9). Pregnancy-associated breast cancer and higher N stage were identified as significant risk factors for OS, while neoadjuvant therapy, absence of adjuvant chemotherapy or endocrine therapy, and higher T stage were significant risk factors affecting patients' PFS. Radiotherapy significantly reduced the survival risk for PMBR patients with pregnancy-associated breast cancer or those receiving neoadjuvant therapy ( P=0.019, 0.027). Compared with other reconstruction methods, implant-based reconstruction was associated with a lower incidence of postmastectomy revision surgery(10.5% vs. 17.0%, P<0.001). Even after radiotherapy, the revision surgery incidence for implant-based reconstruction remained lower than that of other methods (12.2% vs. 14.2%, P=0.591). Compared with other reconstruction types, expander-based reconstruction was associated with an increased incidence of revision surgery (31.9% vs. 10.9%, P<0.001). Conclusions:Postmastectomy radiotherapy can reduce survival risk in PMBR patients with pregnancy-associated breast cancer or who received neoadjuvant therapy, showing positive effects on OS and PFS in high-risk patients. Pregnancy, higher T/N stage, and specific treatment strategies are critical factors influencing the prognosis of PMBR patients. Implant-based reconstruction is associated with a lower incidence of revision surgery, which remains low even after RT, whereas expander-based reconstruction may increase the long-term risk of revision surgery.

A medical image segmentation network (RPR-MLP) based on multi-scale convolution and parallel reverse attention is presented. In the encoder,Res2net modules and tokenized multi-layer perceptron modules are used as the backbone structure to extract multi-scale information and enhance the diversity of semantic features. Meanwhile,the accuracy of semantic information extraction in the decoder is improved through parallel partial decoder. Additionally,reverse attention module re-emphasizes the focus on important regions for further improving the accuracy of segmentation results. The proposed method achieves Dice scores of 0.8967 and 0.8762 on the Kvasir and ISIC 2018 public datasets,respectively,demonstrating its effectiveness and generalization ability in medical image segmentation. Furthermore,when applied to the lung tumor CT image dataset (LungCancer dataset) collected in the study,the proposed network has Dice score,IoU and F1 score of 0.7278,58.83％and 67.85％,respectively,outperforming baseline network (UNeXt) and common CNN (U-Net,AttU-Net,U-Net++and PraNet) by 0.0301-0.0578、3.16％-4.70％,and 6.72％-18.53％,respectively. The study confirms the effectiveness and generalization ability of RPR-MLP network on different datasets,providing important technical support for lung tumor image segmentation.