Epilepsy affects over 50 million people worldwide. Drug-resistant epilepsy (DRE) accounts for up to a third of these cases, and neuro-inflammation is thought to play a role in such cases. Despite being a long-debated issue in the field of DRE, the mechanisms underlying neuroinflammation have yet to be fully elucidated. The pro-inflammatory microenvironment within the brain tissue of people with DRE has been probed using single-cell multimodal transcriptomics. Evidence suggests that inflammatory cells and pro-inflammatory cytokines in the nervous system can lead to extensive biochemical changes, such as connexin hemichannel excitability and disruption of neurotransmitter homeostasis. The presence of inflammation may give rise to neuronal network abnormalities that suppress endogenous antiepileptic systems. We focus on the role of neuroinflammation and brain network anomalies in DRE from multiple perspectives to identify critical points for clinical application. We hope to provide an insightful overview to advance the quest for better DRE treatments.
Humans ; Drug Resistant Epilepsy/metabolism* ; Neuroinflammatory Diseases/immunology* ; Animals ; Brain/pathology* ; Nerve Net/pathology*

Objective:To investigate the risk factors and prognostic value of the textbook outcome (TO) in patients with advanced gastric cancer (AGC) who underwent neoadjuvant chemotherapy followed by surgical resection.Methods:This is a retrospective cohort study. A total of 253 patients with AGC who underwent neoadjuvant chemotherapy combined with gastrectomy and D2 lymphadenectomy in the Department of Gastric Surgery, Fujian Medical University Union Hospital from January 2010 to December 2019 were retrospectively included. There were 195 males and 58 females, aged (60.3±10.0) years (range: 27 to 75 years). The patients were then divided into the TO group ( n=168) and the non-TO group ( n=85). Multivariate Logistic regression was used to analyze the independent predictors of TO. Univariate and multivariate Cox analysis were used to analyze independent prognosis factors for overall survival (OS) and disease-free survival (DFS). Propensity score matching was performed to balance the TO and non-TO groups, and the Kaplan-Meier method was used to calculate survival rates and draw survival curves. Results:Among the 253 patients, 168 patients (66.4%) achieved TO. The Eastern Cooperative Oncology Group score ( OR=0.488, 95% CI: 0.278 to 0.856, P=0.012) and ypN stage ( OR=0.626, 95% CI:0.488 to 0.805, P<0.01) were independently predictive of TO. Multivariate analysis revealed that TO was an independent risk factor for both OS ( HR=0.662, 95% CI: 0.457 to 0.959, P=0.029) and DFS ( HR=0.687, 95% CI: 0.483 to 0.976, P=0.036). After matching, the 5-year OS rate (42.2% vs. 27.8%) and the 5-year DFS rate (37.5% vs. 27.8%) were significantly higher in the TO group than in the non-TO group (both P<0.05). Furthermore, patients in the non-TO group benefited significantly from postoperative chemotherapy (both P<0.05), but those in the TO group did not (both P>0.05). Conclusion:TO is an independent prognosis factor in patients undergoing neoadjuvant chemotherapy and surgery for AGC and is associated with postoperative chemotherapy benefits.

Objective:To investigate the risk factors and prognostic value of the textbook outcome (TO) in patients with advanced gastric cancer (AGC) who underwent neoadjuvant chemotherapy followed by surgical resection.Methods:This is a retrospective cohort study. A total of 253 patients with AGC who underwent neoadjuvant chemotherapy combined with gastrectomy and D2 lymphadenectomy in the Department of Gastric Surgery, Fujian Medical University Union Hospital from January 2010 to December 2019 were retrospectively included. There were 195 males and 58 females, aged (60.3±10.0) years (range: 27 to 75 years). The patients were then divided into the TO group ( n=168) and the non-TO group ( n=85). Multivariate Logistic regression was used to analyze the independent predictors of TO. Univariate and multivariate Cox analysis were used to analyze independent prognosis factors for overall survival (OS) and disease-free survival (DFS). Propensity score matching was performed to balance the TO and non-TO groups, and the Kaplan-Meier method was used to calculate survival rates and draw survival curves. Results:Among the 253 patients, 168 patients (66.4%) achieved TO. The Eastern Cooperative Oncology Group score ( OR=0.488, 95% CI: 0.278 to 0.856, P=0.012) and ypN stage ( OR=0.626, 95% CI:0.488 to 0.805, P<0.01) were independently predictive of TO. Multivariate analysis revealed that TO was an independent risk factor for both OS ( HR=0.662, 95% CI: 0.457 to 0.959, P=0.029) and DFS ( HR=0.687, 95% CI: 0.483 to 0.976, P=0.036). After matching, the 5-year OS rate (42.2% vs. 27.8%) and the 5-year DFS rate (37.5% vs. 27.8%) were significantly higher in the TO group than in the non-TO group (both P<0.05). Furthermore, patients in the non-TO group benefited significantly from postoperative chemotherapy (both P<0.05), but those in the TO group did not (both P>0.05). Conclusion:TO is an independent prognosis factor in patients undergoing neoadjuvant chemotherapy and surgery for AGC and is associated with postoperative chemotherapy benefits.

ObjectiveTo assess the microstructural involvement of gray matter in recovered COVID-19 patients using Synthetic MRI. MethodsThis study was conducted in 29 recovered COVID-19 patients， including severe group （SG， n=11） and ordinary group （OG， n=18）. Healthy volunteers matched by age， sex， BMI and years of education were selected as a healthy control group （HC=23 cases）. Each subject underwent synthetic MRI to generate quantitative T₁ and T₂ maps， and the T₁ and T₂ maps were segmented into 90 regions of interest （ROIs） using automatic anatomical labeling （AAL） mapping. T₁ and T₂ values for each ROI were obtained by averaging all voxels within the ROIs. The T₁ and T₂ values of the 90 brain regions between the three groups were compared. ResultsRelative to HC， the SG had significantly higher T2 values in bilateral orbital superior frontal gyrus， bilateral parahippocampal gyrus， bilateral putamen， bilateral middle temporal gyrus， bilateral Inferior temporal gyrus， left orbital superior frontal gyrus， left orbital inferior frontal gyrus， left gyrus rectus， left anterior cingulate and paracingulate gyri， right median cingulate and paracingulate gyri， left posterior cingulate gyrus， and left supramarginal gyrus （P＜0.05）； Relative to OG， SG showed significantly increased T₂ values in the left rectus gyrus， left parahippocampal gyrus， bilateral middle temporal gyrus， and bilateral inferior temporal gyrus （P＜0.05）. Relative to HC， the T₁ values of SG were significantly increased in bilateral orbital superior frontal gyrus， left rectus gyrus， left anterior cingulate and paracingulate gyri， right posterior cingulate gyrus， left parahippocampal gyrus， left lingual gyrus， left putamen， left thalamus（P＜0.05）； Relative to OG， the T₁ values of SG were significantly higher in the right posterior cingulate gyrus， right calcarine fissure and surrounding cortex， and left putamen （P＜0.05）. ConclusionsEven after recovering from COVID-19， patients may still have persistent or delayed damage to their brain gray matter structure， which is correlated with the severity of the condition. SyMRI can serve as a sensitive tool to assess the extent of microstructural damage to the central nervous system， aiding in early diagnosis of the disease.

Objective To explore the feasibility of the multiplexed sensitivity encoding diffusion weighted imaging(MUSE-DWI)sequence in neck MRI,and to compare with traditional single-shot echo-planar imaging diffusion weighted imaging(SS-EPI-DWI)sequence.Methods Thirty healthy volunteers underwent MUSE-DWI and SS-EPI-DWI sequences scanning in neck.Two groups of images were independently scored by two radiologists for magnetic sensitivity artifact,chemical shift artifact,geometric distortion and overall image quality.The noise,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)of the regions of interest(ROI)of the two groups of images were measured and compared on the nasopharyngeal fossa layer,parotid gland layer,glottic layer and thyroid layer.Results Qualitative analysis showed that the image quality scores of MUSE-DWI sequence were significantly better than those of SS-EPI-DWI sequence in terms of magnetic sensitivity artifact,chemical shift artifact,geometric distortion and overall image quality(P<0.001).Quantitative analysis showed that the noise values of ROIs of MUSE-DWI sequence were significantly lower than those of SS-EPI-DWI sequence(P<0.001).The SNR and CNR of ROIs of MUSE-DWI sequence were higher than those of SS-EPI-DWI sequence(P<0.001).Conclusion MUSE-DWI sequence can significantly reduce geometric distortion,magnetic sensitivity artifact and chemical shift artifact,and SNR and CNR of images are significantly increased compared with SS-EPI-DWI sequence,which is more suitable for neck MRI scanning.

Human beings are inevitably exposed to toxic substances as a result of influences of potential contamination factors in the environment,food and medicines,which poses a threat to human health.In order to effectively screen and prevent the exposure or intake of such substances,it is neces-sary to develop in vitro assays for the detection and toxicity evaluation of toxic substances.High content screening(HCS)has been recognized as an important tool for toxicity testing and risk assessment of compounds due to its high throughput and automation advantages,and has been widely used in in vitro toxicology research.In this review,we described the system components of HCS and its workflow in toxicity screening and toxicity evaluation by focusing on cases of their application in toxicity detection and evaluation studies,including the cytotoxicity,hepatotoxicity,nephrotoxicity,genotoxicity,neurotox-icity,cardiotoxicity,and developmental toxicity.In addition,the applications and developments of machine learning in HCS were explored,especially to the advantages of supervised and unsupervised machine learning strategies for high throughput image screening and data analysis.Finally,the future applications of HCS in toxicity screening and evaluation are outlined,especially in terms of binding new models and gene editing technology.

Objective:To investigate and explore the clinical significance of the expression levels and differences of autophagy related genes ATG3, ATG5, ATG12, ATG16, LC3 and Beclin-1 in peripheral blood mononuclear cells of patients with refractory moderate-to-severe rheumatoid arthritis (RA), who were treated with abatacept.Methods:Peripheral blood samples of 30 patients admitted to the affiliated hospital of North Sichuan Medical College from June 2020 to June 2022 were collected before and after abatacept treatment. Autophagy associated genes were detected by RT-qPCR and, autophagy associated proteins were detected by Western Blot. Correlation analysis with clinical parameters was performed. SPSS26.0 and GraphPad Prism 9.0 were used for statistical analysis, Independent sample t-test was used for comparison between groups, and non-normal distribution data were expressed as M ( Q1, Q3), Spearman correlation analysis was used to analyze the correlation between variables, and P<0.05 was considered statistically significant. Results:①Compared with the mRNA expression levels of ATG12(0.007 6±0.005 9), ATG16(0.003 1±0.002 2) and LC3(0.038 2±0.017 1) before treatment, after 24 weeks treatment with abatacept, the mRNA expression levels of ATG12 (0.011 4±0.003 1) and ATG16 (0.004 2±0.000 7) increased ( t=-2.49, P=0.042; t=-2.15, P=0.038), and the mRNA expression level of LC3 (0.022 6±0.008 3) was decreased ( t=3.28, P=0.003) after 24 weeks of abatacept treatment.②After 24 weeks, the expression level of ATG16 mRNA in the remission group (0.004 8±0.000 8) was higher than that in the non-remission group (0.003 8±0.000 3) ( t=-3.41, P=0.003). The expression level of LC3 mRNA in remission group (0.027 3±0.007 3) was lower than that in non-remission group (0.017 9±0.006 5) ( t=3.69, P=0.017). ③ATG5 mRNA expression level was positively correlated with TJC, ESR and anti-CCP antibody ( r=0.75, P=0.049; r=0.43, P=0.044; r=0.97, P=0.011). The expression level of ATG12 mRNA was negatively correlated with DAS28, ESR and hsCRP ( r=-0.46, P=0.025; r=-0.51, P=0.026; r=-0.41, P=0.031). The expression level of ATG16 mRNA was positively correlated with ESR and hsCRP ( r=0.50, P=0.030; r=0.40, P=0.024). The expression level of Beclin-1 mRNA was significantly higher than TJC, RF-IgG and anti-CCP antibody were negatively correlated ( r=-0.51, P=0.025; r=-0.42, P=0.035; r=-0.81, P=0.043). The expression level of LC-3 mRNA was positively correlated with ESR and hsCRP ( r=0.55, P=0.028; r=0.56, P=0.024). ④Compared with the protein expression level before the treatment, of ATG12 (0.675 3±0.036 3), which (1.547 7±0.080 5) increased after 24 weeks of treatment ( t=-7.80, P=0.001). Compared with the protein expression levels of ATG16 (0.817 1±0.089 0), LC3Ⅱ (0.807 1±0.072 1) and IL-1β (1.129 7±0.118 9) before treatment, 24 weeks after, the protein expression levels of ATG16 (0.424 6±0.103 5), LC3Ⅱ (0.353 7±0.056 9) and IL-1β (0.346 7±0.050 8) decreased ( t=2.62, P=0.042; t=2.88, P=0.045; t=2.25, P=0.038) 24 weeks after treatment. Conclusion:Autophagy related genes is associated with several clinical presentations and disease activity. The results of this study suggest that autophageius are involved in the pathogenesis of RA. Abatacept may be a potential autophage modulator by regulating autophagy related genes including ATG12、ATG16 and LC3.

Objectives:To construct a nomogram prediction model using common preoperative indicators for early weight loss (EWL) 1 year after laparoscopic sleeve gastrectomy (LSG).Methods:Relevant data of obese patients who had undergone LSG from January 2015 to May 2022 in Fujian Medical University Union Hospital and Quanzhou First Hospital Affiliated Fujian Medical University were analyzed. Patients with a history of major abdominal surgery, severe gastroesophageal reflux disease, pregnancy within 1 year after surgery, or who were lost to follow-up were excluded, resulting in a total of 200 patients in the study (190 from Fujian Medical University Union Hospital and 10 from Quanzhou First Hospital Affiliated Fujian Medical University). The participants were 51 men and 149 women of a mean age 29.9±8.2 years and a body mass index (BMI) 38.7±6.5 kg/m 2. All patients in this group underwent standardized LSG procedure. Achieving ideal weight (BMI≤25 kg/m 2) 1 year after LSG was defined as goal of EWL. Logistic regression analyses were performed to identify factors that independently influenced EWL. These factors were incorporated into the nomogram model. Receiver operating characteristic (ROC) curves (the larger the area under the curve [AUC], the better the predictive ability and accuracy of the model), likelihood ratio test (higher likelihood ratio indicates greater model homogeneity), decision curve analysis (higher net benefit indicates a better model), Akaike information criterion (AIC; smaller AIC indicates a better model), and Bayesian information criterion (BIC; smaller BIC indicates a better model) were used to validate the predictive ability of the column line diagram model. Results:In this study of 200 obese patients who underwent LSG surgery, 136 achieved EWL goal, whereas the remaining 64 did not. The rate of EWL goal achievement of the entire group was 68.0%. Compared with patients who did not achieve EWL goal, those who did had lower BMI, alanine transaminase, aspartate transaminase, triglycerides, and higher cholesterol. Additionally, the proportion of female was higher and the proportions of patients with fatty liver and hypertension lower in those who achieved EWL goal (all P<0.05). Univariate and multivariate logistic regression analysis revealed that preoperative BMI (OR=0.852, 95%CI: 0.796-0.912, P<0.001), alanine transaminase (OR=0.992, 95%CI: 0.985-0.999, P=0.024), presence of fatty liver (OR=0.185, 95%CI: 0.038-0.887, P=0.035) and hypertension (OR=0.374, 95%CI: 0.144-0.969, P=0.043) were independently associated with failure to achieve EWL goal. Cholesterol (OR=1.428, 95%CI: 1.052-1.939, P=0.022) was independently associated with achieving EWL goal. We used the above variables to establish an EWL nomogram model. ROC analysis, the likelihood ratio test, decision curve analysis, and AIC all revealed that the predictive value of the model was better than that of BMI alone (nomogram model vs. BMI: area under the curve 0.840 vs. 0.798, P=0.047; likelihood ratio: 58.785 vs. 36.565, AIC: 193.066 vs. 207.063, BIC: 212.856 vs. 213.660). Conclusion:Our predictive model is more accurate in predicting EWL after LSG compared with using BMI.

Objective:To investigate the influencing factors of operation time for laparos-copic sleeve gastrectomy (LSG) and analyze the learning curve of LSG in sarcopenic obesity (SO) and non-sarcopenic obesity (NSO).Methods:The retrospective cohort study was conducted. The clinical data of 240 obesity patients who underwent LSG in the Fujian Medical University Union Hospital from January 2018 to June 2022 were collected. There were 52 males and 188 females, aged (30±8)years. Patients underwent L3 vertebral body horizontal axial computer tomography (CT) scanning before and after receiving LSG to accurately segment muscles and fats. Observation indicators: (1) treatment and follow-up; (2) influencing factors of operation time for LSG; (3) cumulative sum (CUSUM) of learning curve; (4) comparison of clinical data between patients in the initial and profi-cient stages. Measurement data with normal distribution were represent as Mean± SD, and comparison between groups was conducted using the t test. Measurement data with skewed distribution were represented as M(IQR), and comparison between groups was conducted using the non-parameter test. Count data were described as absolute numbers, and comparison between groups was conducted using the chi-square test. Univariate and multivariate analyses were conducted using the Logistic regression model. The CUSUM of learning curve was calculated and the fitting process was conducted on scatter plot of learning curves. Results:(1) Treatment and follow-up. Of the 240 patients, there were 97 cases of SO and 143 cases of NSO. All 240 patients underwent LSG successfully, without conversion to open surgery. The operation time of 240 patients was (108±23)minutes. None of patient died during the perioperative period and all patients underwent follow-up during the postoperative 6 months. (2) Influencing factors of operation time for LSG. Results of multivariate analysis showed that SO was an independent factor influencing operation time for LSG ( odds ratio=2.207, 95% confidence interval as 1.207-4.038, P<0.05). (3) CUSUM of learning curve. Results of CUSUM of operation time in patients of SO and NSO showed that the best fit equation of patients of SO was y=-4E-08x 6+1E-05x 5-0.001 1x 4+0.063 1x 3-1.89x 2+28.126x-48.671 (x means the number of surgical cases), with goodness-of-fit R 2 as 0.833, and the best fit equation of patients of NSO was y=3E-09x 6-1E-06x 5+0.000 2x 4-0.010 9x 3+0.063 8x 2+12.053x-65.025 (x means the number of surgical cases), with goodness-of-fit R 2 as 0.716. Based on the trend of CUSUM of learning curve of operation time, the peak value of number of surgical cases in patients of SO and NSO was 81 and 36, respec-tively, which was used to divide the learning curve as two stages of the initial stage and the proficient stage. (4) Comparison of clinical data between patients in the initial and proficient stages. ① Of the 97 patients of SO, there were 81 cases and 16 cases in the initial stage and the proficient stage of LSG, with the operation time, postoperative duration of hospital stay as (119±23)minutes, (5.9±2.3)days and (106±21)minutes, (4.7±0.5)days, showing significant differences between them ( t=2.074, 2.147, P<0.05). ②Of the 143 patients of NSO, there were 36 cases and 107 cases in the initial stage and the proficient stage of LSG, with gender (female), height, preoperative body mass, defatted body mass, operation time, postoperative duration of hospital stay, body mass at postoperative 6 month, body mass index (BMI) at postoperative 6 month, percentage of excess weight loss (EWL%) at postoperative 6 month, cases with EWL% >100% at postoperative 6 month, excess BMI at post-operative 6 month as 20, (170±10)cm, (110±25)kg, (57±12)kg, (108±22)minutes, (6.1±1.6)days, (80±16)kg, (27.63±4.22)kg/m2, 83%±35%, 9, 1.99(6.03)kg/m2 and 87, (164±8)cm, (99±20)kg, (52±12)kg, (100±19)minutes, (4.7±1.1)days, (71±16)kg, (25.89±4.48)kg/m2, 103%±42%, 48, 0.31(5.82)kg/m2, showing significant differences between them ( χ2=9.484, t=3.266, 2.424, 2.141, 2.137, 5.821, 2.740, 1.993, -2.524, χ2=4.432, Z=-2.300, P<0.05). Conclusions:SO is an independent factor influencing operation time for LSG. It is suggested that the surgeons need to finish 81 cases and 36 cases master LSG in patients of SO and NSO.