Objective To explore the characteristics and correlation between perivascular spaces (PVS) and diffusion tensor image analysis along perivascular spaces (DTI-ALPS) index in patients with amnestic mild cognitive impairment (aMCI). Methods A retrospective study was conducted on a total of 118 participants, including cognitive normal (CN) healthy controls and aMCI patients, recruited from the Department of Neurology, Zhongshan Hospital, Fudan University from September 2020 to September 2022. All participants underwent structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). An automatic segmentation algorithm was used to quantify PVS metrics in the brain, and DTI-ALPS index was calculated based on DTI. Differences in DTI-ALPS index and PVS metrics between the CN and aMCI groups were compared. Multivariate logistic regression was used to identify independent factors influencing aMCI. Correlation analysis was performed to assess relationships among DTI-ALPS index, PVS metrics, and cognitive scores. Results A total of 80 CN healthy controls and 38 aMCI patients were included. The DTI-ALPS index was significantly lower in the aMCI group compared with the CN group (1.28±0.18 vs 1.37±0.21, P＝0.018), while differences in PVS metrics between groups were not statistically significant. Multivariate logistic regression analysis indicated that DTI-ALPS index was an independent factor affecting aMCI (OR＝0.097, 95%CI 0.011–0.833, P＝0.033). Correlation analysis revealed a positive relationship between DTI-ALPS index and MMSE score (r＝0.210, P＝0.023) as well as PVS length in the centrum semiovale (r＝0.216, P＝0.019). Conclusions The DTI-ALPS index may serve as an imaging biomarker for identifying early cognitive impairment, and patients with aMCI exhibit abnormal DTI-ALPS indices, suggesting that brain glymphatic system dysfunction may occur prior to morphological changes.

Objective: Data on syncopal donation-related vasovagal reaction (DRVR) collected from 74 blood centers between 2020 and 2023 was statistically analyzed to provide a reference for developing preventive strategies against syncopal DRVR. Methods: Data on blood donation adverse reactions and basic information of donors from 2020 to 2023 were collected through the information management system at monitoring sentinel sites. Statistical analysis was performed on the following aspects of syncopal DRVR: characteristics of donors who experienced syncope, reported incidence, triggers, duration, presence and occurrence time of syncope-related trauma, clinical management including outpatient and inpatient treatment, and severity grading. Results: From 2020 to 2023, 45 966 donation-related adverse reactions were recorded. Of these, 1 665 (3.72%) cases were syncopal DRVR. The incidence of syncopal DRVR decreased with age, being the highest in the 18-22 age group. Incidence was significantly higher in female donors than male donors, in first-time donors than repeat donors, and in university and individual donors than group donors (all P<0.05). There was no statistically significant difference among different blood donation locations (P>0.05). The top three triggers were tension, fatigue, and needle phobia or fear of blood. Among syncopal DRVR cases, 60.36% occurred during blood collection, 87.63% lasted for less than 60 seconds, and 5.05% were accompanied by trauma. Notably, 57.14% of these traumas occurred after donor had left the blood collection site. Syncope severity was graded based on required treatment: grade 1 (fully recovered without treatment, 95.50%); grade 2 (recovered after outpatient treatment, 4.02%); and grade 3 (recovered after inpatient treatment, 0.48%). Conclusion: By analyzing the data of syncopal DRVR cases, it is possible to provide a reference for formulating blood donor safety policies.

Membrane protein degradation is a cutting-edge field in targeted protein degradation (TPD). Herein, we developed glypican-3 (GPC3)-mediated lysosome-targeting chimeras (GLTACs) as a novel strategy for the targeted degradation of tumor-specific membrane proteins. GLTACs utilize tumor-specific expression and endocytosis properties of GPC3 to degrade membrane proteins. By conjugating a GPC3-targeting peptide with the ligand of protein of interest (POI), GLTACs induce the formation of a ternary complex that is internalized into lysosomes, leading to the degradation of the POI. The effectiveness and specificity of GLTACs were validated by designing PD-L1, c-Met, and FGFR1 degraders. In particular, GLTAC WP0 potently degraded PD-L1 and induced T-cell-mediated tumor killing against HepG2 cells, highlighting the potential therapeutic applications. The development of GLTAC technology expands the scope of TPD strategies and opens new avenues for discovering novel therapeutic modalities against challenging protein targets.

Objective:To assess the efficacy and safety profile of antaitasvir phosphate combined with yiqibuvir in the treatment of chronic hepatitis C (CHC) of various genotypes, without cirrhosis or with compensated cirrhosis.Methods:394 cases with CHC from 22 centers were collected from October 2021 to April 2023. They were randomly assigned to receive either the experimental drugs (antaitasvir phosphate 100 mg+yiqibuvir 600 mg) or placebo treatment in a 3∶1 ratio. The patients were administered drugs once a day for 12 consecutive weeks, and then followed up for 24 weeks after treatment cessation. All subjects were unblinded at the four-week follow-up following drug discontinuation, with the experimental drug group continuing to complete subsequent post-discontinuation follow-up. The placebo group was switched to receive the experimental drugs for a repeated 12-week treatment period and followed up for another 24 weeks after discontinuation of the drug (placebo delayed treatment phase).The sustained virologic response rate (SVR12) was observed for subjects in the double-blind phase and the placebo delayed-treatment phase at 12 weeks after treatment cessation.Virological resistance analysis was performed on subjects who failed treatment. The primary efficacy endpoint was SVR12. The number and percentage of subjects who achieved "HCV RNA

BACKGROUND:Understanding the characteristics and influencing factors of the gut microbiota in athletes can help determine the optimal gut microbial composition for relevant sport events.Further investigation in this area could provide important insights for improving athletic performance and recovery as well as developing personalized nutrition prescriptions.OBJECTIVE:To summarize the characteristics of gut microbiota in athletes,and to elucidate the important factors influencing the gut microbiota characteristics of athletes from the perspectives of exercise training and dietary intake.METHODS:A literature search was conducted using the PubMed,ScienceDirect,CNKI,WanFang and VIP databases for publications from 2004 to 2024.The search terms included"microbiota,microbiome,athlete,exercise,training,diet,nutrition,dietary fiber,protein,ketogenic,fat"in English and Chinese.After excluding studies of poor quality and irrelevant content,a total of 65 articles were included for review and analysis.RESULTS AND CONCLUSION:(1)The gut microbiota of elite athletes differs from that of the general population,characterized by increased α-diversity,elevated Firmicutes/Bacteroidetes ratio,increased abundance of beneficial bacteria,and enrichment of functional pathways contributing to athletic performance.(2)The type of sport and training load are closely related to the species structure and functional expression of the gut microbiota in athletes.(3)The bidirectional communication between the host and gut microbiota mediated by metabolites is an important mechanism by which exercise influences the gut microbiota.(4)Phase training typically induces adaptive changes in the gut microbiota,and alterations in the structure or function of the microbiota have lasting effects.(5)The type,quantity,and combination of macronutrients intake can significantly influence the structure and function of the gut microbiota,and interact synergistically or antagonistically with exercise training.(6)In the future,it is important to continue the exploration of the gut microbiota in athletes,clarify causal relationships,and establish new targets for exercise training interventions.

OBJECTIVE To provide help for further exploring the mechanism of action of traditional Chinese herb by constructing a complex network of traditional Chinese herb-gene-protein,optimizing the mining method of potential associated genes of traditional Chinese herb and improving the mining efficiency of traditional Chinese herb system biology information.METHODS A graph neural network model HERBGAT with an attention mechanism was proposed.A small amount of traditional Chinese herb-related gene data in the public data platform was used as input,and deep mining was performed in the traditional Chinese herb-gene-protein complex net-work to output potential traditional Chinese herb-related genes.The prediction results were analyzed by disease association analysis and KEGG signaling pathway analysis on the bioinformatics platform to clarify their mechanism of action,and the prediction results were verified by the literature retrieval platform.RESULTS The training results showed that the average prediction accuracy of the HERB-GAT model could reach 94%.Compared with the other two advanced complex network mining methods,HERBGAT showed better per-formance in the three indicators of ACC,AUC and AUPR.In the literature verification stage,the model prediction results were verified by TCM clinical literature and modern pharmacology literature,showing the good effect of HERBGAT in practical application.At the end of this paper,taking the HERBGAT model and the improved EMOGI model to explore the mechanism of action of Pinellia ternata in treating lung cancer as an example,199 potential associated genes of Pinellia ternata in treating lung cancer were found,and these potential associated genes were preliminarily analyzed and discussed with the help of bioinformatics methods.CONCLUSION The HERBGAT model can effectively mine potential traditional Chinese herb-associated genes,improve the mining efficiency of traditional Chinese herb-gene-protein complex networks,provide new ideas and references for the optimization of traditional Chinese herb system biology information mining methods,and provide data basis and experimental direction for exploring the mechanism of action of tradi-tional Chinese herb.

OBJECTIVE To provide help for further exploring the mechanism of action of traditional Chinese herb by constructing a complex network of traditional Chinese herb-gene-protein,optimizing the mining method of potential associated genes of traditional Chinese herb and improving the mining efficiency of traditional Chinese herb system biology information.METHODS A graph neural network model HERBGAT with an attention mechanism was proposed.A small amount of traditional Chinese herb-related gene data in the public data platform was used as input,and deep mining was performed in the traditional Chinese herb-gene-protein complex net-work to output potential traditional Chinese herb-related genes.The prediction results were analyzed by disease association analysis and KEGG signaling pathway analysis on the bioinformatics platform to clarify their mechanism of action,and the prediction results were verified by the literature retrieval platform.RESULTS The training results showed that the average prediction accuracy of the HERB-GAT model could reach 94%.Compared with the other two advanced complex network mining methods,HERBGAT showed better per-formance in the three indicators of ACC,AUC and AUPR.In the literature verification stage,the model prediction results were verified by TCM clinical literature and modern pharmacology literature,showing the good effect of HERBGAT in practical application.At the end of this paper,taking the HERBGAT model and the improved EMOGI model to explore the mechanism of action of Pinellia ternata in treating lung cancer as an example,199 potential associated genes of Pinellia ternata in treating lung cancer were found,and these potential associated genes were preliminarily analyzed and discussed with the help of bioinformatics methods.CONCLUSION The HERBGAT model can effectively mine potential traditional Chinese herb-associated genes,improve the mining efficiency of traditional Chinese herb-gene-protein complex networks,provide new ideas and references for the optimization of traditional Chinese herb system biology information mining methods,and provide data basis and experimental direction for exploring the mechanism of action of tradi-tional Chinese herb.

BACKGROUND:Understanding the characteristics and influencing factors of the gut microbiota in athletes can help determine the optimal gut microbial composition for relevant sport events.Further investigation in this area could provide important insights for improving athletic performance and recovery as well as developing personalized nutrition prescriptions.OBJECTIVE:To summarize the characteristics of gut microbiota in athletes,and to elucidate the important factors influencing the gut microbiota characteristics of athletes from the perspectives of exercise training and dietary intake.METHODS:A literature search was conducted using the PubMed,ScienceDirect,CNKI,WanFang and VIP databases for publications from 2004 to 2024.The search terms included"microbiota,microbiome,athlete,exercise,training,diet,nutrition,dietary fiber,protein,ketogenic,fat"in English and Chinese.After excluding studies of poor quality and irrelevant content,a total of 65 articles were included for review and analysis.RESULTS AND CONCLUSION:(1)The gut microbiota of elite athletes differs from that of the general population,characterized by increased α-diversity,elevated Firmicutes/Bacteroidetes ratio,increased abundance of beneficial bacteria,and enrichment of functional pathways contributing to athletic performance.(2)The type of sport and training load are closely related to the species structure and functional expression of the gut microbiota in athletes.(3)The bidirectional communication between the host and gut microbiota mediated by metabolites is an important mechanism by which exercise influences the gut microbiota.(4)Phase training typically induces adaptive changes in the gut microbiota,and alterations in the structure or function of the microbiota have lasting effects.(5)The type,quantity,and combination of macronutrients intake can significantly influence the structure and function of the gut microbiota,and interact synergistically or antagonistically with exercise training.(6)In the future,it is important to continue the exploration of the gut microbiota in athletes,clarify causal relationships,and establish new targets for exercise training interventions.

Objective:To assess the efficacy and safety profile of antaitasvir phosphate combined with yiqibuvir in the treatment of chronic hepatitis C (CHC) of various genotypes, without cirrhosis or with compensated cirrhosis.Methods:394 cases with CHC from 22 centers were collected from October 2021 to April 2023. They were randomly assigned to receive either the experimental drugs (antaitasvir phosphate 100 mg+yiqibuvir 600 mg) or placebo treatment in a 3∶1 ratio. The patients were administered drugs once a day for 12 consecutive weeks, and then followed up for 24 weeks after treatment cessation. All subjects were unblinded at the four-week follow-up following drug discontinuation, with the experimental drug group continuing to complete subsequent post-discontinuation follow-up. The placebo group was switched to receive the experimental drugs for a repeated 12-week treatment period and followed up for another 24 weeks after discontinuation of the drug (placebo delayed treatment phase).The sustained virologic response rate (SVR12) was observed for subjects in the double-blind phase and the placebo delayed-treatment phase at 12 weeks after treatment cessation.Virological resistance analysis was performed on subjects who failed treatment. The primary efficacy endpoint was SVR12. The number and percentage of subjects who achieved "HCV RNA

Objective To retrospectively analyze of factors influencing early preterm birth(EPB)and late preterm birth(LPB)in pregnancy women with placenta previa complicated by placenta accreta spectrum disorders(PAS),and assess maternal and infant outcomes.Methods We included 590 cases of pregnancy women with placenta previa complicated by PAS who underwent cesarean sections at five hospitals in Wuhan and Xianning cities between January 2018 and June 2021.These patients were divided into three groups based on delivery gesta-tional age:EPB,LPB,and term birth(TB).A multiple logistic regression model was employed to analyze the risk factors associated with EPB and LPB.Additionally,differences in early maternal and infant outcomes among these groups were examined.Results Among 590 pregnancy women with placenta previa complicated by PAS,the proportions of EPB and LPB were 9.7%and 54.4%.The use of uterine contraction inhibitors prior to cesarean section,vaginal bleeding,and previous cesarean sections history were identified as risk factors for both EPB and LPB.The proportion of severe postpartum hemorrhage was comparable between the EPB group and the LPB group;however,the incidence of neonatal asphyxia,low birth weight infants,and the rate of newborns transferred to the Neonatal Intensive Care Unit(NICU)within 24 hours after cesarean delivery were significantly higher in the EPB group compared to the LPB group.Conclusions Placenta previa complicated by PAS predominantly leads to LPB.The history of prior cesarean sections,uterine contractions,and vaginal bleeding prior to cesarean section,are sig-nificantly associated with both EPB and LPB.During the perinatal period,efforts should be made to extend gesta-tional weeks under close monitoring to minimize the incidence of premature births and thereby improve early mater-nal and infant outcomes.