Thalidomide (THA) is renowned for its potent anti-inflammatory properties. This study aimed to elucidate its underlying mechanisms in the context of Crohn's disease (CD) development. Mouse colitis models were established by dextran sulfate sodium (DSS) treatment. Fecal microbiota and metabolites were analyzed by metagenomic sequencing and mass spectrometry, respectively. Antibiotic-treated mice served as models for microbiota depletion and transplantation. The expression of forkhead box P3⁺ (FOXP3⁺) regulatory T cells (Tregs) was measured by flow cytometry and immunohistochemical assay in colitis model and patient cohort. THA inhibited colitis in DSS-treated mice by altering the gut microbiota profile, with an increased abundance of probiotics Bacteroides fragilis, while pathogenic bacteria were depleted. In addition, THA increased beneficial metabolites bile acids and significantly restored gut barrier function. Transcriptomic profiling revealed that THA inhibited interleukin-17 (IL-17), IL-1β and cell cycle signaling. Fecal microbiota transplantation from THA-treated mice to microbiota-depleted mice partly recapitulated the effects of THA. Specifically, increased level of gut commensal B. fragilis was observed, correlated with elevated levels of the microbial metabolite 3alpha-hydroxy-7-oxo-5beta-cholanic acid (7-ketolithocholic acid, 7-KA) following THA treatment. This microbial metabolite may stable FOXP3 expression by targeting the receptor FMR1 autosomal homolog 1 (FXR1) to inhibit autophagy. An interaction between FOXP3 and FXR1 was identified, with binding regions localized to the FOXP3 domain (aa238-335) and the FXR1 domain (aa82-222), respectively. Conclusively, THA modulates the gut microbiota and metabolite profiles towards a more beneficial composition, enhances gut barrier function, promotes the differentiation of FOXP3⁺ Tregs and curbs pro-inflammatory pathways.

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

OBJECTIVE: To analyze the distribution characteristics of glucose-6-phosphate-dehydrogenase (G6PD) mutations and their enzyme activity in newborns patients with G6PD deficiency in Guilin region. METHODS: From July 2022 to July 2024, umbilical cord blood samples from 4 554 newborns in Guilin were analyzed for G6PD mutations using fluorescence PCR melting curve analysis. Enzyme activity was detected in 4 467 cases using the rate assay. RESULTS: Among 4 467 newborns who underwent G6PD activity testing, 162 newborns (3.63%) were identified as G6PD-deficient, including 142 males (6.04%) and 20 females (0.94%), the prevalence of G6PD deficiency was significantly higher in males than in females (P < 0.001). Genetic analysis of 4 554 newborns detected G6PD mutations in 410 cases (9%), including 171 males (7.13%) and 239 females (11.09%), with a significantly higher mutation detection rate in females than in males (P < 0.001). A total of nine single mutations and four compound heterozygous mutations were identified. The most common mutations were c.1388G>A (33.66%), c.1376G>T (23.66%) and c.95A>G (16.34%). Among newborns who underwent both enzyme activity and genetic mutation testing, males with G6PD mutations had significantly lower enzyme activity than that of females with G6PD mutations(P < 0.001). Specifically, among newborns carrying the mutations c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T or c.871G>A, males consistently exhibited lower enzymatic activity than females with the same mutations (P < 0.001). Furthermore, in male G6PD-deficient newborns, the enzyme activity levels in those carrying c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T, or c.871G>A were lower than those in both the control group and the c.519C>T group (P < 0.05). CONCLUSION This study provides a comprehensive profile of G6PD deficiency incidence and mutation spectrum in the Guilin region. By analyzing enzyme activity and genetic mutation results, this study provides insights into potential intervention strategies and personalized management approaches for the prevention and treatment of neonatal G6PD deficiency in the region.
Humans ; Infant, Newborn ; Glucosephosphate Dehydrogenase Deficiency/epidemiology* ; Glucosephosphate Dehydrogenase/genetics* ; Female ; Male ; Mutation ; China/epidemiology*

Objective:To compare the differences in the evaluation of hemolysis performance of cellulose hemostatic materials using different detection methods and test media,and to explore a m ore reasonable testing plan for such products.Methods:Hemolysis tests were conducted on cellulose hemostatic materials using the absorbance measurement hemolysis method and hemoglobin concentration measurement hemolysis method in accordance with YY/T 1651.1-2019 standard.We compared the changes in hemolysis rate,pH value,and osmotic pressure under different experimental media.Results:Under the same experimental method,compared to SC,the hemolysis results using PBS as the extraction medium are smaller,and the changes in pH and osmotic pressure are closer to the normal range of human body changes.Conclusions:The changes in pH and osmotic pressure may be one of the reasons for the high hemolysis rate of cellulose hemostatic materials.Choosing PBS with buffering effect as the leaching medium may be more suitable for evaluating the hemolysis performance of cellulose hemostatic materials.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Thalidomide(THA)is renowned for its potent anti-inflammatory properties.This study aimed to eluci-date its underlying mechanisms in the context of Crohn's disease(CD)development.Mouse colitis models were established by dextran sulfate sodium(DSS)treatment.Fecal microbiota and metabolites were analyzed by metagenomic sequencing and mass spectrometry,respectively.Antibiotic-treated mice served as models for microbiota depletion and transplantation.The expression of forkhead box P3+(FOXP3+)regulatory T cells(Tregs)was measured by flow cytometry and immunohistochemical assay in colitis model and patient cohort.THA inhibited colitis in DSS-treated mice by altering the gut microbiota profile,with an increased abundance of probiotics Bacteroides fragilis,while pathogenic bacteria were depleted.In addition,THA increased beneficial metabolites bile acids and significantly restored gut barrier function.Transcriptomic profiling revealed that THA inhibited interleukin-17(IL-17),IL-1β and cell cycle signaling.Fecal microbiota transplantation from THA-treated mice to microbiota-depleted mice partly recapitulated the effects of THA.Specifically,increased level of gut commensal B.fragilis was observed,correlated with elevated levels of the microbial metabolite 3alpha-hydroxy-7-oxo-5beta-cholanic acid(7-ketolithocholic acid,7-KA)following THA treatment.This microbial metabolite may stable FOXP3 expression by targeting the receptor FMR1 autosomal homolog 1(FXR1)to inhibit auto-phagy.An interaction between FOXP3 and FXR1 was identified,with binding regions localized to the FOXP3 domain(aa238-335)and the FXR1 domain(aa82-222),respectively.Conclusively,THA modu-lates the gut microbiota and metabolite profiles towards a more beneficial composition,enhances gut barrier function,promotes the differentiation of FOXP3+Tregs and curbs pro-inflammatory pathways.

Liver failure （LF） is a severe clinical syndrome characterized by severe impairment or decompensation of liver function. At present， the key role of immune molecules in the pathogenesis of LF has been well established. These molecules not only directly participate in the pathological process of LF， but also influence the course of LF by modulating the behavior of immune cells. In addition， immune molecules can be used as potential biomarkers for evaluating the prognosis of LF. This article summarizes the role of immune molecules in LF and explores the therapeutic strategies based on these immune molecules， in order to provide new directions for the diagnosis and treatment of LF.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To investigate the role of the neutrophil-to-lymphocyte ratio(NLR)in predicting the in-hospital mortality risk of patients with acute aortic dissection(AAD)in multicenter hospitals.Methods A multicenter retrospective cohort study was conducted.Clinical data were collected from 2642 AAD patients who were hospitalized in five teaching hospitals:Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology,Henan Provincial People's Hospital,Fuwai Central China Cardiovascular Hospital,the Third Affiliated Hospital of Xinxiang Medical University,and the Second Affiliated Hospital of Chongqing Medical University between August 2010 and December 2021.According to the quartiles of serum NLRlevels,the patients were divided into four groups:first quartile(Q1,n=660),second quartile(Q2,n=661),third quartile(Q3,n=661),and fourth quartile(Q4,n=660).The clinical characteristics and biochemical indicators of each group were compared.Partial correlation analysis was used to assess the relationship between NLR and cardiovascular parameters.Restricted cubic splines,Kaplan-Meier survival analysis,and Cox regression models were employed to evaluate the association between NLR levels and in-hospital mortality risk in AAD patients.Results The median age of all patients was 54[interquartile range(IQR):46-63]years,including 2096 males and 546 females.Compared with Q1-Q3 groups,patients inQ4group had a lower incidence of smoking history and diabetes history,and were more likely to have DeBakey type Ⅰ AAD(P＜0.05).Additionally,the levels of aspartate aminotransferase,high-density lipoprotein cholesterol,creatinine,and D-dimer in Q4 group were higher,while the levels of triglycerides and C-reactive protein(CRP)were lower(P＜0.01).The results of partial correlation analysis showed that the plasma NLR level was positively correlated with D-dimer(r=0.43,P＜0.01)and creatinine(r=0.16,P＜0.01).The restricted cubic spline function in the Cox model revealed a significant non-linear relationship between the plasma NLR level and clinical outcomes in AAD patients(P＜0.01).Kaplan-Meier survival analysis indicated that patients in Q4 group had the highest in-hospital mortality rate compared with Q1-Q3 groups(P＜0.0001).Furthermore,multivariate Cox regression analysis demonstrated that compared with Q1 group,the hazard ratio(HR)of NLR in Q4 group was 1.77(95％CI 1.33-2.37,P＜0.001),which was an independent risk factor for the primary endpoint events.Conclusion A higher plasma NLR level is significantly associated with the occurrence of cardiovascular events in AAD patients,and this association remains significant even after adjusting for potential confounding factors such as the multicenter visiting hospitals.