OBJECTIVE: Exposure to polycyclic aromatic hydrocarbons (PAHs) or metal(loid)s individually has been associated with neural tube defects (NTDs). However, the impacts of PAH and metal(loid) co-exposure and potential interaction effects on NTD risk remain unclear. We conducted a case-control study in China among population with a high prevalence of NTDs to investigate the combined effects of PAH and metal(loid) exposures on the risk of NTD. METHODS: Cases included 80 women who gave birth to offspring with NTDs, whereas controls were 50 women who delivered infants with no congenital malformations. We analyzed the levels of placental PAHs using gas chromatography and mass spectrometry, PAH-DNA adducts with ³²P-post-labeling method, and metal(loid)s with an inductively coupled plasma mass spectrometer. Unconditional logistic regression was employed to estimate the associations between individual exposures and NTDs. Least absolute shrinkage and selection operator (LASSO) penalized regression models were used to select a subset of exposures, while additive interaction models were used to identify interaction effects. RESULTS: In the single-exposure models, we found that eight PAHs, PAH-DNA adducts, and 28 metal(loid)s were associated with NTDs. Pyrene, selenium, molybdenum, cadmium, uranium, and rubidium were selected through LASSO regression and were statistically associated with NTDs in the multiple-exposure models. Women with high levels of pyrene and molybdenum or pyrene and selenium exhibited significantly increased risk of having offspring with NTDs, indicating that these combinations may have synergistic effects on the risk of NTDs. CONCLUSION Our findings suggest that individual PAHs and metal(loid)s, as well as their interactions, may be associated with the risk of NTDs, which warrants further investigation.
Humans ; Neural Tube Defects/chemically induced* ; Polycyclic Aromatic Hydrocarbons/adverse effects* ; Female ; Case-Control Studies ; China/epidemiology* ; Adult ; Pregnancy ; Environmental Pollutants ; Maternal Exposure/adverse effects* ; Metals/toxicity* ; Young Adult ; Risk Factors

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Objective To develop an intelligent model for differential diagnosis of atrioventricular nodal re-entrant tachycardia(AVNRT)and atrioventricular re-entrant tachycardia(AVRT)using 12-lead wearable electrocardiogram devices.Methods A total of 356 samples of 12-lead supraventricular tachycardia(SVT)electrocardiograms recorded by wearable devices were randomly divided into training and validation sets using 5-fold cross validation to establish the intelligent classification model,and 101 patients with the diagnosis of SVT undergoing electrophysiological studies and radiofrequency ablation from October,2021 to March,2023 were selected as the testing set.The changes in electrocardiogram parameters before and during induced tachycardia were compared.Based on multiscale deep neural network,an intelligent diagnosis model for classifying SVT mechanisms was constructed and validated.The 3-lead electrocardiogram signals from Ⅱ,Ⅲ,and V1 were extracted to build new classification models,whose diagnostic efficacy was compared with that of the 12-lead model.Results Of the 101 patients with SVT in the testing set,68 were diagnosed with AVNRT and 33 were diagnosed with AVRT by electrophysiological study.The pre-trained model achieved a high area under the precision-recall curve(0.9492)and F1 score(0.8195)for identifying AVNRT in the validation set.The total F1 scores of the lead Ⅱ,Ⅲ,V1,3-lead and 12-lead intelligent diagnostic models in the testing set were 0.5597,0.6061,0.3419,0.6003 and 0.6136,respectively.Compared with the 12-lead classification model,the lead-Ⅲ model had a net reclassification index improvement of-0.029(P=0.878)and an integrated discrimination index improvement of-0.005(P=0.965).Conclusion The intelligent diagnostic model based on multiscale deep neural network using wearable electrocardiogram devices has an acceptable accuracy for classifying SVT mechanisms.

Objective:To evaluate the efficacy and safety of antaitasvir phosphate 100 mg or 200 mg combined with yiqibuvir for 12 weeks in patients with various genotypes of chronic hepatitis C, without cirrhosis or compensated stage cirrhosis.Methods:Patients with chronic hepatitis C (without cirrhosis or compensated stage cirrhosis) were randomly assigned to the antaitasvir phosphate 100 mg+yiqibuvir 600 mg group (100 mg group) or the antaitasvir phosphate 200 mg+yiqibuvir 600 mg group (200 mg group) in a 1∶1 ratio. The drugs were continuously administered once a day for 12 weeks and observed for 24 weeks after drug withdrawal. The drug safety profile was assessed concurrently with the observation of the sustained virological response (SVR12) in the two patient groups 12 weeks following the drug cessation. The intention-to-treat concept was used to define as closely as possible a full analysis set, including all randomized cases who received the experimental drug at least once. The safety set was collected from all subjects who received the experimental drug at least once (regardless of whether they participated in the randomization group) in this study. All efficacy endpoints and safety profile data were summarized using descriptive statistics. The primary efficacy endpoint was SVR12. The primary analysis was performed on a full analysis set. The frequency and proportion of cases were calculated in the experimental drug group (antaitasvir phosphate capsules combined with yiqibuvir tablets) that achieved "HCV RNA

Objective To establish the finite element model of spinal canal reconstruction and internal fixation,analysis influence of spinal canal reconstruction and internal fixation on spinal stability,and verify the effectiveness and reliability of spinal canal reconstruction and internal fixation in spinal canal surgery.Methods A 30-year-old male healthy volunteer with a height of 172 cm and weight of 75 kg was selected and his lumbar CT data were collected to establish a finite element model of normal lumbar Lo3-L,and the results were compared with in vitro solid results and published finite element analysis results to verify the validity of the model.They were divided into normal group,laminectomy group and spinal canal reconstruction group according to different treatment methods.Under the same boundary fixation and physiological load conditions,six kinds of ac-tivities were performed,including forward bending,backward extension,left bending,right bending,left rotation and right rota-tion,and the changes of range of motion(ROM)of L3-L4,L4-L5 segments and overall maximum ROM of L3-L5 were analyzed under the six conditions.Results The ROM displacement range of each segment of the constructed L3-L5 finite element model was consistent with the in vitro solid results and previous literature data,which confirms the validity of the model.In L3-L4,ROM of spinal canal reconstruction group was slightly increased than that of normal group during posterior extension(＞5％dif-ference),and ROM of other conditions was similar to that of normal group(＜5％difference).ROM in laminectomy group was significantly increase than that in normal group and spinal canal reconstruction group under the condition of flexion,extension,left and right rotation.In L4-L5,ROM in spinal canal reconstruction group was similar to that in normal group(＜5％differ-ence),while ROM in laminectomy group was significantly higher than that in normal group and spinal canal reconstruction group(＞5％difference).In the overall maximum ROM of L3-L5,spinal canal reconstruction group was only slightly higher than normal group under the condition of posterior extension(＞5％difference),while laminectomy was significantly higher than normal group and spinal canal reconstruction group under the condition of anterior flexion,posterior extension,left and right rotation(＞5％difference).The changes of each segment ROM and overall ROM of L3-L5 showed laminectomy group＞spinal canal reconstruction group＞normal group.Conclusion Laminectomy could seriously affect biomechanical stability of the spine,but application of spinal canal reconstruction and internal fixation could effectively reduce ROM displacement of the responsi-ble segment of spine and maintain its biomechanical stability.

Objective:To explore expression and prognostic value of oncostatin M(OSM)in endometrial cancer and to analyze relationship between OSM expression and immune cell infiltration in endometrial cancer tissues.Methods:OSM expression in pan-can-cer was analyzed by TIMER database,OSM expression in endometrial cancer and normal tissues was compared,and survival analysis for patients with different OSM expression was performed;relationship between OSM expression and immune cell infiltration was analyzed by TIMER and TISIDB,and ssGSEA algorithm was used to calculate difference in abundance of immune cell infiltration in samples with different OSM expression;GSEA software was applied to perform enrichment analysis;clinical tissue samples were collected for validation.Results:OSM expression was higher in endometrial cancer tissues than that in normal endometrial tissues(P=4.1e-28),and endometrial cancer patients with high OSM expression had prolonged recurrence-free survival(RFS)(P=0.004 8).OSM expression was positively correlated with abundance of immune cell infiltration and genetic markers of immune cells(P<0.05).OSM was mainly enriched in immune-related signaling pathways.OSM expression was higher in endometrial cancer tissues than normal and atypical hyperplastic tissues(P=0.016 9).Proportions of immune cell markers CD4,CD8,and CD68 were increased in tumor tissues with high OSM expression(all P<0.05),which were positively correlated with OSM expression.Conclusion:OSM is highly expressed in endometrial cancer tissues and correlated with prognosis;OSM expression is positively correlated with immune cell infiltration level and can be used as a biomarker for immunotherapy and prognosis.

Objective:To investigate the clinical characteristics of patients with hemophagocytic lymphohistiocytosis(HLH)and quantify the diagnostic value of various indexes in patients with elevated soluble interleukin-2 receptor(sCD25),so as to construct a diagnostic prediction model of HLH.Methods:The clinical characteristics of 121 patients with elevated sCD25(≥ 2 400 U/ml)in the Third Affiliated Hospital of Sun Yat-Sen University were analyzed retrospectively.The patients were divided into HLH group and non-HLH group according to the diagnostic criteria of HLH.The patients with HLH were divided into infection group,tumor group,macrophage activation syndrome(MAS)group and unknown etiology group according to their etiology.The basic data and treatment of the patients were collected for univariate and multivariate logistic analysis to establish a diagnostic prediction model of HLH.Results:Among the 121 enrolled patients with elevated sCD25,68 were diagnosed as HLH.The proportion of patients using vasopressors,the incidence rate of disseminated intravascular coagulation(DIC),and the HScore in the HLH group were higher than those in the non-HLH group(P＜0.05).Hepatomegaly,splenomegaly,and hemophagocytosis were more common in HLH patients(P＜0.05).Compared with the patients in non-HLH group,patients in HLH group had lower levels of neutrophils,platelets,fibrinogen,IgG,and IgM,while the levels of triglycerides,ferritin(FER),sCD25,serum glutamic oxaloacetic transaminase(SGOT),alkaline phosphatase(ALP),total bilirubin(TBil),lactate dehydrogenase(LDH),and D-dimer were higher(P＜0.05).In subgroup analysis,the level of sCD25 in tumor group was higher than that in infection group.The level of sCD25/ferritin in tumor group was higher than that in infection group and MAS group.Compared with HLH patients in the tumor group,the procalcitonin(PCT)level,proportion of patients using vasopressors,positive rate of hemophagocytosis,and incidence rate of DIC were all higher in the infection group,and the differences were statistically significant(P＜0.05).The results of multivariate analysis showed that fever,splenomegaly,hemophagocytosis,cytopenias,IgM,M.sCD25[multiple of sCD25 detection value relative to the diagnostic threshold(2400 U/ml)],fibrinogen,and triglycerides were independent predictive factors for HLH(P＜0.05).The diagnostic prediction model H constructed based on temperature,splenomegaly,hemophagocytosis,cytopenias,IgM,M.sCD25,fibrinogen,triglycerides showed good predictive accuracy.The optimal cutoff value of H was 39.45,the sensitivity of the model was 94.12％,the specificity was 83.02％.Conclusion:sCD25,sCD25/FER,PCT,hemophagocytosis,hemodynamic instability and DIC could help to distinguish the underlying etiology of HLH.The prediction model H has high discrimination and calibration,which could be used as a relatively accurate clinical diagnostic tool for HLH.