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: 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

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

Accurate determination of the thickness of multi-layered nanofilm materials is of great importance to advance the development of thin film deposition technology and ensure the quality assurance of photovoltaic materials.Laser ablation inductively coupled plasma mass spectrometry(LA-ICP-MS)has been successfully employed for depth profiling of thin film materials,such as metal coatings.However,the accuracy of interface discrimination and thin layer thickness measurement is limited by the mixing effects of elemental signals.In this work,a high-depth resolution method for measuring the thin film thickness of lead sulfide(PbS)colloidal quantum dot(CQD)photovoltaic devices by LA-ICP-MS was introduced.The influence of different laser parameters on the mixing effects of element signals during the ablation process was compared,and the results showed that the laser ablation behavior of multi-layered nanofilm materials were improved and the mixing of element signals were reduced by optimizing parameters such as laser energy density and spot diameter.Meanwhile,a self-developed aerosol rapid wash-out small volume tubular ablation cell was used to effectively improve the aerosol transport efficiency,and the wash-out time of aerosol was(1.60±0.6)s.Compared with commercial cylindrical ablation cells,the depth profile of multi-layer thin film samples was clearer.The depth profile of the interlayer interface showed a significant melting phenomenon during the ablation of the PbS CQD layer,leading to severe mixing of elemental signals at the PbS/ZnO layer interface.Under the conditions such as 2.5 J/cm2 laser energy,32 μm spot diameter,and 1 Hz repetition rate,the average ablation rates of Au,PbS and ZnO layers in PbS CQD photovoltaic devices were(60±2)nm/pulse,(69±5)nm/pulse,and(22±2)nm/pulse,with depth resolution of(26±2)nm,(213±11)nm,and(68±6)nm,respectively.The thickness of PbS CQD photovoltaic device films from the same batch was determined,and the test results exhibited good consistency with scanning electron microscope(SEM)measurement values,with a relative deviation of less than 6％.This method could accurately determine the thickness of nanoscale multilayer thin film samples,which was crucial for improving the performance of photovoltaic devices and controlling product quality.

As a Chinese saying goes， "good Chinese medicinal material makes good medicine"， the quality of Chinese herbal medicines is related to the development prospect of Chinese medicine industry in China. With the rapid development of new technologies such as traceability methods and monitoring instruments， it is imperative to integrate and innovate traditional Chinese herbal medicines with new-generation information technology in view of the quality problems existing in the current production and circulation of Chinese herbal medicines， and it is of great significance for the construction of traceability system to ensure the quality and safety of Chinese herbal medicines and to promote the industry of Chinese herbal medicines to move towards high-quality development. This paper reviews the development history of the traceability system of Chinese herbal medicines in China， takes the influencing factors of the quality of Chinese herbal medicines as the entry point， and proposes that the construction of the traceability system should satisfy the traceability requirements of the characteristics of Chinese herbal medicines and their traditional medication experience. By analyzing the influencing factors of the quality of Chinese herbal medicines， it is pointed out that focusing on the influencing factors to build a traceability system is of great significance for targeting the problematic links at a later stage and exploring the interrelationship between environmental factors and the quality of Chinese herbal medicines. Based on the previous explorations， the author summarizes the system framework， functional modules and practical applications of the traceability system of Chinese herbal medicines， and looks forward to the development of a traceability system with risk early warning function and expert decision-making function in its functional development. Finally， based on the factors affecting the quality of Chinese herbal medicines， the author puts forward several thoughts on construction of the traceability system， and makes an in-depth analysis and puts forward a solution for the current situation that a unified， standardized and universal traceability system has not yet been built， with a view to providing ideas and references for the construction of traceability system of Chinese herbal medicines.

Objective To investigate the effects of perineal massage combined with hip joint exercise on the outcome of delivery and mental resilience of primipara.Methods 90 pregnant women in the third trimester(after 36 weeks)who obtained the knowledge about perineal massage from midwife clinic were randomly divided into two groups with 45 cases each.The control group received regular antenatal examination and family self-exercise;the experimental group received perineal massage and hip joint training combined treatment.The delivery outcome,birth experience and maternal mental resilience of the two groups were compared.Results the number of vaginal delivery in the experimental group were higher than that in the control group(P<0.05);the second stage of labor was significantly shorter than that of the control group(P<0.05);the perineal integrity rate was higher than that of the control group(P<0.05);the scores of all dimensions in delivery experience questionnaire were higher than that of the control group(P<0.05);the scores of all dimensions in maternal mental resilience were higher than those of the control group(P<0.05)after intervention.Conclusion The perineal massage which conducted by midwives combined with hip movement can effectively improve the quality of delivery,relieve the negative emotions of pregnant women,improve the psychological elasticity level of pregnant women,and improve the delivery outcomes.

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.