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.

Humans ; Consensus ; Hypersensitivity ; Desensitization, Immunologic/adverse effects* ; Immunotherapy/adverse effects* ; Injections, Subcutaneous ; Allergens

Brain functional network changes over time along with the process of brain development, disease, and aging. However, most of the available measurements for evaluation of the difference (or similarity) between the individual brain functional networks are for charactering static networks, which do not work with the dynamic characteristics of the brain networks that typically involve a long-span and large-scale evolution over the time. The current study proposes an index for measuring the similarity of dynamic brain networks, named as dynamic network similarity (DNS). It measures the similarity by combining the "evolutional" and "structural" properties of the dynamic network. Four sets of simulated dynamic networks with different evolutional and structural properties (varying amplitude of changes, trend of changes, distribution of connectivity strength, range of connectivity strength) were generated to validate the performance of DNS. In addition, real world imaging datasets, acquired from 13 stroke patients who were treated by transcranial direct current stimulation (tDCS), were used to further validate the proposed method and compared with the traditional similarity measurements that were developed for static network similarity. The results showed that DNS was significantly correlated with the varying amplitude of changes, trend of changes, distribution of connectivity strength and range of connectivity strength of the dynamic networks. DNS was able to appropriately measure the significant similarity of the dynamics of network changes over the time for the patients before and after the tDCS treatments. However, the traditional methods failed, which showed significantly differences between the data before and after the tDCS treatments. The experiment results demonstrate that DNS may robustly measure the similarity of evolutional and structural properties of dynamic networks. The new method appears to be superior to the traditional methods in that the new one is capable of assessing the temporal similarity of dynamic functional imaging data.
Aging/physiology* ; Brain/physiology* ; Brain Mapping ; Humans ; Magnetic Resonance Imaging/methods* ; Nerve Net/physiology* ; Transcranial Direct Current Stimulation/methods*

The UHPLC-LTQ-orbitrap-MS metabolomics technique was used to determine the effect of deapio-platycodin D (DPD) on endogenous metabolites in lung tissues of mice with ammonia-induced cough, and to identify the metabolic regulatory pathways of DPD in its antitussive and expectorant activities. This work was approved by the Animal Ethics Committee of Jiangxi University of Chinese Medicine (Approval No. JZLLSC-20190235). Metabolites were identified by UHPLC-LTQ-orbitrap-MS method and the metabolic pathways related to differentially-expressed metabolites were analyzed by the MetaboAnalyst platform. DPD significantly prolonged (P < 0.05) cough latency, reduced the number of coughs, and significantly increased (P < 0.05) phenol red excretion in ammonia-induced cough mice. Twenty-five metabolites related to cough and 38 metabolites related to sputum excretion were identified by UHPLC-LTQ-orbitrap-MS. Changes in the metabolism of linoleic acid, arachidonic acid, glycerophospholipid, alanine, aspartic acid and glutamic acid, pentose and glucuronate interconversions, and lysine degradation were evident with DPD treatment of ammonia-induced cough mice. Changes in the metabolism of linoleic acid, taurine and hypotaurine, glycerophospholipid, purines and pyrimidines, arachidonic acid and the biosynthesis of unsaturated fatty acids after DPD treatment were related to phenol red excretion. Linoleic acid metabolism, arachidonic acid metabolism and glycerophospholipid metabolism are common regulatory pathways by which DPD appears to exert its antitussive and expectorant activity. These metabolic pathways are closely related to anti-inflammatory pathways, immune function regulation, neurotransmitter release, cell signal transduction, energy metabolism and apoptosis. This study clarifies the antitussive and expectorant activity and mechanism of DPD.

Intracytoplasmic sperm injection (ICSI) is an important treatment option for male infertility at pre-sent.However, a few patients still suffer from repeated ICSI fertilization failure because their sperm is unable to activate oocytes.Artificial oocyte activation (AOA) technology can improve the fertilization rate, pregnancy rate, live birth rate, etc., but it remains unknown whether AOA has short- and long-term effect on offspring.In this article, recent literature about the effect of AOA technology on perinatal outcomes, genetics, physical development and neurological development of offspring was summarized.This paper aims to provide reference for reproductive medicine workers and pediatricians in clinical practice.

Objective:To study the clinical medication regulation for the prevention and treatment of new coronavirus pneumonia with traditional Chinese medicine（TCM），especially prescriptions，on the basis of "treatment in accordance with seasonal conditions". Method:The guidelines and suggestions on novel coronavirus pneumonia formulated and published by national，provincial and municipal governments and experts before February 17，2020, were retrieved and summarized. Data was recorded in stages according to "prevention period，clinical observation period，pre-clinical period，middle clinical period，late clinical period and recovery period". The frequency analysis of TCM and its efficacy，prescription and proprietary Chinese medicine was carried out，and then the factor analysis and cluster analysis of TCM were carried out to obtain rational drug combinations. Result:Totally 172 suggestions on combined structure of drugs，50 suggestions on prescriptions and 31 suggestions on proprietary Chinese medicine were involved in the study，and provided by 24 official agencies and 24 medical experts， 147 kinds of herbs，44 prescriptions and 16 proprietary Chinese medicines were collected. No matter for the drug category or for the specific drug selection，the law of drug use in different stages was not the same. Huoxiang Zhengqi capsule，Shufeng Jiedu capsule，Lianhua Qingwen capsule and Jinhua Qinggan capsule can be used in the observation period. Xuanbai Chengqitang can be used in the middle of the disease. Angong Niuhuangwan，Suhexiangwan or Zixuedan, and Angong Niuhuangwan can be selected in the middle of the disease. And Qingfei Paidu decoction can be used in all stages of the disease. Conclusion:Doctors need to adjust their prescriptions along with the progress of the disease，because the law of medication in each stage of the new coronavirus pneumonia is different.