Objective To explore the relationship between postpartum depression and experiential avoidance of parturient and to provide empirical evidences for acceptance and commitment therapy in mental treatment of postpartum depression.Methods 309 pregnant women were assessed with self-made general information questionnaire,self-rating depression scale (SDS) and acceptance and action questionnaire-2nd edition (AAQ-Ⅱ) in predelivery periods and 3-7 days after childbirth respectively.Results AAQ-Ⅱ scores in the predelivery or postpartum depression group ((18.54±8.25),(19.07±7.82)) were higher than that in the normal group((15.47±7.03),(14.57±6.57)),and the difference was statistically significant(t=-3.15,-5.07,all P＜0.01).It was found that the predelivery or postpartum AAQ-Ⅱ scores were positively associated with the SDS scores of predelivery periods and postpartum periods respectively(r=0.34,0.34,0.24,0.42,all P＜0.01).Hierarchical multiple regression analyses were then conducted.In the first block,neonatal exceptional conditions and the predelivery SDS significantly explained variance in postpartum depression(β=0.09,0.62,all P＜0.01).In the second block,the predelivery AAQ-Ⅱ still had a significant effect on postpartum depression (β=0.13,P=0.006,△R2=0.01,P=0.006),despite control the age of parturient women,postpartum complication,neonatal exceptional conditions and the predelivery SDS.Conclusion A function to predict the occurrence of maternal postpartum depression is obtained from the experiential avoidance which is attributed to the risk of maternal postpartum depression.

Alzheimer's disease(AD)is gradually increasing in prevalence and the complexity of its pathogenesis has led to a lengthy process of developing therapeutic drugs with limited success.Faced with this challenge,we proposed using a state-of-the-art drug screening algorithm to identify potential therapeutic com-pounds for AD from traditional Chinese medicine formulas with strong empirical support.We developed four deep neural network(DNN)models for AD drugs screening at the disease and target levels.The AD model was trained with compounds labeled for AD activity to predict active compounds at the disease level,while the acetylcholinesterase(AChE),monoamine oxidase-A(MAO-A),and 5-hydroxytryptamine 6(5-HT6)models were trained for specific AD targets.All four models performed excellently and were used to identify potential AD agents in the Kaixinsan(KXS)formula.High-scoring compounds underwent experimental validation at the enzyme,cellular,and animal levels.Compounds like 2,4-di-tert-butyl-phenol and elemicin showed significant binding and inhibitory effects on AChE and MAO-A.Additionally,13 compounds,including α-asarone,penetrated the blood-brain barrier(BBB),indicating potential brain target binding,and eight compounds enhanced microglial β-amyloid phagocytosis,aiding in clearing AD pathological substances.Our results demonstrate the effectiveness of deep learning models in devel-oping AD therapies and provide a strong platform for AD drug discovery.

Objective To investigate the correlation between type D personality and cognitive fusion in 388 employees from state-owned enterprises,and to provide a theoretical basis for psychological intervention for type D personality.Methods In May 2014,cluster random sampling was used to randomly select 400 employees from two state-owned enterprises who underwent physical examination and were willing to participate in the test.The test was performed with Cognitive Fusion Questionnaire(CFQ) and Type D Personality Scale(DS-14).Results The social inhibition group and the group without negative affectivity and social inhibition had a significantly lower mean cognitive fusion score than the type D personality group (25.62±8.92/20.58±8.26 vs 32.38±9.66,P ＜ 0.01).The group without negative affectivity and social inhibition had a significantly lower mean cognitive fusion score than the negative affectivity group (31.96±10.20) and the social inhibition group (P＜0.01).The social inhibition group had a significantly lower mean cognitive fusion score than the negative affectivity group (P＜0.05).In the employees with type D personality,the subscales negative affectivity and social inhibition were positively correlated with cognitive fusion(r=0.599 and 0.392,P＜0.01).Negative affectivity(△F=211.484,P＜0.05) played a role in explaining cognitive fusion.Conclusion In the employees of state-owned enterprises,cognitive fusion is different between those with type D personality and those without type D personality.In the employees with type D personality,social inhibition and negative affectivity are correlated with cognitive infusion,and negative affectivity plays a role in explaining cognitive fusion.

Objective To investigate the correlation between type D personality and cognitive fusion in 388 employees from state-owned enterprises,and to provide a theoretical basis for psychological intervention for type D personality.Methods In May 2014,cluster random sampling was used to randomly select 400 employees from two state-owned enterprises who underwent physical examination and were willing to participate in the test.The test was performed with Cognitive Fusion Questionnaire(CFQ) and Type D Personality Scale(DS-14).Results The social inhibition group and the group without negative affectivity and social inhibition had a significantly lower mean cognitive fusion score than the type D personality group (25.62±8.92/20.58±8.26 vs 32.38±9.66,P ＜ 0.01).The group without negative affectivity and social inhibition had a significantly lower mean cognitive fusion score than the negative affectivity group (31.96±10.20) and the social inhibition group (P＜0.01).The social inhibition group had a significantly lower mean cognitive fusion score than the negative affectivity group (P＜0.05).In the employees with type D personality,the subscales negative affectivity and social inhibition were positively correlated with cognitive fusion(r=0.599 and 0.392,P＜0.01).Negative affectivity(△F=211.484,P＜0.05) played a role in explaining cognitive fusion.Conclusion In the employees of state-owned enterprises,cognitive fusion is different between those with type D personality and those without type D personality.In the employees with type D personality,social inhibition and negative affectivity are correlated with cognitive infusion,and negative affectivity plays a role in explaining cognitive fusion.

Pharmaceutical analysis is a discipline based on chemical, physical, biological, and information technologies. At present, biotechnological analysis is a short branch in pharmaceutical analysis; however, bioanalysis is the basis and an important part of medicine. Biotechnological approaches can provide information on biological activity and even clinical efficacy and safety, which are important characteristics of drug quality. Because of their advantages in reflecting the overall biological effects or functions of drugs and providing visual and intuitive results, some biotechnological analysis methods have been gradually applied to pharmaceutical analysis from raw material to manufacturing and final product analysis, including DNA super-barcoding, DNA-based rapid detection, multiplex ligation-dependent probe amplification, hyperspectral imaging combined with artificial intelligence, 3D biologically printed organoids, omics-based artificial intelligence, microfluidic chips, organ-on-a-chip, signal transduction pathway-related reporter gene assays, and the zebrafish thrombosis model. The applications of these emerging biotechniques in pharmaceutical analysis have been discussed in this review.