Identifying Highly Active and Selective Cobalt X-Ides for Electrocatalytic Hydrogenation of Quinoline.

Earth-abundant Co X-ides are emerging as promising catalysts for the electrocatalytic hydrogenation of quinoline (ECHQ), yet challenging due to the limited fundamental understanding of ECHQ mechanism on Co X-ides. This work identifies the catalytic performance differences of Co X-ides in ECHQ and provides significant insights into the catalytic mechanism of ECHQ. Among selected Co X-ides, the Co3O4 presents the best ECHQ performance with a high conversion of 98.2% and 100% selectivity at ambient conditions. The Co3O4 sites present a higher proportion of 2-coordinated hydrogen-bonded water at the interface than other Co X-ides at a low negative potential, which enhances the kinetics of subsequent water dissociation to produce H*. An ideal 1,4/2,3-H* addition pathway on Co3O4 surface with a spontaneous desorption of 1,2,3,4-tetrahydroquinoline is demonstrated through operando tracing and theoretical calculations. In comparison, the Co9S8 sites display the lowest ECHQ performance due to the high thermodynamic barrier in the H* formation step, which suppresses subsequent hydrogenation; while the ECHQ on Co(OH)F and CoP sites undergo the 1,2,3,4- and 4,3/1,2-H* addition pathway respectively with the high desorption barriers and thus low conversion of quinoline. Moreover, the Co3O4 presents a wide substrate scope and allows excellent conversion of other quinoline derivatives and N-heterocyclic substrates.

[Dynamic Prediction of Recidivism in Violence in Community-Based Schizophrenia Spectrum Disorder Patients: A Joint Model]. / ç¤¾åŒºç²¾ç¥žåˆ†è£‚ç—‡è°±ç³»éšœç¢æ‚£è€ æš´åŠ›å†çŠ¯åŠ¨æ€é¢„æµ‹ï¼šä¸€ç§è”åˆæ¨¡åž‹.

Objective: To construct a model for predicting recidivism in violence in community-based schizophrenia spectrum disorder patients (SSDP) by adopting a joint modeling method. Methods: Based on the basic data on severe mental illness in Southwest China between January 2017 and June 2018, 4565 community-based SSDP with baseline violent behaviors were selected as the research subjects. We used a growth mixture model (GMM) to identify patterns of medication adherence and social functioning. We then fitted the joint model using a zero-inflated negative binomial regression model and compared it with traditional static models. Finally, we used a 10-fold training-test cross validation framework to evaluate the models' fitting and predictive performance. Results: A total of 157 patients (3.44%) experienced recidivism in violence. Medication compliance and social functioning were fitted into four patterns. In the counting model, age, marital status, educational attainment, economic status, historical types of violence, and medication compliance patterns were predictive factors for the frequency of recidivism of violence (P<0.05). In the zero-inflated model, age, adverse drug reactions, historical types of violence, medication compliance patterns, and social functioning patterns were predictive factors for the recidivism in violence (P<0.05). For the joint model, the average value of Akaike information criterion (AIC) for the train set was 776.5±9.4, the average value of root mean squared error (RMSE) for the testing set was 0.168±0.013, and the average value of mean absolute error (MAE) for the testing set was 0.131±0.018, which were all lower than those of the traditional static models. Conclusion: Joint modeling is an effective statistical strategy for identifying and processing dynamic variables, exhibiting better predictive performance than that of the traditional static models. It can provide new ideas for promoting the construction of comprehensive intervention systems.

Social support and sleep quality in people with schizophrenia living in the community: the mediating roles of anxiety and depression symptoms.

Introduction: Research has demonstrated that higher social support is associated with better psychological health, quality of life, cognition, activities of daily living, and social participation, but the relationship between social support and sleep quality remains unknown. This study aims to investigate the mediating effects of anxiety and depression in the relationship between social support and sleep among community-dwelling patients with schizophrenia. Method: Purposive sampling was used to collect face-to-face data from 1,107 community-dwelling patients with schizophrenia in Chengdu, Sichuan Province, China, between April and July 2023. The Athens Insomnia Scale (AIS) was used to assess sleep quality; the Generalized Anxiety Disorder 7-item scale (GAD-7) was utilized to evaluate anxiety symptoms; and the Patient Health Questionnaire-9 (PHQ-9) was employed to assess depressive symptoms. The mediating effect of anxiety and depression symptoms was assessed using the bootstrap method via Model 6 (Serial multiple mediator model) of the SPSS PROCESS macro. Results: Among the 1,107 participants, the proportions of people with schizophrenia experiencing anxiety, depressive symptoms, and poor sleep quality were 22.8, 37.7, and 42.1%, respectively. Mediation analyses indicated that although social support had no direct effect on sleep quality, anxiety and depressive symptoms fully mediated the relationship between social support and sleep quality. Conclusion: Patients with schizophrenia experience low levels of social support and poor sleep quality. To enhance the sleep quality of individuals with schizophrenia, all levels of society (government, medical institutions, and communities) must pay more attention to mental health. Implementing diverse intervention measures to strengthen social support and improve symptoms of anxiety and depression should be considered. This approach may potentially lead to an improvement in sleep quality among individuals with schizophrenia.

Medication non-adherence and self-inflicted violence behaviors among 185,800 patients with schizophrenia in the community: a 12-year cohort study.

BACKGROUND: Despite the importance of medication adherence in treatment effectiveness, little is known about the association between medication non-adherence and self-inflicted violence behaviors. We aimed to assess whether medication non-adherence increased the risk of self-inflicted violence behaviors among schizophrenics in communities (hypothesis 1) and whether the dose-response relationship existed (hypothesis 2). METHODS: This 12-year cohort study in western China recruited 292,667 community-dwelling schizophrenics. The proportion of regular medication (PRM) was calculated by dividing the time of "regular adherence" by the total time of antipsychotic treatment during follow-up period as an indicator of medication adherence. For hypothesis 1, medication adherence was designated as a binary variable with a threshold of 0.8 (PRM); for hypothesis 2, medication adherence was specified as five-category and continuous variables, respectively. Inverse probability weighting and mixed effects Cox proportional hazards models were conducted for confounders control and survival analyses. RESULTS: One hundred eighty-five thousand eight hundred participants were eligible for the final analyses, with a mean age of 47.49 years (SD 14.55 years), of whom 53.6% were female. For hypothesis 1, the medication non-adherence group (PRM < 0.8) had a lower risk of suicide (HR, 0.527, 95% CI, 0.447-0.620), an increased risk of NSSI (HR, 1.229, 95% CI, 1.088-1.388), and non-significant risk of attempted suicide compared with adherence group (PRM ≥ 0.8). For hypothesis 2, the lowest medication adherence (PRM < 0.2) was associated with increased risks of suicide attempt (HR, 1.614, 95% CI, 1.412-1.845), NSSI (HR, 1.873, 95% CI, 1.649-2.126), and a decreased risk of suicide (HR, 0.593, 95% CI, 0.490-0.719). The other non-adherence groups had lower risks for all three self-inflicted violence behaviors. The associations between medication adherence in continuous-variable and three outcomes were consistent with the categorical medication adherence results. CONCLUSIONS: Almost no medication taken as prescribed was associated with an increased risk of suicide attempt and NSSI. However, medication adherence did not appear to prevent completed suicide. Besides, patients with moderate adherence had a lower incidence of suicide attempt and NSSI. These findings highlight the need for a more detailed portrayal of medication adherence and the need to be vigilant for suicide intent in schizophrenics with good medication adherence who may be overlooked previously.

Simultaneously optimizing multiple properties of ß-glucosidase Bgl6 using combined (semi-)rational design strategies and investigation of the underlying mechanisms.

The performance of ß-glucosidase during cellulose saccharification is determined by thermostability, activity and glucose tolerance. However, conflicts between them make it challenging to simultaneously optimize three properties. In this work, such a case was reported using Bgl6-M3 as a starting point. Firstly, four thermostability-enhancing mutations were obtained using computer-aided engineering strategies (mutant M7). Secondly, substrate binding pocket of M7 was reshaped, generating two mutations that increased activity but decreased glucose tolerance (mutant M9). Then a key region lining active site cavity was redesigned, resulting in three mutations that boosted glucose tolerance and activity. Finally, mutant M12 with simultaneously improved thermostability (half-life of 20-fold), activity (kcat/Km of 5.6-fold) and glucose tolerance (ΔIC50 of 200 mM) was obtained. Mechanisms for property improvement were elucidated by structural analysis and molecular dynamics simulations. Overall, the strategies used here and new insights into the underlying mechanisms may provide guidance for multi-property engineering of other enzymes.

A method of hepatocyte extraction conjugated with HPLC is established for screening potential active components in Chinese medicines--probing Herba Artemisiae Scopariae as an exemplifying approach.

In order to establish an effective and quick method for screening potential bioactive compounds in Traditional Chinese Medicines (TCMs), hepatocytes were employed for extracting either bifendate, a clinical medicine for liver diseases, or chemicals in Herba Artemisiae Scopariae (A. Scopariae), a commonly used traditional Chinese medicine for remedying liver diseases such as hepatitis induced by viruses, chemicals or alcohol. After hepatocyte extraction the compounds were analyzed by HPLC, therefore this method was referrred to as hepatocyte extraction conjugated with HPLC (HE-HPLC). In the first part of this study, HE-HPLC showed that bifendate was extracted by hepatocytes and detected by HPLC-DAD which indicated the feasibility of this method. Then in the second part of the study, the potential active components in the A. scopariae extract were studied using HE-HPLC. Six chemicals in the A. scopariae extract, which could bind to hepatocytes in vitro, were detected by HPLC-DAD and three were identified as 7-hydroxy-coumarin (7-OH-C), capillartemisin A and 7-methoxy-coumarin, respectively. In vitro assays showed that 7-OH-C protected HL-7702 hepatocytes from H2O2 injury. The results indicated that these compounds could be extracted by hepatocytes, could be detected by HPLC and more importantly were bioactive. It is suggested that HE-HPLC is a useful method for screening potent active components in Chinese medicines used to treat liver diseases.