Transition metals anchored on nitrogen-doped graphdiyne for an efficient oxygen reduction reaction: a DFT study.

The search for highly active and low-cost single-atom catalysts for the oxygen reduction reaction (ORR) is essential for the widespread application of proton exchange membrane fuel cells. Transition metals anchored on nitrogen-doped graphdiyne (GDY) have attracted considerable interest as potentially excellent catalysts for the ORR. However, the relationship between the active site and nitrogen-doped GDY remains unclear. In this work, we conducted a systematic investigation of sp-hybridized N atoms anchoring single transition metal atoms of 3d and 4d on GDY (TMC2N2) as electrocatalysts for the ORR. Firstly, 18 kinds of TMC2N2 were determined to have good thermodynamic stability. Due to the extremely strong adsorption of *OH, TMC2N2 exhibits inferior ORR performance compared to traditional Pt(111). Considering that *OH adsorption hinders the catalytic activity of TMC2N2, we modified the OH ligand of TMC2N2 to develop the high-valent metal complex (TMC2N2-OH) aiming to enhance the electrocatalytic activity. The adsorption of intermediates on most TMC2N2-OH is weakened after the modification of the OH ligand, especially for the adsorption of *OH. Thus, by comparing the ORR overpotential of catalysts before and after ligand modification, we find that the catalytic activity of different TMC2N2-OHs improves to various degrees. MnC2N2-OH, TMC2N2-OH, and TcC2N2-OH exhibit relatively high ORR catalytic activity, with overpotentials of 0.93 V, 1.19 V, and 0.92 V, respectively. Furthermore, we investigated the cause of improved catalytic activity of TMC2N2-OH and found that the modified coordination environment of the catalyst led to adjusted adsorption of ORR intermediates. In summary, our work sheds light on the relationship between nitrogen-doped GDY and transition metal sites, thus contributing to the development of more efficient catalysts.

'Let's Talk About Children' family focused practice for children of parents with schizophrenia and bipolar disorder: protocol for a randomized controlled trial.

INTRODUCTION: 'Let's Talk About Children' is a brief family focused intervention developed to improve mental health outcomes of children of parents with mental illness (COPMI). This study aims to assess the efficacy of LTC in improving mental health of children of parents with schizophrenia or bipolar disorder in China. METHODS: The planned study is a multicentre parallel group randomized wait-list controlled trial. A total of 400 eligible families with children aged 8 to 18 years will be recruited, 200 each for families with parental schizophrenia or bipolar disorder. The intervention group will receive Let's Talk About Children delivered by a trained therapist, while the control group will receive treatment as usual. The primary outcomes are child mental health measured by the strengths and difficulties questionnaire and parent-child communication measured using the parent-adolescent communication scale. Parental mental health and family functioning are secondary outcomes. This study also plans to explore mediating factors for the effect of Let's Talk About Children on child mental health, as well as conduct a cost-effectiveness analysis on using Let's Talk About Children in China. CONCLUSION: The present study will provide evidence for the efficacy of Let's Talk About Children in families with parental schizophrenia and bipolar disorder in China. In addition, it will evaluate potential mechanisms of action and cost-effectiveness of Let's Talk About Children, providing a basis for future implementation. TRIAL REGISTRATION: ChiCTR2300073904.

Density Functional Theory Study of Triple Transition Metal Cluster Anchored on the C2N Monolayer for Nitrogen Reduction Reactions.

The electrochemical nitrogen reduction reaction (NRR) is an attractive pathway for producing ammonia under ambient conditions. The development of efficient catalysts for nitrogen fixation in electrochemical NRRs has become increasingly important, but it remains challenging due to the need to address the issues of activity and selectivity. Herein, using density functional theory (DFT), we explore ten kinds of triple transition metal atoms (M3 = Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, and Zn) anchored on the C2N monolayer (M3-C2N) as NRR electrocatalysts. The negative binding energies of M3 clusters on C2N mean that the triple transition metal clusters can be stably anchored on the N6 cavity of the C2N structure. As the first step of the NRR, the adsorption configurations of N2 show that the N2 on M3-C2N catalysts can be stably adsorbed in a side-on mode, except for Zn3-C2N. Moreover, the extended N-N bond length and electronic structure indicate that the N2 molecule has been fully activated on the M3-C2N surface. The results of limiting potential screen out the four M3-C2N catalysts (Co3-C2N, Cr3-C2N, Fe3-C2N, and Ni3-C2N) that have a superior electrochemical NRR performance, and the corresponding values are -0.61 V, -0.67 V, -0.63 V, and -0.66 V, respectively, which are smaller than those on Ru(0001). In addition, the detailed NRR mechanism studied shows that the alternating and enzymatic mechanisms of association pathways on Co3-C2N, Cr3-C2N, Fe3-C2N, and Ni3-C2N are more energetically favorable. In the end, the catalytic selectivity for NRR on M3-C2N is investigated through the performance of a hydrogen evolution reaction (HER) on them. We find that Co3-C2N, Cr3-C2N, Fe3-C2N, and Ni3-C2N catalysts possess a high catalytic activity for NRR and exhibit a strong capability of suppressing the competitive HER. Our findings provide a new strategy for designing NRR catalysts with high catalytic activity and selectivity.

Interfacial Tension-Temperature-Pressure-Salinity Relationship for the Hydrogen-Brine System under Reservoir Conditions: Integration of Molecular Dynamics and Machine Learning.

Hydrogen (H2) underground storage has attracted considerable attention as a potentially efficient strategy for the large-scale storage of H2. Nevertheless, successful execution and long-term storage and withdrawal of H2 necessitate a thorough understanding of the physical and chemical properties of H2 in contact with the resident fluids. As capillary forces control H2 migration and trapping in a subsurface environment, quantifying the interfacial tension (IFT) between H2 and the resident fluids in the subsurface is important. In this study, molecular dynamics (MD) simulation was employed to develop a data set for the IFT of H2-brine systems under a wide range of thermodynamic conditions (298-373 K temperatures and 1-30 MPa pressures) and NaCl salinities (0-5.02 mol·kg-1). For the first time to our knowledge, a comprehensive assessment was carried out to introduce the most accurate force field combination for H2-brine systems in predicting interfacial properties with an absolute relative deviation (ARD) of less than 3% compared with the experimental data. In addition, the effect of the cation type was investigated for brines containing NaCl, KCl, CaCl2, and MgCl2. Our results show that H2-brine IFT decreases with increasing temperature under any pressure condition, while higher NaCl salinity increases the IFT. A slight decrease in IFT occurs when the pressure increases. Under the impact of cation type, Ca2+ can increase IFT values more than others, i.e., up to 12% with respect to KCl. In the last step, the predicted IFT data set was used to provide a reliable correlation using machine learning (ML). Three white-box ML approaches of the group method of data handling (GMDH), gene expression programming (GEP), and genetic programming (GP) were applied. GP demonstrates the most accurate correlation with a coefficient of determination (R2) and absolute average relative deviation (AARD) of 0.9783 and 0.9767%, respectively.

Chinese mental health workers' family-focused practices: a cross-sectional survey.

BACKGROUND: Mental disorders impose heavy burdens on patients' families and children. It is imperative to provide family-focused services to avoid adverse effects from mental disorders on patients' families and children. However, implementing such services requires a great deal of involvement of mental health workers. This study investigated the attitudes, knowledge, skills, and practices in respect to family-focused practices (FFP) in a sample of Chinese mental health workers. METHODS: A cross-sectional study design was employed to examine the attitudes, knowledge, skills, and practices of a convenience sample of Chinese mental health workers in respect to FFP, using the Chinese version of the Family-Focused Mental Health Practice Questionnaire (FFMHPQ). RESULTS: In total, 515 mental health workers participated in our study, including 213 psychiatrists, 269 psychiatric nurses, and 34 allied mental health professionals (20 clinical psychologists, 9 mental health social workers, and 4 occupational therapists). Compared with psychiatric nurses, psychiatrists and allied mental health professionals provided more support for families and children of patients with mental illness and were more willing to receive further training in FFP. However, there were no significant differences on knowledge, skills, and confidence across different profession types. After adjusting for demographic and occupational variables, previous training in FFP was positively associated with mental health workers' knowledge, skills, and confidence about FFP, but not actual support to families and children. CONCLUSIONS: Professional differences on FFP exist in Chinese mental health workers. Training is needed to engage psychiatrists and other allied workforce in dissemination and implementation of FFP in China.

Gender differences of neurocognitive functioning in patients with first-episode schizophrenia in China.

AIMS: To investigate the gender differences in neurocognitive functioning in patients with first-episode schizophrenia (FES) in China. METHODS: A total of 449 Chinese patients with FES (210 males, 239 females) were included in this study. Participants' psychopathology was assessed by the Positive and Negative Syndrome Scale (PANSS). Neurocognitive functioning was assessed by 10 neuropsychological tests from a battery. Neurocognitive test scores were converted to scale scores and t-scores using normative data from Chinese populations. RESULTS: Males were younger and less likely to be married, had an earlier age of illness onset and a longer duration of untreated psychosis (DUP), and scored higher on the PANSS negative, general and total scales than females. After controlling for potential confounders, females performed better than males in the verbal learning and memory domain (p=0.016). While most neurocognitive domains were correlated with PANSS negative scores for male patients with FES, for female patients with FES, negative associations were found between scores on the PANSS general subscales and neurocognitive domains. We also performed a case-control comparison with a group of patients with clinically stable schizophrenia (CSS) (n=60) who were matched by age, sex and education years with patients with FES (n=58). After controlling for potential confounders, no significant differences were found between patients with FES and patients with CSS in all neurocognitive domains. Female patients still performed better in the verbal learning and memory domain (t=2.14, p=0.034). No interaction effects of gender and disease were found. CONCLUSIONS: Gender was an independent influence factor for the verbal learning and memory domain. Both female patients with first-episode schizophrenia and female patients with clinically stable schizophrenia performed better than male patients.

[Reliability and validity of Professional Quality of Life Scale among government staff in earthquake - stricken areas in China].

OBJECTIVE: To evaluate the reliability and validity of Professional Quality of Life Scale (ProQOL-30, 4th version, 30 items) among government staff in the Wenchuan earthquake-stricken areas METHODS: A total of 1,175 members of government staff in the Wenchuan earthquake-stricken areas were selected by convenience sampling and required to complete the ProQOL and Self-Reporting Questionnair (SRQ). The reliability and validity of the scale was evaluated by correlation analysis, t-test, and confirmatory factor analysis. RESULTS: Item-total correlation coefficients of the three subscales were 0.590 - 0.752, 0.389 - 0.603, and 0.340 - 0.647, respectively (P<0.05), and the average coefficients were 0.672, 0.482, and 0.555 respectively (P<0.05). The Cronbach's α coefficients of the three subscales were 0.864, 0.569, and 0.742 respectively, and the split-half reliabilities were 0.829, 0.490, and 0.677, respectively. P value was 0.88 in thE chi-square test of confirmatory factor analysis model. Goodness-of-fit indices of ProQOL-30 included GFI=0.895 NFI=0.856, CFI=0.895, RMSEA=0.063, and AGFI=0.912. For the ProQOL-28 as an optimized version o ProQOL-30, the Cronbach's a coefficients for burnout and trauma/compassion fatigue increased to 0.616 and 0.757, respectively. P value was 0.91 in the chi-square test of confirmatory factor analysis model test. Goodness-of-fit indices of ProQOL-28 were GFI =0.913, AGFI =0.924, NFI =0.900, CFI =0.913, and RMSEA =0.031 CONCLUSION: ProQOL-28 has good reliability and validity among government staff in the earthquake-stricker areas in China.

Structural Coarse-Graining via Multiobjective Optimization with Differentiable Simulation.

In the realm of multiscale molecular simulations, structure-based coarse-graining is a prominent approach for creating efficient coarse-grained (CG) representations of soft matter systems, such as polymers. This involves optimizing CG interactions by matching static correlation functions of the corresponding degrees of freedom in all-atom (AA) models. Here, we present a versatile method, namely, differentiable coarse-graining (DiffCG), which combines multiobjective optimization and differentiable simulation. The DiffCG approach is capable of constructing robust CG models by iteratively optimizing the effective potentials to simultaneously match multiple target properties. We demonstrate our approach by concurrently optimizing bonded and nonbonded potentials of a CG model of polystyrene (PS) melts. The resulting CG-PS model effectively reproduces both the structural characteristics, such as the equilibrium probability distribution of microscopic degrees of freedom and the thermodynamic pressure of the AA counterpart. More importantly, leveraging the multiobjective optimization capability, we develop a precise and efficient CG model for PS melts that is transferable across a wide range of temperatures, i.e., from 400 to 600 K. It is achieved via optimizing a pairwise potential with nonlinear temperature dependence in the CG model to simultaneously match target data from AA-MD simulations at multiple thermodynamic states. The temperature transferable CG-PS model demonstrates its ability to accurately predict the radial distribution functions and density at different temperatures, including those that are not included in the target thermodynamic states. Our work opens up a promising route for developing accurate and transferable CG models of complex soft-matter systems through multiobjective optimization with differentiable simulation.

The Bidirectional Relationship between Weight Gain and Cognitive Function in First-Episode Schizophrenia: A Longitudinal Study in China.

Patients with schizophrenia often encounter notable weight gain during their illness, heightening the risk of metabolic diseases. While previous studies have noted a correlation between obesity and cognitive impairment in schizophrenia, many were cross-sectional, posing challenges in establishing a causal relationship between weight gain and cognitive function. The aim of this longitudinal study is to examine the relationship between weight gain and cognitive function in patients with first-episode schizophrenia (FES) during the initial 6-month antipsychotic treatments. Employing linear and logistic regression analyses, the study involved 337 participants. Significantly, baseline scores in processing speed (OR = 0.834, p = 0.007), working memory and attention (OR = 0.889, p = 0.043), and executive function (OR = 0.862, p = 0.006) were associated with clinically relevant weight gain (CRW, defined as an increase in body weight > 7%) at the 6-month endpoint. On the other hand, CRW correlated with improvements in the Brief Visuospatial Memory Test (p = 0.037). These findings suggest that patients with lower baseline cognitive performance undergo more substantial weight gain. Conversely, weight gain was correlated with cognitive improvements, particularly in the domain of visual learning and memory. This suggested a potential bidirectional relationship between weight gain and cognitive function in first-episode schizophrenia patients.

Machine learning-enabled performance prediction and optimization for iron-chromium redox flow batteries.

Iron-chromium flow batteries (ICRFBs) are regarded as one of the most promising large-scale energy storage devices with broad application prospects in recent years. However, transitioning from laboratory-scale development to industrial-scale deployment can be a time-consuming process due to the multitude of complex factors that impact ICRFB stack performance. Herein, a data-driven optimization methodology applying active learning, informed by an extensive survey of the literature encompassing diverse experimental conditions, is proposed to enable exceptional precision in predicting ICRFB system performance considering both operation conditions and key materials selection. Specifically, multitask ML models are trained on experimental data with a high prediction accuracy (R2 > 0.92) to link ICRFB properties to energy efficiency, coulombic efficiency, and capacity. We also interpret the ML models based on Shapley additive explanations and extract valuable insights into the importance of descriptors. It is noted that the operation conditions (current density and cycle number) and the electrode type are the most critical descriptors affecting the voltage efficiency and coulombic efficiency while the electrode size strongly affects the capacity. Moreover, active learning is used to explore the most optimized cases considering the highest energy efficiency and capacity. The versatility and robustness of the approach are demonstrated by the successful validation between ML prediction and our experiments of energy efficiency (±0.15%) and capacity (±0.8%). This work not only affords fruitful data-driven insight into the property-performance relationship, but also unveils the explainability of critical properties on the performance of ICRFBs, which accelerates the rational design of next-generation ICRFBs.

Molecular Dynamics Simulation on the Heat Transfer in the Cross-Linked Poly(dimethylsiloxane).

In this work, the effect of cross-linking degree and stretching on the thermal conductivity of poly(dimethylsiloxane) (PDMS) is explored by performing a molecular dynamics simulation. Our results demonstrate that the thermal conductivity of PDMS exhibits a monotonous rise with an increase in the cross-linking degree. By decomposing the total heat flux into three microscopic heat transfer modes, the high cross-linking degree improves the contribution from bonding interactions to the heat transfer more than that from the nonbonding interactions. An analysis of the vibrational density of states shows a blue-shift of the vibrational modes at low frequencies, indicating a large phonon group velocity due to the strong interchain bonding interaction. From the spectral distribution of heat flux, the spectral contributions are shifted toward the higher frequencies with the increasing cross-linking degree, which reflects more contribution from the high-frequency modes to the heat transfer. Stretching can improve the thermal conductivity parallel to the tensile direction with the increase in strain. This is mainly due to the further improved contribution of bonding interactions or high-frequency modes to heat transfer. Interestingly, the anisotropy of the thermal conductivity first decreases and then increases with the increasing cross-linking degree. Our study conducts a detailed investigation of the thermal conductivity of cross-linked PDMS, providing guidance on the application of thermal interface materials.

Optimal cutoff scores of the Chinese version of 15-item negative symptom assessment that indicate prominent negative symptoms of schizophrenia.

Objective: The Chinese version of 15-item negative symptom assessment (NSA-15) is an instrument with a three-factor structure specifically validated for assessing negative symptoms of schizophrenia. To provide a reference for future practical applications in the recognition of schizophrenia patients with negative symptoms, this study aimed to determine an appropriate NSA-15 cutoff score regarding negative symptoms to identify prominent negative symptoms (PNS). Methods: A total of 199 participants with schizophrenia were recruited and divided into the PNS group (n = 79) and non-PNS group (n = 120) according to scale for assessment of negative symptoms (SANS) scores. Receiver-operating characteristic (ROC) curve analysis was used to determine the optimal NSA-15 cutoff score for identifying PNS. Results: The optimal cutoff NSA-15 score for identifying PNS was 40. Communication, emotion and motivation factors in the NSA-15 had cutoffs of 13, 6, and 16, respectively. The communication factor score had slightly better discrimination than scores on the other two factors. The discriminant ability of the global rating of the NSA-15 was not as good as that of the NSA-15 total score (area under the curve (AUC): 0.873 vs. 0.944). Conclusion: The optimal NSA-15 cutoff scores for identifying PNS in schizophrenia were determined in this study. The NSA-15 provides a convenient and easy-to-use assessment for identifying patients with PNS in Chinese clinical situations. The communication factor of the NSA-15 also has excellent discrimination.

Weight changes following treatment with aripiprazole, risperidone and olanzapine: A 12-month study of first-episode schizophrenia patients in China.

OBJECTIVES: This study aimed to assess weight changes following antipsychotic treatment in first-episode schizophrenia (FES) patients and make a comparison of aripiprazole, risperidone and olanzapine. Predictors for long-term clinically relevant weight gain (CRW, ≥7%) were examined. METHODS: We carried out a second analysis of data from the Chinese First-Episode Schizophrenia Trial. Repeated measures general linear model (GLM) statistics were used to compare body weight at each follow-up point (month of 1, 2, 3, 6, 9and 12). Logistic regression models were constructed to evaluate possible predictors for CRW. RESULTS: Body weight increased with an average rate of 0.93 % per month, with the fastest growth rate occurring in first 3 months. CRW was observed in 79 % of patients. Participants from olanzapine group showed significantly higher weight gain than risperidone group and aripiprozole group. Repeated measures GLM revealed a significant main effect of time (p < 0.001) and asignificant time*group interaction was revealed (p < 0.001), while the between-subject group effect was not statistically significant (p = 0.272). Multivariate logistic regressionmodel showed that with smaller baseline BMI (OR = 1.33, p < 0.001), with a family history of mental disorder (OR = 5.08, p = 0.004), receiving olanzapine (OR = 2.35, p = 0.001), and CRW at first-month (OR = 4.29, p = 0.032) were independent predictors for first-year CRW. CONCLUSION: Antipsychotics are associated with a clinically significant weight gain in FES patients, which occurs mostly in first 3 months. Aripiprazole might not be an ideal choice in terms of long-term metabolic side-effects. Early and close metabolic monitoring should accompany antipsychotic prescription.

Childhood experiences and needs of offspring living with paternal and maternal severe mental illness: A retrospective study in China.

OBJECTIVE: Parental mental illness is considered one of the strongest risk factors for the development of children. This study aimed to describe the adverse childhood experiences and needs of offspring living with parental severe mental illness (SMI) in China and to compare the differences in needs between offspring living with maternal SMI and those living with paternal SMI. METHOD: Overall, 381 participants, including 76 living with paternal SMI, 104 living with maternal SMI, and 201 living without parental mental illness, were enrolled. Data were collected using questionnaires from five sites in China. Differences among the three groups were compared using analysis of variance and chi-square test. Factors were extracted using exploratory factor analysis, and differences in factor scores between the paternal and maternal SMI groups were compared using the rank sum test. RESULTS: The percentages of poverty, family care, and housework were significantly higher in the paternal SMI group and maternal SMI group, compared with the control group, and those of school dropout and relationship with friends were significantly higher in the maternal SMI group (p < 0.0167). The need for stigma reduction in the maternal SMI group was significantly higher than that in the paternal SMI group (p = 0.015). CONCLUSION: Our findings highlight the importance of considering the impact of maternal and paternal SMI on child development. There is an urgent need to develop a national program to assist families with mentally ill parents to provide services for children living with parental SMI.

Factors that influence family-focused practice in Chinese mental health workers: A cross-sectional survey.

INTRODUCTION: Family-focused practice has become an emerging paradigm in mental health services. However, little is known about family-focused practice and associated factors in Chinese mental health workers. AIM: To examine family-focused practice and associated factors in Chinese mental health workers. METHOD: A cross-sectional survey was conducted in a convenience sample of mental health workers (n = 515) in Beijing, China. The Family-Focused Mental Health Practice Questionnaire was used to measure family-focused practice, as well as worker, workplace and client factors that might influence family-focused practice. Multiple linear regression analysis was performed to investigate the factors associated with family-focused practice. RESULTS: On average, the participants exhibited a moderate level of engagement in family-focused practice. The factors that most significantly influenced family-focused practice in Chinese mental health workers were skill and knowledge, worker confidence and time and workload. Moreover, psychiatrists were found to engage more in family-focused practice than psychiatric nurses, and community mental health workers were more active in family-focused practice than hospital-based ones. DISCUSSION: This study provided important data concerning family-focused practice and associated factors in Chinese mental health workers. IMPLICATIONS FOR PRACTICE: The varying level of Chinese mental health workers to engage in family-focused practice has advocacy, training, research and organizational implications for mental health services in China and elsewhere.

How Ethanolic Disinfectants Disintegrate Coronavirus Model Membranes: A Dissipative Particle Dynamics Simulation Study.

We have developed dissipative particle dynamics models for pure dipalmitoylphosphatidylcholine (DPPC), dioleoylphosphatidylcholine (DOPC), and dimyristoylphosphatidylcholine (DMPC) as well as their binary and ternary mixed membranes, as coronavirus model membranes. The stabilities of pure and mixed membranes, surrounded by aqueous solutions containing up to 70 mol % ethanol (alcoholic disinfectants), have been investigated at room temperature. We found that aqueous solutions containing 5-10 mol % ethanol already have a significant weakening effect on the pure and mixed membranes. The magnitude of the effect depends on the membrane composition and the ethanol concentration. Ethanol permeabilizes the membrane, causing its lateral swelling and thickness shrinking and reducing the orientational order of the hydrocarbon tail of the bilayer. The free energy barrier for the permeation of ethanol in the bilayers is considerably reduced by the ethanol uptake. The rupture-critical ethanol concentrations causing the membrane failure are 20.7, 27.5, and 31.7 mol % in the aqueous phase surrounding pure DMPC, DOPC, and DPPC membranes, respectively. Characterizing the failure of lipid membranes by a machine-learning neural network framework, we found that all mixed binary and/or ternary membranes disrupt when immersed in an aqueous solution containing a rupture-critical ethanol concentration, ranging from 20.7 to 31.7 mol %, depending on the composition of the membrane; the DPPC-rich membranes are more intact, while the DMPC-rich membranes are least intact. Due to the tight packing of long, saturated hydrocarbon tails in DPPC, increasing the DPPC content of the mixed membrane increases its stability against the disinfectant. At high DPPC concentrations, where the DOPC and DMPC molecules are confined between the DPPC lipids, the ordered hydrocarbon tails of DPPC also induce order in the DOPC and DMPC molecules and, hence, stabilize the membrane more. Our simulations on pure and mixed membranes of a diversity of compositions reveal that a maximum ethanol concentration of 32 mol % (55 wt %) in the alcohol-based disinfectants is enough to disintegrate any membrane composed of these three lipids.

Negative symptom dimensions and social functioning in Chinese patients with schizophrenia.

Objective: Negative symptoms can seriously affect social functioning in patients with schizophrenia. However, the role of various components of negative symptoms in social functioning remains unclear. This study aimed to explore the associations among three different dimensions of negative symptoms (i.e., communication, emotion, and motivation) and social functioning to identify potential therapeutic targets. Methods: This cross-sectional study enrolled 202 Chinese participants with schizophrenia. Negative symptoms were evaluated using the Negative Symptom Assessment (NSA). Social functioning was represented by the Personal and Social Performance Scale (PSP) total score and employment status. Correlation analysis was conducted to clarify the relationship between negative symptoms and the PSP total score. Regression analysis was performed to explore the determinants of the PSP total score and employment status, considering negative symptoms and possible confounders, such as demographic features, positive symptoms, cognitive symptoms, depressive symptoms, and extrapyramidal side effects. Results: The PSP total score was correlated with all three dimensions of negative symptoms (i.e., emotion, motivation, and communication; rs = -0.509, -0.662, and -0.657, respectively). Motivation, instead of emotion or communication, predicted both low PSP total scores and unemployment. Conclusion: Social functioning in patients with schizophrenia was significantly related to motivation. Further studies should focus on motivation and consider it as a therapeutic target to improve patients' social functioning.

Development and Validation of a Self-Administered Screening Test for Betel Quid Use Disorders in Betel Quid Chewers in Hunan, China.

Introduction: Processed betel quid product chewing is a public health problem in areca non-plant areas in China. However, there is no valid instrument to screen for betel quid use disorder (BQUD) in mainland China. We developed a self-administered screening test for betel quid use disorders (SST-BQUD) and tested its reliability and validity in a sample of betel quid chewers (BQCers) in Hunan, China. Methods: Items of SST-BQUD were selected from the test results of an item pool, which includes 52 questions related to the psycho-social and behavioral presentations of BQUD. All participants, in a self-administered manner, completed the item pool. A subsample completed the re-test one week later. Two psychiatrists interviewed all participants to ascertain the presence of BQUD. The receiver Operating Characteristic curve was used to determine the best cut-off value to discriminate BQUD. Results: One hundred and twelve BQCers were recruited. Based on the statistical analysis of receiver operating characteristic (ROC) curves, 14 yes/no questions were selected for SST-BQUD. As indicated by Cronbach's α coefficient, the internal consistency was 0.876. The area under the curve of SST-BQUD was 0.881, representing a satisfactory diagnostic value. The one-week re-test reliability test was 0.771 (P<0.001), suggesting good stability over time. The optimal cut-off score for BQUD screening was six, with a sensitivity of 0.921 and a specificity of 0.716, implying the satisfactory accuracy of SST-BQUD to screen for BQUD. Conclusion: The standard version of SST-BQUD consists of 14 items. The total score of SST-BQUD was the sum of affirmative answers, with higher scores denoting a more severe BQUD symptom. If one answered six or more times "yes" to these 14 questions, they can be classified with BQUD. The SST-BQUD is a valid screening method for BQUD among BQCers in betel quid processed area.

Negative symptoms correlate with altered brain structural asymmetry in amygdala and superior temporal region in schizophrenia patients.

Negative symptoms play an important role in development and treatment of schizophrenia. However, brain changes relevant to negative symptoms are still unclear. This study examined brain structural abnormalities and their asymmetry in schizophrenia patients and the association with negative symptoms. Fifty-nine schizophrenia patients and 66 healthy controls undertook structural brain scans. Schizophrenia patients were further divided into predominant negative symptoms (PNS, n = 18) and non-PNS (n = 34) subgroups. Negative symptoms were assessed by the Negative Symptom Assessment (NSA). T1-weighted images were preprocessed with FreeSurfer to estimate subcortical volumes, cortical thickness and surface areas, asymmetry Index (AI) was then calculated. MANOVA was performed for group differences while partial correlations in patients were analyzed between altered brain structures and negative symptoms. Compared to healthy controls, schizophrenia patients exhibited thinner cortices in frontal and temporal regions, and decreased leftward asymmetry of superior temporal gyrus (STG) in cortical thickness. Patients with PNS exhibited increased rightward asymmetry of amygdala volumes than non-PNS subgroup. In patients, AI of cortical thickness in the STG was negatively correlated with NSA-Emotion scores (r = -0.30, p = 0.035), while AI of amygdala volume was negatively correlated with NSA-Communication (r = -0.30, p = 0.039) and NSA-Total scores (r = -0.30, p = 0.038). Our findings suggested schizophrenia patients exhibited cortical thinning and altered lateralization of brain structures. Emotion and communication dimensions of negative symptoms also correlated with the structural asymmetry of amygdala and superior temporal regions in schizophrenia patients.

Sequence-Engineering Polyethylene-Polypropylene Copolymers with High Thermal Conductivity Using a Molecular-Dynamics-Based Genetic Algorithm.

Polymer sequence engineering is emerging as a potential tool to modulate material properties. Here, we employ a combination of a genetic algorithm (GA) and atomistic molecular dynamics (MD) simulation to design polyethylene-polypropylene (PE-PP) copolymers with the aim of identifying a specific sequence with high thermal conductivity. PE-PP copolymers with various sequences at the same monomer ratio are found to have a broad distribution of thermal conductivities. This indicates that the monomer sequence has a crucial effect on thermal energy transport of the copolymers. A non-periodic and non-intuitive optimal sequence is indeed identified by the GA, which gives the highest thermal conductivity compared with any regular block copolymers, for example, diblock, triblock, and hexablock. In comparison to the bulk density, chain conformations, and vibrational density of states, the monomer sequence has the strongest impact on the efficiency of thermal energy transport via inter- and intra-molecular interactions. Our work highlights polymer sequence engineering as a promising approach for tuning the thermal conductivity of copolymers, and it provides an example application of integrating atomistic MD modeling with the GA for computational material design.