An investigation into the abnormal dynamic connection mechanism of generalized anxiety disorders based on non-homogeneous Markov models.

BACKGROUND: The dynamic and hierarchical nature of the functional brain network. The neural dynamical systems tend to converge to multiple attractors (stable fixed points or dynamical states) in long run. Little is known about how the changes in this brain dynamic "long-term" behavior of the connectivity flow of brain network in generalized anxiety disorder (GAD). METHODS: This study recruited 92 patients with GAD and 77 healthy controls (HC). We applied a reachable probability approach combining a Non-homogeneous Markov model with transition probability to quantify all possible connectivity flows and the hierarchical structure of brain functional systems at the dynamic level and the stationary probability vector (10-step transition probabilities) to describe the steady state of the system in the long run. A random forest algorithm was conducted to predict the severity of anxiety. RESULTS: The dynamic functional patterns in distributed brain networks had larger possibility to converge in bilateral thalamus, posterior cingulate cortex (PCC), right superior occipital gyrus (SOG) and smaller possibility to converge in bilateral superior temporal gyrus (STG) and right parahippocampal gyrus (PHG) in patients with GAD compared to HC. The abnormal transition probability pattern could predict anxiety severity in patients with GAD. LIMITATIONS: Small samples and subjects taking medications may have influenced our results. Future studies are expected to rule out the potential confounding effects. CONCLUSION: Our results have revealed abnormal dynamic neural communication and integration in emotion regulation in patients with GAD, which give new insights to understand the dynamics of brain function of patients with GAD.

Sex-based influential factors for dental caries in patients with schizophrenia.

BACKGROUND: Schizophrenia is a common mental disorder that seriously affects patients' daily lives and brings heavy psychological and economic burdens to their families and society. The oral problems of patients with schizophrenia are gradually gaining attention, among which dental caries are among the most common oral diseases. Sex differences may be related not only to the various clinical symptoms of schizophrenia but also to different oral hygiene statuses; therefore, the main purpose of this paper is to investigate sex differences related to influencing factors for dental caries in patients with schizophrenia. METHOD: Inpatients with schizophrenia over 18 years old were included in this study, and multidimensional indicators such as demographics, symptom and cognitive impairment assessments, medications, and the caries index of decayed, missing, and filled teeth (DMFT) were collected. An analysis of sex-based influential factors for dental caries in schizophrenia patients was performed. RESULTS: Four-hundred and ninety-six patients with schizophrenia were included, with a mean age of 46.73 ± 12.23 years, of which 142 were females and 354 were males. The mean DMFT was significantly higher in males (8.81 ± 8.50) than in females (5.63 ± 6.61, p < 0.001), and the odd ratio of caries in males to females was significantly higher as well (OR = 2.305, p < 0.001). The influential factors of caries in male patients were independently associated with age and smoking status, in which current smokers were at the highest risk for developing caries, and different smoking statuses had various influencing factors for caries. The influencing factors for caries in female patients were independently associated with age, antipsychotic dose, PANSS-positive symptoms, and MMSE levels. CONCLUSION: Our findings suggest sex differences exist among influential factors for caries in patients with schizophrenia. These risk factors may even be associated with and affect the treatment and prognosis of psychiatric symptoms in patients. Therefore, oral hygiene management of patients with schizophrenia should be enhanced. These differential factors provide new visions and ideas for formulating individual interventions, treatments, and care priorities.

Dynamic functional thalamocortical dysconnectivity in schizophrenia correlates to antipsychotics response.

Although many studies have showed abnormal thalamocortical networks in patients with schizophrenia (SCZ), the dynamic functional thalamocortical connectivity of individuals with SCZ and the effect of antipsychotics on this connectivity have not been investigated. Drug-naïve first-episode individuals with SCZ and healthy controls were recruited. Patients were treated with risperidone for 12 weeks. Resting-state functional magnetic resonance imaging was acquired at baseline and week 12. We identified six functional thalamic subdivisions. The sliding window strategy was used to determine the dynamic functional connectivity (dFC) of each functional thalamic subdivision. Individuals with SCZ displayed decreased or increased dFC variance in different thalamic subdivisions. The baseline dFC between ventral posterior-lateral (VPL) portions and right dorsolateral superior frontal gyrus (rdSFG) correlated with psychotic symptoms. The dFC variance between VPL and right medial orbital superior frontal gyrus (rmoSFG) or rdSFG decreased after 12-week risperidone treatment. The decreased dFC variance between VPL and rmoSFG correlated with the reduction of PANSS scores. Interestingly, the dFC between VPL and rmoSFG or rdSFG decreased in responders. The dFC variance change of VPL and the averaged whole brain signal correlated with the risperidone efficacy. Our study demonstrates abnormal variability in thalamocortical dFC may be implicated in psychopathological symptoms and risperidone response in individuals with schizophrenia, suggesting that thalamocortical dFC variance may be correlated to the efficacy of antipsychotic treatment.Registration: ClinicalTrials.gov Identifier: NCT00435370. https://www.clinicaltrials.gov/ct2/show/NCT00435370?term=NCT00435370&draw=2&rank=1.

Sex differences in factors influencing hospital-acquired pneumonia in schizophrenia patients receiving modified electroconvulsive therapy.

Background: Sex differences may be presented in the clinical features or symptoms of schizophrenia patients but also affect the occurrence of hospital-acquired pneumonia (HAP). Modified electroconvulsive therapy (mECT) is a common treatment method for schizophrenia, used in combination with antipsychotics. This retrospective research explores the sex difference in HAP affecting patients with schizophrenia who have received mECT treatment during hospitalization. Methods: We included schizophrenia inpatients treated with mECT and antipsychotics between January 2015 and April 2022. Blood-related and demographic data collected on admission were analyzed. Influencing factors of HAP in male and female groups were assessed separately. Results: A total of 951 schizophrenia patients treated with mECT were enrolled in the study, including 375 males and 576 females, of which 62 patients experienced HAP during hospitalization. The risk period of HAP in these patients was found to be the first day after each mECT treatment and the first three sessions of mECT treatment. Statistically significant differences in the incidence of HAP were identified in male vs. female groups, with an incidence in men about 2.3 times higher than that in women (P < 0.001). Lower total cholesterol (Z = -2.147, P = 0.032) and the use of anti-parkinsonian drugs (χ2 = 17.973, P < 0.001) were found to be independent risk factors of HAP in male patients, while lower lymphocyte count (Z = -2.408, P = 0.016), hypertension (χ2 = 9.096, P = 0.003), and use of sedative-hypnotic drugs (χ2 = 13.636, P < 0.001) were identified in female patients. Conclusion: Influencing factors of HAP in schizophrenia patients treated with mECT have gender differences. The first day after each mECT treatment and the first three sessions of mECT treatment were identified to have the greatest risk for HAP development. Therefore, it would be imperative to monitor clinical management and medications during this period according to these gender differences.

Comparative Analysis of the Pre- and Post-Medication Effects of Antipsychotic Agents on the Blood-Based Oxidative Stress Biomarkers in Patients with Schizophrenia: A Meta-Analysis.

OBJECTIVE: Studies have shown that oxidative stress (OS) is related to the pathophysiology of schizophrenia (SCZ), but whether antipsychotics can induce OS has not been investigated well. Moreover, antipsychotics have differential effects on the OS level modulation, i.e., different types of antipsychotics have different effects on the cellular antioxidants or pro-oxidants. METHODS: We followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and investigated the OS indicators including both enzymatic and nonenzymatic markers, such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), malondialdehyde (MDA), glutathione (GSH), vitamin C, etc., of SCZ patients at baseline and follow-up of mono-medication. RESULTS: Twenty studies met the inclusion criteria, with a total of 1162 patients enrolled at baseline, and 1105 patients completed the follow-up. OS markers were changed after a period of antipsychotic treatment in SCZ patients. The GPx activity and MDA level decreased in the whole blood (P<0.05), also the serum MDA level decreased (P<0.05). For the first-episode SCZ patients, the activity of GPx and the level of MDA decreased, while the level of vitamin C increased (all P<0.05). The levels of MDA in patients receiving atypical antipsychotics decreased (P<0.05), while the level of GSH in patients with typical antipsychotics decreased (P=0.05). CONCLUSION: Antipsychotic medication may cause changes in the levels of OS markers in different blood samples of SCZ patients. However, the available studies might not be sufficient to reveal the underlying facts accurately due to the poor quality of experimental designs in the published literature.

Identifying spatial relations of industrial carbon emissions among provinces of China: evidence from unsupervised clustering algorithms.

Reducing the total carbon emissions of modern industry is of great significance for China to achieve the carbon peak mission. The MD-SNA spatial correlation measure methodology was innovatively proposed in this paper, which was based on the clustering algorithm of similarity measure. Furthermore, the social network analysis (SNA) method was incorporated to explore the spatial relationship of provincial industrial carbon emissions. The GINI coefficient, Theil index (GE0), and mean of logarithmic deviation (GE1) were used to measure the regional differences of China's industrial carbon emissions. More specifically, we adopted a combined tactic of spatial difference and spatial correlation frameworks. The primary objective of the proposed methodology is to empirically investigate the structural characteristics and spatial relations of different provinces. The results of the case study are as follows. First, the regional industrial carbon emission intensity was unbalanced, among which energy-rich provinces and eastern developed provinces were relatively strong. Second, Beijing, Shandong, Shaanxi, Henan, Sichuan, and Xinjiang were located at the center of the spatial network of industrial carbon emissions. Third, our work clarified the node attributes and different functions of provinces. More than half of the core provinces belonged to the primary beneficial block, which was in the central position of spatial correlation network. The conclusion can help policymakers clarify the overall industrial sector spatial pattern and provinces' roles and functions.

Convergence or divergence? The effects of economic openness on low-carbon innovation in Chinese manufacturing industry.

Low-carbon innovation can address both economic and environmental concerns; patterns of low-carbon innovation convergence can determine the effectiveness of mitigating the adverse consequences of climate change. Considering that economic openness has a huge impact on the development of innovation capability, this paper uses a conditional ß convergence model to examine the convergence of low-carbon innovation in Chinese manufacturing industry and its relationship with economic openness. We incorporate the spatial spillover effect into the convergence function by constructing spatial error model, spatial lag model, and spatial Durbin model. Based on a panel data set of 30 Chinese provinces over the period 2004-2016, the results show that low-carbon innovation in Chinese manufacturing industry has a strong feature of conditional ß convergence. The convergence rate of low-carbon innovation is slightly slowed down by economic openness, and the main reason is that the spillover effect is weak and the convergence rate is slow in lower open areas, so the convergence rate of the whole country is slowed down by that of the lower open areas. Although the economic openness in adjacent areas can contribute to the development of local innovation ability, but generally speaking, economic openness in local areas takes a stronger effect in promoting the convergence of low-carbon innovation than that in adjacent areas. The findings have important policy implications as they suggest the need for a more equal degree of economic openness among Chinese provinces to speed up the convergence of low-carbon innovation.