Isoselective Polymerization of rac-Lactide by Magnesium Initiators Bearing Achiral Di(2-pyridyl)methyl Substituted Aminophenolate Ligands.

Reactions of achiral di(2-pyridyl)methyl substituted aminophenols L1-6H (2-{N-R3-N-[di(2-pyridyl)methyl]aminomethyl}-4-R1-6-R2-C6H2OH: R1 = R2 = tBu, R3 = nBu (L1H), R3 = nhexyl (L2H), R3 = cyclohexyl (L3H); R1 = R2 = cumyl, R3 = nBu (L4H), R3 = nhexyl (L5H), R3 = cyclohexyl (L6H)) with {Mg[N(SiMe3)2]2}2 ([L1-6H]:[Mg] = 1:1) afforded a series of magnesium silylamido complexes 1-6. In the solid state, the magnesium center of 3, 4, and 6 is penta-coordinated by the tetradentate aminophenloate ligand and one silylamido ligand to form a seriously distorted square-pyramidal geometry as confirmed by X-ray crystallography diffraction analysis. VT 1H NMR and ROESY experiments further indicate that these magnesium complexes are also five-coordinated in solutions where the coordination of either of the two pyridyl pendants to the magnesium center is maintained. Complexes 1-6 are highly active toward the ring-opening polymerization of rac-lactide (rac-LA) at r.t. both in toluene and in tetrahydrofuran, capable of polymerizing 500 equiv of monomer to high conversions just within minutes. Among them, complex 3 exhibited the highest iso-stereoselectivity, affording moderately isotactic polylactide in toluene (Pm = 0.75). It is found that the isoselectivities and activities of these magnesium complexes toward the polymerization of rac-LA are closely associated with the substituents at the ortho-position of the phenoxide unit and on the skeleton nitrogen atom of the ligand. On the basis of NMR spectroscopic studies, the formation of isotactic PLAs with dominant stereoblock sequences was witnessed by using these magnesium complexes as initiators, and the inequivalent coordination of two pyridyl pendant arms in these magnesium complexes might be the source of exerting isoselective control.

The percentage and clinical correlates of alexithymia in stable patients with schizophrenia.

Alexithymia is a common, but less-recognized affective deficit in patients with schizophrenia. To date, no definitive conclusions have been drawn about the relationship between alexithymia and the clinical symptoms or their clinical correlates, particularly in stable patients with schizophrenia. The purpose of this study was to investigate the link between alexithymia and psychopathological symptoms, as well as any associated correlates, in stable patients with schizophrenia. A total of 435 Chinese patients with schizophrenia were recruited. The Positive and Negative Symptoms Scale (PANSS) was used to evaluate each patient's psychopathological symptoms. The Toronto Alexithymia Scale (TAS-20) was used to measure alexithymia. The percentage of alexithymia was 35.2% in stable patients with schizophrenia. Compared to non-alexithymia patients, patients with alexithymia had higher PANSS total scores, negative subscores, depressive subscores, and cognitive subscores (all p < 0.05). Multivariate regression analysis revealed that the following variables were positively associated with TAS-20 total scores: PANSS negative subscores (ß = 0.274, t = 3.198, p = 0.001) and PANSS depressive subscores (ß = 0.366, t = 2.500, p = 0.013). Education years (ß = - 0.453, t = - 2.824, p = 0.005) was negatively associated with TAS-20 total scores. Our results suggest that the percentage of alexithymia was relatively higher in stable patients with schizophrenia. Education levels, negative symptoms, and depressive symptoms were independently associated with alexithymia in this specific population.

Sex differences in the association between suicidal ideation and neurocognitive function in Chinese patients with schizophrenia.

There is increasing evidence that sex differences exist in many clinical manifestations of patients with schizophrenia, including suicidal ideation (SI) and neurocognitive function. The present study was performed to explore the sex differences in the association between SI and neurocognitive function in Chinese patients with schizophrenia. A total of 1188 inpatients with schizophrenia were recruited from multicenter psychiatric hospitals. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was utilized to evaluate the neurocognitive function of all patients. The Positive and Negative Syndrome Scale (PANSS) was utilized to assess the psychopathology of patients. The Beck Scale for Suicide Ideation (BSSI) was used to assess the severity of SI. In male patients, the suicide risk score was significantly associated with PANSS negative symptoms (r = 0.167, p = 0.043), visuospatial subscale (r = - 0.261, p = 0.001), and RBANS total scores (r = - 0.172, p = 0.037). Furthermore, multivariate linear regression analysis showed that the visuospatial subscale (ß = - 0.490, t = - 3.273, p = 0.001) was independently associated with the suicide risk score in male patients. In female patients, the suicide risk score was significantly correlated with PANSS positive symptoms (r = 0.249, p = 0.021), negative symptoms (r = 0.394, p < 0.001), general psychopathology (r = 0.276, p = 0.01) and PANSS total score (r = 0.365, p = 0.001). Multivariate linear regression analysis showed that PANSS negative symptoms (ß = 1.849, t = 3.933, p = 0.001) were significantly associated with suicide risk scores in female patients. Our findings indicate that there are sex differences in the association between SI and neurocognitive function in patients with schizophrenia. Based on the findings of our study, gender-specific prevention and intervention strategies may make a difference in reducing SI in Chinese schizophrenia patients.

Analysis of EEG features and study of automatic classification in first-episode and drug-naïve patients with major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) has a high incidence and an unknown mechanism. There are no objective and sensitive indicators for clinical diagnosis. OBJECTIVE: This study explored specific electrophysiological indicators and their role in the clinical diagnosis of MDD using machine learning. METHODS: Forty first-episode and drug-naïve patients with MDD and forty healthy controls (HCs) were recruited. EEG data were collected from all subjects in the resting state with eyes closed for 10 min. The severity of MDD was assessed by the Hamilton Depression Rating Scale (HAMD-17). Machine learning analysis was used to identify the patients with MDD. RESULTS: Compared to the HC group, the relative power of the low delta and theta bands was significantly higher in the right occipital region, and the relative power of the alpha band in the entire posterior occipital region was significantly lower in the MDD group. In the MDD group, the alpha band scalp functional connectivity was overall lower, while the scalp functional connectivity in the gamma band was significantly higher than that in the HC group. In the feature set of the relative power of the ROI in each band, the highest accuracy of 88.2% was achieved using the KNN classifier while using PCA feature selection. In the explanatory model using SHAP values, the top-ranking influence feature is the relative power of the alpha band in the left parietal region. CONCLUSIONS: Our findings reveal that the abnormal EEG neural oscillations may reflect an imbalance of excitation, inhibition and hyperactivity in the cerebral cortex in first-episode and drug-naïve patients with MDD. The relative power of the alpha band in the left parietal region is expected to be an objective electrophysiological indicator of MDD.

The Navigation System of a Logistics Inspection Robot Based on Multi-Sensor Fusion in a Complex Storage Environment.

To reliably realize the functions of autonomous navigation and cruise of logistics robots in a complex logistics storage environment, this paper proposes a new robot navigation system based on vision and multiline lidar information fusion, which can not only ensure rich information and accurate map edges, but also meet the real-time and accurate positioning and navigation in complex logistics storage scenarios. Simulation and practical verification showed that the robot navigation system is feasible and robust, and overcomes the problems of low precision, poor robustness, weak portability, and difficult expansion of the mobile robot system in a complex environment. It provides a new idea for inspection in an actual logistics storage scenario and has a good prospective application.

Increased plasma level of kynurenic acid in drug-free patients with first-episode schizophrenia compared to patients with chronic schizophrenia and healthy controls: preliminary data.

BACKGROUND: Kynurenic acid (KYNA) is a metabolite of tryptophan (TRP). KYNA levels have been reported with controversial findings in patients with schizophrenia. AIM: This study aimed to investigate the probable effects of medication and illness chronicity on peripheral KYNA levels in schizophrenia. METHODS: We assessed peripheral (plasma) TRP metabolite levels in 38 drug-free patients with first-episode schizophrenia (FES), 65 patients with chronic schizophrenia (CHS), and 70 healthy controls by using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). The symptom severity of patients was evaluated by using the Positive and Negative Syndrome Scale (PANSS). Finally, we analyzed the association of TRP metabolites with symptom severity. RESULTS: We found significantly higher KYNA levels in FES patients than in both healthy controls (p < 0.01) and CHS patients (p < 0.05). No significant association was observed between plasma TRP metabolite levels and PANSS scores in either FES or CHS patients. CONCLUSIONS: In conclusion, elevated plasma KYNA levels may be a promising biomarker in FES patients. Medication and illness chronicity may affect peripheral KYNA levels with a currently unknown mechanism.

Prevalence of small intestinal bacterial overgrowth in Chinese patients with Parkinson's disease.

Parkinson's disease (PD) is associated with gastrointestinal motility abnormalities that could favor the occurrence of small intestinal bacterial overgrowth (SIBO). The aim of the study was to assess the prevalence of SIBO in Chinese patients with PD and the potential impact of SIBO on gastrointestinal symptoms and motor function. 182 consecutive Chinese patients with PD patients and 200 sex, age, and BMI-matched subjects without PD were included. All participants underwent the glucose breath test to assess SIBO. We examined the associations between factors and SIBO with logistic regression using SPSS. Fifty-five of the 182 PD patients were SIBO positive (30.2 %; 95 % CI 23.5-36.9 %) compared with 19 of 200 in the control group (9.5 %; 95 % CI 5.4-13.6 %); the difference was statistically significant (P < 0.0001; OR 4.13; 95 % CI 2.34-7.29). Motor fluctuations present was higher in the PD patients with SIBO than in the patients without SIBO (70.9 vs. 45.7 %; P = 0.002). Multivariate analysis showed that disease duration, Hoehn and Yahr stage, Unified PD Rating-III score, Unified PD Rating-IV score, and Non-Motor Symptoms Scale score were the factors associated with the SIBO-positive status in PD patients. SIBO was highly prevalent in PD, and nearly one-third was detected. SIBO was associated with worse gastrointestinal symptoms and worse motor function. Further studies are needed to specify the reasons underlying SIBO and worse motor function in PD.

Overweight and Obesity in Young Adulthood and the Risk of Stroke: a Meta-analysis.

BACKGROUND: A systematic review assessing the association between overweight and obesity in young adulthood and stroke risk is lacking. Therefore, we conducted a meta-analysis to evaluate the association between overweight and obesity in young adulthood and stroke risk. METHODS: We systematically searched PubMed and Embase databases for related studies of human subjects in the English language. Two investigators independently selected original studies in a 2-step process. Fixed- and random-effects models were used to calculate pooled relative risks (RRs) and 95% confidence intervals (CIs). Subgroup analyses were also performed. RESULTS: Eight studies met the inclusion criteria. The pooled adjusted RR of stroke was 1.36 (95% CI: 1.28-1.44) for overweight in young adulthood and 1.81 (95% CI: 1.45-2.25) for obesity in young adulthood. In subgroup analyses, overweight and obesity in young adulthood increased the risk of stroke in most groups, except for the group of stroke subtype. For ischemic stroke, the adjusted RR was 1.40 (95% CI: 1.24-1.58) for overweight in young adulthood and 1.78 (95% CI: 1.003-3.16) for obesity in young adulthood, whereas adjusted RR for hemorrhagic stroke was 1.25 (95% CI: .83-1.90) for overweight in young adulthood and 1.80 (95% CI: .97-3.35) for obesity in young adulthood. CONCLUSIONS: Overweight and obesity in young adulthood are associated with an increased risk of stroke, probably, independent of other cardiovascular risk factors. The risk effect gradually increases with increasing body weight.

Controllable π-π coupling of intramolecular dimer models in aggregated states.

π-π coupling as a common interaction plays a key role in emissions, transport and mechanical properties of organic materials. However, the precise control of π-π coupling is still challenging owing to the possible interference from other intermolecular interactions in the aggregated state, usually resulting in uncontrollable emission properties. Herein, with the rational construction of intramolecular dimer models and crystal engineering, π-π coupling can be subtly modulated by conformation variation with balanced π-π and π-solvent interactions and visualized by green-to-blue emission switching. Moreover, it can rapidly respond to temperature, pressure and mechanical force, affording a facile way to modulate π-π coupling in situ. This work contributes to a deeper understanding of the internal mechanism of molecular motions in aggregated states.

Dynamic effective connectivity in the cerebellar dorsal dentate nucleus and the cerebrum, cognitive impairment, and clinical correlates in patients with schizophrenia.

BACKGROUND: Schizophrenia (SZ) is characterized by disconnected cerebral networks. Recent studies have shown that functional connectivity between the cerebellar dorsal dentate nucleus (dDN) and cerebrum is correlated with psychotic symptoms, and processing speed in SZ patients. Dynamic effective connectivity (dEC) is a reliable indicator of brain functional status. However, the dEC between the dDN and cerebrum in patients with SZ remains largely unknown. METHODS: Resting-state functional MRI data, symptom severity, and cognitive performance were collected from 74 SZ patients and 53 healthy controls (HC). Granger causality analysis and sliding time window methods were used to calculate dDN-based dEC maps for all subjects, and k-means clustering was performed to obtain several dEC states. Finally, between-group differences in dynamic effective connectivity variability (dECV) and clinical correlations were obtained using two-sample t-tests and correlation analysis. RESULTS: We detected four dEC states from the cerebrum to the right dDN (IN states) and three dEC states from the right dDN to the cerebrum (OUT states), with SZ group having fewer transitions in the OUT states. SZ group had increased dECV from the right dDN to the right middle frontal gyrus (MFG) and left lingual gyrus (LG). Correlations were found between the dECV from the right dDN to the right MFG and symptom severity and between the dECV from the right dDN to the left LG and working memory performance. CONCLUSIONS: This study reveals a dynamic causal relationship between cerebellar dDN and the cerebrum in SZ and provides new evidence for the involvement of cerebellar neural circuits in neurocognitive functions in SZ.

The relationship between the gut microbiota and oxidative stress in the cognitive function of schizophrenia: A pilot study in China.

Cognitive impairment is a core symptom of schizophrenia. The gut microbiota (GM) and oxidative stress may play important roles in the pathophysiological mechanisms of cognitive impairment. This study aimed to explore the relationship between GM and oxidative stress in the cognitive function of schizophrenia. GM obtained by 16S RNA sequencing and serum superoxide dismutase (SOD) levels from schizophrenia patients (N = 68) and healthy controls (HCs, N = 72) were analyzed. All psychiatric symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). Cognitive function was assessed using the MATRICS Consensus Cognitive Battery (MCCB). Correlation analysis was used to explore the relationship between GM, SOD, and cognitive function. Machine learning models were used to identify potential biomarkers. Compared to HCs, the relative abundances of Collinsella, undefined Ruminococcus, Lactobacillus, Eubacterium, Mogibacterium, Desulfovibrio, Bulleidia, Succinivibrio, Corynebacterium, and Atopobium were higher in patients with schizophrenia, but Faecalibacterium, Anaerostipes, Turicibacter, and Ruminococcus were lower. In patients with schizophrenia, the positive factor, general factor, and total score of MCCB positively correlated with Lactobacillus, Collinsella, and Lactobacillus, respectively; SOD negatively correlated with Eubacterium, Collinsella, Lactobacillus, Corynebacterium, Bulleidia, Mogibacterium, and Succinivibrio, but positively correlated with Faecalibacterium, Ruminococcus, and MCCB verbal learning index scores; Faecalibacterium and Turicibacter were positively correlated with MCCB visual learning index scores and speed of processing index scores, respectively. Our findings revealed a correlation between SOD and GM and confirmed that cognitive dysfunction in patients with schizophrenia involves abnormal SOD levels and GM changes.

Relationships among the gut microbiome, brain networks, and symptom severity in schizophrenia patients: A mediation analysis.

The microbiome-gut-brain axis (MGBA) plays a critical role in schizophrenia (SZ). However, the underlying mechanisms of the interactions among the gut microbiome, brain networks, and symptom severity in SZ patients remain largely unknown. Fecal samples, structural and functional magnetic resonance imaging (MRI) data, and Positive and Negative Syndrome Scale (PANSS) scores were collected from 38 SZ patients and 38 normal controls, respectively. The data of 16S rRNA gene sequencing were used to analyze the abundance of gut microbiome and the analysis of human brain networks was applied to compute the nodal properties of 90 brain regions. A total of 1,691,280 mediation models were constructed based on 261 gut bacterial, 810 nodal properties, and 4 PANSS scores in SZ patients. A strong correlation between the gut microbiome and brain networks (r = 0.89, false discovery rate (FDR) -corrected p < 0.05) was identified. Importantly, the PANSS scores were linearly correlated with both the gut microbiome (r = 0.5, FDR-corrected p < 0.05) and brain networks (r = 0.59, FDR-corrected p < 0.05). The abundance of genus Sellimonas significantly affected the PANSS negative scores of SZ patients via the betweenness centrality of white matter networks in the inferior frontal gyrus and amygdala. Moreover, 19 significant mediation models demonstrated that the nodal properties of 7 brain regions, predominately from the systems of visual, language, and control of action, showed significant mediating effects on the PANSS scores with the gut microbiome as mediators. Together, our findings indicated the tripartite relationships among the gut microbiome, brain networks, and PANSS scores and suggested their potential role in the neuropathology of SZ.

Association between degree centrality and neurocognitive impairments in patients with Schizophrenia: A Longitudinal rs-fMRI Study.

BACKGROUND: Evidence indicates that patients with schizophrenia (SZ) experience significant changes in their functional connectivity during antipsychotic treatment. Despite previous reports of changes in brain network degree centrality (DC) in patients with schizophrenia, the relationship between brain DC changes and neurocognitive improvement in patients with SZ after antipsychotic treatment remains elusive. METHODS: A total of 74 patients with acute episodes of chronic SZ and 53 age- and sex-matched healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS), Symbol Digit Modalities Test, digital span test (DST), and verbal fluency test were used to evaluate the clinical symptoms and cognitive performance of the patients with SZ. Patients with SZ were treated with antipsychotics for six weeks starting at baseline and underwent MRI and clinical interviews at baseline and after six weeks, respectively. We then divided the patients with SZ into responding (RS) and non-responding (NRS) groups based on the PANSS scores (reduction rate of PANSS ≥50%). DC was calculated and analyzed to determine its correlation with clinical symptoms and cognitive performance. RESULTS: After antipsychotic treatment, the patients with SZ showed significant improvements in clinical symptoms, semantic fluency performance. Correlation analysis revealed that the degree of DC increase in the left anterior inferior parietal lobe (aIPL) after treatment was negatively correlated with changes in the excitement score (r = -0.256, p = 0.048, adjusted p = 0.080), but this correlation failed the multiple test correction. Patients with SZ showed a significant negative correlation between DC values in the left aIPL and DST scores after treatment, which was not observed at the baseline (r = -0.359, p = 0.005, adjusted p = 0.047). In addition, we did not find a significant difference in DC between the RS and NRS groups, neither at baseline nor after treatment. CONCLUSIONS: The results suggested that DC changes in patients with SZ after antipsychotic treatment are correlated with neurocognitive performance. Our findings provide new insights into the neuropathological mechanisms underlying antipsychotic treatment of SZ.

Associations of genetic polymorphisms of SAA1 with cerebral infarction.

BACKGROUND: Serum amyloid A protein (SAA) is both an inflammatory factor and an apolipoprotein. However, the relation between genetic polymorphisms of SAA and cerebral infarction (CI) remains unclear. METHODS AND RESULTS: The previously reported 4 Single Nucleotide Polymorphisms (rs12218, rs4638289, rs7131332, and rs11603089) of SAA1 gene were genotyped by TaqMan method in a case-control study including 287 cerebral infarction patients and 376 control subjects. We found rs12218 CC genotype and rs7131332 AA genotype were more frequent among CI patients than among controls (9.76% versus 3.19%, P = 0.001; 32.75% versus 24.20%; p = 0.017; respectively). After adjustment of confounding factors such as sex, age, smoking, drinking, hypertension, diabetes, and lipids profile, the difference remained significant in rs12218 (P < 0.01, OR = 2.106, 95% CI: 1.811-7.121). CONCLUSION: Genetic polymorphism of SAA1 may be a genetic maker of cerebral infarction in Chinese.

Association of serum homocysteine levels with intestinal flora and cognitive function in schizophrenia.

Some studies have indicated that elevated homocysteine (Hcy) levels and intestinal flora may be involved in schizophrenia (SZ) cognition pathophysiology. This study was the first to investigate the association among Hcy, intestinal flora and schizophrenia cognition. Here, 140 individuals were divided into two groups: SZ patients (N = 68) and healthy controls (HCs, N = 72). Participant data on serum Hcy levels, intestinal flora and cognitive function evaluation using the MATRICS Consensus Cognitive Battery (MCCB) were collected. Clinical symptoms of patients were evaluated using the Positive and Negative Syndrome Scale. Serum Hcy levels and the incidence of hyperhomocysteinaemia were considerably increased in SZ patients compared with HCs. Hcy levels were significantly negatively associated with verbal learning index scores (r = -0.425, p < 0.001) but positively associated with Eubacterium (r = 0.32, p = 0.007), Lactobacillus (r = 0.32, p = 0.008), Corynebacterium (r = 0.26, p = 0.035), Mogibacterium (r = 0.31, p = 0.01), and Bulleidia (r = 0.31, p = 0.01) in SZ patients. Our findings suggest that serum Hcy levels are associated with cognitive function and intestinal flora in SZ patients. However, the mechanism of the interaction between Hcy and intestinal flora and its effects on cognitive function in SZ patients requires further investigation.

Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis.

Introduction: Recent studies in human brain connectomics with multimodal magnetic resonance imaging (MRI) data have widely reported abnormalities in brain structure, function and connectivity associated with schizophrenia (SZ). However, most previous discriminative studies of SZ patients were based on MRI features of brain regions, ignoring the complex relationships within brain networks. Methods: We applied a graph convolutional network (GCN) to discriminating SZ patients using the features of brain region and connectivity derived from a combined multimodal MRI and connectomics analysis. Structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 140 SZ patients and 205 normal controls. Eighteen types of brain graphs were constructed for each subject using 3 types of node features, 3 types of edge features, and 2 brain atlases. We investigated the performance of 18 brain graphs and used the TopK pooling layers to highlight salient brain regions (nodes in the graph). Results: The GCN model, which used functional connectivity as edge features and multimodal features (sMRI + fMRI) of brain regions as node features, obtained the highest average accuracy of 95.8%, and outperformed other existing classification studies in SZ patients. In the explainability analysis, we reported that the top 10 salient brain regions, predominantly distributed in the prefrontal and occipital cortices, were mainly involved in the systems of emotion and visual processing. Discussion: Our findings demonstrated that GCN with a combined multimodal MRI and connectomics analysis can effectively improve the classification of SZ at an individual level, indicating a promising direction for the diagnosis of SZ patients. The code is available at https://github.com/CXY-scut/GCN-SZ.git.

Corrigendum: Discriminative analysis of schizophrenia patients using graph convolutional networks: a combined multimodal MRI and connectomics analysis.

[This corrects the article DOI: 10.3389/fnins.2023.1140801.].

Kynurenine pathway metabolites are associated with gray matter volume in subjects with schizophrenia.

Background: There has been growing evidence of the existence of abnormalities in the kynurenine pathway (KP) and structural gray matter volume (GMV) in schizophrenia (SCZ). Numerous studies have suggested that abnormal kynurenine metabolism (KM) in the brain is clearly associated with the pathogenesis of schizophrenia and may be one of the pathological mechanisms of SCZ. In this pilot study, we investigated whether there was a correlation between KP and GMV in schizophrenia patients. Methods: The plasma levels of KM were measured in 41 patients who met the Structured Clinical Interview of the Diagnostic IV criteria for schizophrenia and 60 healthy controls by using liquid chromatography-tandem mass spectrometry, and cortical thickness (as measured via magnetic resonance imaging) was obtained. Results: Our study showed no statistically significant differences in the concentrations of kynurenine (KYN), tryptophan (TRP), and KYNA/TRP (all p > 0.05), but kynurenic acid (KYNA) and the KYNA/KYN ratio were significantly higher in the schizophrenia subjects than in the healthy controls (F = 4.750, p = 0.032; F = 6.153, p = 0.015, respectively) after controlling for age and sex. Spearman's tests showed that KYN concentrations in SCZ patients were negatively correlated with GMV in the left front cingulate belt (r = -0.325, p = 0.046) and that KYN/TRP was negatively correlated with GMV in the left island (r = -0.396, p = 0.014) and right island (r = -0.385, p = 0.017). Conclusion: Our findings appear to provide new insights into the predisposition of an imbalance in the relative metabolism of KYN/TRP and KYN to GMV in schizophrenia.

Violence, neurocognitive function and clinical correlates in patients with schizophrenia.

Background: Schizophrenia patients with violent behavior are a severe public health concern, but the correlates of this violent behavior are unknown. Additionally, the relationship between neurocognitive function and violent behavior in Chinese patients with schizophrenia has not yet been investigated. Methods: A total of 337 schizophrenia inpatients were recruited. The Positive and Negative Syndrome Scale (PANSS) was used to assess psychopathological symptoms. Neurocognitive functioning was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Results: The percentage of violent behavior was 10.4% in patients with schizophrenia. Patients with violent behavior had higher PANSS-positive, excited, and total subscale scores than patients who did not show violent behavior. Patients with violent behavior also had lower RBANS language, semantic fluency, and total subscale scores. Gender (OR = 0.066∼0.819, p = 0.023), illness duration (OR = 0.876∼0.971, p = 0.002), smoking (OR = 1.127∼2.950, p = 0.014), the PANSS positive subscale (OR = 1.050∼1.197, p = 0.001), and the RBANS language subscale (OR = 0.927∼0.987, p = 0.005) significantly contributed to the development of violent behavior in schizophrenia patients. Conclusion: Our findings revealed that cognitive and clinical assessments should be considered in comprehensive assessments of future risks of violence in schizophrenia patients.

Multimodal Magnetic Resonance Imaging Reveals Aberrant Brain Age Trajectory During Youth in Schizophrenia Patients.

Accelerated brain aging had been widely reported in patients with schizophrenia (SZ). However, brain aging trajectories in SZ patients have not been well-documented using three-modal magnetic resonance imaging (MRI) data. In this study, 138 schizophrenia patients and 205 normal controls aged 20-60 were included and multimodal MRI data were acquired for each individual, including structural MRI, resting state-functional MRI and diffusion tensor imaging. The brain age of each participant was estimated by features extracted from multimodal MRI data using linear multiple regression. The correlation between the brain age gap and chronological age in SZ patients was best fitted by a positive quadratic curve with a peak chronological age of 47.33 years. We used the peak to divide the subjects into a youth group and a middle age group. In the normal controls, brain age matched chronological age well for both the youth and middle age groups, but this was not the case for schizophrenia patients. More importantly, schizophrenia patients exhibited increased brain age in the youth group but not in the middle age group. In this study, we aimed to investigate brain aging trajectories in SZ patients using multimodal MRI data and revealed an aberrant brain age trajectory in young schizophrenia patients, providing new insights into the pathophysiological mechanisms of schizophrenia.