The fractional amplitude of low-frequency fluctuations (fALFF) has been widely used as potential clinical biomarkers for resting-state functional magnetic resonance imaging based schizophrenia diagnosis. However, previous studies usually measure the fALFF with specific bands from 0.01-0.08 Hz, which cannot fully delineate the complex variations of spontaneous fluctuations in the resting-state brain. As we konow, fALFF data is intrinsically constrained by the brain structure, but most of the traditional methods have not consider it in feature selection. For addressing these problems, we propose a model to classify schizophrenia in multi-frequency bands with tree-guided group sparse learning. In detail, we first acquire the fALFF data in multi-frequency bands (i.e., slow-5:0.01-0.027 Hz, slow-4:0.027-0.073 Hz, slow-3:0.073-0.198 Hz and slow-2:0.198-0.25 Hz). Then, we divide the whole brain into different candidate patches, and select those significant patches related to schizophrenia using random forest-based importancescore. Moreover, we use tree-structured sparse learning method for feature selection with above patches spatial constraint. Finally, considering biomarkers from multi-frequency bands can reflect complementary information among multiple frequency bands, we adopt the multi-kernel learning (MKL) method to combine features of multi-frequency bands for classification. Our experimental results show that these biomarkers from multi-frequency bands can achieve a classification accuracy of 91.1% on 17 schizophrenia patients and 17 healthy controls, further demonstrating the multi-frequency bands analysis can better account for classification of schizophrenia.

Background: Patients with treatment-resistant schizophrenia (TRS) and non-treatment-resistant schizophrenia (NTRS) respond to antipsychotic drugs differently. Previous studies demonstrated that patients with TRS or NTRS exhibited abnormal neural activity in different brain regions. Accordingly, in the present study, we tested the hypothesis that a regional homogeneity (ReHo) approach could be used to distinguish between patients with TRS and NTRS.Methods: A total of 17 patients with TRS, 17 patients with NTRS, and 29 healthy controls (HCs) matched in sex, age, and education levels were recruited to undergo resting-state functional magnetic resonance imaging (RS-fMRI). ReHo was used to process the data. ANCOVA followed by post-hoc t-tests, receiver operating characteristic curves (ROC), and correlation analyses were applied for the data analysis.Results: ANCOVA analysis revealed widespread differences in ReHo among the three groups in the occipital, frontal, temporal, and parietal lobes. ROC results indicated that the optimal sensitivity and specificity of the ReHo values in the left postcentral gyrus, left inferior frontal gyrus/triangular part, and right fusiform could differentiate TRS from NTRS, TRS from HCs, and NTRS from HCs were 94.12 and 82.35%, 100 and 86.21%, and 82.35 and 93.10%, respectively. No correlation was found between abnormal ReHo and clinical symptoms in patients with TRS or NTRS.Conclusions: TRS and NTRS shared most brain regions with abnormal neural activity. Abnormal ReHo values in certain brain regions might be applied to differentiate TRS from NTRS, TRS from HC, and NTRS from HC with high sensitivity and specificity.

No abstract

Background: Schizophrenia, regarded as a neurodevelopmental disorder, is characterized by positive symptoms, negative symptoms, and cognitive dysfunction. Investigating the spontaneous brain activity in patients with schizophrenia can help us understand the underlying pathophysiologic mechanism of schizophrenia. However, results concerning abnormal neural activities and their correlations with cognitive dysfunction/psychopathology of patients with schizophrenia were inconsistent. Methods: We recruited 57 first-diagnosed and drug-naive patients with schizophrenia and 50 matched healthy controls underwent magnetic resonance imaging. The Positive and Negative Syndrome Scale (PANSS) and the MATRICS Consensus Cognitive Battery were used to assess the psychopathology/cognitive dysfunction. Regional homogeneity (ReHo) was used to explore neural activities. Correlation analyses were calculated between abnormal ReHo values and PANSS scores/standardized cognitive scores. Lastly, support vector machine analyses were conducted to evaluate the accuracy of abnormal ReHo values in distinguishing patients with schizophrenia from healthy controls. Results: Patients with schizophrenia showed cognitive dysfunction, and increased ReHo values in the right gyrus rectus, right inferior frontal gyrus/insula and left inferior frontal gyrus/insula compared with those of healthy controls. The ReHo values in the right inferior frontal gyrus/insula were positively correlated with negative symptom scores and negatively correlated with Hopkins verbal learning test-revised/verbal learning. Our results showed that the combination of increased ReHo values in the left inferior frontal gyrus/insula and right gyrus rectus had 78.5% (84/107) accuracy, 85.96% (49/57) sensitivity, and 70.00% specificity, which were higher than other combinations. Gao et al. ReHo and Cognition/Psychopathology in Schizophrenia Conclusions: Hyperactivities were primarily located in the prefrontal regions, and increased ReHo values in the right inferior frontal gyrus/insula might reflect the severity of negative symptoms and verbal learning abilities. The combined increases of ReHo values in these regions might be an underlying biomarker in differentiating patients with schizophrenia from healthy controls.

The ultimate goal of depression treatment is to achieve functional recovery. Psychosocial functioning is the main component of functional impairment in depressed patients. The concept of psychosocial functioning has an early origin; however, its concept and connotation are still ambiguous, which is the basic and key problem faced by the relevant research and clinical application. In this study, we start from the paradox of symptoms remission and functional recovery, describe the concept, connotation, and characteristics of psychosocial functioning impairment in depressed patients, and re-emphasize its importance in depression treatment to promote research and clinical applications related to psychosocial functioning impairment in depressed patients to achieve functional recovery.

No abstract

Objective Attractin (ATRN) is a widely expressed member of the cell adhesion and guidance protein family in humans that is closely related to cellular immunity and neurodevelopment. However, while previous studies in our laboratory have confirmed the effect of ATRN mutations on long‐term memory, its specific role and the molecular mechanism by which it influences spatial cognition are poorly understood. Methods This study aimed to examine the effect of ATRN mutations on working memory in water maze with a novel ATRN‐mutant rat generated by the CRISPR/Cas9 system; the mutation involved the substitution of the 505th amino acid, glycine (G), with cysteine (C), namely, a mutation from GGC to TGC. The changes in myelin basic protein (MBP) expression in rats were also analyzed with the western blot. Results The ATRN‐G505C(KI/KI) rats exhibited significant increases in the required latency and distance traveled to locate the escape platform in a Morris water maze test of working memory. In addition, the expression of MBP was reduced in ATRN‐mutant rats, as shown in the western blot analysis. Conclusion Our results indicate that ATRN gene mutations may directly lead to the impairment of working memory in the water maze; this impairment may be due to the inhibition of MBP expression, which in turn affects the spatial cognition.

Attractin (ATRN) is a widely expressed glycoprotein that is involved in energy homeostasis, neurodevelopment, and immune response. It is encoded by a gene spanning 180 kb on chromosome 20p13, a region previously implicated in schizophrenia by linkage studies. To address a possible role of ATRN in disorders of the central nervous system, we created an atrn knockout zebrafish line and performed behavioral tests. Adult atrn–/– zebrafish exhibited more pronounced attack behavior relative to wild-type control zebrafish in a tracking analysis. Biochemical analysis revealed elevated testosterone levels in atrn–/– zebrafish. At the gene expression level, we noted an upregulation of cyp51 and hsd17b7, key proteins in testosterone synthesis in the brains of both adult and larvae of atrn–/– zebrafish. In order to further elucidate the relationship between testosterone and behavioral syndromes, we then compared testosterone levels of 9,008 psychiatric patients and 247 healthy controls from the same catchment area. Of all subjects examined, male subjects with schizophrenia exhibited lower testosterone levels compared with controls. In contrast, female subjects with a diagnosis of schizophrenia or bipolar disorder featured higher testosterone levels than did same sex controls. Purposeful sampling of extreme groups showed reduced ATRN expression in a subset of these subjects. Finally, we identified 14 subjects with ATRN mutations. All of whom displayed abnormal testosterone levels. In summary, the interplay of ATRN and testosterone may help to explain sexual dimorphisms in selected behavioral phenotypes.