Microglia Modulate Neurodevelopment in Autism Spectrum Disorder and Schizophrenia.

Neurodevelopmental disorders (NDDs) include various neurological disorders with high genetic heterogeneity, characterized by delayed or impaired cognition, communication, adaptive behavior, and psychomotor skills. These disorders result in significant morbidity for children, thus burdening families and healthcare/educational systems. However, there is a lack of early diagnosis and effective therapies. Therefore, a more connected approach is required to explore these disorders. Microglia, the primary phagocytic cells within the central nervous system, are crucial in regulating neuronal viability, influencing synaptic dynamics, and determining neurodevelopmental outcomes. Although the neurobiological basis of autism spectrum disorder (ASD) and schizophrenia (SZ) has attracted attention in recent decades, the role of microglia in ASD and SZ remains unclear and requires further discussion. In this review, the important and frequently multifaceted roles that microglia play during neurodevelopment are meticulously emphasized and potential microglial mechanisms that might be involved in conditions such as ASD and SZ are postulated. It is of utmost importance to acquire a comprehensive understanding of the complexities of the interplay between microglia and neurons to design effective, targeted therapeutic strategies to mitigate the effects of NDDs.

Sex Differences in Brain Disorders.

A remarkable feature of the brain is its sexual dimorphism. Sexual dimorphism in brain structure and function is associated with clinical implications documented previously in healthy individuals but also in those who suffer from various brain disorders. Sex-based differences concerning some features such as the risk, prevalence, age of onset, and symptomatology have been confirmed in a range of neurological and neuropsychiatric diseases. The mechanisms responsible for the establishment of sex-based differences between men and women are not fully understood. The present paper provides up-to-date data on sex-related dissimilarities observed in brain disorders and highlights the most relevant features that differ between males and females. The topic is very important as the recognition of disparities between the sexes might allow for the identification of therapeutic targets and pharmacological approaches for intractable neurological and neuropsychiatric disorders.

Insulin-like Growth Factor 2 (IGF-2) and Insulin-like Growth Factor Binding Protein 7 (IGFBP-7) Are Upregulated after Atypical Antipsychotics in Spanish Schizophrenia Patients.

Insulin-like growth factor 2 (IGF-2) and IGF binding protein 7 (IGFBP-7) have been related to schizophrenia (SZ) due to their implication in neurodevelopment. The purpose of this study was to assess whether the alterations in IGF-2 and IGFBP-7 in SZ patients are intrinsically related to the psychiatric disorder itself or are a secondary phenomenon due to antipsychotic treatment. In order to test this hypothesis, we measured plasma IGF-2 and IGFBP-7 in drug-naïve first episode (FE) and multiple episodes or chronic (ME) SZ Caucasian patients who have been following treatment for years. A total of 55 SZ patients (FE = 15, ME = 40) and 45 healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS) and the Self-Assessment Anhedonia Scale (SAAS) were employed to check schizophrenic symptomatology and anhedonia, respectively. Plasma IGF-2 and IGFBP-7 levels were measured by Enzyme-Linked Immunosorbent Assay (ELISA). The FE SZ patients had much lower IGF-2, but not IGFBP-7, than controls. Moreover, both IGF-2 and IGFBP-7 significantly increased after atypical antipsychotic treatment (aripiprazole, olanzapine, or risperidone) in these patients. On the other hand, chronic patients showed higher levels of both proteins when compared to controls. Our study suggests that circulatory IGF-2 and IGFBP-7 increase after antipsychotic treatment, regardless of long-term conditions and being lower in drug-naïve FE patients.

PGC-1α regulate critical period plasticity via gene × environment interaction in the developmental trajectory to schizophrenia.

Genes and environmental conditions are thought to interact in the development of postnatal brain in schizophrenia (SZ). Genome wide association studies have identified that PPARGC1A being one of the top candidate genes for SZ. We previously reported GABAergic neuron-specific PGC-1α knockout mice (Dlx5/6-Cre:PGC-1αfl/fl) presented some characteristic features of SZ. However, there is a fundamental gap of the molecular mechanism by which PGC-1α gene involved in the developmental trajectory to SZ. To explore whether PGC-1α regulates environmental factors interacting with genetic susceptibility to trigger symptom onset and disease progression, PGC-1α deficient mice were utilized to model genetic effect and an additional oxidative stress was induced by GBR injection. We confirm that PGC-1α gene deletion prolongs critical period (CP) timing, as revealed by delaying maturation of PV interneurons (PVIs), including their perineuronal nets (PNNs). Further, we confirm that gene × environment (G × E) influences CP plasticity synergistically and the interaction varies as a function of age, with the most sensitive period being at preweaning stage, and the least sensitive one at early adult age in PGC-1α deficient mice. Along this line, we find that the synergic action of G × E is available in ChABC-infusion PGC-1α KO mice, even though during the adulthood, and the neuroplasticity seems to remain open to fluctuate. Altogether, these results refine the observations made in the PGC-1α deficient mice, a potential mouse model of SZ, and illustrate how PGC-1α regulates CP plasticity via G × E interaction in the developmental trajectory to SZ.

Pharmacoinformatics and molecular docking reveal potential drug candidates against Schizophrenia to target TAAR6.

Schizophrenia (SZ) is a complex disabling disorder that leads to the mental disability and afflicts 1% of the world's total population and placed in top ten medical disorders. In current work, bioinformatics analyses were carried out on Trace amine (TA)-associated receptor 6 (TAAR6) to recognize the potential drugs and compounds against SZ. Comparative modeling and threading-based approaches were utilized for the structure prediction of TAAR6. Fifty-nine predicted structures were evaluated by various model assessment techniques and final model having only eight amino acids in the outlier region and 98.5% overall quality factor was chosen for further pharmacoinformatics and molecular docking analyses. From an extensive literature review, 11 Food and Drug Administration (FDA) approved drugs were analyzed by computational techniques and Aripiprazole was found as the most effective drug against SZ by targeting TAAR6. Here, we report five novel molecules which exhibited the highest binding affinity, effective drug properties, and interestingly, observed better results than the approved selected drugs against SZ by targeting TAAR6. The docking analyses revealed that Arg-92, Trp-98, Gln-191, Thr-192, Ala-290, Cys-291, Tyr-293, and Glu-294 residues were observed as critical interacting residues in receptor-ligand interactions. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, Lipinski rule of five, highest binding affinity coupled with virtual screening (VS), and pharmacophore modeling approach illustrated that aripiprazole (-8.6 kcal/mol) and TAAR6_0094 (-9.3 kcal/mol) are potential inhibitors for targeting TAAR6. It is suggested that schizophrenic patients have to use Aripiprazole for the medication of SZ by targeting TAAR6 and develop effective therapies by utilizing scrutinized novel compound.

Investigation of fasciculation and elongation protein ζ-1 (FEZ1) in peripheral blood reveals differences in gene expression in patients with schizophrenia.

Schizophrenia (SZ) is a chronic neuropsychiatric disorder characterized by affective, neuromorphological and cognitive impairment, deteriorated social functioning and psychosis with underlying molecular abnormalities, including gene expression changes. Observations have suggested that fasciculation and elongation protein ζ-1 (FEZ1) may be implicated in the pathogenesis of schizophrenia. Nevertheless, our current knowledge of the expression of FEZ1 in peripheral blood of schizophrenia patients remains unclear. The purpose of this study was to identify the characteristic gene expression patterns of FEZ1 in peripheral blood samples from schizophrenia patients. We performed quantitative reverse-transcriptase (qRT-PCR) analysis using peripheral blood from drug-free schizophrenia patients (n = 29) and age and gender-matched general population controls (n = 24). For the identification of FEZ1 gene expression patterns, we applied a comparative threshold cycle (CT) method. A statistically significant difference of FEZ1 mRNA level was revealed in schizophrenia subjects compared to healthy controls (p = 0.0034). To the best of our knowledge, this study is the first describing a down-regulation of FEZ1 gene expression in peripheral blood of patients with schizophrenia. Our results suggested a possible functional role of FEZ1 in the pathogenesis of schizophrenia and confirmed the utility of peripheral blood samples for molecular profiling of psychiatric disorders including schizophrenia. The current study describes FEZ1 gene expression changes in peripheral blood of patients with schizophrenia with significantly down-regulation of FEZ1 mRNA. Thus, our results provide support for a model of SZ pathogenesis that includes the effects of FEZ1 expression.

Female specific association between NNMT gene and schizophrenia in a Han Chinese population.

Accumulating evidence has shown that alterations in one carbon metabolism might play an important role in the pathogenesis of schizophrenia (SZ). Nicotinamide-N-methyltransferase (NNMT) is one of the key enzymes of one-carbon metabolism. To examine whether NNMT gene was associated with SZ in Han Chinese population, we selected seven single nucleotide polymorphisms (SNPs) in NNMT gene, and investigated its association with SZ from a cohort of 42 SZ patients and 86 healthy controls by Mass-ARRAY technology. Statistical analyses revealed that one (rs694539) of the SNPs in the female subgroup showed significant difference between SZ patients and controls both in genotypic (p= 0.0170) and allelic frequencies (p = 0.0059). We also found that the frequency of haplotype 'A G G C T C T' in the female patients was significantly higher than in controls (p=0.0015). Our results suggest that NNMT rs694539 may have a role in the etiology of SZ in a Han Chinese female population.

System biology approaches to identify hub genes linked with ECM organization and inflammatory signaling pathways in schizophrenia pathogenesis.

Schizophrenia (SZ) is a chronic and devastating mental illness that affects around 20 million individuals worldwide. Cognitive deficits and structural and functional changes of the brain, abnormalities of brain ECM components, chronic neuroinflammation, and devastating clinical manifestation during SZ are likely etiological factors shown by affected individuals. However, the pathophysiological events associated with multiple regulatory pathways involved in the brain of this complex disorder are still unclear. This study aimed to develop a pipeline based on bioinformatics and systems biology approaches for identifying potential therapeutic targets involving possible biological mechanisms from SZ patients and healthy volunteers. About 420 overlapping differentially expressed genes (DEGs) from three RNA-seq datasets were identified. Gene ontology (GO), and pathways analysis showed several biological mechanisms enriched by the commonly shared DEGs, including extracellular matrix organization (ECM) organization, collagen fibril organization, integrin signaling pathway, inflammation mediated by chemokines and cytokines signaling pathway, and GABA-B receptor II and IL4 mediated signaling. Besides, 15 hub genes (FN1, COL1A1, COL3A1, COL1A2, COL5A1, COL2A1, COL6A2, COL6A3, MMP2, THBS1, DCN, LUM, HLA-A, HLA-C, and FBN1) were discovered by comprehensive analysis, which was mainly involved in the ECM organization and inflammatory signaling pathway. Furthermore, the miRNA target of the hub genes was analyzed with the random-forest-based approach software miRTarBase. In addition, the transcriptional factors and protein kinases regulating overlapping DEGs in SZ, namely, SUZ12, EZH2, TRIM28, TP53, EGR1, CSNK2A1, GSK3B, CDK1, and MAPK14, were also identified. The results point to a new understanding that the hub genes (fibronectin 1, collagen, matrix metalloproteinase-2, and lumican) in the ECM organization and inflammatory signaling pathways may be involved in the SZ occurrence and pathogenesis.

State of the Art in Sub-Phenotyping Midbrain Dopamine Neurons.

Dopaminergic neurons in the ventral tegmental area (VTA) and the substantia nigra pars compacta (SNpc) comprise around 75% of all dopaminergic neurons in the human brain. While both groups of dopaminergic neurons are in close proximity in the midbrain and partially overlap, development, function, and impairments in these two classes of neurons are highly diverse. The molecular and cellular mechanisms underlying these differences are not yet fully understood, but research over the past decade has highlighted the need to differentiate between these two classes of dopaminergic neurons during their development and in the mature brain. This differentiation is crucial not only for understanding fundamental circuitry formation in the brain but also for developing therapies targeted to specific dopaminergic neuron classes without affecting others. In this review, we summarize the state of the art in our understanding of the differences between the dopaminergic neurons of the VTA and the SNpc, such as anatomy, structure, morphology, output and input, electrophysiology, development, and disorders, and discuss the current technologies and methods available for studying these two classes of dopaminergic neurons, highlighting their advantages, limitations, and the necessary improvements required to achieve more-precise therapeutic interventions.

Correlations between omega-3 fatty acids and inflammatory/glial abnormalities: the involvement of the membrane and neurotransmitter dysfunction in schizophrenia.

Introduction: Macrophages or T-lymphocytes triggered inflammation and, consequently, activated glial cells may contribute to neuroinflammation and neurotransmitter dysfunction in schizophrenia (SZ), while omega(n)-3 polyunsaturated fatty acids (PUFAs) can attenuate some SZ symptoms through anti-inflammatory effects. However, the correlations between macrophage/T-lymphocyte-produced cytokines and glia phenotypes, between inflammatory status and PUFAs composition, between cytokines and neurotransmitter function, and between n-3 PUFAs and neurotransmitter abnormality in SZ are unclear. Methods: Changes in T-helper (h) patterns, peripheral macrophage/glial markers, PUFAs profile, membrane fluidity, and neurotransmitter functions were evaluated in SZ patients (n = 50) and healthy controls (n = 30) using ELISA, gas chromatography, fluorescence anisotropy techniques, and HPLC, respectively. Results: Compared to the control, blood lymphocyte proliferation, the concentration of macrophage/microglia phenotype M1 markers, including cytokines IL-1ß, TNF-α (Th1) and IL-6 (Th2), and astrocyte phenotype A1 marker S100ß was significantly increased, while IL-17 and n-3 PUFAs contents, n-3/n-6 ratio, and membrane fluidity (FLU) were significantly decreased in SZ. Moreover, increased DA and HVA, decreased 5-HT and NE, and their metabolites appeared in SZ. Moreover, negative correlations between IL-6 and A2 marker Brain-Derived Neurotrophic Factor (BDNF) or n-3 PUFAs EPA and between IL-1ß and FLU or 5HIAA, while positive correlations between EPA and 5-HIAA and between FLU and DHA were found in SZ. Discussion: These findings showed (1) no clear Th pattern, but pro-inflammatory-dominant immunity occurred; (2) the pro-inflammatory pattern may result in the activated microglia M1 and astrocyte A1 phenotype; and (3) increased pro-inflammatory cytokines were related to decreased n-3 PUFA and decreased membrane fluidity and dysfunctional neurotransmitter systems in SZ.

Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and Their Links to Genetic Risk.

BACKGROUND: Schizophrenia research reveals sex differences in incidence, symptoms, genetic risk factors, and brain function. However, a knowledge gap remains regarding sex-specific schizophrenia alterations in brain function. Schizophrenia is considered a dysconnectivity syndrome, but the dynamic integration and segregation of brain networks are poorly understood. Recent advances in resting-state functional magnetic resonance imaging allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. Nevertheless, estimating time-resolved networks remains challenging due to low signal-to-noise ratio, limited short-time information, and uncertain network identification. METHODS: We adapted a reference-informed network estimation technique to capture time-resolved networks and their dynamic spatial integration and segregation for 193 individuals with schizophrenia and 315 control participants. We focused on time-resolved spatial functional network connectivity, an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to genomic data. RESULTS: Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spatial functional network connectivity exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and is correlated with genetic risk for schizophrenia. This dysfunction is reflected in regions with weak functional connectivity to corresponding networks. CONCLUSIONS: Our method can effectively capture spatially dynamic networks, detect nuanced schizophrenia effects including sex-specific ones, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the clinical potential of dynamic spatial dependence and weak connectivity.

Networks extracted from nonlinear fMRI connectivity exhibit unique spatial variation and enhanced sensitivity to differences between individuals with schizophrenia and controls.

Functional magnetic resonance imaging (fMRI) studies often estimate brain intrinsic connectivity networks (ICNs) from temporal relationships between hemodynamic signals using approaches such as independent component analysis (ICA). While ICNs are thought to represent functional sources that play important roles in various psychological phenomena, current approaches have been tailored to identify ICNs that mainly reflect linear statistical relationships. However, the elements comprising neural systems often exhibit remarkably complex nonlinear interactions that may be involved in cognitive operations and altered in psychiatric conditions such as schizophrenia. Consequently, there is a need to develop methods capable of effectively capturing ICNs from measures that are sensitive to nonlinear relationships. Here, we advance a novel approach to estimate ICNs from explicitly nonlinear whole-brain functional connectivity (ENL-wFC) by transforming resting-state fMRI (rsfMRI) data into the connectivity domain, allowing us to capture unique information from distance correlation patterns that would be missed by linear whole-brain functional connectivity (LIN-wFC) analysis. Our findings provide evidence that ICNs commonly extracted from linear (LIN) relationships are also reflected in explicitly nonlinear (ENL) connectivity patterns. ENL ICN estimates exhibit higher reliability and stability, highlighting our approach's ability to effectively quantify ICNs from rsfMRI data. Additionally, we observed a consistent spatial gradient pattern between LIN and ENL ICNs with higher ENL weight in core ICN regions, suggesting that ICN function may be subserved by nonlinear processes concentrated within network centers. We also found that a uniquely identified ENL ICN distinguished individuals with schizophrenia from healthy controls while a uniquely identified LIN ICN did not, emphasizing the valuable complementary information that can be gained by incorporating measures that are sensitive to nonlinearity in future analyses. Moreover, the ENL estimates of ICNs associated with auditory, linguistic, sensorimotor, and self-referential processes exhibit heightened sensitivity towards differentiating between individuals with schizophrenia and controls compared to LIN counterparts, demonstrating the translational value of our approach and of the ENL estimates of ICNs that are frequently reported as disrupted in schizophrenia. In summary, our findings underscore the tremendous potential of connectivity domain ICA and nonlinear information in resolving complex brain phenomena and revolutionizing the landscape of clinical FC analysis.

Pilot and Feasibility Studies of a Lifestyle Modification Program Based on the Health Belief Model to Prevent the Lifestyle-Related Diseases in Patients with Mental Illness.

In this study we have examined the feasibility of a program based on the health belief model (HBM), for its effectiveness in improving lifestyle-related diseases in patients with schizophrenia (SZ) and bipolar disorder (BD), which are often complicated with physical conditions. In this model, we attempted to enable patients to identify a "threat" and to find "balance between benefits and disadvantages". Subjects were carefully selected from among psychiatric patients by excluding any bias. Thus, the enrolled patients were 30 adult men and women with lifestyle-related diseases, or those with a body mass index (BMI) of over 24. Of these 30 subjects, 15 were randomly assigned to the intervention group and 10 the control group, since 5 subjects in the control voluntarily left from the study. Comparison of the intervention and control groups revealed significant improvement (p < 0.05) in HDL cholesterol in the intervention group. However, there were no significant changes in other variables. These findings support the usefulness and efficacy of HMB-based nutritional interventions for preventing lifestyle-related disorders among psychiatric patients. Further evaluation is needed with a larger sample size and a longer intervention period. This HMB-based intervention could be useful for the general population as well.

Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and its Links to Genetic Risk.

Background: Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects. Methods: We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data. Results: Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks. Conclusions: Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape.

Detection of schizophrenia using hybrid of deep learning and brain effective connectivity image from electroencephalogram signal.

Detection of mental disorders such as schizophrenia (SZ) through investigating brain activities recorded via Electroencephalogram (EEG) signals is a promising field in neuroscience. This study presents a hybrid brain effective connectivity and deep learning framework for SZ detection on multichannel EEG signals. First, the effective connectivity matrix is measured based on the Transfer Entropy (TE) method that estimates directed causalities in terms of brain information flow from 19 EEG channels for each subject. Then, TE effective connectivity elements were represented by colors and formed a 19 × 19 connectivity image which, simultaneously, represents the time and spatial information of EEG signals. Created images are used to be fed into the five pre-trained Convolutional Neural Networks (CNN) models named VGG-16, ResNet50V2, InceptionV3, EfficientNetB0, and DenseNet121 as Transfer Learning (TL) models. Finally, deep features from these TL models equipped with the Long Short-Term Memory (LSTM) model for the extraction of most discriminative spatiotemporal features are used to classify 14 SZ patients from 14 healthy controls. Results show that the hybrid framework of pre-trained CNN-LSTM models achieved higher accuracy than pre-trained CNN models. The highest average accuracy and F1-score were achieved using the EfficientNetB0-LSTM model through the 10-fold cross-validation method equal to 99.90% and 99.93%, respectively. Therefore, the superior performance of the hybrid framework of brain effective connectivity images from EEG signals and pre-trained CNN-LSTM models show that the proposed method is highly capable of detecting SZ patients from healthy controls.

Physical activity and childhood trauma experiences in patients with schizophrenia or bipolar disorders.

BACKGROUND: Physical activity promotes resilience and reduces stress. Here we aimed to clarify the impact of physical activity and childhood trauma experiences on current mood and cognitive function in patients with schizophrenia (SZ) or bipolar disorders (BD). METHODS: Three-hundred-and-six patients with DSM-IV schizophrenia (SZ) or bipolar disorder (BD) were included in the study. Diagnoses were assessed using the Structured Clinical Interview for DSM-IV Axis I disorders (SCID-I). Physical activity was measured as hours spent on any regular physical activity per week. All patients underwent a neuropsychological test battery. History of Childhood trauma was assessed using the Childhood Trauma Questionnaire and mood symptoms were assessed with the Inventory of Depressive Symptoms. RESULTS: Patients with childhood trauma who were physically inactive (˂90 min per week) had the most severe clinical profile, characterised by the highest depressive symptoms (p ˂ 0.001) and lowest performance on working memory tasks (p ˂ 0.001). Among patients with childhood trauma, those who were physically active (≥90 min per week) had better working memory performance than physically inactive patients (p = 0.02). DISCUSSION: A history of childhood trauma was associated with poorer working memory and more depressive symptoms only in patients who were physically inactive, suggesting a possible protective factor of physical activity in severe mental disorder.

Left prefrontal transcranial direct-current stimulation reduces symptom-severity and acutely enhances working memory in schizophrenia.

Recent studies indicated that left dorsolateral prefrontal cortex (DLPFC) transcranial direct current stimulation (tDCS) may improve clinical status and cognitive functioning in schizophrenia patients. The current study examined the effects of left prefrontal anodal tDCS on symptom-severity and on working memory performance in schizophrenia (SZ) patients. We conducted a double-blind, randomized sham-controlled parallel-group trial. Following baseline clinical and WM assessments, 19 chronic SZ patients were randomly assigned to receive 10 sessions of either active left dorsolateral prefrontal cortex (DLPFC) tDCS or sham DLPFC-tDCS across five consecutive days, followed by post-tDCS assessments every four weeks across 12 weeks. Active tDCS significantly alleviated symptom-severity versus baseline and versus sham tDCS. WM-performance improved versus baseline in the active tDCS group. Patients' symptom alleviation was maintained for four weeks after tDCS intervention. Patients' Post-tDCS WM scores were comparable to healthy controls' WM scores. The present findings highlight the benefits of left-prefrontal tDCS interventions and support the association between DLPFC dysfunction and symptom-severity in schizophrenia.

Current and emerging long-acting antipsychotics for the treatment of schizophrenia.

Introduction: In this review, the authors discuss the role of long-acting injectable antipsychotics (LAIs) for schizophrenia, focusing on the effectiveness and new perspectives introduced by such treatment strategy. Despite their promising pharmacokinetic features and their potential advantages in medication adherence, clinical outcomes, and medical costs, LAIs are not habitually presented as an option for patients, especially in the early phase of schizophrenia.Areas covered: This review explores the panorama of available LAIs for the treatment of schizophrenia, first-episode of psychosis, approved indications, medical costs, medication adherence, side effects, effectiveness and differences between first-generation (FGA)-LAIs and second-generation (SGA)-LAIs.Expert Opinion: LAIs differ in terms of specific indications, approved injection sites, needle size, injection volume, injection interval as well as potential drug-drug interactions, and commonly reported adverse reactions. The approved indications have expanded beyond schizophrenia to include bipolar and schizoaffective disorder. SGA-LAIs are often preferred to FGA-LAIs. FGA-LAIs although are less chosen in new patients due to the induction of cognitive and extrapyramidal side effects, even if, on the other hand, many SGA-LAIs are burden by hyperprolactinemia and weight gain. After a review of the available evidence, insight is provided into the potential and current therapeutic opportunities offered by LAI antipsychotic formulations.

Long Non-Coding RNA (lncRNA) Roles in Cell Biology, Neurodevelopment and Neurological Disorders.

Development is a complex process regulated both by genetic and epigenetic and environmental clues. Recently, long non-coding RNAs (lncRNAs) have emerged as key regulators of gene expression in several tissues including the brain. Altered expression of lncRNAs has been linked to several neurodegenerative, neurodevelopmental and mental disorders. The identification and characterization of lncRNAs that are deregulated or mutated in neurodevelopmental and mental health diseases are fundamental to understanding the complex transcriptional processes in brain function. Crucially, lncRNAs can be exploited as a novel target for treating neurological disorders. In our review, we first summarize the recent advances in our understanding of lncRNA functions in the context of cell biology and then discussing their association with selected neuronal development and neurological disorders.

Circular RNA in Schizophrenia and Depression.

Schizophrenia (SZ) and depression (DEP) are two common major psychiatric disorders that are associated with high risk of suicide. These disorders affect not only physical and mental health, but they also affect the social function of the individual. However, diagnoses of SZ and DEP are mainly based on symptomatic changes and the clinical experience of psychiatrists. These rather subjective measures can induce misdiagnoses and missed diagnoses. Therefore, it is necessary to further explore objective indexes for improving the early diagnoses and prognoses of SZ and DEP. Current research indicates that non-coding RNA (ncRNA) may play a role in the occurrence and development of SZ and DEP. Circular RNA (circRNA), as an important component of ncRNA, is associated with many biological functions, especially post-transcriptional regulation. Since circRNA is easily detected in peripheral blood and has a high degree of spatiotemporal tissue specificity and stability, these attributes provide us with a new idea to further explore the potential value for the diagnosis and treatment of SZ and DEP. Here, we summarize the classification, characteristics, and biological functions of circRNA and the most significant results of experimental studies, aiming to highlight the involvement of circRNA in SZ and DEP.