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Atypical antipsychotics have greatly enhanced the treatment of schizophrenia. The mechanisms underlying the effectiveness and adverse effects of these drugs are, to date, not sufficiently explained. This article summarises the hypothetical mechanisms of action of atypical antipsychotics with respect to the neurobiology of schizophrenia.When considering treatment models for schizophrenia, the role of dopamine receptor blockade and modulation remains dominant. The optimal occupancy of dopamine D(2) receptors seems to be crucial to balancing efficacy and adverse effects - transient D(2) receptor antagonism (such as that attained with, for example, quetiapine and clozapine) is sufficient to obtain an antipsychotic effect, while permanent D(2) receptor antagonism (as is caused by conventional antipsychotics) increases the risk of adverse effects such as extrapyramidal symptoms. Partial D(2) receptor agonism (induced by aripiprazole) offers the possibility of maintaining optimal blockade and function of D(2) receptors. Balancing presynaptic and postsynaptic D(2) receptor antagonism (e.g. induced by amisulpride) is another mechanism that can, through increased release of endogenous dopamine in the striatum, protect against excessive blockade of D(2) receptors. Serotonergic modulation is associated with a beneficial increase in striatal dopamine release. Effects on the negative and cognitive symptoms of schizophrenia relate to dopamine release in the prefrontal cortex; this can be modulated by combined D(2) and serotonin 5-HT(2A) receptor antagonism (e.g. by olanzapine and risperidone), partial D(2) receptor antagonism or the preferential blockade of inhibitory dopamine autoreceptors. In the context of the neurodevelopmental disconnection hypothesis of schizophrenia, atypical antipsychotics (in contrast to conventional antipsychotics) induce neuronal plasticity and synaptic remodelling, not only in the striatum but also in other brain areas such as the prefrontal cortex and hippocampus. This mechanism may normalise glutamatergic dysfunction and structural abnormalities and affect the core pathophysiological substrates for schizophrenia.

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Twenty-five years have passed since the major socio-political changes in Central and Eastern Europe and our aim was to map and analyze the development of mental health care practice for people with severe mental illnesses in this region since then. A scoping review was complemented by an expert survey in 24 countries. Mental health care practice in the region differs greatly across as well as within individual countries. National policies often exist but reforms remain mostly in the realm of aspiration. Services are predominantly based in psychiatric hospitals. Decision making on resource allocation is non-transparent, and full economic evaluations of complex interventions and rigorous epidemiological studies are lacking. Stigma seems to be high compared to other European countries, but consideration of human rights and user involvement are increasing. The region has seen respectable development, which occurred due to grassroots initiatives supported by international organizations, rather than due to systematic implementation of government policies.(150 words, unstructured)Funding: This study had no specific funding.

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Background-To translate our knowledge about neuroanatomy of bipolar disorder (BD) into a diagnostic tool, it is necessary to identify the neural signature of predisposition for BD and separate it from effects of long-standing illness and treatment. Thus, we examined the associations among genetic risk, illness burden, lithium treatment, and brain structure in BD.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

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