Metabolic syndrome (MS), which consists of several metabolic abnormalities, is highly prevalent in patients with schizophrenia. According to some studies, MS is characterized by a mild chronic inflammatory state, while for the elevated white blood cell (WBC) and neutrophil counts are considered to be positively associated with MS.

To determine the WBC and neutrophil counts and to establish their possible association with MS and its components in schizophrenic patients.

We conducted a cross-sectional study. The study group consisted of schizophrenic patients from the University Clinical Hospital Mostar (n=100), while the control group consisted of healthy subjects who came to the systematic medical examinations in the Health Center Mostar (n=100). The diagnosis of MS was made according to ATP III criteria, and on that basis the subjects from both groups were divided into two subgroups, one with and one without MS.

Schizophrenic subjects had significantly higher average WBC (p<0,001) and neutrophil (p<0,001) counts compared to the control group. Schizophrenic subjects with MS had significantly higher WBC and neutrophil counts compared to both control subgroups. WBC and neutrophil counts correlated positively with fasting blood glucose level and MS prevalence. There were no significant correlations between WBC or neutrophil counts with the number of MS components.

WBC and neutrophil counts are positively associated with MS prevalence and fasting glucose level. Routine monitoring of these inflamatory indicators might have an important role in predicting MS development in schizophrenic patients.

Previous studies using resting-state functional neuroimaging have revealed alterations in whole-brain images, connectome-wide functional connectivity and graph-based metrics in groups of patients with schizophrenia relative to groups of healthy controls. However, it is unclear which of these measures best captures the neural correlates of this disorder at the level of the individual patient.

Here we investigated the relative diagnostic value of these measures. A total of 295 patients with schizophrenia and 452 healthy controls were investigated using resting-state functional Magnetic Resonance Imaging at five research centres. Connectome-wide functional networks were constructed by thresholding correlation matrices of 90 brain regions, and their topological properties were analyzed using graph theory-based methods. Single-subject classification was performed using three machine learning (ML) approaches associated with varying degrees of complexity and abstraction, namely logistic regression, support vector machine and deep learning technology.

Connectome-wide functional connectivity allowed single-subject classification of patients and controls with higher accuracy (average: 81%) than both whole-brain images (average: 53%) and graph-based metrics (average: 69%). Classification based on connectome-wide functional connectivity was driven by a distributed bilateral network including the thalamus and temporal regions.

These results were replicated across the three employed ML approaches. Connectome-wide functional connectivity permits differentiation of patients with schizophrenia from healthy controls at single-subject level with greater accuracy; this pattern of results is consistent with the ‘dysconnectivity hypothesis’ of schizophrenia, which states that the neural basis of the disorder is best understood in terms of system-level functional connectivity alterations.

Cognitive remediation (CR) training has emerged as a promising approach to improving cognitive deficits in schizophrenia and related psychosis. The limited availability of psychological services for psychosis is a major barrier to accessing this intervention however. This study investigated the effectiveness of a low support, remotely accessible, computerised working memory (WM) training programme in patients with psychosis.

Ninety patients were enrolled into a single blind randomised controlled trial of CR. Effectiveness of the intervention was assessed in terms of neuropsychological performance, social and occupational function, and functional MRI 2 weeks post-intervention, with neuropsychological and social function again assessed 3–6 months post-treatment.

Patients who completed the intervention showed significant gains in both neuropsychological function (measured using both untrained WM and episodic task performance, and a measure of performance IQ), and social function at both 2-week follow-up and 3–6-month follow-up timepoints. Furthermore, patients who completed MRI scanning showed improved resting state functional connectivity relative to patients in the placebo condition.

CR training has already been shown to improve cognitive and social function in patient with psychosis. This study demonstrates that, at least for some chronic but stable outpatients, a low support treatment was associated with gains that were comparable with those reported for CR delivered entirely on a 1:1 basis. We conclude that CR has potential to be delivered even in services in which psychological supports for patients with psychosis are limited.

The aim of this analysis was to compare the effects of 2 atypical antipsychotic agents, lurasidone (80 mg/d or 160 mg/d) and quetiapine XR (600 mg/d), on daytime alertness, and to evaluate the effects of daytime sleepiness on treatment outcomes in patients with an acute exacerbation of schizophrenia.

Patients who met Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision (DSM-IV-TR) criteria for schizophrenia were randomized to 6 weeks of double-blind treatment with fixed doses of lurasidone 80 mg/d (n = 125), lurasidone 160 mg/d (n = 121), quetiapine XR 600 mg/d (n = 119), or placebo (n = 121), all dosed once daily in the evening, with food. Daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS).

Daytime sleepiness improved in the lurasidone and placebo-treated groups but worsened in the quetiapine XR treatment group when compared to placebo (p = 0.001) and to either dose of lurasidone (both p < 0.01). Sedation associated with quetiapine XR treatment mediated an improvement in agitation [assessed by the Positive and Negative Syndrome Scale—Excitement (PANSS-EC) subscale] and a worsening in functional capacity [assessed by the University of California–San Diego (UCSD) Performance-Based Skills Assessment—Brief Version (UPSA-B) total score]; these mediating relationships were not observed for the lurasidone or placebo treatment groups.

In this 6-week double-blind study, treatment with lurasidone 80 mg or 160 mg, administered once daily in the evening, was associated with a reduction in daytime sleepiness similar in magnitude to placebo, while quetiapine XR 600 mg/d was associated with a significant increase in daytime sleepiness, compared to both lurasidone dose groups and placebo. Daytime sleepiness was associated with improvement in agitation and worsening in functional capacity for quetiapine XR, but not lurasidone or placebo-treated patients.

People with psychoses often report fixed, delusional beliefs that are sustained even in the presence of unequivocal contrary evidence. Such delusional beliefs are the result of integrating new and old evidence inappropriately in forming a cognitive model. We propose and test a cognitive model of belief formation using experimental data from an interactive ‘Rock Paper Scissors’ (RPS) game.

Participants (33 controls and 27 people with schizophrenia) played a competitive, time-pressured interactive two-player game (RPS). Participants' behavior was modeled by a generative computational model using leaky integrator and temporal difference methods. This model describes how new and old evidence is integrated to form a playing strategy to beat the opponent and to provide a mechanism for reporting confidence in one's playing strategy to win against the opponent.

People with schizophrenia fail to appropriately model their opponent's play despite consistent (rather than random) patterns that can be exploited in the simulated opponent's play. This is manifest as a failure to weigh existing evidence appropriately against new evidence. Furthermore, participants with schizophrenia show a ‘jumping to conclusions’ (JTC) bias, reporting successful discovery of a winning strategy with insufficient evidence.

The model presented suggests two tentative mechanisms in delusional belief formation: (i) one for modeling patterns in other's behavior, where people with schizophrenia fail to use old evidence appropriately, and (ii) a metacognitive mechanism for ‘confidence’ in such beliefs, where people with schizophrenia overweight recent reward history in deciding on the value of beliefs about the opponent.