Serum HMGB1 and Beclin 1 Levels in Patients with a Diagnosis of Schizophrenia. / Sizofreni Tanili Hastalarda Serum HMGB1 ve Beklin 1 Düzeyleri.

OBJECTIVE: It is known that inflammation plays a role in the etiopathogenesis of schizophrenia. In this study, we examined high mobility group box 1 protein (HMGB1) and Beclin 1 levels and their relationship with clinical variables in patients with schizophrenia. METHOD: Forty-three patients with schizophrenia and 43 healthy controls were included in this study. The patients were administered sociodemographic data form, the Positive Negative Symptoms Assessment Scale (PANSS) and the Clinical Global Impressions (CGI) scale. After the scales were filled, venous blood samples were taken from both the patient and control groups to measure serum HMGB1 and Beclin 1 levels. Serum samples obtained at the end of centrifugation were measured by Enzyme-Linked ImmunoSorbent Assay (ELISA) method. RESULTS: The mean serum HMGB1 levels were significantly increased and the mean serum Beclin 1 levels were significantly decreased in the schizophrenia group compared to the control group. In addition, a negative correlation was found between HMGB1 and Beclin 1 levels. CONCLUSION: In conclusion, current research shows that HMGB1 is increased and Beclin 1 is decreased in patients with schizophrenia, and these findings may contribute to the role of autophagy in the pathogenesis of schizophrenia.

A preliminary metabolomics study of the database for biological samples of schizophrenia among Chinese ethnic minorities.

BACKGROUND: Schizophrenia (SCZ) is a profound mental disorder with a multifactorial etiology, including genetics, environmental factors, and demographic influences such as ethnicity and geography. Among these, the studies of SCZ also shows racial and regional differences. METHODS: We first established a database of biological samples for SCZ in China's ethnic minorities, followed by a serum metabolomic analysis of SCZ patients from various ethnic groups within the same region using the LC-HRMS platform. RESULTS: Analysis identified 47 metabolites associated with SCZ, with 46 showing significant differences between Miao and Han SCZ patients. These metabolites, primarily fatty acids, amino acids, benzene, and derivatives, are involved in fatty acid metabolism pathways. Notably, L-Carnitine, L-Cystine, Aspartylphenylalanine, and Methionine sulfoxide demonstrated greater diagnostic efficacy in Miao SCZ patients compared to Han SCZ patients. CONCLUSION: Preliminary findings suggest that there are differences in metabolic levels among SCZ patients of different ethnicities in the same region, offering insights for developing objective diagnostic or therapeutic monitoring strategies that incorporate ethnic considerations of SCZ.

Multiple serum anti-glutamate receptor antibody levels in clozapine-treated/naïve patients with treatment-resistant schizophrenia.

BACKGROUND: Glutamatergic function abnormalities have been implicated in the etiology of treatment-resistant schizophrenia (TRS), and the efficacy of clozapine may be attributed to its impact on the glutamate system. Recently, evidence has emerged suggesting the involvement of immune processes and increased prevalence of antineuronal antibodies in TRS. This current study aimed to investigate the levels of multiple anti-glutamate receptor antibodies in TRS and explore the effects of clozapine on these antibody levels. METHODS: Enzyme linked immunosorbent assay (ELISA) was used to measure and compare the levels of anti-glutamate receptor antibodies (NMDAR, AMPAR, mGlur3, mGluR5) in clozapine-treated TRS patients (TRS-C, n = 37), clozapine-naïve TRS patients (TRS-NC, n = 39), and non-TRS patients (nTRS, n = 35). Clinical symptom severity was assessed using the Positive and Negative Symptom Scale (PANSS), while cognitive function was evaluated using the MATRICS Consensus Cognitive Battery (MCCB). RESULT: The levels of all four glutamate receptor antibodies in TRS-NC were significantly higher than those in nTRS (p < 0.001) and in TRS-C (p < 0.001), and the antibody levels in TRS-C were comparable to those in nTRS. However, no significant associations were observed between antibody levels and symptom severity or cognitive function across all three groups after FDR correction. CONCLUSION: Our findings suggest that TRS may related to increased anti-glutamate receptor antibody levels and provide further evidence that glutamatergic dysfunction and immune processes may contribute to the pathogenesis of TRS. The impact of clozapine on anti-glutamate receptor antibody levels may be a pharmacological mechanism underlying its therapeutic effects.

Theta-burst rTMS in schizophrenia to ameliorate negative and cognitive symptoms: study protocol for a double-blind, sham-controlled, randomized clinical trial.

BACKGROUND: Treatment effects of conventional approaches with antipsychotics or psychosocial interventions are limited when it comes to reducing negative and cognitive symptoms in schizophrenia. While there is emerging clinical evidence that new, augmented protocols based on theta-burst stimulation can increase rTMS efficacy dramatically in depression, data on similar augmented therapies are limited in schizophrenia. The different patterns of network impairments in subjects may underlie that some but not all patients responded to given stimulation locations. METHODS: Therefore, we propose an augmented theta-burst stimulation protocol in schizophrenia by stimulating both locations connected to negative symptoms: (1) the left dorsolateral prefrontal cortex (DLPFC), and (2) the vermis of the cerebellum. Ninety subjects with schizophrenia presenting negative symptoms and aging between 18 and 55 years will be randomized to active and sham stimulation in a 1:1 ratio. The TBS parameters we adopted follow the standard TBS protocols, with 3-pulse 50-Hz bursts given every 200 ms (at 5 Hz) and an intensity of 100% active motor threshold. We plan to deliver 1800 stimuli to the left DLPFC and 1800 stimuli to the vermis daily in two 9.5-min blocks for 4 weeks. The primary endpoint is the change in negative symptom severity measured by the Positive and Negative Syndrome Scale (PANSS). Secondary efficacy endpoints are changes in cognitive flexibility, executive functioning, short-term memory, social cognition, and facial emotion recognition. The difference between study groups will be analyzed by a linear mixed model analysis with the difference relative to baseline in efficacy variables as the dependent variable and treatment group, visit, and treatment-by-visit interaction as independent variables. The safety outcome is the number of serious adverse events. DISCUSSION: This is a double-blind, sham-controlled, randomized medical device study to assess the efficacy and safety of an augmented theta-burst rTMS treatment in schizophrenia. We hypothesize that social cognition and negative symptoms of patients on active therapy will improve significantly compared to patients on sham treatment. TRIAL REGISTRATION: The study protocol is registered at "ClinicalTrials.gov" with the following ID: NCT05100888. All items from the World Health Organization Trial Registration Data Set are registered. Initial release: 10/19/2021.

Psychometric evaluation of the Arabic language version of the Birchwood Insight Scale in patients with schizophrenia.

BACKGROUND: Clinical insight (i.e., impaired insight into illness) is increasingly recognized by the scientific community as a significant contributor to an array of psychological and clinical outcomes in schizophrenia. Therefore, its assessment using a reliable, rapid, easy and economic tool is important for clinical practice. This study proposes to investigate the psychometric properties of an Arabic translation of the Birchwood Insight Scale (BIS) in Arabic-speaking chronic patients with schizophrenia. Our objectives were to identify the most adequate factor structure of the BIS among the several measurement models previously proposed in the literature, verify the reliability and measurement invariance of the BIS across sex groups, and explore the concurrent validity of the BIS through examining its patterns of correlations with psychotic symptoms. METHOD: One hundred seventeen Arabic-speaking chronic, remitted patients with schizophrenia took part in this study. An Arabic translated version of the BIS and the Positive and Negative Syndrome Scale (PANSS) were administered to participants. RESULTS: Confirmatory factor analyses (CFA) showed that, after omitting two items with low loadings (items 1 and 2), the unidimensional factor model of the BIS showed good fit indices and a reliability of α = 0.68 and ω = 0.68. However, analyses failed to show good fit for the full-length one-, two-, and three-factor models of the BIS in its Arabic version. Measurement invariance of the Arabic 6-item one-factor BIS was established between males and females at the configural, metric and scalar levels; no statistically significant difference between males and females was found in terms of BIS scores. Finally, BIS scores correlated significantly with the PANSS scores in our sample, thus demonstrating adequate concurrent validity. CONCLUSION: This study offers valuable additional psychometric information about the BIS based on results of CFA and other analyses in schizophrenia from a non-Western cultural environment. We believe that making the BIS available in Arabic might benefit clinicians working with Arabic-speaking patients with schizophrenia, open new avenues of research and gain a better knowledge into the nature of clinical insight and its relevance to psychopathology.

Simultaneous SERS Sensing of Cysteine and Homocysteine in Blood Based on the CBT-Cys Click Reaction: Toward Precisive Diagnosis of Schizophrenia.

At present, there is a lack of sufficiently specific laboratory diagnostic indicators for schizophrenia. Serum homocysteine (Hcy) levels have been found to be related to schizophrenia. Cysteine (Cys) is a demethylation product in the metabolism of Hcy, and they always coexist with highly similar structures in vivo. There are few reports on the use of Cys as a diagnostic biomarker for schizophrenia in collaboration with Hcy, mainly because the rapid, economical, accurate, and high-throughput simultaneous detection of Cys and Hcy in serum is highly challenging. Herein, a click reaction-based surface-enhanced Raman spectroscopy (SERS) sensor was developed for simultaneous and selective detection of Cys and Hcy. Through the efficient and specific CBT-Cys click reaction between the probe containing cyan benzothiazole and Cys/Hcy, the tiny methylene difference between the molecular structures of Cys and Hcy was converted into the difference between the ring skeletons of the corresponding products that could be identified by plasmonic silver nanoparticle enhanced molecular fingerprint spectroscopy to realize discriminative detection. Furthermore, the SERS sensor was successfully applied to the detection in related patient serum samples, and it was found that the combined analysis of Cys and Hcy can improve the diagnostic accuracy of schizophrenia compared to a single indicator.

Assessment of sarcopenic obesity as a predictor of pneumonia in patients with stable schizophrenia-A prospective study.

OBJECTIVE: The European Society for Clinical Nutrition and Metabolism (ESPEN) and the European Association for the Study of Obesity (EASO) recently released the first international consensus on the diagnostic criteria for Sarcopenic obesity (SO). The present study aimed to explore the ability of SO to predict the risk of pneumonia in patients with stable schizophrenia. METHODS: This was a prospective study involving hospitalized patients with schizophrenia aged ≥50 years from two mental health centers in western China. Baseline patient data were collected from September 1 to September 30, 2020. Follow-up data on pneumonia were collected from October 2020 to October 2022. The diagnosis of SO was based on the ESPEN/EASO criteria. Patients were assessed for handgrip strength (HGS), skeletal muscle mass/weight (SMM/W), and fat mass percentage (FM%). Logistic regression analysis was used to explore the effect of SO on the risk of pneumonia in patients with stable schizophrenia. RESULTS: A total of 320 patients with stable schizophrenia were included. Of these, 74 (23.13%) were diagnosed with SO, while 117 (36.56%) developed pneumonia. Compared with patients in the non-low HGS, non-low HGS + non-low SMM/W (or non-low HGS + low SMM/W or low HGS + non-low SMM/W) and non-SO groups, the proportions of patients with pneumonia in the low HGS (42.3% vs. 25.9%, p = 0.004), low HGS + low SMM/W (45.3% vs. 33.3%, p = 0.048), and SO (47.3% vs. 33.3%, p = 0.029) groups, respectively, were higher. However, there was no difference in the proportion of patients with pneumonia in the low SMM/W group and the obese group compared with the non-low SMM/W and non-obese groups. Further logistic regression analysis after adjustment for potential influencing factors showed that compared with the non-low HGS group, patients in the low HGS group had a higher risk of pneumonia (OR = 1.892, 95%CI: 1.096-3.264). CONCLUSION: SO defined according to the ESPEN/EASO criteria was not found to be significantly associated with the development of pneumonia in patients with stable schizophrenia. Further verification of these results is needed with larger sample sizes and the establishment of a cutoff value for this population.

Studying the relationship between intelligence quotient and schizophrenia polygenic scores in a family design with first-episode psychosis population.

BACKGROUND: The intelligence quotient (IQ) of patients with first-episode psychosis (FEP) and their unaffected relatives may be related to the genetic burden of schizophrenia (SCZ). The polygenic score approach can be useful for testing this question. AIM: To assess the contribution of the polygenic risk scores for SCZ (PGS-SCZ) and polygenic scores for IQ (PGS-IQ) to the individual IQ and its difference from the mean IQ of the family (named family-IQ) through a family-based design in an FEP sample. METHODS: The PAFIP-FAMILIES sample (Spain) consists of 122 FEP patients, 131 parents, 94 siblings, and 176 controls. They all completed the WAIS Vocabulary subtest for IQ estimation and provided a DNA sample. We calculated PGS-SCZ and PGS-IQ using the continuous shrinkage method. To account for relatedness in our sample, we performed linear mixed models. We controlled for covariates potentially related to IQ, including age, years of education, sex, and ancestry principal components. RESULTS: FEP patients significantly deviated from their family-IQ. FEP patients had higher PGS-SCZ than other groups, whereas the relatives had intermediate scores between patients and controls. PGS-IQ did not differ between groups. PGS-SCZ significantly predicted the deviation from family-IQ, whereas PGS-IQ significantly predicted individual IQ. CONCLUSIONS: PGS-SCZ discriminated between different levels of genetic risk for the disorder and was specifically related to patients' lower IQ in relation to family-IQ. The genetic background of the disorder may affect neurocognition through complex pathological processes interacting with environmental factors that prevent the individual from reaching their familial cognitive potential.

Automating the analysis of facial emotion expression dynamics: A computational framework and application in psychotic disorders.

Facial emotion expressions play a central role in interpersonal interactions; these displays are used to predict and influence the behavior of others. Despite their importance, quantifying and analyzing the dynamics of brief facial emotion expressions remains an understudied methodological challenge. Here, we present a method that leverages machine learning and network modeling to assess the dynamics of facial expressions. Using video recordings of clinical interviews, we demonstrate the utility of this approach in a sample of 96 people diagnosed with psychotic disorders and 116 never-psychotic adults. Participants diagnosed with schizophrenia tended to move from neutral expressions to uncommon expressions (e.g., fear, surprise), whereas participants diagnosed with other psychoses (e.g., mood disorders with psychosis) moved toward expressions of sadness. This method has broad applications to the study of normal and altered expressions of emotion and can be integrated with telemedicine to improve psychiatric assessment and treatment.

Taste dysfunction as a predictor of depression in schizophrenia: A systematic review and meta-analysis.

OBJECTIVE: This study aims to investigate the relationship between taste dysfunction and depression among patients with schizophrenia, to achieve early detection of depression in clinical practice. METHODS: Following PRISMA guidance, a comprehensive literature search was conducted globally, covering papers published from 1961 to June 2023. A total of 17 manuscripts were selected through meta-analysis and sensitivity analysis after examining available materials from seven databases to determine the correlation between depression and taste dysfunction. RESULTS: The comparison of the 17 selected manuscripts revealed that individuals with gustatory dysfunction may be more likely to experience depressive symptoms (SMD, 0.51, 95% CI, 0.08 to 0.93, p = 0.02). Depression is associated with taste dysfunction in certain aspects, as indicated by the pleasantness ratings of sucrose solutions (SMD, -0.53, 95% confidence interval [CI] -1.11 to 0.05, p = 0.08), gustatory identification ability (SMD, 0.96, 95% CI, 0.03 to 1.89, p = 0.04), and the perception threshold of sweet taste (MD, 0.80, 95% CI, 0.79 to 0.81, p < 0.00001). CONCLUSIONS: Due to variations in the methods, designs, and selection criteria employed in the included studies, it is necessary to establish a feasible framework. Future research using detailed and targeted approaches can provide clearer and more unified conclusions on the relationship between taste dysfunction and depression. Moreover, further high-quality research is needed to obtain clearer conclusions and explore the potential of taste dysfunction as an effective tool for early screening of depression. TRIAL REGISTRATION: This review has been registered in the PROSPERO on April 2022 with the identifier CRD42023400172.

Speech markers to predict and prevent recurrent episodes of psychosis: A narrative overview and emerging opportunities.

Preventing relapse in schizophrenia improves long-term health outcomes. Repeated episodes of psychotic symptoms shape the trajectory of this illness and can be a detriment to functional recovery. Despite early intervention programs, high relapse rates persist, calling for alternative approaches in relapse prevention. Predicting imminent relapse at an individual level is critical for effective intervention. While clinical profiles are often used to foresee relapse, they lack the specificity and sensitivity needed for timely prediction. Here, we review the use of speech through Natural Language Processing (NLP) to predict a recurrent psychotic episode. Recent advancements in NLP of speech have shown the ability to detect linguistic markers related to thought disorder and other language disruptions within 2-4 weeks preceding a relapse. This approach has shown to be able to capture individual speech patterns, showing promise in its use as a prediction tool. We outline current developments in remote monitoring for psychotic relapses, discuss the challenges and limitations and present the speech-NLP based approach as an alternative to detect relapses with sufficient accuracy, construct validity and lead time to generate clinical actions towards prevention.

A naturalistic cohort study of first-episode schizophrenia spectrum disorder: A description of the early phase of illness in the PSYSCAN cohort.

BACKGROUND: We examined the course of illness over a 12-month period in a large, international multi-center cohort of people with a first-episode schizophrenia spectrum disorder (FES) in a naturalistic, prospective study (PSYSCAN). METHOD: Patients with a first episode of schizophrenia, schizoaffective disorder (depressive type) or schizophreniform disorder were recruited at 16 institutions in Europe, Israel and Australia. Participants (N = 304) received clinical treatment as usual throughout the study. RESULTS: The mean age of the cohort was 24.3 years (SD = 5.6), and 67 % were male. At baseline, participants presented with a range of intensities of psychotic symptoms, 80 % were taking antipsychotic medication, 68 % were receiving psychological treatment, with 46.5 % in symptomatic remission. The mean duration of untreated psychosis was 6.2 months (SD = 17.0). After one year, 67 % were in symptomatic remission and 61 % were in functional remission, but 31 % had been readmitted to hospital at some time after baseline. In the cohort as a whole, depressive symptoms remained stable over the follow-up period. In patients with a current depressive episode at baseline, depressive symptoms slightly improved. Alcohol, tobacco and cannabis were the most commonly used substances, with daily users of cannabis ranging between 9 and 11 % throughout the follow-up period. CONCLUSIONS: This study provides valuable insight into the early course of a broad range of clinical and functional aspects of illness in FES patients in routine clinical practice.

Association between elevated serum matrix metalloproteinase-2 and tumor necrosis factor-α, and clinical symptoms in male patients with treatment-resistant and chronic medicated schizophrenia.

BACKGROUND: Inflammation has an important role in the pathogenesis of schizophrenia. The aim of this study was to investigate the levels of tumor necrosis factor (TNF) and matrix metalloproteinase-2 (MMP-2) in male patients with treatment-resistant schizophrenia (TRS) and chronic medicated schizophrenia (CMS), and the relationship with psychopathology. METHODS: The study enrolled 31 TRS and 49 cm male patients, and 53 healthy controls. Serum MMP-2 and TNF-α levels were measured by the Luminex liquid suspension chip detection method. Positive and Negative Syndrome Scale (PANSS) scores were used to evaluate symptom severity and Repeatable Battery for the Assessment of Neuropsychological Status was used to assess cognitive function. RESULTS: Serum TNF-α and MMP-2 levels differed significantly between TRS, CMS and healthy control patients (F = 4.289, P = 0.016; F = 4.682, P = 0.011, respectively). Bonferroni correction demonstrated that serum TNF-α levels were significantly elevated in CMS patients (P = 0.022) and MMP-2 levels were significantly higher in TRS patients (P = 0.014) compared to healthy controls. In TRS patients, TNF-α was negatively correlated with age (r=-0.435, P = 0.015) and age of onset (r=-0.409, P = 0.022). In CMS patients, MMP-2 and TNF-α were negatively correlated with PANSS negative and total scores, and TNF-α was negatively correlated with PANSS general psychopathology scores (all P < 0.05). MMP-2 levels were positively correlated with TNF-α levels (P < 0.05), but not with cognitive function (P > 0.05). CONCLUSION: The results indicate the involvement of inflammation in the etiology of TRS and CMS. Further studies are warranted.

Quantum Machine-Based Decision Support System for the Detection of Schizophrenia from EEG Records.

Schizophrenia is a serious chronic mental disorder that significantly affects daily life. Electroencephalography (EEG), a method used to measure mental activities in the brain, is among the techniques employed in the diagnosis of schizophrenia. The symptoms of the disease typically begin in childhood and become more pronounced as one grows older. However, it can be managed with specific treatments. Computer-aided methods can be used to achieve an early diagnosis of this illness. In this study, various machine learning algorithms and the emerging technology of quantum-based machine learning algorithm were used to detect schizophrenia using EEG signals. The principal component analysis (PCA) method was applied to process the obtained data in quantum systems. The data, which were reduced in dimensionality, were transformed into qubit form using various feature maps and provided as input to the Quantum Support Vector Machine (QSVM) algorithm. Thus, the QSVM algorithm was applied using different qubit numbers and different circuits in addition to classical machine learning algorithms. All analyses were conducted in the simulator environment of the IBM Quantum Platform. In the classification of this EEG dataset, it is evident that the QSVM algorithm demonstrated superior performance with a 100% success rate when using Pauli X and Pauli Z feature maps. This study serves as proof that quantum machine learning algorithms can be effectively utilized in the field of healthcare.

A quality improvement program for managing clozapine-induced constipation in a long-term structured residential setting for persons with serious mental illness.

OBJECTIVES: The goal of this quality improvement project (QIP) was to increase awareness of the serious medical consequences of clozapine-associated constipation to front line nursing staff and patients with schizophrenia. METHODS: The QIP was developed iteratively by psychiatric nurses, psychiatrists and pharmacists with input from patients. The processes involved a literature review, development of educational materials for staff and patients, and the creation of a daily bowel movements log (BML). Implementation involved review of the BML at treatment team meetings, and deployment of pharmacological and non-pharmacological interventions to resolve constipation and increase awareness and knowledge of this clinical concern. OUTCOMES: The initial pilot screened for symptoms of constipation in patients receiving clozapine and non-clozapine antipsychotic agents and intervening as necessary during multidisciplinary team meetings. Patients benefited from relief of constipation and improved bowel habits. Staff benefited from improved knowledge and making requisite changes in workflow and practice. Feedback allowed refinements to be made to the educational materials for patients and staff. Since full implementation, bowel habits are routinely monitored, and interventions are reviewed for effectiveness. Staff satisfaction with this QIP is reflected in answers to a structured questionnaire and in patient reports (n = 50). CONCLUSIONS: Clozapine, the only approved and efficacious medication for treatment-resistant schizophrenia is significantly underutilized. Medically consequential constipation can be a serious barrier to retention of patients benefiting from clozapine. Increased awareness and use of educational materials for patients and staff, routine monitoring of bowel habits combined with pharmacological and non-pharmacological interventions can successfully address this clinical problem.

[The relationship between the functional state of the brain and clinical and constitutional factors in schizophrenia]. / Svyaz' funktsional'nogo sostoyaniya golovnogo mozga s klinicheskimi i konstitutsional'nymi faktorami pri shizofrenii.

OBJECTIVE: To establish the relationships of functional changes of the brain of patients with schizophrenia with clinical manifestations of the disease and their constitutional and morphological features. MATERIAL AND METHODS: One hundred and eighteen patients with schizophrenia (64 men and 54 women), aged 33 [29; 40], years were examined. The following clinical and dynamic parameters were used: age of manifestation of the disease, duration of the disease, severity of clinical and psychopathological symptoms according to the PANSS. The anthropometric examination of patients was carried out according to V.V. Bunak's method in V.P. Chitetsov's modification for adult samples with calculation of Rees-Eysenk and Tanner indices. The EEG was recorded and analyzed in a state of calm, relaxed wakefulness with closed eyes with the calculation of the absolute spectral power for theta (4-7 Hz), alpha (8-13 Hz) and beta (14-30 Hz) rhythms. RESULTS: Significant (p<0.05) direct correlations between the age of the disease manifestation and the spectral power of the beta rhythm in the frontal leads (Fp1, Fp2, F3 and F4) were revealed. Inverse correlations (p<0.05) were found between the duration of the disease in patients with schizophrenia and the spectral power of the alpha rhythm in the left temporal (T3) and right central leads (C4), the spectral power of the beta rhythm in the parietal-occipital (P3, P4, O1,O2) and temporal leads (T3, T4, T5), the spectral power of the theta rhythm in the left occipital (O1) and posterior temporal leads (T5). Significant inverse correlations were also found between the Tanner index and the spectral power of the alpha rhythm in the frontal and temporal leads, between the Rees-Eysenk index and the spectral power of the theta rhythm in the frontal leads. CONCLUSION: The results indicate the presence of the conjugation of functional changes in the brain of patients with schizophrenia with clinical manifestations of the disease and their constitutional and morphological features. Thus, the assessment of the functional state of the central nervous system in patients with schizophrenia is an important component of the diagnostic search.

No relations between executive functions and dimensional models of psychopathology or is time the missing link?

Impaired executive functions (EF) have been found within various mental disorders (e.g., attention deficit hyperactivity disorder, autism spectrum disorder, schizophrenia spectrum disorders) as described in DSM-5. However, although impaired EF has been observed within several categories of mental disorders, empirical research on direct relations between EF and broader dimension of psychopathology is still scarce. Therefore, in the current investigation we examined relations between three EF performance tasks and self-reported dimensions of psychopathology (i.e., the internalizing, externalizing, and thought disorder spectra) in a combined dataset of patients with a broad range of mental disorders (N = 440). Despite previously reported results that indicate impaired EF in several categories of mental disorders, in this study no direct relations were found between EF performance tasks and self-reported broader dimensions of psychopathology. These results indicate that relations between EF and psychopathology could be more complex and non-linear in nature. We evaluate the need for integration of EF and dimensional models of psychopathology and reflect on EF as a possible transdiagnostic factor of psychopathology.

From periphery immunity to central domain through clinical interview as a new insight on schizophrenia.

Identifying disease predictors through advanced statistical models enables the discovery of treatment targets for schizophrenia. In this study, a multifaceted clinical and laboratory analysis was conducted, incorporating magnetic resonance spectroscopy with immunology markers, psychiatric scores, and biochemical data, on a cohort of 45 patients diagnosed with schizophrenia and 51 healthy controls. The aim was to delineate predictive markers for diagnosing schizophrenia. A logistic regression model was used, as utilized to analyze the impact of multivariate variables on the prevalence of schizophrenia. Utilization of a stepwise algorithm yielded a final model, optimized using Akaike's information criterion and a logit link function, which incorporated eight predictors (White Blood Cells, Reactive Lymphocytes, Red Blood Cells, Glucose, Insulin, Beck Depression score, Brain Taurine, Creatine and Phosphocreatine concentration). No single factor can reliably differentiate between healthy patients and those with schizophrenia. Therefore, it is valuable to simultaneously consider the values of multiple factors and classify patients using a multivariate model.