DN interaction from meson exchange

A model of the DN interaction is presented which is developed in close analogy to the meson-exchange KbarN potential of the Juelich group utilizing SU(4) symmetry constraints. The main ingredients of the interaction are provided by vector meson (rho, omega) exchange and higher-order box diagrams involving D*N, D\Delta, and D*\Delta intermediate states. The coupling of DN to the pi-Lambda_c and pi-Sigma_c channels is taken into account. The interaction model generates the Lambda_c(2595) resonance dynamically as a DN quasi-bound state. Results for DN total and differential cross sections are presented and compared with predictions of an interaction model that is based on the leading-order Weinberg-Tomozawa term. Some features of the Lambda_c(2595) resonance are discussed and the role of the near-by pi-Sigma_c threshold is emphasized. Selected predictions of the orginal KbarN model are reported too. Specifically, it is pointed out that the model generates two poles in the partial wave corresponding to the Lambda(1405) resonance.Comment: 14 pages, 8 figure

Impact of previous tobacco use with or without cannabis on first psychotic experiences in patients with first-episode psychosis

Objective: There is high prevalence of cigarette smoking in individuals with first-episode psychosis (FEP) prior to psychosis onset. The purpose of the study was to determine the impact of previous tobacco use with or without cannabis on first psychotic experiences in FEP and the impact of this use on age of onset of symptoms, including prodromes. Methods: Retrospective analyses from the naturalistic, longitudinal, multicentre, “Phenotype-Genotype and Environmental Interaction. Application of a Predictive Model in First Psychotic Episodes (PEPs)” Study. The authors analysed sociodemographic/clinical data of 284 FEP patients and 231 matched healthy controls, and evaluated first psychotic experiences of patients using the Symptom Onset in Schizophrenia Inventory. Results: FEP patients had significantly higher prevalence of tobacco, cannabis, and cocaine use than controls. The FEP group with tobacco use only prior to onset (N = 56) had more sleep disturbances (42.9% vs 18.8%, P = 0.003) and lower prevalence of negative symptoms, specifically social withdrawal (33.9% vs 58%, P = 0.007) than FEP with no substance use (N = 70), as well as lower prevalence of ideas of reference (80.4% vs 92.4%, P = 0.015), perceptual abnormalities (46.4% vs 67.4%, P = 0.006), hallucinations (55.4% vs 71.5%, P = 0.029), and disorganised thinking (41.1% vs 61.1%, P = 0.010) than FEP group with previous tobacco and cannabis use (N = 144). FEP patients with cannabis and tobacco use had lower age at first prodromal or psychotic symptom (mean = 23.73 years [SD = 5.09]) versus those with tobacco use only (mean = 26.21 [SD = 4.80]) (P = 0.011). Conclusions: The use of tobacco alone was not related to earlier age of onset of a first psychotic experience, but the clinical profile of FEP patients is different depending on previous tobacco use with or without cannabis. © 2021 The Author

A longitudinal study of gene expression in first-episode schizophrenia; exploring relapse mechanisms by co-expression analysis in peripheral blood

Little is known about the pathophysiological mechanisms of relapse in first-episode schizophrenia, which limits the study of potential biomarkers. To explore relapse mechanisms and identify potential biomarkers for relapse prediction, we analyzed gene expression in peripheral blood in a cohort of first-episode schizophrenia patients with less than 5 years of evolution who had been evaluated over a 3-year follow-up period. A total of 91 participants of the 2EPs project formed the sample for baseline gene expression analysis. Of these, 67 provided biological samples at follow-up (36 after 3 years and 31 at relapse). Gene expression was assessed using the Clariom S Human Array. Weighted gene co-expression network analysis was applied to identify modules of co-expressed genes and to analyze their preservation after 3 years of follow-up or at relapse. Among the 25 modules identified, one module was semi-conserved at relapse (DarkTurquoise) and was enriched with risk genes for schizophrenia, showing a dysregulation of the TCF4 gene network in the module. Two modules were semi-conserved both at relapse and after 3 years of follow-up (DarkRed and DarkGrey) and were found to be biologically associated with protein modification and protein location processes. Higher expression of DarkRed genes was associated with higher risk of suffering a relapse and early appearance of relapse (p = 0.045). Our findings suggest that a dysregulation of the TCF4 network could be an important step in the biological process that leads to relapse and suggest that genes related to the ubiquitin proteosome system could be potential biomarkers of relapse. © 2021, The Author(s)

Three-dimensional full automated software in the evaluation of the left ventricle function: from theory to clinical practice

Left ventricular systolic function evaluation is an essential part of all transthoracic echocardiographic (TTE) studies. 3D echocardiography (3DE) is superior to 2D and is recommended as the method of choice. However, since it is time consuming and requires training, it is rarely performed. Different automatic analysis software tries to overcome these limitations but they need to be accurate and reproducible before they can be used clinically. The aim of this study was to test the accuracy and reproducibility of new 3D automatic quantitative software in everyday clinical practice. 69 patients referred to our Echo Lab for a clinically indicated echocardiographic examination were included. All patients underwent a full TTE with 3D image acquisition. Left ventricular volumes and ejection fraction (LVEF) were obtained using Heart Model software, and compared with conventional 3D volumetric data. Automated analysis was performed using three different sliders setting, with or without regional editing if necessary. 20 patients underwent a cardiac magnetic resonance (CMR) study the same day of the echo and automated measurements were also compared with a CMR reference. Intra- and inter-technique comparisons including linear regression with Pearson correlation coefficients and Bland–Altman analyses were calculated. Mean age of the patients was 59 years, with 49.3% male. The automated 3DE model demonstrated excellent correlation with the conventional 3DE measurements of LVEF, using three different sliders settings (r = 0.906; r = 0.898 and r = 0.940). Correlations with CMR values were very good as well (r = 0.888; r = 0.869; r = 0.913). Similarly, no significant differences were noted between the values of EDV and ESV, measured with the automated model or CMR, with excellent correlation (EDV: r = 0.892, r = 0.842, 0.910; ESV: r = 0.925, r = 0.860, r = 0.907). Finally, volumes calculated with the automated software were significantly greater than those obtained manually, but they showed a very good correlation (EDV: r = 0.875, r = 0.856, r = 0.891; ESV: r = 0.929, r = 0.879, r = 949). 3D automatic software for LV quantification is feasible and shows excellent correlations with both CMR and 3D echocardiography, considered the gold standard. No clinically relevant differences were noted when applying different border settings. This technique holds promise to facilitate the integration of 3D TTE into clinical practice

Impact of previous tobacco use with or without cannabis on first psychotic experiences in patients with first-episode psychosis

Altres ajuts: Ministerio de Economía y Competitividad; Fondo Europeo de Desarrollo Regional (FEDER "A Way of Shaping Europe"); Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM).Objective: There is high prevalence of cigarette smoking in individuals with first-episode psychosis (FEP) prior to psychosis onset. The purpose of the study was to determine the impact of previous tobacco use with or without cannabis on first psychotic experiences in FEP and the impact of this use on age of onset of symptoms, including prodromes. Methods: Retrospective analyses from the naturalistic, longitudinal, multicentre, "Phenotype-Genotype and Environmental Interaction. Application of a Predictive Model in First Psychotic Episodes (PEPs)" Study. The authors analysed sociodemographic/clinical data of 284 FEP patients and 231 matched healthy controls, and evaluated first psychotic experiences of patients using the Symptom Onset in Schizophrenia Inventory. Results: FEP patients had significantly higher prevalence of tobacco, cannabis, and cocaine use than controls. The FEP group with tobacco use only prior to onset (N = 56) had more sleep disturbances (42.9% vs 18.8%, P = 0.003) and lower prevalence of negative symptoms, specifically social withdrawal (33.9% vs 58%, P = 0.007) than FEP with no substance use (N = 70), as well as lower prevalence of ideas of reference (80.4% vs 92.4%, P = 0.015), perceptual abnormalities (46.4% vs 67.4%, P = 0.006), hallucinations (55.4% vs 71.5%, P = 0.029), and disorganised thinking (41.1% vs 61.1%, P = 0.010) than FEP group with previous tobacco and cannabis use (N = 144). FEP patients with cannabis and tobacco use had lower age at first prodromal or psychotic symptom (mean = 23.73 years [SD = 5.09]) versus those with tobacco use only (mean = 26.21 [SD = 4.80]) (P = 0.011). Conclusions: The use of tobacco alone was not related to earlier age of onset of a first psychotic experience, but the clinical profile of FEP patients is different depending on previous tobacco use with or without cannabis

The contribution of cannabis use to variation in the incidence of psychotic disorder across Europe (EU-GEI): a multicentre case-control study

Background: Cannabis use is associated with increased risk of later psychotic disorder but whether it affects incidence of the disorder remains unclear. We aimed to identify patterns of cannabis use with the strongest effect on odds of psychotic disorder across Europe and explore whether differences in such patterns contribute to variations in the incidence rates of psychotic disorder. Methods: We included patients aged 18–64 years who presented to psychiatric services in 11 sites across Europe and Brazil with first-episode psychosis and recruited controls representative of the local populations. We applied adjusted logistic regression models to the data to estimate which patterns of cannabis use carried the highest odds for psychotic disorder. Using Europe-wide and national data on the expected concentration of Δ9-tetrahydrocannabinol (THC) in the different types of cannabis available across the sites, we divided the types of cannabis used by participants into two categories: low potency (THC <10%) and high potency (THC ≥10%). Assuming causality, we calculated the population attributable fractions (PAFs) for the patterns of cannabis use associated with the highest odds of psychosis and the correlation between such patterns and the incidence rates for psychotic disorder across the study sites. Findings: Between May 1, 2010, and April 1, 2015, we obtained data from 901 patients with first-episode psychosis across 11 sites and 1237 population controls from those same sites. Daily cannabis use was associated with increased odds of psychotic disorder compared with never users (adjusted odds ratio [OR] 3·2, 95% CI 2·2–4·1), increasing to nearly five-times increased odds for daily use of high-potency types of cannabis (4·8, 2·5–6·3). The PAFs calculated indicated that if high-potency cannabis were no longer available, 12·2% (95% CI 3·0–16·1) of cases of first-episode psychosis could be prevented across the 11 sites, rising to 30·3% (15·2–40·0) in London and 50·3% (27·4–66·0) in Amsterdam. The adjusted incident rates for psychotic disorder were positively correlated with the prevalence in controls across the 11 sites of use of high-potency cannabis (r = 0·7; p=0·0286) and daily use (r = 0·8; p=0·0109). Interpretation: Differences in frequency of daily cannabis use and in use of high-potency cannabis contributed to the striking variation in the incidence of psychotic disorder across the 11 studied sites. Given the increasing availability of high-potency cannabis, this has important implications for public health. Funding source: Medical Research Council, the European Community's Seventh Framework Program grant, São Paulo Research Foundation, National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and King's College London and the NIHR BRC at University College London, Wellcome Trust