Negative symptoms and social cognition as mediators of the relationship between neurocognition and functional outcome in schizophrenia.

Introduction: In this study we assessed the contribution of psychopathology, including the two domains of negative symptoms (motivational deficit and expressive deficit), processing speed as an index of neurocognition, and emotion recognition, as an index of social cognition, to poor functional outcomes in people with schizophrenia. Methods: The Positive and Negative Syndrome Scale was used to evaluate positive symptoms and disorganization and the Brief Negative Symptom Scale to assess negative symptoms. The Symbol Coding and the Trail Making Test A and B were used to rate processing speed and the Facial Emotion Identification Test to assess emotion recognition. Functional outcome was assessed with the Personal and Social Performance Scale (PSP). Regression analyses were performed to identify predictors of functional outcome. Mediation analyses was used to investigate whether social cognition and negative symptom domains fully or partially mediated the impact of processing speed on functional outcome. Results: One hundred and fifty subjects from 8 different European centers were recruited. Our data showed that the expressive deficit predicted global functioning and together with motivational deficit fully mediated the effects of neurocognition on it. Motivational deficit was a predictor of personal and social functioning and fully mediated neurocognitive impairment effects on the same outcome. Both motivational deficit and neurocognitive impairment predicted socially useful activities, and the emotion recognition domain of social cognition partially mediated the impact of neurocognitive deficits on this outcome. Conclusions: Our results indicate that pathways to functional outcomes are specific for different domains of real-life functioning and that negative symptoms and social cognition mediate the impact of neurocognitive deficits on different domains of functioning. Our results suggest that both negative symptoms and social cognition should be targeted by psychosocial interventions to enhance the functional impact of neurocognitive remediation.

Influence of psychopathology and metabolic parameters on quality of life in patients with first-episode psychosis before and after initial antipsychotic treatment.

The impact of psychological and physical health on quality of life (QoL) in patients with early psychosis remain relatively unexplored. We evaluated the predictive value of psychopathological and metabolic parameters on QoL in antipsychotic-naïve patients with first-episode psychosis before and after initial antipsychotic treatment. At baseline, 125 patients underwent assessments of psychopathology, prevalence of metabolic syndrome (MetS), and QoL. After 6 weeks of antipsychotic monotherapy, 89 patients were re-investigated. At baseline, the prevalence of MetS was 19.3% (n = 22). After 6 weeks, body weight (1.3 kg, p < 0.001) and body mass index (0.4 kg/m2, p < 0.001) increased, and four additional patients developed MetS. Multivariate linear regression revealed that positive and negative symptoms, and to some degree waist circumference, were predictors of QoL at both time points. Our findings suggest that in the earliest stages of antipsychotic treatment, metabolic side-effects may be less influential on QoL than psychopathological severity.

Fibre density and fibre-bundle cross-section of the corticospinal tract are distinctly linked to psychosis-specific symptoms in antipsychotic-naïve patients with first-episode schizophrenia.

Multiple lines of research support the dysconnectivity hypothesis of schizophrenia. However, findings on white matter (WM) alterations in patients with schizophrenia are widespread and non-specific. Confounding factors from magnetic resonance image (MRI) processing, clinical diversity, antipsychotic exposure, and substance use may underlie some of the variability. By application of refined methodology and careful sampling, we rectified common confounders investigating WM and symptom correlates in a sample of strictly antipsychotic-naïve first-episode patients with schizophrenia. Eighty-six patients and 112 matched controls underwent diffusion MRI. Using fixel-based analysis (FBA), we extracted fibre-specific measures such as fibre density and fibre-bundle cross-section. Group differences on fixel-wise measures were examined with multivariate general linear modelling. Psychopathology was assessed with the Positive and Negative Syndrome Scale. We separately tested multivariate correlations between fixel-wise measures and predefined psychosis-specific versus anxio-depressive symptoms. Results were corrected for multiple comparisons. Patients displayed reduced fibre density in the body of corpus callosum and in the middle cerebellar peduncle. Fibre density and fibre-bundle cross-section of the corticospinal tract were positively correlated with suspiciousness/persecution, and negatively correlated with delusions. Fibre-bundle cross-section of isthmus of corpus callosum and hallucinatory behaviour were negatively correlated. Fibre density and fibre-bundle cross-section of genu and splenium of corpus callosum were negative correlated with anxio-depressive symptoms. FBA revealed fibre-specific properties of WM abnormalities in patients and differentiated associations between WM and psychosis-specific versus anxio-depressive symptoms. Our findings encourage an itemised approach to investigate the relationship between WM microstructure and clinical symptoms in patients with schizophrenia.

Clustering of antipsychotic-naïve patients with schizophrenia based on functional connectivity from resting-state electroencephalography.

Schizophrenia is associated with aberrations in the Default Mode Network (DMN), but the clinical implications remain unclear. We applied data-driven, unsupervised machine learning based on resting-state electroencephalography (rsEEG) functional connectivity within the DMN to cluster antipsychotic-naïve patients with first-episode schizophrenia. The identified clusters were investigated with respect to psychopathological profile and cognitive deficits. Thirty-seven antipsychotic-naïve, first-episode patients with schizophrenia (mean age 24.4 (5.4); 59.5% males) and 97 matched healthy controls (mean age 24.0 (5.1); 52.6% males) underwent assessments of rsEEG, psychopathology, and cognition. Source-localized, frequency-dependent functional connectivity was estimated using Phase Lag Index (PLI). The DMN-PLI was factorized for each frequency band using principal component analysis. Clusters of patients were identified using a Gaussian mixture model and neurocognitive and psychopathological profiles of identified clusters were explored. We identified two clusters of patients based on the theta band (4-8 Hz), and two clusters based on the beta band (12-30 Hz). Baseline psychopathology could predict theta clusters with an accuracy of 69.4% (p = 0.003), primarily driven by negative symptoms. Five a priori selected cognitive functions conjointly predicted the beta clusters with an accuracy of 63.6% (p = 0.034). The two beta clusters displayed higher and lower DMN connectivity, respectively, compared to healthy controls. In conclusion, the functional connectivity within the DMN provides a novel, data-driven means to stratify patients into clinically relevant clusters. The results support the notion of biological subgroups in schizophrenia and endorse the application of data-driven methods to recognize pathophysiological patterns at earliest stage of this syndrome.

Add-On MEmaNtine to Dopamine Antagonism to Improve Negative Symptoms at First Psychosis- the AMEND Trial Protocol.

Background: Antipsychotic drugs are primarily efficacious in treating positive symptoms by blocking the dopamine D2 receptor, but they fail to substantially improve negative symptoms and cognitive deficits. The limited efficacy may be attributed to the fact that the pathophysiology of psychosis involves multiple neurotransmitter systems. In patients with chronic schizophrenia, memantine, a non-competitive glutamatergic NMDA receptor antagonist, shows promise for ameliorating negative symptoms and improving cognition. Yet, it is unknown how memantine modulates glutamate levels, and memantine has not been investigated in patients with first-episode psychosis. Aims: This investigator-initiated double-blinded randomized controlled trial is designed to (1) test the clinical effects on negative symptoms of add-on memantine to antipsychotic medication, and (2) neurobiologically characterize the responders to add-on memantine. Materials and Equipment: Antipsychotic-naïve patients with first-episode psychosis will be randomized to 12 weeks treatment with [amisulpride + memantine] or [amisulpride + placebo]. We aim for a minimum of 18 patients in each treatment arm to complete the trial. Brain mapping will be performed before and after 12 weeks focusing on glutamate and neuromelanin in predefined regions. Regional glutamate levels will be probed with proton magnetic resonance spectroscopy (MRS), while neuromelanin signal will be mapped with neuromelanin-sensitive magnetic resonance imaging (MRI). We will also perform structural and diffusion weighted, whole-brain MRI. MRS and MRI will be performed at an ultra-high field strength (7 Tesla). Alongside, participants undergo clinical and neuropsychological assessments. Twenty matched healthy controls will undergo similar baseline- and 12-week examinations, but without receiving treatment. Outcome Measures: The primary endpoint is negative symptom severity. Secondary outcomes comprise: (i) clinical endpoints related to cognition, psychotic symptoms, side effects, and (ii) neurobiological endpoints related to regional glutamate- and neuromelanin levels, and structural brain changes. Anticipated Results: We hypothesize that add-on memantine to amisulpride will be superior to amisulpride monotherapy in reducing negative symptoms, and that this effect will correlate with thalamic glutamate levels. Moreover, we anticipate that add-on memantine will restore regional white matter integrity and improve cognitive functioning. Perspectives: By combining two licensed, off-patent drugs, AMEND aims to optimize treatment of psychosis while investigating the memantine response. Alongside, AMEND will provide neurobiological insights to effects of dual receptor modulation, which may enable future stratification of patients with first-episode psychosis before initial antipsychotic treatment. Clinical Trial Registration: [ClinicalTrials.gov], identifier [NCT04789915].

Lower Vitamin C Levels Are Associated With Less Improvement in Negative Symptoms in Initially Antipsychotic-Naïve Patients With First-Episode Psychosis.

Low levels of vitamin C have been observed in patients with schizophrenia and psychosis, and vitamin C may affect the dopaminergic system. Likewise, antipsychotic medication modulates striatal dopamine D2 receptors. We measured vitamin C levels in 52 patients with first-episode psychoses (24 females, age 23.1 ± 5.2 years) and 57 matched HCs (20 females, age 22.7 ± 4.3 years) before and after 6 weeks where patients received aripiprazole monotherapy (mean dose 10.4 mg ± 4.8 mg). At baseline, patients displayed lower levels of vitamin C (57.4 ± 25.9 µM) than controls (72.7 ± 21.4 µM) (t = 3.4, P = .001). Baseline symptoms and vitamin C levels were not correlated. Higher baseline vitamin C levels were associated with more improvement in negative symptoms (n = 39, R2 = 0.20, F = 8.2, P = .007), but not with age, sex, or p-aripiprazole. Because negative symptoms are generally considered challenging to alleviate, a potential adjunctive effect of vitamin C on treatment response should be tested in future randomized clinical trials.

Scalability of the Positive and Negative Syndrome Scale in first-episode schizophrenia assessed by Rasch models.

OBJECTIVE: Historically, assessment of the psychometric properties of the Positive and Negative Syndrome Scale (PANSS) has had several foci: (1) calculation of reliability indexes, (2) extraction of subdimensions from the scale, and (3) assessment of the validity of the total score. In this study, we aimed to examine the scalability and to assess the clinical performance of the 30-item PANSS total score as well as the scalability of a shorter version (PANSS-6) of the scale. METHODS: A composite data set of 1073 patients with first-episode schizophrenia or schizophrenia spectrum disorder was subjected to Rasch analysis of PANSS data from baseline and 4-6 weeks follow-up. RESULTS: The central tests of fit of the Rasch model failed to satisfy the statistical requirements behind item homogeneity for the PANSS-30 as well as the PANSS-6 total score. For the PANSS-30, Differential Item Functioning was pronounced both for the 7-point Likert scale rating categories and when dichotomizing the rating categories. Subsequently, the Rasch structure analysis in the context of dichotomized items was used to isolate and estimate a systematic error because of item inhomogeneity, as well as a random error. The size of the combined sources of error for the PANSS-30 total score approximated 20% which is often regarded as clinical cut-off between response versus no-response. CONCLUSION: The results demonstrate the operational consequences of a lack of statistical fit of the Rasch model and suggest that the calculated measure of uncertainty needs to be considered when using the PANSS-30 total score.

European Validation of the Self-Evaluation of Negative Symptoms (SNS): A Large Multinational and Multicenter Study.

BACKGROUND: Negative symptoms are usually evaluated with scales based on observer ratings and up to now self-assessments have been overlooked. The aim of this paper was to validate the Self-evaluation of Negative Symptoms (SNS) in a large European sample coming from 12 countries. We wanted to demonstrate: (1) good convergent and divergent validities; (2) relationships between SNS scores and patients' functional outcome; (3) the capacity of the SNS compared to the Brief Negative Symptom Scale (BNSS) to detect negative symptoms; and (4) a five-domain construct in relation to the 5 consensus domains (social withdrawal, anhedonia, alogia, avolition, blunted affect) as the best latent structure of SNS. METHODS: Two hundred forty-five subjects with a DSM-IV diagnosis of schizophrenia completed the SNS, the Positive and Negative Syndrome Scale (PANSS), the BNSS, the Calgary Depression Scale for Schizophrenia (CDSS), and the Personal and Social Performance (PSP) scale. Spearman's Rho correlations, confirmatory factor analysis investigating 4 models of the latent structure of SNS and stepwise multiple regression were performed. RESULTS: Significant positive correlations were observed between the total score of the SNS and the total scores of the PANSS negative subscale (r = 0.37; P < 0.0001) and the BNSS (r = 0.43; p < 0.0001). SNS scores did not correlate with the level of insight, parkinsonism, or the total score of the PANSS positive subscale. A positive correlation was found between SNS and CDSS (r = 0.35; p < 0.0001). Among the 5 SNS subscores, only avolition subscores entered the regression equation explaining a lower functional outcome. The 1-factor and 2-factor models provided poor fit, while the 5-factor model and the hierarchical model provided the best fit, with a small advantage of the 5-factor model. The frequency of each negative dimension was systematically higher using the BNSS and the SNS vs. the PANSS and was higher for alogia and avolition using SNS vs. BNSS. CONCLUSION: In a large European multicentric sample, this study demonstrated that the SNS has: (1) good psychometric properties with good convergent and divergent validities; (2) a five-factor latent structure; (3) an association with patients' functional outcome; and (4) the capacity to identify subjects with negative symptoms that is close to the BNSS and superior to the PANSS negative subscale.

Prediction of Early Symptom Remission in Two Independent Samples of First-Episode Psychosis Patients Using Machine Learning.

BACKGROUND: Validated clinical prediction models of short-term remission in psychosis are lacking. Our aim was to develop a clinical prediction model aimed at predicting 4-6-week remission following a first episode of psychosis. METHOD: Baseline clinical data from the Athens First Episode Research Study was used to develop a Support Vector Machine prediction model of 4-week symptom remission in first-episode psychosis patients using repeated nested cross-validation. This model was further tested to predict 6-week remission in a sample of two independent, consecutive Danish first-episode cohorts. RESULTS: Of the 179 participants in Athens, 120 were male with an average age of 25.8 years and average duration of untreated psychosis of 32.8 weeks. 62.9% were antipsychotic-naïve. Fifty-seven percent attained remission after 4 weeks. In the Danish cohort, 31% attained remission. Eleven clinical scale items were selected in the Athens 4-week remission cohort. These included the Duration of Untreated Psychosis, Personal and Social Performance Scale, Global Assessment of Functioning and eight items from the Positive and Negative Syndrome Scale. This model significantly predicted 4-week remission status (area under the receiver operator characteristic curve (ROC-AUC) = 71.45, P < .0001). It also predicted 6-week remission status in the Danish cohort (ROC-AUC = 67.74, P < .0001), demonstrating reliability. CONCLUSIONS: Using items from common and validated clinical scales, our model significantly predicted early remission in patients with first-episode psychosis. Although replicated in an independent cohort, forward testing between machine learning models and clinicians' assessment should be undertaken to evaluate the possible utility as a routine clinical tool.

Associations between cognition and white matter microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls: A multivariate pattern analysis.

BACKGROUND: Cognitive functions have been associated with white matter (WM) microstructure in schizophrenia, but most studies are limited by examining only select cognitive measures and single WM tracts in chronic, medicated patients. It is unclear if the cognition-WM relationship differs between antipsychotic-naïve patients with schizophrenia and healthy controls, as differential associations have not been directly examined. Here we examine if there are differential patterns of associations between cognition and WM microstructure in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls, and we characterize reliable contributors to the pattern of associations across multiple cognitive domains and WM regions, in order to elucidate white matter contribution to the neural underpinnings of cognitive deficits. METHODS: Thirty-six first-episode antipsychotic-naïve patients with schizophrenia and 52 matched healthy controls underwent cognitive tests and diffusion-weighted imaging on a 3T Magnetic Resonance Imaging scanner. Using a multivariate partial least squares correlation analysis, we included 14 cognitive variables and mean fractional anisotropy values of 48 WM regions. RESULTS: Initial analyses showed significant group differences in both measures of WM and cognition. There was no group interaction effect in the pattern of associations between cognition and WM microstructure. The combined analysis of patients and controls lead to a significant pattern of associations (omnibus test p = .015). Thirty-four regions and seven cognitive functions contributed reliably to the associations. CONCLUSIONS: The lack of an interaction effect suggests similar associations in first-episode antipsychotic-naïve patients with schizophrenia and healthy controls. This, together with the differences in both WM and cognitive measurements, supports the involvement of WM in cognitive deficits in schizophrenia. Our findings add to the field by showing a coherent picture of the overall pattern of association between cognition and WM. These findings increase our understanding of the impact of WM on cognition, contributing to the search for neuromarkers of cognitive deficits in schizophrenia.

Multimodal assessment of white matter microstructure in antipsychotic-naïve schizophrenia patients and confounding effects of recreational drug use.

Cerebral white matter (WM) aberrations in schizophrenia have been linked to multiple neurobiological substrates but the underlying mechanisms remain unknown. Moreover, antipsychotic treatment and substance use constitute potential confounders. Multimodal studies using diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI) may provide deeper insight into the whole brain WM pathophysiology in schizophrenia. We combined DTI and MTI to investigate WM integrity in 51 antipsychotic-naïve, first-episode schizophrenia patients and 55 matched healthy controls, using 3 T magnetic resonance imaging (MRI). Psychopathology was assessed with the positive and negative syndrome scale (PANSS). A whole brain partial least squares correlation (PLSC) method was used to conjointly analyze DTI-derived measures (fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), mode of anisotropy (MO)) and the magnetization transfer ratio (MTR) to identify group differences, and associations with psychopathology. In secondary analyses, we excluded recreational substance users from both groups resulting in 34 patients and 51 healthy controls. The primary PLSC group difference analysis identified a significant pattern of lower FA, AD, MO and higher RD in patients (p = 0.04). This pattern suggests disorganized WM microstructure in patients. The secondary PLSC group difference analysis without recreational substance users revealed a significant pattern of lower FA and higher AD, RD, MO, MTR in patients (p = 0.04). This pattern in the substance free patients is consistent with higher extracellular free-water concentrations, which may reflect neuroinflammation. No significant associations with psychopathology were observed. Recreational substance use appears to be a confounding issue, which calls for attention in future WM studies.

A machine-learning framework for robust and reliable prediction of short- and long-term treatment response in initially antipsychotic-naïve schizophrenia patients based on multimodal neuropsychiatric data.

The reproducibility of machine-learning analyses in computational psychiatry is a growing concern. In a multimodal neuropsychiatric dataset of antipsychotic-naïve, first-episode schizophrenia patients, we discuss a workflow aimed at reducing bias and overfitting by invoking simulated data in the design process and analysis in two independent machine-learning approaches, one based on a single algorithm and the other incorporating an ensemble of algorithms. We aimed to (1) classify patients from controls to establish the framework, (2) predict short- and long-term treatment response, and (3) validate the methodological framework. We included 138 antipsychotic-naïve, first-episode schizophrenia patients with data on psychopathology, cognition, electrophysiology, and structural magnetic resonance imaging (MRI). Perinatal data and long-term outcome measures were obtained from Danish registers. Short-term treatment response was defined as change in Positive And Negative Syndrome Score (PANSS) after the initial antipsychotic treatment period. Baseline diagnostic classification algorithms also included data from 151 matched controls. Both approaches significantly classified patients from healthy controls with a balanced accuracy of 63.8% and 64.2%, respectively. Post-hoc analyses showed that the classification primarily was driven by the cognitive data. Neither approach predicted short- nor long-term treatment response. Validation of the framework showed that choice of algorithm and parameter settings in the real data was successfully guided by results from the simulated data. In conclusion, this novel approach holds promise as an important step to minimize bias and obtain reliable results with modest sample sizes when independent replication samples are not available.

Striatal Volume Increase After Six Weeks of Selective Dopamine D2/3 Receptor Blockade in First-Episode, Antipsychotic-Naïve Schizophrenia Patients.

Patients with chronic schizophrenia often display enlarged striatal volumes, and antipsychotic drugs may contribute via the dopamine D2/3 receptor (D2/3R) blockade. Separating the effects of disease from medication is challenging due to the lack of a proper placebo-group. To address this, we conducted a longitudinal study of antipsychotic-naïve, first-episode schizophrenia patients to test the hypothesis that selective blockade of D2/3R would induce a dose-dependent striatal volume increase. Twenty-one patients underwent structural magnetic resonance imaging (sMRI), single-photon emission computed tomography (SPECT), and symptom severity ratings before and after six weeks of amisulpride treatment. Twenty-three matched healthy controls underwent sMRI and baseline SPECT. Data were analyzed using repeated measures and multiple regression analyses. Correlations between symptom severity decrease, volume changes, dose and receptor occupancy were explored. Striatal volumes did not differ between patients and controls at baseline or follow-up, but a significant group-by-time interaction was found (p = 0.01). This interaction was explained by a significant striatal volume increase of 2.1% in patients (Cohens d = 0.45). Striatal increase was predicted by amisulpride dose, but not by either D2/3R occupancy or baseline symptom severity. A significant reduction in symptom severity was observed at a mean dose of 233.3 (SD = 109.9) mg, corresponding to D2/3R occupancy of 44.65%. Reduction in positive symptoms correlated significantly with striatal volume increase, driven by reductions in hallucinations. Our data demonstrate a clear link between antipsychotic treatment and striatal volume increase in antipsychotic-naïve schizophrenia patients. Moreover, the treatment-induced striatal volume increase appears clinically relevant by correlating to reductions in core symptoms of schizophrenia.

Prenatal over- and undernutrition differentially program small intestinal growth, angiogenesis, absorptive capacity, and endocrine function in sheep.

The aim was to test the hypothesis that prenatal under- and overnutrition in late gestation can program small intestinal (SI) growth, angiogenesis, and endocrine function to predispose for a hyperabsorptive state, thereby increasing the susceptibility to the adverse effects of an early postnatal obesogenic diet. Twin-pregnant ewes were exposed to adequate (NORM), LOW (50% of NORM), or HIGH (150% energy and 110% protein of NORM) diets through the last trimester (term ~147 days). From 3 days to 6 months of age, their lambs were fed either a moderate (CONV) or a high-carbohydrate high-fat (HCHF) diet. At 6 months of age, responses in plasma metabolites and insulin to refeeding after fasting were determined and then different segments of the SI were sampled at autopsy. Prenatal overnutrition impacts were most abundant in the duodenum where HIGH had increased villus amplification factor and lowered villi thickness with increased IRS-1 and reduced GH-R expressions. In jejunum, HIGH lambs had an increased expression of Lactate gene and amplified when exposed to HCHF postnatally. Specifically, in LOW, sensitivity to HCHF was affected in ileum. Thus, the mismatching LOW-HCHF nutrition increased expressions of angiogenic genes (VEGF, VEGF-R1, ANGPT1, RTK) and increased mucosa layer (tunica mucosa) thickness but reduced muscle layer (Tunica muscularis) thickness. The SI is a target of prenatal nutritional programming, where late gestation overnutrition increased and shifted digestive capacity for carbohydrates toward the jejunum, whereas late gestation undernutrition predisposed for ileal angiogenesis and carbohydrate and fat hyperabsorptive capacity upon subsequent exposure to postnatal obesogenic diet.

Rasch analysis of the PANSS negative subscale and exploration of negative symptom trajectories in first-episode schizophrenia - data from the OPTiMiSE trial.

The observed heterogeneity in negative symptom treatment response may be partly attributable to inadequate measurement tools or limitations in methods of analysis. Previous Item Response Theory models of the Positive and Negative Syndrome Scale (PANSS) have only examined samples of chronic patients and with mixed results. We examined the scalability of the negative subscale embedded in the PANSS and subsequently explored negative symptom trajectories across four weeks of amisulpride treatment. Data were derived from the OPTiMiSE trial comprising 446 patients with first-episode schizophrenia or schizophreniform disorder. Using the Rasch Model to examine psychometric properties of the PANSS negative subscale, we found that the composite score across items was not an adequate measure of negative symptom severity. Consequently, we chose an exploratory statistical approach involving Principal Component Analysis which yielded one significant component clustering into two significant symptom trajectories: 1) Subtle but constant decrease in negative symptom severity (N = 323; 72%), and 2) symptom instability across visits (N = 19; 4%). Explorative analytic methods as presented here may pave the way for more efficient and sensitive methods of analyzing negative symptom response in research and in clinical practice.

Impact of Dietary Supplementation of Lactic Acid Bacteria Fermented Rapeseed with or without Macroalgae on Performance and Health of Piglets Following Omission of Medicinal Zinc from Weaner Diets.

The feeding of medicinal zinc oxide (ZnO) to weaner piglets will be phased out after 2022 in Europe, leaving pig producers without options to manage post-weaning disorders. This study assessed whether rapeseed meal, fermented alone (FRM) or co-fermented with a single (Ascophylum nodosum; FRMA), or two (A. nodossum and Saccharina latissima; FRMAS) brown macroalagae species, could improve weaner piglet performance and stimulate intestinal development as well as maturation of gut microbiota in the absence of in-feed zinc. Weaned piglets (n = 1240) were fed, during 28-85 days of age, a basal diet with no additives (negative control; NC), 2500 ppm in-feed ZnO (positive control; PC), FRM, FRMA or FRMAS. Piglets fed FRM and FRMA had a similar or numerically improved, respectively, production performance compared to PC piglets. Jejunal villus development was stimulated over NC in PC, FRM and FRMAS (gender-specific). FRM enhanced colon mucosal development and reduced signs of intestinal inflammation. All fermented feeds and PC induced similar changes in the composition and diversity of colon microbiota compared to NC. In conclusion, piglet performance, intestinal development and health indicators were sustained or numerically improved when in-feed zinc was replaced by FRM.

Short communication: Effects of electrochemically activated drinking water on bovine milk production and composition, including chlorate, perchlorate, and fatty acid profile.

The objective of this study was to assess the effects of electrochemically activated drinking water (ECW) on milk chlorate, milk perchlorate, milk iodine, milk composition, milk fatty acid profile, and overall performance of dairy cows. Ten Red Danish cows in mid-lactation (203 ± 31 d in milk; average ± SD) were chosen from these 2 groups for intensive sampling. The treated group drank water with 4 ppm of ECW (29 mg/L of chlorate of Neuthox, Danish Clean Water A/S, Sønderborg, Denmark). The treatment lasted 60 consecutive days, with milk and water sampling on d 0, 30, and 60. Additionally, milk samples from both the control group and treated group were taken on d 90 to assess if any carry-over effect was present. Interactions between period and milk yield and somatic cell for the full group and period and milk fat content and milk urea nitrogen in the selected animals occurred. Milk yield was not significantly affected by treatments. Milk fat, milk fatty acid profile, chlorate, perchlorate, and iodine contents were not significantly different between treatments. Milk urea increased, whereas ß-hydroxybutyrate and somatic cell count decreased significantly in the treated groups. Results showed that at a dosing of 4 ppm of ECW, both chlorate and perchlorate concentrations in milk (<0.002 mg/kg) were low, and no deleterious effects on milk production or milk chemical composition were observed. These data can be of use when assessing the effects of ECW on milk and milk powder chlorate and perchlorate levels and provide a context for assessing the potential for influencing human health under the conditions prevailing on a commercial dairy farm.

Diagnostic stability and long-term symptomatic and functional outcomes in first-episode antipsychotic-naïve patients with schizophrenia.

OBJECTIVE: In a prospective cohort design, we investigated: i) diagnostic stability of initially antipsychotic-naïve schizophrenia patients, ii) symptom severity including symptomatic remission, and iii) functional remission including full recovery. METHODS: We included 143 antipsychotic-naïve patients with first-episode schizophrenia or schizoaffective disorder. After 4-18 years, we clinically re-evaluated diagnosis, symptom severity and functioning for 70 patients. From the nationwide Danish registers, we extracted pragmatic outcome measures for 142 patients. We examined associations between baseline variables (age at diagnosis, sex, and premorbid intelligence) and long-term outcome status (symptomatic and functional remission). RESULTS: At 4-18 years follow-up, 80% met the criteria for schizophrenia or schizoaffective disorder, however, despite the high diagnostic stability 53% met the criteria of symptomatic and/or functional remission. Symptomatic remission characterized 34% of the patients and was associated with female sex, better premorbid intelligence, and a younger age at schizophrenia diagnosis. Functional remission characterized 41% of the patients and 17% of patients met criteria for full recovery both of which were associated with female sex. The clinically re-evaluated patients did not differ from the drop-outs on key register-based variables. CONCLUSION: We confirm the emerging evidence of a decreasing long-term diagnostic stability of schizophrenia, and a protective role of female sex. The association between premorbid intelligence and symptomatic remission underscores the pertinence of including cognitive deficits in the diagnostic category of schizophrenia. The association between younger age at diagnosis and symptomatic remission may reflect positive effects of early detection or a drift in the interpretation of the diagnostic classification system.