Cannabis-induced psychotic disorders are of great clinical and prognostic importance.

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Farrowing duration is rather long in sows most likely due to selection for large litters, and we hypothesized that prolonged farrowings would compromise sow energy status during farrowing and in turn the farrowing process. Two studies were performed as follows: 1) to evaluate whether sow energy status during farrowing compromise the farrowing kinetics (FK, i.e., farrowing duration and birth intervals) and 2) to study the underlying mechanisms potentially affecting stillbirth rate and farrowing assistance. In study-1, parameters affecting FK were characterized based on data from a total of 166 farrowings from 7 feeding trials focused on sow colostrum production. The data were screened for associations with FK using the CORR procedure of SAS. Traits that were correlated with the FK at P < 0.05 were included in a multivariate regression model. Time since last meal until the onset of farrowing greatly affected the farrowing duration (r = 0.76; n = 166; P < 0.001) and a broken-line model was fitted to describe that relationship. According to the model, farrowing duration was constant (3.8 ± 1.5 h) if the farrowing started before the breakpoint (3.13 ± 0.34 h after the last meal), whereas farrowing duration increased to 9.3 h if the farrowing started 8 h after the last meal. Subsequently, sows were divided into 3 categories based on that trait (≤3, 3 to 6, and >6 h) to evaluate the impact on birth intervals, farrowing assistance, and stillbirth rate. Birth intervals (P < 0.001), odds for farrowing assistance (P < 0.001), and odds for stillbirth (P = 0.02) were low, intermediate, and high when time since last meal was ≤3, 3 to 6, and >6 h, respectively. In study-2, blood samples were collected once or twice each week in late gestation and each hour during farrowing to measure arterial concentrations and uterine extractions of plasma metabolites. Time since last meal was strongly negatively correlated with arterial glucose 1 h after the onset of farrowing (r= -0.96; n = 9; P < 0.001). Glucose appeared to be the key energy metabolite for oxidative metabolism of gravid uterus. In conclusion, the present study strongly suggests that a substantial proportion of sows suffer from low-energy status at the onset farrowing and that this negatively affects the farrowing process. Transferring this knowledge into practice, the results suggest that sows should be fed at least 3 daily meals in late gestation.

Linkage studies suggest that chromosome 22q12-13 may contain one or more shared susceptibility genes for schizophrenia (SZ) and bipolar affective disorder (BPD). In a Faeroese sample, we previously reported association between microsatellite markers located at 22q13.31-qtel and both disorders. The present study reports an association analysis across five genes (including 14 single nucleotide and two microsatellite polymorphisms) in this interval using a case-control sample of 162 BPD, 103 SZ patients and 200 controls. The bromodomain-containing 1 gene (BRD1), which encodes a putative regulator of transcription showed association with both disorders with minimal P-values of 0.0046 and 0.00001 for single marker and overall haplotype analysis, respectively. A specific BRD1 2-marker 'risk' haplotype showed a frequency of B10% in the combined case group versus B1% in controls (P-value 2.8 Â 10 À7 ). Expression analysis of BRD1 mRNA revealed widespread expression in mammalian brain tissue, which was substantiated by immunohistochemical detection of BRD1 protein in the nucleus, perikaryal cytosol and proximal dendrites of the neurons in the adult rat, rabbit and human CNS. Quantitative mRNA analysis in developing fetal pig brain revealed spatiotemporal differences with high expression at early embryonic stages, with intense nuclear and cytosolar immunohistochemical staining of the neuroepithelial layer and early neuroblasts, whilst more mature neurons at later embryonic stages had less nuclear staining. The results implicate BRD1 with SZ and BPD susceptibility and provide evidence that suggests a role for BRD1 in neurodevelopment.

Subjects with prior depression do not use cannabis as a mean of self-medication. They are more likely to experience specific increases of adverse symptoms while under the influence of cannabis, and are less likely to experience specific symptom relief. There is some evidence that cannabis is used as a means of self-medication for problems controlling aggression.

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Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R 2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R 2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.