Grape skin improves antioxidant capacity in rats fed a high fat diet

This study was conducted to investigate the effect of dietary grape skin on lipid peroxidation and antioxidant defense system in rats fed high fat diet. The Sprague-Dawley rats were fed either control (5% fat) diet or high fat (25% fat) diet which was based on AIN-93 diet for 2 weeks, and then they were grouped as control group (C), control + 5% grape skin group (CS), high-fat group (HF), high fat + 5% grape skin group (HFS) with 10 rats each and fed corresponding diets for 4 weeks. The hepatic thiobarbituric acid reacting substances (TBARS) were increased in high fat group as compared with control group, but reduced by grape skin. The serum total antioxidant status, and activities of hepatic catalase and superoxide dismutase, xanthine oxidase and glucose-6-phosphatase were increased by supplementation of grape skin. Glutathione peroxidase activity was significantly higher in CS group than in C group. Grape skin feeding tended to increase the concentration of total glutathione, especially in control group. The ratio of reduced glutathione to oxidized glutathione was lower in high fat groups than in control groups. The ratio was increased by dietary supplementation of grape skin in control group. These results suggest that dietary supplementation of grape skin would be effective on protection of oxidative damage by lipid peroxidation through improvement of antioxidant defense system in rats fed high fat diet as well as rats with low fat diet

Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer’s disease: a feature selection ensemble combining stability and predictability

Background Predicting progression from Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) is an utmost open issue in AD-related research. Neuropsychological assessment has proven to be useful in identifying MCI patients who are likely to convert to dementia. However, the large battery of neuropsychological tests (NPTs) performed in clinical practice and the limited number of training examples are challenge to machine learning when learning prognostic models. In this context, it is paramount to pursue approaches that effectively seek for reduced sets of relevant features. Subsets of NPTs from which prognostic models can be learnt should not only be good predictors, but also stable, promoting generalizable and explainable models. Methods We propose a feature selection (FS) ensemble combining stability and predictability to choose the most relevant NPTs for prognostic prediction in AD. First, we combine the outcome of multiple (filter and embedded) FS methods. Then, we use a wrapper-based approach optimizing both stability and predictability to compute the number of selected features. We use two large prospective studies (ADNI and the Portuguese Cognitive Complaints Cohort, CCC) to evaluate the approach and assess the predictive value of a large number of NPTs. Results The best subsets of features include approximately 30 and 20 (from the original 79 and 40) features, for ADNI and CCC data, respectively, yielding stability above 0.89 and 0.95, and AUC above 0.87 and 0.82. Most NPTs learnt using the proposed feature selection ensemble have been identified in the literature as strong predictors of conversion from MCI to AD. Conclusions The FS ensemble approach was able to 1) identify subsets of stable and relevant predictors from a consensus of multiple FS methods using baseline NPTs and 2) learn reliable prognostic models of conversion from MCI to AD using these subsets of features. The machine learning models learnt from these features outperformed the models trained without FS and achieved competitive results when compared to commonly used FS algorithms. Furthermore, the selected features are derived from a consensus of methods thus being more robust, while releasing users from choosing the most appropriate FS method to be used in their classification task.PTDC/EEI-SII/1937/2014; SFRH/BD/95846/2013; SFRH/BD/118872/2016info:eu-repo/semantics/publishedVersio

Modern Clinical Research on LSD

All modern clinical studies using the classic hallucinogen lysergic acid diethylamide (LSD) in healthy subjects or patients in the last 25 years are reviewed herein. There were five recent studies in healthy participants and one in patients. In a controlled setting, LSD acutely induced bliss, audiovisual synesthesia, altered meaning of perceptions, derealization, depersonalization, and mystical experiences. These subjective effects of LSD were mediated by the 5-HT2A receptor. LSD increased feelings of closeness to others, openness, trust, and suggestibility. LSD impaired the recognition of sad and fearful faces, reduced left amygdala reactivity to fearful faces, and enhanced emotional empathy. LSD increased the emotional response to music and the meaning of music. LSD acutely produced deficits in sensorimotor gating, similar to observations in schizophrenia. LSD had weak autonomic stimulant effects and elevated plasma cortisol, prolactin, and oxytocin levels. Resting-state functional magnetic resonance studies showed that LSD acutely reduced the integrity of functional brain networks and increased connectivity between networks that normally are more dissociated. LSD increased functional thalamocortical connectivity and functional connectivity of the primary visual cortex with other brain areas. The latter effect was correlated with subjective hallucinations. LSD acutely induced global increases in brain entropy that were associated with greater trait openness 14 days later. In patients with anxiety associated with life-threatening disease, anxiety was reduced for 2 months after two doses of LSD. In medical settings, no complications of LSD administration were observed. These data should contribute to further investigations of the therapeutic potential of LSD in psychiatry