Is a combination of melatonin and amino acids useful to sarcopenic elderly patients? A randomized trial

This study evaluated the effectiveness of a 4-week intervention of melatonin and essential aminoacid supplementation on body composition, protein metabolism, strength and inflammation in 159 elderly sarcopenic patients (42/117, men/women), assigned to four groups: isocaloric placebo (P, n = 44), melatonin (M, 1 mg/daily, n = 42), essential amino acids (eAA 4 g/daily, n = 40) or eAA plus melatonin (eAAM, 4 g eAA and 1 mg melatonin/daily, n = 30). Data from body composition (dual X-ray absortiometry (DXA)), strength (handgrip test) and biochemical parameters for the assessment of protein metabolism (albumin) and inflammation (CRP) were collected at baseline and after the 4-week intervention. Compared with P and M, supplementation with eAA plus M increased total fat-free mass (vs. P: +2190 g; p < 0.01; vs. M: +2107 g; p < 0.05). M alone lowered albumin levels (vs. P: -0.39 g; p < 0.01; vs. eAA: -0.47 g; p < 0.01). This data on albumin was confirmed by within-group analysis (M -0.44g; p < 0.001; eAAM: -0.34 p < 0.05). M and eAA seemed to lower the percentage of gynoid fat (p < 0.05) and android fat (p < 0.01). No significant changes in inflammation or strength were reported. A 4-week intervention with eAA plus M together may be effective in enhancing fat-free-mass compared to M and P but not versus eAA. M alone demonstrates a negative effect on albumin level

Thiopurine metabolites variations during co-treatment with aminosalicylates for inflammatory bowel disease: effect of N-acetyl transferase polymorphisms

AIM: To evaluate variation of the concentration of thiopurine metabolites after 5-aminosalicylate (5-ASA) interruption and the role of genetic polymorphisms of N-acetyl transferase (NAT) 1 and 2. METHODS: Concentrations of thioguanine nucleotides (TGN) and methymercaptopurine nucleotides (MMPN), metabolites of thiopurines, were measured by high performance liquid chromatography in 12 young patients (3 females and 9 males, median age 16 years) with inflammatory bowel disease (6 Crohn's disease and 6 ulcerative colitis) treated with thiopurines (7 mercaptopurine and 5 azathioprine) and 5-ASA. Blood samples were collected one month before and one month after the interruption of 5-ASA. DNA was extracted and genotyping of NAT1, NAT2, inosine triphosphate pyrophosphatase (ITPA) and thiopurine methyl transferase (TPMT) genes was performed using PCR assays. RESULTS: Median TGN concentration before 5-ASA interruption was 270 pmol/8 x 108 erythrocytes (range: 145-750); after the interruption of the aminosalicylate, a 35% reduction in TGN mean concentrations (absolute mean reduction 109 pmol/8 7 108 erythrocytes) was observed (median 221 pmol/8 7 108 erythrocytes, range: 96-427, P value linear mixed effects model 0.0011). Demographic and clinical covariates were not related to thiopurine metabolites concentrations. All patients were wild-type for the most relevant ITPA and TPMT variants. For NAT1 genotyping, 7 subjects presented an allele combination corresponding to fast enzymatic activity and 5 to slow activity. NAT1 genotypes corresponding to fast enzymatic activity were associated with reduced TGN concentration (P value linear mixed effects model 0.033), putatively because of increased 5-ASA inactivation and consequent reduced inhibition of thiopurine metabolism. The effect of NAT1 status on TGN seems to be persistent even after one month since the interruption of the aminosalicylate. No effect of NAT1 genotypes was shown on MMPN concentrations. NAT2 genotyping revealed that 6 patients presented a genotype corresponding to fast enzymatic activity and 6 to slow activity; NAT2 genotypes were not related to thiopurine metabolites concentration in this study. CONCLUSION: NAT1 genotype affects TGN levels in patients treated with thiopurines and aminosalicylates and could therefore influence the toxicity and efficacy of these drugs; however the number of patients evaluated is limited and this has to be considered a pilot study

A Machine Learning Approach for the Differential Diagnosis of Alzheimer and Vascular Dementia Fed by MRI Selected Features

Among dementia-like diseases, Alzheimer disease (AD) and vascular dementia (VD) are two of the most frequent. AD and VD may share multiple neurological symptoms that may lead to controversial diagnoses when using conventional clinical and MRI criteria. Therefore, other approaches are needed to overcome this issue. Machine learning (ML) combined with magnetic resonance imaging (MRI) has been shown to improve the diagnostic accuracy of several neurodegenerative diseases, including dementia. To this end, in this study, we investigated, first, whether different kinds of ML algorithms, combined with advanced MRI features, could be supportive in classifying VD from AD and, second, whether the developed approach might help in predicting the prevalent disease in subjects with an unclear profile of AD or VD. Three ML categories of algorithms were tested: artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS). Multiple regional metrics from resting-state fMRI (rs-fMRI) and diffusion tensor imaging (DTI) of 60 subjects (33 AD, 27 VD) were used as input features to train the algorithms and find the best feature pattern to classify VD from AD. We then used the identified VD–AD discriminant feature pattern as input for the most performant ML algorithm to predict the disease prevalence in 15 dementia patients with a “mixed VD–AD dementia” (MXD) clinical profile using their baseline MRI data. ML predictions were compared with the diagnosis evidence from a 3-year clinical follow-up. ANFIS emerged as the most efficient algorithm in discriminating AD from VD, reaching a classification accuracy greater than 84% using a small feature pattern. Moreover, ANFIS showed improved classification accuracy when trained with a multimodal input feature data set (e.g., DTI + rs-fMRI metrics) rather than a unimodal feature data set. When applying the best discriminant pattern to the MXD group, ANFIS achieved a correct prediction rate of 77.33%. Overall, results showed that our approach has a high discriminant power to classify AD and VD profiles. Moreover, the same approach also showed potential in predicting earlier the prevalent underlying disease in dementia patients whose clinical profile is uncertain between AD and VD, therefore suggesting its usefulness in supporting physicians' diagnostic evaluations

Circadian temporal organization of lipidic fractions in elderly people. Entrainment to the dietary schedule

Background and aims: Changes in some rhythmometric parameters have been reported in the elderly as a consequence of both structural and neurochemical changes occurring in the central nervous system. Since alterations of lipid and lipoprotein metabolism are directly involved in several age-related disorders, the aim of this study was to investigate the circadian temporal organization of some important lipidic fractions (total cholesterol, triacylglycerol, apolipoprotein A1 and B) in physiological aging. Methods: Thirty old hospitalized subjects were synchronized for daily activities, sleeping/waking habits, and time/quality of meals. Twenty-four healthy young individuals served as controls. After an overnight fast, samples were taken beginning at 08:00 every 4 hours until 20:00, and every 2 hours from 20:00 to 04:00. Rhythmometric data were analyzed by single and population mean Cosinor analysis, and by ANOVA; the comparison of the rhythm's parameters between elderly and young subjects was carried out by the Mesor test and the amplitude-acrophase using Hotelling's test. Results: Elderly subjects exhibited statistically significant circadian rhythms for total cholesterol (p<0.00002), triacylglycerol (p<0.000001), apo A-1 (p<0.0013), and apo B (p<0.0104). Young subjects also exhibited statistically significant daily fluctuations for total cholesterol (p<0.0003), triacylglycerol (p<0.03), apo A-1 (p<0.002) and apo B (p<0.003). The mean level of apo B rhythm was higher in old subjects than in controls. Conclusions: These data suggest that the circadian temporal organization of lipidic fractions is maintained in physiological aging and underline the importance of the feeding schedule as a powerful synchronizer of the daily lipidic profile