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In recent years there has been increasing interest in knowing the function of the microbiota, especially its role in the gut-brain axis. The microbiota is the set of millions of microorganisms that coexist in a symbiotic way in our body and are located in the digestive tract mainly. Numerous evidences show that the microbiota could modulate the information directed to the brain and therefore the pathogenic basis of numerous psychiatric and neurological disorders.
A better understanding of the microbiota and its interaction with the brain and mental health.
Review of recent literature about the implications of the gut microbiota in psychiatry.
The connection between the microbiota and the central nervous system (gut-brain axis) occurs through the vagus nerve, the systemic pathway (through the release of hormones, metabolites and neurotransmitters) and the immune system (through the action of cytokines). Changes in the microbiota are associated not only with gastrointestinal diseases, but also with disorders such as depression, anxiety, autism, anorexia, attention deficit and hyperactivity, Alzheimer’s disease and Parkinson’s disease. As some research indicates, changes in diet and composition of the microbiota can reduce the risk of suffering these diseases or reduce their symptoms. Other therapeutic alternatives postulated are the use of probiotics or fecal microbiota transplantation.
Despite growing interest in the microbiota in the last few years, little is known about the mechanisms underlying this communication. More research is expected to contribute to the design of strategies that modulate the gut microbiota and its functions in order to improve mental health.
Branched-chain amino acids (BCAA) are considered markers of insulin resistance (IR) in subjects with obesity. In this study, we evaluated whether the presence of the SNP of the branched-chain aminotransferase 2 (BCAT2) gene can modify the effect of a dietary intervention (DI) on the plasma concentration of BCAA in subjects with obesity and IR. A prospective cohort study of adult subjects with obesity, BMI ≥ 30 kg/m2, homeostatic model assessment-insulin resistance (HOMA-IR ≥ 2·5) no diagnosed chronic disease, underwent a DI with an energy restriction of 3140 kJ/d and nutritional education for 1 month. Anthropometric measurements, body composition, blood pressure, resting energy expenditure, oral glucose tolerance test results, serum biochemical parameters and the plasma amino acid profile were evaluated before and after the DI. SNP were assessed by the TaqMan SNP genotyping assay. A total of eighty-two subjects were included, and fifteen subjects with a BCAT2 SNP had a greater reduction in leucine, isoleucine, valine and the sum of BCAA. Those subjects also had a greater reduction in skeletal muscle mass, fat-free mass, total body water, blood pressure, muscle strength and biochemical parameters after 1 month of the DI and adjusting for age and sex. This study demonstrated that the presence of the BCAT2 SNP promotes a greater reduction in plasma BCAA concentration after adjusting for age and sex, in subjects with obesity and IR after a 1-month energy-restricted DI.
Several recent reports have raised concern that infected coworkers may be an important source of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) acquisition by healthcare personnel. In a suspected outbreak among emergency department personnel, sequencing of SARS-CoV-2 confirmed transmission among coworkers. The suspected 6-person outbreak included 2 distinct transmission clusters and 1 unrelated infection.
Schizophrenia (SKZ) is a disease characterized by positive and negative symptoms, thoughts and behaviour disorganization with a progressive socio-cognitive impairment1; deficits in facial emotion recognition (FER) represent one of the most serious problems linked to interpersonal problems2. In addition, these patients have often comorbid condition of alcohol and substances abuse3.
to compare the ability of FER in patients with SKZ using alcohol and/or substances (SKZ+SUD) compared to schizophrenics without SUD (SUD-SKZ).
we enrolled 53 subjects (M=40, F=13) with a DSM-IV diagnosis of SKZ (SCID I). The sample was divided according to alcohol and/or substance abuse (AUS and DUS) into two groups, compared for socio-demographic and clinic characteristics (PANSS and Bell model4). We analyzed the association between abuse condition and Ekman test performance.
SKZ+SUD (n=20; M=16, F=4) and SKZ-SUD (n=33; M=24, F=9) show a statistically significant age difference with a mean (SD) of 38.4 years (10.5) and 46.0 years (8.7) respectively (p=0.006). SKZ+SUD Ekman test score (mean=43.1, SD=6.9) was statistically higher (p=0.006) than SKZ-SUD (mean=34.6, SD=12.0). The different performance was more evident in comparison with poly-abusers (44.94±7.05 vs 12.04±34.6; p=0.002). We further noticed the role of disorganization as a mediator of the relationship between abuse and FER score (p=0.017): the proportion of the effect of abuse on Ekman test score was 48%.
In subjects with SKZ, FER seems to be less impaired in abusers than non-abusers. We also showed an important role of thoughts and behavioral disorganization as a mediator between SKZ+SUD and FER.
Little is known about who would benefit from Internet-based personalised nutrition (PN) interventions. This study aimed to evaluate the characteristics of participants who achieved greatest improvements (i.e. benefit) in diet, adiposity and biomarkers following an Internet-based PN intervention. Adults (n 1607) from seven European countries were recruited into a 6-month, randomised controlled trial (Food4Me) and randomised to receive conventional dietary advice (control) or PN advice. Information on dietary intake, adiposity, physical activity (PA), blood biomarkers and participant characteristics was collected at baseline and month 6. Benefit from the intervention was defined as ≥5 % change in the primary outcome (Healthy Eating Index) and secondary outcomes (waist circumference and BMI, PA, sedentary time and plasma concentrations of cholesterol, carotenoids and omega-3 index) at month 6. For our primary outcome, benefit from the intervention was greater in older participants, women and participants with lower HEI scores at baseline. Benefit was greater for individuals reporting greater self-efficacy for ‘sticking to healthful foods’ and who ‘felt weird if [they] didn’t eat healthily’. Participants benefited more if they reported wanting to improve their health and well-being. The characteristics of individuals benefiting did not differ by other demographic, health-related, anthropometric or genotypic characteristics. Findings were similar for secondary outcomes. These findings have implications for the design of more effective future PN intervention studies and for tailored nutritional advice in public health and clinical settings.
The disease caused by the influenza virus is a global public health problem due to its high rates of morbidity and mortality. Thus, analysis of the information generated by epidemiological surveillance systems has vital importance for health decision making. A retrospective analysis was performed using data generated by the four molecular diagnostic laboratories of the Mexican Social Security Institute between 2010 and 2016. Demographics, influenza positivity, seasonality, treatment choices and vaccination status analyses were performed for the vaccine according to its composition for each season. In all cases, both the different influenza subtypes and different age groups were considered separately. The circulation of A/H1N1pdm09 (48.7%), influenza A/H3N2 (21.1%), influenza B (12.6%), influenza A not subtyped (11%) and influenza A/H1N1 (6.6%) exhibited well-defined annual seasonality between November and March, and there were significant increases in the number of cases every 2 years. An inadequate use of oseltamivir was determined in 38% of cases, and the vaccination status in general varied between 12.1 and 18.5% depending on the season. Our results provide current information about influenza in Mexico and demonstrate the need to update both operational case definitions and medical practice guidelines to reduce the inappropriate use of antibiotics and antivirals.
Human papillomavirus (HPV) is a DNA virus linked to mucosal and cutaneous carcinogenesis. More than 200 different HPV types exist. We carried out a transversal study to investigate the prevalence of HPV types in two regions of Mexico. A total of 724 genital and non-genital samples from women (F) and men (M) were studied; 241 (33%) from North-Eastern (NE) and 483 (66%) from South-Central (SC) Mexico. The overall prevalence was 87%. In genital lesions from females, the NE group showed a prevalence of HPV types 16 (37%), 6 (13%), 59 (6%), 11, 18 and 66 (5.4% each); and the SC group showed types 6 (17%), 16 (15%), 11 (14.5%), 18 (12%) and 53 (6%). In the genital lesions from males, NE group showed types 16 (38%), 6 (21%), 11 (13%) and 59 plus 31 (7.5%) and the SC group showed types 6 (25%), 11 (22%), 18 (17%) and 16 (11.5%). When the two regions were compared, a higher prevalence of low-risk HPV 6 and 11 was found in the SC region and of high-risk HPV 59, 31 and 66 (the latter can also be present in benign lesions) in the NE region. Our findings complement efforts to understand HPV demographics as a prerequisite to guide and assess the impact of preventive interventions.
By using electrochemical tests, small signal variations were study by digital signal processing techniques. Electrochemical noise and electrochemical polarization curves were very useful to obtained electrochemical behavior of alloys, but the low signal levels of measurements obtained showed that some of the information was not likely to be measured and, therefore, not being able to identify. Graphene oxides (GO) samples were prepared by ball milling procedure adding Lithium. SIGVIEW software was used for Digital Signal studies. Comparing, the signals obtained by electrochemical techniques and the research by computational tools; it was possible to find out a behavior path of samples. Display devices made by graphene were observed to provide new information about the structure of samples and how nanotechnology area can be improved. The current investigation aimed at maintaining electrochemical stability, since different deformations, as twisting and bending are quite relevant in portable electronics devices.
Traditionally, personalised nutrition was delivered at an individual level. However, the concept of delivering tailored dietary advice at a group level through the identification of metabotypes or groups of metabolically similar individuals has emerged. Although this approach to personalised nutrition looks promising, further work is needed to examine this concept across a wider population group. Therefore, the objectives of this study are to: (1) identify metabotypes in a European population and (2) develop targeted dietary advice solutions for these metabotypes. Using data from the Food4Me study (n 1607), k-means cluster analysis revealed the presence of three metabolically distinct clusters based on twenty-seven metabolic markers including cholesterol, individual fatty acids and carotenoids. Cluster 2 was identified as a metabolically healthy metabotype as these individuals had the highest Omega-3 Index (6·56 (sd 1·29) %), carotenoids (2·15 (sd 0·71) µm) and lowest total saturated fat levels. On the basis of its fatty acid profile, cluster 1 was characterised as a metabolically unhealthy cluster. Targeted dietary advice solutions were developed per cluster using a decision tree approach. Testing of the approach was performed by comparison with the personalised dietary advice, delivered by nutritionists to Food4Me study participants (n 180). Excellent agreement was observed between the targeted and individualised approaches with an average match of 82 % at the level of delivery of the same dietary message. Future work should ascertain whether this proposed method could be utilised in a healthcare setting, for the rapid and efficient delivery of tailored dietary advice solutions.
Individual response to dietary interventions can be highly variable. The phenotypic characteristics of those who will respond positively to personalised dietary advice are largely unknown. The objective of this study was to compare the phenotypic profiles of differential responders to personalised dietary intervention, with a focus on total circulating cholesterol. Subjects from the Food4Me multi-centre study were classified as responders or non-responders to dietary advice on the basis of the change in cholesterol level from baseline to month 6, with lower and upper quartiles defined as responder and non-responder groups, respectively. There were no significant differences between demographic and anthropometric profiles of the groups. Furthermore, with the exception of alcohol, there was no significant difference in reported dietary intake, at baseline. However, there were marked differences in baseline fatty acid profiles. The responder group had significantly higher levels of stearic acid (18 : 0, P=0·034) and lower levels of palmitic acid (16 : 0, P=0·009). Total MUFA (P=0·016) and total PUFA (P=0·008) also differed between the groups. In a step-wise logistic regression model, age, baseline total cholesterol, glucose, five fatty acids and alcohol intakes were selected as factors that successfully discriminated responders from non-responders, with sensitivity of 82 % and specificity of 83 %. The successful delivery of personalised dietary advice may depend on our ability to identify phenotypes that are responsive. The results demonstrate the potential use of metabolic profiles in identifying response to an intervention and could play an important role in the development of precision nutrition.
To characterise clusters of individuals based on adherence to dietary recommendations and to determine whether changes in Healthy Eating Index (HEI) scores in response to a personalised nutrition (PN) intervention varied between clusters.
Food4Me study participants were clustered according to whether their baseline dietary intakes met European dietary recommendations. Changes in HEI scores between baseline and month 6 were compared between clusters and stratified by whether individuals received generalised or PN advice.
Individuals in cluster 1 (C1) met all recommended intakes except for red meat, those in cluster 2 (C2) met two recommendations, and those in cluster 3 (C3) and cluster 4 (C4) met one recommendation each. C1 had higher intakes of white fish, beans and lentils and low-fat dairy products and lower percentage energy intake from SFA (P<0·05). C2 consumed less chips and pizza and fried foods than C3 and C4 (P<0·05). C1 were lighter, had lower BMI and waist circumference than C3 and were more physically active than C4 (P<0·05). More individuals in C4 were smokers and wanted to lose weight than in C1 (P<0·05). Individuals who received PN advice in C4 reported greater improvements in HEI compared with C3 and C1 (P<0·05).
The cluster where the fewest recommendations were met (C4) reported greater improvements in HEI following a 6-month trial of PN whereas there was no difference between clusters for those randomised to the Control, non-personalised dietary intervention.
To characterise participants who dropped out of the Food4Me Proof-of-Principle study.
The Food4Me study was an Internet-based, 6-month, four-arm, randomised controlled trial. The control group received generalised dietary and lifestyle recommendations, whereas participants randomised to three different levels of personalised nutrition (PN) received advice based on dietary, phenotypic and/or genotypic data, respectively (with either more or less frequent feedback).
Seven recruitment sites: UK, Ireland, The Netherlands, Germany, Spain, Poland and Greece.
Adults aged 18–79 years (n 1607).
A total of 337 (21 %) participants dropped out during the intervention. At baseline, dropouts had higher BMI (0·5 kg/m2; P<0·001). Attrition did not differ significantly between individuals receiving generalised dietary guidelines (Control) and those randomised to PN. Participants were more likely to drop out (OR; 95 % CI) if they received more frequent feedback (1·81; 1·36, 2·41; P<0·001), were female (1·38; 1·06, 1·78; P=0·015), less than 45 years old (2·57; 1·95, 3·39; P<0·001) and obese (2·25; 1·47, 3·43; P<0·001). Attrition was more likely in participants who reported an interest in losing weight (1·53; 1·19, 1·97; P<0·001) or skipping meals (1·75; 1·16, 2·65; P=0·008), and less likely if participants claimed to eat healthily frequently (0·62; 0·45, 0·86; P=0·003).
Attrition did not differ between participants receiving generalised or PN advice but more frequent feedback was related to attrition for those randomised to PN interventions. Better strategies are required to minimise dropouts among younger and obese individuals participating in PN interventions and more frequent feedback may be an unnecessary burden.