Metabarcoding analysis of gut microbiota of healthy individuals reveals impact of probiotic and maltodextrin consumption

In a previously published double-blind, placebo-controlled study, we showed that probiotics intake exerted a positive effect on sleep quality and a general improvement across time in different aspects of the profile of mood state, like sadness, anger, and fatigue in 33 healthy individuals. The present work investigates the impact of the probiotic product, constituted of Limosilactobacillus fermentum LF16, Lacticaseibacillus rhamnosus LR06, Lactiplantibacillus plantarum LP01 (all former members of Lactobacillus genus), and Bifidobacterium longum 04, on the gut microbiota composition of the same cohort through a metabarcoding analysis. Both the placebo and probiotic treatments had a significant impact on the microbiota composition. Statistical analysis showed that the microbiota of the individuals could be clustered into three groups, or bacteriotypes, at the baseline, and, inherently, bacterial compositions were linked to different responses to probiotic and placebo intakes. Interestingly, L. rhamnosus and L. fermentum were retrieved in the probiotic-treated cohort, while a bifidogenic effect of maltodextrin, used as placebo, was observed. The present study shed light on the importance of defining bacteriotypes to assess the impact of interventions on the gut microbiota and allowed to reveal microbial components which could be related to positive effects (i.e. sleep quality improvement) to be verified in further studies

Analyzing the Effect of Time in Migration Measurement Using Georeferenced Digital Trace Data

Georeferenced digital trace data offer unprecedented flexibility in migration estimation. Because of their high temporal granularity, many migration estimates can be generated from the same data set by changing the definition parameters. Yet despite the growing application of digital trace data to migration research, strategies for taking advantage of their temporal granularity remain largely underdeveloped. In this paper, we provide a general framework for converting digital trace data into estimates of migration transitions and for systematically analyzing their variation along a quasi-continuous time scale, analogous to a survival function. From migration theory, we develop two simple hypotheses regarding how we expect our estimated migration transition functions to behave. We then test our hypotheses on simulated data and empirical data from three platforms in two internal migration contexts: geotagged Tweets and Gowalla check-ins in the United States, and cell-phone call detail records in Senegal. Our results demonstrate the need for evaluating the internal consistency of migration estimates derived from digital trace data before using them in substantive research. At the same time, however, common patterns across our three empirical data sets point to an emergent research agenda using digital trace data to study the specific functional relationship between estimates of migration and time and how this relationship varies by geography and population characteristics

Daily bathing with 4% chlorhexidine gluconate in intensive care settings: a randomized controlled trial

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Resposta da cultura do milho a adubação nitrogenada após cultivo de tremoço branco (Lupinus albus) em duas unidades de solos.

Este trabalho teve por objetivo estudar a influência de dois fertilizantes nitrogenados na produção de grãos e de matéria seca do milho nos solos Podzolico Vermelho Amarelo Latossolico eutrofico (PVLe) e Podzolico Vermelho Amarelo Latossolico distrofico (PVLd), cultivados previamente com tremoço branco

Effects of PPARγ agonists on the expression of leptin and vascular endothelial growth factor in breast cancer cells.

The obesity hormone leptin has been implicated in breast cancer development. Breast cancer cells express the leptin receptor and are able to synthesize leptin in response to obesity-related stimuli. Furthermore, leptin is a positive regulator of vascular endothelial growth factor (VEGF) and high levels of both proteins are associated with worse prognosis in breast cancer patients. Peroxisome proliferator-activated receptor (PPAR) ligands are therapeutic agents used in patient with Type 2 diabetes and obesity which have recently been studied for their potential anti-tumor effect. Here, we studied if these compounds, ciglitazone and GW1929, can affect the expression of leptin and VEGF in breast cancer cells. In MDA-MB-231 and MCF-7 breast cancer cells, treatment with submolar concentrations of ciglitazone and GW1929 elevated the expression of leptin and VEGF mRNA and protein, and increased cell viability and migration. These effects coincided with increased recruitment of PPAR to the proximal leptin promoter and decreased association of a transcriptional factor Sp1 with this DNA region