143 resultados para Diet records
Resumo:
Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.
Resumo:
Background: Obese adults are prone to develop metabolic and cardiovascular diseases. Furthermore, over-weight expectant mothers give birth to large babies who also have increased likelihood of developing metabolic and cardiovascular diseases. Fundamental advancements to better understand the pathophysiology of obesity are critical in the development of anti-obesity therapies not only for this but also future generations. Skeletal muscle plays a major role in fat metabolism and much work has focused in promoting this activity in order to control the development of obesity. Research has evaluated myostatin inhibition as a strategy to prevent the development of obesity and concluded in some cases that it offers a protective mechanism against a high-fat diet. Results: We hypothesised that myostatin inhibition should protect not only the mother but also its developing foetus from the detrimental effects of a high-fat diet. Unexpectedly, we found muscle development was attenuated in the foetus of myostatin null mice raised on a high-fat diet. We therefore re-examined the effect of the high-fat diet on adults and found myostatin null mice were more susceptible to diet-induced obesity through a mechanism involving impairment of inter-organ fat utilization. Conclusions: Loss of myostatin alters fatty acid uptake and oxidation in skeletal muscle and liver. We show that abnormally high metabolic activity of fat in myostatin null mice is decreased by a high-fat diet resulting in excessive adipose deposition and lipotoxicity. Collectively, our genetic loss-of-function studies offer an explanation of the lean phenotype displayed by a host of animals lacking myostatin signalling. Keywords: Muscle, Obesity, High-fat diet, Metabolism, Myostatin
Resumo:
The importance of chronic low-grade inflammation in the pathology of numerous age-related chronic conditions is now clear. An unresolved inflammatory response is likely to be involved from the early stages of disease development. The present position paper is the most recent in a series produced by the International Life Sciences Institute's European Branch (ILSI Europe). It is co-authored by the speakers from a 2013 workshop led by the Obesity and Diabetes Task Force entitled ‘Low-grade inflammation, a high-grade challenge: biomarkers and modulation by dietary strategies’. The latest research in the areas of acute and chronic inflammation and cardiometabolic, gut and cognitive health is presented along with the cellular and molecular mechanisms underlying inflammation–health/disease associations. The evidence relating diet composition and early-life nutrition to inflammatory status is reviewed. Human epidemiological and intervention data are thus far heavily reliant on the measurement of inflammatory markers in the circulation, and in particular cytokines in the fasting state, which are recognised as an insensitive and highly variable index of tissue inflammation. Potential novel kinetic and integrated approaches to capture inflammatory status in humans are discussed. Such approaches are likely to provide a more discriminating means of quantifying inflammation–health/disease associations, and the ability of diet to positively modulate inflammation and provide the much needed evidence to develop research portfolios that will inform new product development and associated health claims.
Resumo:
Although milk consumption is recommended in most dietary guidelines around the world, its contribution to overall diet quality remains a matter of debate in the scientific community as well as in the public. This paper summarizes the discussion among experts in the field on the place of milk in a balanced, healthy diet. The evidence to date suggests at least a neutral effect of milk intake on health outcomes. The possibility that milk intake is simply a marker of higher nutritional quality diets cannot be ruled out. This review also identifies a number of key research gaps pertaining to the impact of milk consumption on health. These need to be addressed to better inform future dietary guidelines.
Resumo:
Accurate knowledge of species’ habitat associations is important for conservation planning and policy. Assessing habitat associations is a vital precursor to selecting appropriate indicator species for prioritising sites for conservation or assessing trends in habitat quality. However, much existing knowledge is based on qualitative expert opinion or local scale studies, and may not remain accurate across different spatial scales or geographic locations. Data from biological recording schemes have the potential to provide objective measures of habitat association, with the ability to account for spatial variation. We used data on 50 British butterfly species as a test case to investigate the correspondence of data-derived measures of habitat association with expert opinion, from two different butterfly recording schemes. One scheme collected large quantities of occurrence data (c. 3 million records) and the other, lower quantities of standardised monitoring data (c. 1400 sites). We used general linear mixed effects models to derive scores of association with broad-leaf woodland for both datasets and compared them with scores canvassed from experts. Scores derived from occurrence and abundance data both showed strongly positive correlations with expert opinion. However, only for occurrence data did these fell within the range of correlations between experts. Data-derived scores showed regional spatial variation in the strength of butterfly associations with broad-leaf woodland, with a significant latitudinal trend in 26% of species. Sub-sampling of the data suggested a mean sample size of 5000 occurrence records per species to gain an accurate estimation of habitat association, although habitat specialists are likely to be readily detected using several hundred records. Occurrence data from recording schemes can thus provide easily obtained, objective, quantitative measures of habitat association.
Resumo:
The present study aims to investigate the dose dependent effects of consuming diets enriched in flavonoid-rich and flavonoid-poor fruits and vegetables on the urine metabolome of adults who had a C1.5 fold increased risk of cardiovascular diseases. A single-blind, dose-dependent, parallel randomized controlled dietary intervention was conducted where volunteers (n = 126) were randomly assigned to one of three diets: high flavonoid diet, low flavonoid diet or habitual diet as a control for 18 weeks. High resolution LC– MS untargeted metabolomics with minimal sample cleanup was performed using an Orbitrap mass spectrometer. Putative biomarkers which characterize diets with high and low flavonoid content were selected by state-of-the-art data analysis strategies and identified by HR-MS and HR-MS/MS assays. Discrimination between diets was observed by application of two linear mixedmodels: one including a diet-time interaction effect and the second containing only a time effect. Valerolactones, phenolic acids and their derivatives were among sixteen biomarkers related to the high flavonoid dietary exposure. Four biomarkers related to the low flavonoid diet belonged to the family of phenolic acids. For the first time abscisic acid glucuronide was reported as a biomarker after a dietary intake, however its origins have to be examined by future hypothesis driven experiments using a more targeted approach. This metabolomic analysis has identified a number of dose dependent urinary biomarkers (i.e. proline betaine or iberin-N-acetyl cysteine), which can be used in future observation and intervention studies to assess flavonoids and nonflavonoid phenolic intakes and compliance to fruit and vegetable intervention.