Human evolution, nutritional ecology and prebiotics in ancient diet

Modern studies of prebiotic non digestible carbohydrates continue to expand and demonstrate their colonic and systemic benefits. However, virtually nothing is known of their use among ancient populations. In this paper we discuss evidence for prebiotic use in the archaeological record from select areas of the world. It is suggested that members of our genus Homo would have had sufficient ecological opportunity to include prebiotic-bearing plants in diet as early as ~ 2 million years ago, but that significant dietary intake would not have taken place until the advent of technological advances that characterized the Upper Paleolithic of ~40,000 years ago. Throughout human evolution, hominid populations that diversified their diet to include prebiotic-bearing plants would have had a selective advantage over competitors.

Artificial neural networks: A novel approach to analysing the nutritional ecology of a blowfly species, Chrysomya megacephala

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Nutritional ecology of blowflies (Diptera, Calliphoridae): estimates of critical larval weight for pupation on two different diets

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Ecología nutricional del lactante y del niño en edad preescolar: problemas de nutrición en América Latina = The nutritional ecology of the infant and pre-school child: nutritional problems in Latin America

Incluye Bibliografía

Landscape Diversity Influences Dispersal and Establishment of Pest with Complex Nutritional Ecology

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Sex differences in insect immune function : a consequence of diet choice?

Males often have reduced immune function compared to females but the proximate mechanisms underlying this taxonomically widespread pattern are unclear. Because immune function is resource-dependent and sexes may have different nutritional requirements, we hypothesized that sexual dimorphism in immune function may arise from differential nutrient intake (acquisition hypothesis). To test this hypothesis, we examined patterns of phenoloxidase (PO) activity in relation to nutrient consumption in Queensland fruit flies (Q-flies). In the first experiment, flies were allowed to choose their preferred nutrient intake. Compared with males, female Q-flies had higher PO activity, consumed more calories, and preferred a higher protein:carbohydrate (P:C) diet, suggesting that differential acquisition could explain sex differences. In the second experiment, we restricted flies to one of 12 diets varying in protein and carbohydrate concentrations and mapped PO activity for each sex onto a nutritional landscape. Counter to our hypothesis, females had higher PO activity than males at any given level of nutrient intake. Both carbohydrate and protein intake affected PO activity in females but only protein affected PO activity in males. Our results indicate that sex differences in Q-fly immune function are not solely explained by sex differences in nutrient intake, although nutrition does contribute to the magnitude of these sex differences.

Ecologia populacional de Lucilia cuprina (Wiedemann, 1830) (Diptera, Calliphoridae): aspecto do desenvolvimento em diferentes densidades larvais e seus efeitos sobre os adultos resultantes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Consumo foliar da traça-das-crucíferas em couve e brócolis tratados com sinigrina

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A mathematical approach to simulate spatio-temporal patterns of an insect-pest, the corn rootworm Diabrotica speciosa (Coleoptera: Chrysomelidae) in intercropping systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)