Wolbachia endosymbiont in a species of the Anastrepha fraterculus complex (Diptera: Tephritidae)

In Anastrepha sp.2 aff. fraterculus, the egg-cell harbours a large population of endosymbionts. The bacteria were identified as belonging to genus Wolbachia by PCR assay using primers of the ftsZ gene followed by sequencing of the amplified band. Newly deposited eggs stained in toto by Hoechst show that the bacteria are unevenly dispersed throughout the egg-cell, with a higher accumulation at the posterior pole, and that the degree of infestation varies from egg to egg. Analysis by transmission electron microscopy shows that bacteria are present in the female germ line of embryonic and larval stages, as well as in the different cell types of the ovaries at the adult stage. Mature ova within the follicles harbour a large population of the symbionts. The results indicate the existence of a transovarian transmission of the endosymbionts in this fly.

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)

Cytoplasmic bridges, intercellular junctions, and individualization of germ cells during spermatogenesis in Dermatobia hominis (Diptera: Cuterebridae)

During mitotic and meiotic divisions in Dermatobia hominis spermatogenesis, the germ cells stay interlinked by cytoplasm, bridges as a result of incomplete cytokinesis. By the end of each division, cytoplasmic bridges flow to the center of the cyst, forming a complex, called the fusoma. During meiotic prophase I, spermatocytes I present desmosome-like junctions and meiotic cytoplasmic bridges. At the beginning of spermiogenesis, the fusoma moves to the future caudal end of the cyst, and at this time the early spermatids are linked by desmosome-like junctions. Throughout spermiogensis, new and sometimes broad cytoplasmic bridges are formed among spermatids at times making them share cytoplasm. In this case the individualization of cells is assured by the presence of smooth cisternae that outline then structures The more differentiated spermatids have in addition to narrow cytoplasmic bridges, plasmic membranes junctions. By the end of spermiogenesis the excess cytoplasmic mass is eliminated leading to spermatid individualization. Desmosome-like junctions of spermatocytes I and early spermatids appear during the fusoma readjustment and segregations; on the other hand, plasmic membrane junctions appear in differentiating spermatids and are eliminated along with the cytoplasmic excess. These circumstances suggest that belt desmosome-like and plasmic membrane junctions are involved in the maintenance of the relative positions of male germ cells in D. hominis while they are inside the cysts. © 1996 Wiley-Liss, Inc.

Dinâmica populacional de Zaprionus indianus (Gupta, 1970) (Diptera: Drosophilidae) sob condições experimentais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Post-Embryonic Development in Zaprionus indianus (Diptera: Drosophilidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Resposta olfativa de fêmeas de Chrysomya Megacephala (F.) (Diptera: Calliphoridae) frente a posturas prévias e caracterização química dos compostos apolares da superfície de seus ovos

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

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.