Modes of cell death in the hypopharyngeal gland of the honey bee (Apis mellifera L)

Different modes of cell death have been revealed in the regressing hypopharyngeal glands of worker honey bees. The hypopharyngeal gland, which is well developed in young nursing bees to produce protein for larval food, was seen to regress naturally in foraging adult worker bees. A range of techniques including histology, cytochemistry, in situ TUNEL, Annexin V and Comet assays indicated that cells within the gland demonstrate progressive symptoms of apoptosis, necrosis and a vacuolar form of programmed cell death. The latter mode of cell death did not display chromatin margination, but was accompanied by an enhanced level of autophagic and hydrolytic activity in which a cytosolic source of acid phosphatase became manifest in the extra-cisternal spaces. Normal and annexin-positive cells were found to occur in the younger nursing bees, whilst necrosis and an aberrant vacuolar type of apoptosis predominated in the older foraging bees. The relevance of these results to the classification of programmed cell death is discussed. (C) 2000 Academic Press.

Morphological characterization of cell death during the ovary differentiation in worker honey bee

Cell death that occurs during ovary differentiation in the honeybee worker's larval development accounts for ovariole reabsorption. From a morphological standpoint, three modes of death were detected. Germinative cells in the ovarioles die by an apoptotic-like process, whereas the somatic cells die by an autophagic process, type 11 cell death; and during pupation, stromatic and ovarian capsular cells die through cytoplasmic disintegration, releasing their components into the hemolymph. These modes of cell death are in part determined by the pattern of tissue organization within which the cell occurs. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

Morphological alteration of peritoneal mast cells and macrophages in the mouse peritoneal cavity during the early phases of an allergic inflammatory reaction

We investigated the presence of mast cell granules in macrophages following an in vivo model of an allergic reaction. Injection of ovalbumin (100 mug) into the peritoneal cavity of sensitised mice produced a rapid (within 2 h) influx of neutrophils followed by a slower (after >4 h) eosinophil migration. Ovalbumin treatment induced a high incidence (similar to 50%) of mast cell degranulation compared to control phosphated-buffered saline-treated mice. The majority (similar to 90%) of peritoneal macrophages contained mast cell granules as early as 2 It post-ovalbumin, with lower values at later time-points, as determined by staining with Toluidine blue and Berberine sulphate. This was confirmed by electron microscopy which enabled us to identify the complex mast cell granule sub-structural components in macrophage phagosomes. In conclusion, we used histochemical and ultrastructural analyses to show that mast cell granules become internalised with macrophages during the early stages of an experimental allergic reaction. (C) 2001 Academic Press.

Representação, acesso, uso e reuso da imagem digital

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

A scalable re-ranking method for content-based image retrieval

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

Image Re-Ranking Acceleration on GPUs

Huge image collections are becoming available lately. In this scenario, the use of Content-Based Image Retrieval (CBIR) systems has emerged as a promising approach to support image searches. The objective of CBIR systems is to retrieve the most similar images in a collection, given a query image, by taking into account image visual properties such as texture, color, and shape. In these systems, the effectiveness of the retrieval process depends heavily on the accuracy of ranking approaches. Recently, re-ranking approaches have been proposed to improve the effectiveness of CBIR systems by taking into account the relationships among images. The re-ranking approaches consider the relationships among all images in a given dataset. These approaches typically demands a huge amount of computational power, which hampers its use in practical situations. On the other hand, these methods can be massively parallelized. In this paper, we propose to speedup the computation of the RL-Sim algorithm, a recently proposed image re-ranking approach, by using the computational power of Graphics Processing Units (GPU). GPUs are emerging as relatively inexpensive parallel processors that are becoming available on a wide range of computer systems. We address the image re-ranking performance challenges by proposing a parallel solution designed to fit the computational model of GPUs. We conducted an experimental evaluation considering different implementations and devices. Experimental results demonstrate that significant performance gains can be obtained. Our approach achieves speedups of 7x from serial implementation considering the overall algorithm and up to 36x on its core steps.