Modeling mesothelioma risk associated with environmental asbestos exposure

BACKGROUND: Environmental asbestos pollution can cause malignant mesothelioma, but few studies have involved dose–response analyses with detailed information on occupational, domestic, and environmental exposures. OBJECTIVES: In the present study, we examined the spatial variation of mesothelioma risk in an area with high levels of asbestos pollution from an industrial plant, adjusting for occupational and domestic exposures. METHODS: This population-based case–control study included 103 incident cases of mesothelioma and 272 controls in 1987–1993 in the area around Casale Monferrato, Italy, where an important asbestos cement plant had been active for decades. Information collected included lifelong occupational and residential histories. Mesothelioma risk was estimated through logistic regression and a mixed additive–multiplicative model in which an additive scale was assumed for the risk associated with both residential distance from the plant and occupational exposures. The adjusted excess risk gradient by residential distance was modeled as an exponential decay with a threshold. RESULTS: Residents at the location of the asbestos cement factory had a relative risk for mesothelioma of 10.5 [95% confidence interval (CI), 3.8–50.1), adjusted for occupational and domestic exposures. Risk decreased rapidly with increasing distance from the factory, but at 10-km the risk was still 60% of its value at the source. The relative risk for occupational exposure was 6.0 (95% CI, 2.9–13.0), but this increased to 27.5 (95% CI, 7.8–153.4) when adjusted for residential distance. CONCLUSIONS: This study provides strong evidence that asbestos pollution from an industrial source greatly increases mesothelioma risk. Furthermore, relative risks from occupational exposure were underestimated and were markedly increased when adjusted for residential distance

Destruction of Tissue, Cells and Organelles in Type 1 Diabetic Rats Presented at Macromolecular Resolution

<p>Finding alternatives for insulin therapy and making advances in etiology of type 1 diabetes benefits from a full structural and functional insight into Islets of Langerhans. Electron microscopy (EM) can visualize Islet morphology at the highest possible resolution, however, conventional EM only provides biased snapshots and lacks context. We developed and employed large scale EM and compiled a resource of complete cross sections of rat Islets during immuno-destruction to provide unbiased structural insight of thousands of cells at macromolecular resolution. The resource includes six datasets, totalling 25.000 micrographs, annotated for cellular and ultrastructural changes during autoimmune diabetes. Granulocytes are attracted to the endocrine tissue, followed by extravasation of a pleiotrophy of leukocytes. Subcellullar changes in beta cells include endoplasmic reticulum stress, insulin degranulation and glycogen accumulation. Rare findings include erythrocyte extravasation and nuclear actin-like fibers. While we focus on a rat model of autoimmune diabetes, our approach is general applicable.</p>

Dark side illuminated: imaging of Toxoplasma gondii through the decades

In the more than 100 years since its discovery, our knowledge of Toxoplasma biology has improved enormously. The evolution of molecular biology, immunology and genomics has had profound influences on our understanding of this ubiquitous bug. However, it could be argued that in science today the adage "seeing is believing" has never been truer. Images are highly influential and in the time since the first description of T. gondii, advances in microscopy and imaging technology have been and continue to be dramatic. In this review we recount the discovery of T. gondii and the contribution of imaging techniques to elucidating its life cycle, biology and the immune response of its host