The Rotterdam Study: 2010 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in close to a 1,000 research articles and reports (see www.epib.nl/rotterdamstudy). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods

Bacterial Infection Increases Periodontal Bone Loss in Diabetic Rats through Enhanced Apoptosis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Periodontal disease is the most common osteolytic disease in humans and is significantly increased by diabetes mellitus. We tested the hypothesis that bacterial infection induces bone loss in diabetic animals through a mechanism that involves enhanced apoptosis. Type II diabetic rats were inoculated with Aggregatibacter actinomycetemcomitans and treated with a caspase-3 inhibitor, ZDEVD-FMK, or vehicle alone. Apoptotic cells were measured with TUNEL; osteoblasts and bone area were measured in H&E sections. New bone formation was assessed by labeling with fluorescent dyes and by osteocalcin mRNA levels. Osteoclast number, eroded bone surface, and new bone formation were measured by tartrate-resistant acid phosphatase staining. Immunohistochemistry was performed with an antibody against tumor necrosis factor-alpha. Bacterial infection doubled the number of tumor necrosis factor-alpha-expressing cells and increased apoptotic cells adjacent to bone 10-fold (P < 0.05). Treatment with caspase inhibitor blocked apoptosis, increased the number of osteoclasts, and eroded bone surface (P < 0.05); yet, inhibition of apoptosis resulted in significantly greater net bone area because of an increase in new bone formation, osteoblast numbers, and an increase in bone coupling. Thus, bacterial infection in diabetic rats stimulates periodontitis, in part through enhanced apoptosis of osteoblastic cells that reduces osseous coupling through a caspase-3 dependent mechanism.183619281935NIH [DE017732]Penn Center for Musculoskeletal Disorders from NIAMS [P30AR050950]Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)NIH [DE017732]Penn Center for Musculoskeletal Disorders from NIAMS [P30AR050950

CellECT: cell evolution capturing tool

BACKGROUND: Robust methods for the segmentation and analysis of cells in 3D time sequences (3D+t) are critical for quantitative cell biology. While many automated methods for segmentation perform very well, few generalize reliably to diverse datasets. Such automated methods could significantly benefit from at least minimal user guidance. Identification and correction of segmentation errors in time-series data is of prime importance for proper validation of the subsequent analysis. The primary contribution of this work is a novel method for interactive segmentation and analysis of microscopy data, which learns from and guides user interactions to improve overall segmentation. RESULTS: We introduce an interactive cell analysis application, called CellECT, for 3D+t microscopy datasets. The core segmentation tool is watershed-based and allows the user to add, remove or modify existing segments by means of manipulating guidance markers. A confidence metric learns from the user interaction and highlights regions of uncertainty in the segmentation for the user’s attention. User corrected segmentations are then propagated to neighboring time points. The analysis tool computes local and global statistics for various cell measurements over the time sequence. Detailed results on two large datasets containing membrane and nuclei data are presented: a 3D+t confocal microscopy dataset of the ascidian Phallusia mammillata consisting of 18 time points, and a 3D+t single plane illumination microscopy (SPIM) dataset consisting of 192 time points. Additionally, CellECT was used to segment a large population of jigsaw-puzzle shaped epidermal cells from Arabidopsis thaliana leaves. The cell coordinates obtained using CellECT are compared to those of manually segmented cells. CONCLUSIONS: CellECT provides tools for convenient segmentation and analysis of 3D+t membrane datasets by incorporating human interaction into automated algorithms. Users can modify segmentation results through the help of guidance markers, and an adaptive confidence metric highlights problematic regions. Segmentations can be propagated to multiple time points, and once a segmentation is available for a time sequence cells can be analyzed to observe trends. The segmentation and analysis tools presented here generalize well to membrane or cell wall volumetric time series datasets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-0927-7) contains supplementary material, which is available to authorized users