Measuring the Refractive Index of Bovine Corneal Stromal Cells Using Quantitative Phase Imaging.

The cornea is the primary refractive lens in the eye and transmits >90% of incident visible light. It has been suggested that the development of postoperative corneal haze could be due to an increase in light scattering from activated corneal stromal cells. Quiescent keratocytes are thought to produce crystallins that match the refractive index of their cytoplasm to the surrounding extracellular material, reducing the amount of light scattering. To test this, we measured the refractive index (RI) of bovine corneal stromal cells, using quantitative phase imaging of live cells in vitro, together with confocal microscopy. The RI of quiescent keratocytes (RI = 1.381 ± 0.004) matched the surrounding matrix, thus supporting the hypothesis that keratocyte cytoplasm does not scatter light in the normal cornea. We also observed that the RI drops after keratocyte activation (RI = 1.365 ± 0.003), leading to a mismatch with the surrounding intercellular matrix. Theoretical scattering models showed that this mismatch would reduce light transmission in the cornea. We conclude that corneal transparency depends on the matching of refractive indices between quiescent keratocytes and the surrounding tissue, and that after surgery or wounding, the resulting RI mismatch between the activated cells and their surrounds significantly contributes to light scattering.

A multi-stage random forest classifier for phase contrast cell segmentation.

We present a machine learning based approach to automatically detect and segment cells in phase contrast images. The proposed method consists of a multi-stage classification scheme based on random forest (RF) classifier. Both low level and mid level image features are used to determine meaningful cell regions. Pixel-wise RF classification is first carried out to categorize pixels into 4 classes (dark cell, bright cell, halo artifact, and background) and generate a probability map for cell regions. K-means clustering is then applied on the probability map to group similar pixels into candidate cell regions. Finally, cell validation is performed by another RF to verify the candidate cell regions. The proposed method has been tested on U2-OS human osteosarcoma phase contrast images. The experimental results show better performance of the proposed method with precision 92.96% and recall 96.63% compared to a state-of-the-art segmentation technique.

ProtocolNavigator: emulation-based software for the design, documentation and reproduction biological experiments.

MOTIVATION: Experimental reproducibility is fundamental to the progress of science. Irreproducible research decreases the efficiency of basic biological research and drug discovery and impedes experimental data reuse. A major contributing factor to irreproducibility is difficulty in interpreting complex experimental methodologies and designs from written text and in assessing variations among different experiments. Current bioinformatics initiatives either are focused on computational research reproducibility (i.e. data analysis) or laboratory information management systems. Here, we present a software tool, ProtocolNavigator, which addresses the largely overlooked challenges of interpretation and assessment. It provides a biologist-friendly open-source emulation-based tool for designing, documenting and reproducing biological experiments. AVAILABILITY AND IMPLEMENTATION: ProtocolNavigator was implemented in Python 2.7, using the wx module to build the graphical user interface. It is a platform-independent software and freely available from http://protocolnavigator.org/index.html under the GPL v2 license.

Elevated breast cancer mortality in women younger than age 40 years compared with older women is attributed to poorer survival in early-stage disease.

BACKGROUND: We investigated differences in breast cancer mortality between younger (younger than 40 years of age) and older (40 years of age and older) women by stage at diagnosis to identify patient and tumor characteristics accounting for disparities. STUDY DESIGN: We conducted a retrospective study of women diagnosed with breast cancer in the 1988 to 2003 Surveillance, Epidemiology, and End Results Program data. Multivariate Cox regression models calculated adjusted hazard ratios (aHR) and 95% confidence intervals to compare overall and stage-specific breast cancer mortality in women younger than 40 years old and women 40 years and older, controlling for potential confounding variables identified in univariate tests. RESULTS: Of 243,012 breast cancer patients, 6.4% were younger than 40 years old, and 93.6% were 40 years of age or older. Compared with older women, younger women were more likely to be African American, single, diagnosed at later stages, and treated by mastectomy. Younger women had tumors that were more likely to be higher grade, larger size, estrogen receptor/progesterone receptor-negative, and lymph-node positive (p < 0.001). Younger women were more likely to die from breast cancer compared with older women (crude HR = 1.39; CI, 1.34 to 1.45). Controlling for confounders, younger women were more likely to die compared with older women if diagnosed with stage I (aHR = 1.44; CI, 1.27 to 1.64) or stage II (aHR = 1.09; CI, 1.03 to 1.15) disease and less likely to die if diagnosed with stage IV disease (aHR = 0.85; CI, 0.76 to 0.95). CONCLUSIONS: Higher breast cancer mortality in younger women was attributed to poorer outcomes with early-stage disease. Additional studies should focus on specific tumor biology contributing to the increased mortality of younger women with early-stage breast cancer.

ProgeniDB: a novel cell lineage database for generation associated phenotypic behavior in cell-based assays.

ProgeniDB is a web-accessible cell lineage database, which comprises data derived from time-lapse microscopy image sequences, using our novel encoding software tool called ProgeniTRAK. This database provides information on qualitative and quantitative changes in cellular dynamics in response to anti-cancer drugs variation, which is critical for pharmacodynamic modeling and validation. The lineage data for each progenitor cell centers around the construction of a bifurcation map, locating in both space and time critical cellular events such as cell division and cell death. This database provides the opportunity to select a set of lineages based on different experimental constraints and observe the associated phenotypic behavior of progenitor cells. The output generated from this database depicts the cellular dynamic of selected population which can be downloaded to explore and exploit in relation to hypothesis-driven drug discovery. A case study is presented where we interrogate drug-induced perturbations on ensuing cell lineages. The database is available at http://biodiversity.cs.cf.ac.uk/cymart/progenidb.html.