Seasonality of suicide behavior in Northwest Alaska: 1990-2009.

OBJECTIVES: Suicide is a leading cause of death worldwide, and disproportionately affects Indigenous populations. Seasonal suicide patterns are variable in the literature, and could offer novel approaches to the timing and focus of prevention efforts if better understood. With a suicide surveillance system in place since 1989, this study offers an unprecedented opportunity to explore seasonal variations in both fatal and non-fatal suicide behavior in an Indigenous Arctic region. STUDY DESIGN: Cross-sectional. METHODS: In this descriptive study, we analyzed data collected from 1990 to 2009 in the rural northwest region of Alaska, both graphically and using the chi-squared test for multinomials. RESULTS: We found a significant monthly variation for suicide attempts, with a peak in suicide behavior observed between April and August (P = 0.0002). Monthly variation was more pronounced among individuals ≤29 years of age, and was present in both males and females, although the seasonal pattern differed by sex. CONCLUSIONS: Our findings of a significant seasonal pattern in suicide behavior, with monthly variation (summer peak) in non-fatal suicide behavior among younger age groups, and among both males and females can assist planners in targeting subpopulations for prevention at different times of the year.

A cell-ECM screening method to predict breast cancer metastasis.

Breast cancer preferentially spreads to the bone, brain, liver, and lung. The clinical patterns of this tissue-specific spread (tropism) cannot be explained by blood flow alone, yet our understanding of what mediates tropism to these physically and chemically diverse tissues is limited. While the microenvironment has been recognized as a critical factor in governing metastatic colonization, the role of the extracellular matrix (ECM) in mediating tropism has not been thoroughly explored. We created a simple biomaterial platform with systematic control over the ECM protein density and composition to determine if integrin binding governs how metastatic cells differentiate between secondary tissue sites. Instead of examining individual behaviors, we compiled large patterns of phenotypes associated with adhesion to and migration on these controlled ECMs. In combining this novel analysis with a simple biomaterial platform, we created an in vitro fingerprint that is predictive of in vivo metastasis. This rapid biomaterial screen also provided information on how ß1, α2, and α6 integrins might mediate metastasis in patients, providing insights beyond a purely genetic analysis. We propose that this approach of screening many cell-ECM interactions, across many different heterogeneous cell lines, is predictive of in vivo behavior, and is much simpler, faster, and more economical than complex 3D environments or mouse models. We also propose that when specifically applied toward the question of tissue tropism in breast cancer, it can be used to provide insight into certain integrin subunits as therapeutic targets.