Mitochondrial preprotein translocase of trypanosomatids has a bacterial origin

Mitochondria are found in all eukaryotic cells and derive from a bacterial endosymbiont [1, 2]. The evolution of a protein import system was a prerequisite for the conversion of the endosymbiont into a true organelle. Tom40, the essential component of the protein translocase of the outer membrane, is conserved in mitochondria of almost all eukaryotes but lacks bacterial orthologs [3-6]. It serves as the gateway through which all mitochondrial proteins are imported. The parasitic protozoa Trypanosoma brucei and its relatives do not have a Tom40-like protein, which raises the question of how proteins are imported by their mitochondria [7, 8]. Using a combination of bioinformatics and in vivo and in vitro studies, we have discovered that T. brucei likely employs a different import channel, termed ATOM (archaic translocase of the outer mitochondria! membrane). ATOM mediates the import of nuclear-encoded proteins into mitochondria and is essential for viability of trypanosomes. It is not related to Tom40 but is instead an ortholog of a subgroup of the 0mp85 protein superfamily that is involved in membrane translocation and insertion of bacterial outer membrane proteins [9]. This suggests that the protein import channel in trypanosomes is a relic of an archaic protein transport system that was operational in the ancestor of all eukaryotes.

Smooth Hazard Function Estimation for Interval Censored Data with Time Varying Covariates

In this paper we propose methods for smooth hazard estimation of a time variable where that variable is interval censored. These methods allow one to model the transformed hazard in terms of either smooth (smoothing splines) or linear functions of time and other relevant time varying predictor variables. We illustrate the use of this method on a dataset of hemophiliacs where the outcome, time to seroconversion for HIV, is interval censored and left-truncated.

PROBABILISTIC MODELING OF RAINFALL INDUCED LANDSLIDE HAZARD ASSESSMENT IN SAN JUAN LA LAGUNA, SOLOLÁ, GUATEMALA

The municipality of San Juan La Laguna, Guatemala is home to approximately 5,200 people and located on the western side of the Lake Atitlán caldera. Steep slopes surround all but the eastern side of San Juan. The Lake Atitlán watershed is susceptible to many natural hazards, but most predictable are the landslides that can occur annually with each rainy season, especially during high-intensity events. Hurricane Stan hit Guatemala in October 2005; the resulting flooding and landslides devastated the Atitlán region. Locations of landslide and non-landslide points were obtained from field observations and orthophotos taken following Hurricane Stan. This study used data from multiple attributes, at every landslide and non-landslide point, and applied different multivariate analyses to optimize a model for landslides prediction during high-intensity precipitation events like Hurricane Stan. The attributes considered in this study are: geology, geomorphology, distance to faults and streams, land use, slope, aspect, curvature, plan curvature, profile curvature and topographic wetness index. The attributes were pre-evaluated for their ability to predict landslides using four different attribute evaluators, all available in the open source data mining software Weka: filtered subset, information gain, gain ratio and chi-squared. Three multivariate algorithms (decision tree J48, logistic regression and BayesNet) were optimized for landslide prediction using different attributes. The following statistical parameters were used to evaluate model accuracy: precision, recall, F measure and area under the receiver operating characteristic (ROC) curve. The algorithm BayesNet yielded the most accurate model and was used to build a probability map of landslide initiation points. The probability map developed in this study was also compared to the results of a bivariate landslide susceptibility analysis conducted for the watershed, encompassing Lake Atitlán and San Juan. Landslides from Tropical Storm Agatha 2010 were used to independently validate this study’s multivariate model and the bivariate model. The ultimate aim of this study is to share the methodology and results with municipal contacts from the author's time as a U.S. Peace Corps volunteer, to facilitate more effective future landslide hazard planning and mitigation.

Materials-Handling Hazard Controls: Assessment of Haddon’s Injury Control Strategies

This investigation assessed the applicability of Dr. William Haddon’s strategies for controlling hazards involving materials-handling operations in industrial and mining workplaces. Published over 20 years ago, Haddon’s strategies purport to include all strategies for preventing and mitigating harm to people, property, and the environment. Students in an undergraduate class were assigned to find tactical examples of each of Haddon’s strategies applicable to material handling. Haddon’s tenth strategy involving medical care and rehabilitation was not included. Their classifications were analyzed to identify points of confusion as well as points of general agreement. Students found numerous tactics for strategies involving engineering and behavioral strategies. Fewer tactics were identified for strategies involving damage control through effective and timely response.