Host and Bacterial Proteins That Repress Recruitment of LC3 to Shigella Early during Infection

Shigella spp. are intracytosolic gram-negative pathogens that cause disease by invasion and spread through the colonic mucosa, utilizing host cytoskeletal components to form propulsive actin tails. We have previously identified the host factor Toca-1 as being recruited to intracellular S. flexneri and being required for efficient bacterial actin tail formation. We show that at early times during infection (40 min.), the type three-secreted effector protein IcsB recruits Toca-1 to intracellular bacteria and that recruitment of Toca-1 is associated with repression of recruitment of LC3, as well as with repression of recruitment of the autophagy marker NDP52, around these intracellular bacteria. LC3 is best characterized as a marker of autophagosomes, but also marks phagosomal membranes in the process LC3-associated phagocytosis. IcsB has previously been demonstrated to be required for S. flexneri evasion of autophagy at late times during infection (4–6 hr) by inhibiting binding of the autophagy protein Atg5 to the Shigella surface protein IcsA (VirG). Our results suggest that IcsB and Toca-1 modulation of LC3 recruitment restricts LC3-associated phagocytosis and/or LC3 recruitment to vacuolar membrane remnants. Together with published results, our findings suggest that IcsB inhibits innate immune responses in two distinct ways, first, by inhibiting LC3-associated phagocytosis and/or LC3 recruitment to vacuolar membrane remnants early during infection, and second, by inhibiting autophagy late during infection

Automatic covariate selection in logistic models for chest pain diagnosis: A new approach

A newly established method for optimizing logistic models via a minorization-majorization procedure is applied to the problem of diagnosing acute coronary syndromes (ACS). The method provides a principled approach to the selection of covariates which would otherwise require the use of a suboptimal method owing to the size of the covariate set. A strategy for building models is proposed and two models optimized for performance and for simplicity are derived via ten-fold cross-validation. These models confirm that a relatively small set of covariates including clinical and electrocardiographic features can be used successfully in this task. The performance of the models is comparable with previously published models using less principled selection methods. The models prove to be portable when tested on data gathered from three other sites. Whilst diagnostic accuracy and calibration diminishes slightly for these new settings, it remains satisfactory overall. The prospect of building predictive models that are as simple as possible for a required level of performance is valuable if data-driven decision aids are to gain wide acceptance in the clinical situation owing to the need to minimize the time taken to gather and enter data at the bedside

Imperial Lessons: Discourses of Domination and Dissent in the 1929 Kwangju Student Protests.

This dissertation examines the relationship between language, power, and public space in two different public student protest movements that began in colonial Korea under Japanese rule, both originating in the southwestern city of Kwangju. In Imperial Lessons, I combine retrospective personal narratives and contemporary documentary sources to analyze how colonial-era Korean student protest was enacted, witnessed, repressed, and remembered by differently-positioned actors. The 1929-1930 Kwangju Student Movement was the second-largest anti-Japanese protest movement of the colonial period, second only to the March First Movement. In this dissertation, I historicize 1929-1930 activism to reveal how colonial rule and student resistance evolved in complex and mutually constitutive ways throughout the colonial period. I argue that Japanese rule created new spatial conceptions on the Korean peninsula both by transforming local public spaces in Korea and by requiring Koreans to imagine themselves as members of a larger Japanese empire and that it was within this framework that the new subject position of the student protester emerged. Also, by contrasting 1929-1930 student activism to a second, smaller 1943 student movement, I trace how student protesters’ relationships to public space, language, and conceptions of their own identities all transformed along with wartime imperial mobilization. Colonial-era student protest provides a window into how both Korean and Japanese residents of colonial Korea not only envisioned Korea’s future, but also into how they used language as a tool to inscribe their own competing meanings onto contested public spaces.Ph.D.HistoryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64746/1/debsol_1.pd

An effector of the Irish potato famine pathogen antagonizes a host autophagy cargo receptor

Plants use autophagy to safeguard against infectious diseases. However, how plant pathogens interfere with autophagy-related processes is unknown. Here, we show that PexRD54, an effector from the Irish potato famine pathogen Phytophthora infestans, binds host autophagy protein ATG8CL to stimulate autophagosome formation. PexRD54 depletes the autophagy cargo receptor Joka2 out of ATG8CL complexes and interferes with Joka2's positive effect on pathogen defense. Thus, a plant pathogen effector has evolved to antagonize a host autophagy cargo receptor to counteract host defenses

Comparison of artificial neural network and logistic regression models for prediction of mortality in head trauma based on initial clinical data

BACKGROUND: In recent years, outcome prediction models using artificial neural network and multivariable logistic regression analysis have been developed in many areas of health care research. Both these methods have advantages and disadvantages. In this study we have compared the performance of artificial neural network and multivariable logistic regression models, in prediction of outcomes in head trauma and studied the reproducibility of the findings. METHODS: 1000 Logistic regression and ANN models based on initial clinical data related to the GCS, tracheal intubation status, age, systolic blood pressure, respiratory rate, pulse rate, injury severity score and the outcome of 1271 mainly head injured patients were compared in this study. For each of one thousand pairs of ANN and logistic models, the area under the receiver operating characteristic (ROC) curves, Hosmer-Lemeshow (HL) statistics and accuracy rate were calculated and compared using paired T-tests. RESULTS: ANN significantly outperformed logistic models in both fields of discrimination and calibration but under performed in accuracy. In 77.8% of cases the area under the ROC curves and in 56.4% of cases the HL statistics for the neural network model were superior to that for the logistic model. In 68% of cases the accuracy of the logistic model was superior to the neural network model. CONCLUSIONS: ANN significantly outperformed the logistic models in both fields of discrimination and calibration but lagged behind in accuracy. This study clearly showed that any single comparison between these two models might not reliably represent the true end results. External validation of the designed models, using larger databases with different rates of outcomes is necessary to get an accurate measure of performance outside the development population

RNF166 Determines Recruitment of Adaptor Proteins during Antibacterial Autophagy

Xenophagy is a form of selective autophagy that involves the targeting and elimination of intracellular pathogens through several recognition, recruitment, and ubiquitination events. E3 ubiquitin ligases control substrate selectivity in the ubiquitination cascade; however, systematic approaches to map the role of E3 ligases in antibacterial autophagy have been lacking. We screened more than 600 putative human E3 ligases, identifying E3 ligases that are required for adaptor protein recruitment and LC3-bacteria colocalization, critical steps in antibacterial autophagy. An unbiased informatics approach pinpointed RNF166 as a key gene that interacts with the autophagy network and controls the recruitment of ubiquitin as well as the autophagy adaptors p62 and NDP52 to bacteria. Mechanistic studies demonstrated that RNF166 catalyzes K29- and K33-linked polyubiquitination of p62 at residues K91 and K189. Thus, our study expands the catalog of E3 ligases that mediate antibacterial autophagy and identifies a critical role for RNF166 in this process.Leona M. and Harry B. Helmsley Charitable Trust (2014PG-IBD016)National Institutes of Health (U.S.) (R01DK097485)National Institutes of Health (U.S.) (U19AI109725)National Institutes of Health (U.S.) (P30DK043351