PINK1 deficiency impairs mitochondrial homeostasis and promotes lung fibrosis.

Although aging is a known risk factor for idiopathic pulmonary fibrosis (IPF), the pathogenic mechanisms that underlie the effects of advancing age remain largely unexplained. Some age-related neurodegenerative diseases have an etiology that is related to mitochondrial dysfunction. Here, we found that alveolar type II cells (AECIIs) in the lungs of IPF patients exhibit marked accumulation of dysmorphic and dysfunctional mitochondria. These mitochondrial abnormalities in AECIIs of IPF lungs were associated with upregulation of ER stress markers and were recapitulated in normal mice with advancing age in response to stimulation of ER stress. We found that impaired mitochondria in IPF and aging lungs were associated with low expression of PTEN-induced putative kinase 1 (PINK1). Knockdown of PINK1 expression in lung epithelial cells resulted in mitochondria depolarization and expression of profibrotic factors. Moreover, young PINK1-deficient mice developed similarly dysmorphic, dysfunctional mitochondria in the AECIIs and were vulnerable to apoptosis and development of lung fibrosis. Our data indicate that PINK1 deficiency results in swollen, dysfunctional mitochondria and defective mitophagy, and promotes fibrosis in the aging lung.

Are math readiness and personality predictive of first-year retention in engineering?

On the basis of J. G. Borkowski, L. K. Chan, and N. Muthukrishna's model of academic success (2000), the present authors hypothesized that freshman retention in an engineering program would be related to not only basic aptitude but also affective factors. Participants were 129 college freshmen with engineering as their stated major. Aptitude was measured by SAT verbal and math scores, high school grade-point average (GPA), and an assessment of calculus readiness. Affective factors were assessed by the NEO-Five Factor Inventory (FFI; P. I. Costa & R. R. McCrae, 2007), and the Nowicki-Duke Locus of Control (LOC) scale (S. Nowicki & M. Duke, 1974). A binary logistic regression analysis found that calculus readiness and high school GPA were predictive of retention. Scores on the Neuroticism and Openness subscales from the NEO-FFI and LOC were correlated with retention status, but Openness was the only affective factor with a significant unique effect in the binary logistic regression. Results of the study lend modest support to Borkowski's model.

Emerging bacterial, fungal, and viral respiratory infections in transplantation.

Kidney, liver, heart, pancreas, lung, and small intestine transplantations are viable therapeutic options for patients with end-stage organ failure. Ongoing advancements of surgical techniques, immunosuppressive regimens, and perioperative management have resulted in improved survival of allograft recipients. Despite these refinements, infections still contribute to substantial morbidity and mortality, limiting long-term success rates of these procedures. This article discusses the emerging bacterial, fungal, and viral respiratory infections in transplantation.

Predictive model to identify positive tuberculosis skin test results during contact investigations.

CONTEXT: Budgetary constraints in tuberculosis (TB) control programs require streamlining contact investigations without sacrificing disease control. OBJECTIVE: To develop more efficient methods of TB contact investigation by creating a model of TB transmission using variables that best predict a positive tuberculin skin test among contacts of an active TB case. DESIGN, SETTING, AND SUBJECTS: After standardizing the interview and documentation process, data were collected on 292 consecutive TB cases and their 2941 contacts identified by the Alabama Department of Public Health between January and October 1998. Generalized estimating equations were used to create a model for predicting positive skin test results in contacts of active TB cases. The model was then validated using data from a prospective cohort of 366 new TB cases and their 3162 contacts identified between October 1998 and April 2000. MAIN OUTCOME MEASURE: Tuberculin skin test result. RESULTS: Using generalized estimating equations to build a predictive model, 7 variables were found to significantly predict a positive tuberculin skin test result among contacts of an active TB case. Further testing showed this model to have a sensitivity, specificity, and positive predictive value of approximately 89%, 36%, and 26%, respectively. The false-negative rate was less than 10%, and about 40% of the contact workload could be eliminated using this model. CONCLUSIONS: Certain characteristics can be used to predict contacts most likely to have a positive tuberculin skin test result. Use of such models can significantly reduce the number of contacts that public health officials need to investigate while still maintaining excellent disease control.