Magnetic studies of GaN nanoceramics

The synthesis, morphology and magnetization measurements of GaN nanoceramics obtained under high pressure are reported. In particular the effect of grain size on magnetic properties of GaN nanopowders and nanoceramics was investigated. It was found that for the GaN nanoceramic characterized by the stronger deformation of nanocrystalline grains the diamagnetic signal changes with external magnetic field similarly to the Meissner effect in superconductors.Comment: 3 pages, 4 figures, accepted Appl.Phys.Let

Diagnostic test interpretation and referral delay in patients with interstitial lung disease.

BACKGROUND:Diagnostic delays are common in patients with interstitial lung disease (ILD). A substantial percentage of patients experience a diagnostic delay in the primary care setting, but the factors underpinning this observation remain unclear. In this multi-center investigation, we assessed ILD reporting on diagnostic test interpretation and its association with subsequent pulmonology referral by a primary care physician (PCP). METHODS:A retrospective cohort analysis of patients referred to the ILD programs at UC-Davis and University of Chicago by a PCP within each institution was performed. Computed tomography (CT) of the chest and abdomen and pulmonary function test (PFT) were reviewed to identify the date ILD features were first present and determine the time from diagnostic test to pulmonology referral. The association between ILD reporting on diagnostic test interpretation and pulmonology referral was assessed, as was the association between years of diagnostic delay and changes in fibrotic features on longitudinal chest CT. RESULTS:One hundred and forty-six patients were included in the final analysis. Prior to pulmonology referral, 66% (n = 97) of patients underwent chest CT, 15% (n = 21) underwent PFT and 15% (n = 21) underwent abdominal CT. ILD features were reported on 84, 62 and 33% of chest CT, PFT and abdominal CT interpretations, respectively. ILD reporting was associated with shorter time to pulmonology referral when undergoing chest CT (1.3 vs 15.1 months, respectively; p = 0.02), but not PFT or abdominal CT. ILD reporting was associated with increased likelihood of pulmonology referral within 6 months of diagnostic test when undergoing chest CT (rate ratio 2.17, 95% CI 1.03-4.56; p = 0.04), but not PFT or abdominal CT. Each year of diagnostic delay was associated with a 1.8% increase in percent fibrosis on chest CT. Patients with documented dyspnea had shorter time to chest CT acquisition and pulmonology referral than patients with documented cough and lung crackles. CONCLUSIONS:Determinants of ILD diagnostic delays in the primary care setting include underreporting of ILD features on diagnostic testing and prolonged time to pulmonology referral even when ILD is reported. Interventions to modulate these factors may reduce ILD diagnostic delays in the primary care setting

Investigating Predictors of Plant Establishment During Roadside Restoration

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91190/1/j.1526-100X.2011.00802.x.pd

A functional genomic model for predicting prognosis in idiopathic pulmonary fibrosis

Background: The course of disease for patients with idiopathic pulmonary fibrosis (IPF) is highly heterogeneous. Prognostic models rely on demographic and clinical characteristics and are not reproducible. Integrating data from genomic analyses may identify novel prognostic models and provide mechanistic insights into IPF. Methods: Total RNA of peripheral blood mononuclear cells was subjected to microarray profiling in a training (45 IPF individuals) and two independent validation cohorts (21 IPF/10 controls, and 75 IPF individuals, respectively). To identify a gene set predictive of IPF prognosis, we incorporated genomic, clinical, and outcome data from the training cohort. Predictor genes were selected if all the following criteria were met: 1) Present in a gene co-expression module from Weighted Gene Co-expression Network Analysis (WGCNA) that correlated with pulmonary function (p 1.5 and false discovery rate (FDR) < 2 %; and 3) Predictive of mortality (p < 0.05) in univariate Cox regression analysis. "Survival risk group prediction" was adopted to construct a functional genomic model that used the IPF prognostic predictor gene set to derive a prognostic index (PI) for each patient into either high or low risk for survival outcomes. Prediction accuracy was assessed with a repeated 10-fold cross-validation algorithm and independently assessed in two validation cohorts through multivariate Cox regression survival analysis. Results: A set of 118 IPF prognostic predictor genes was used to derive the functional genomic model and PI. In the training cohort, high-risk IPF patients predicted by PI had significantly shorter survival compared to those labeled as low-risk patients (log rank p < 0.001). The prediction accuracy was further validated in two independent cohorts (log rank p < 0.001 and 0.002). Functional pathway analysis revealed that the canonical pathways enriched with the IPF prognostic predictor gene set were involved in T-cell biology, including iCOS, T-cell receptor, and CD28 signaling. Conclusions: Using supervised and unsupervised analyses, we identified a set of IPF prognostic predictor genes and derived a functional genomic model that predicted high and low-risk IPF patients with high accuracy. This genomic model may complement current prognostic tools to deliver more personalized care for IPF patients