Bouguer gravity anomaly map of Iowa,1981.

Gravity values on this map are based on 1967 International Gravity Formula and are reduced to sea level with a Bouguer Density of 2.67 g/cm3.

Traffic map, Iowa,1984.

Traffic volumes represented on this map are average volumes between major traffic generators: highway junctions, cities, recreational areas or high volume secondary roads.

Integrative molecular bioinformatics study of human adrenocortical tumors : microRNA, tissue-specific target prediction, and pathway analysis.

MicroRNAs (miRs) are involved in the pathogenesis of several neoplasms; however, there are no data on their expression patterns and possible roles in adrenocortical tumors. Our objective was to study adrenocortical tumors by an integrative bioinformatics analysis involving miR and transcriptomics profiling, pathway analysis, and a novel, tissue-specific miR target prediction approach. Thirty-six tissue samples including normal adrenocortical tissues, benign adenomas, and adrenocortical carcinomas (ACC) were studied by simultaneous miR and mRNA profiling. A novel data-processing software was used to identify all predicted miR-mRNA interactions retrieved from PicTar, TargetScan, and miRBase. Tissue-specific target prediction was achieved by filtering out mRNAs with undetectable expression and searching for mRNA targets with inverse expression alterations as their regulatory miRs. Target sets and significant microarray data were subjected to Ingenuity Pathway Analysis. Six miRs with significantly different expression were found. miR-184 and miR-503 showed significantly higher, whereas miR-511 and miR-214 showed significantly lower expression in ACCs than in other groups. Expression of miR-210 was significantly lower in cortisol-secreting adenomas than in ACCs. By calculating the difference between dCT(miR-511) and dCT(miR-503) (delta cycle threshold), ACCs could be distinguished from benign adenomas with high sensitivity and specificity. Pathway analysis revealed the possible involvement of G2/M checkpoint damage in ACC pathogenesis. To our knowledge, this is the first report describing miR expression patterns and pathway analysis in sporadic adrenocortical tumors. miR biomarkers may be helpful for the diagnosis of adrenocortical malignancy. This tissue-specific target prediction approach may be used in other tumors too.

Thérapie cellulaire en cardiologie: bilan des premiers essais cliniques randomisés [Cell therapies in cardiology: results from the first randomized clinical trials]

Following acute myocardial infarction, necrotic cardiac tissue is replaced by scar leading to ventricular remodeling and pump failure. Transplantation of autologous bone marrow-derived cells into the heart, early post-infarct, aims to prevent ventricular remodeling. This strategy has been evaluated in four controlled, randomized clinical trials, which provided mixed results. A transient improvement in ventricular function was observed in one trial, and a modest improvement (the duration of which remains to be determined) in an additional trial, whereas two trials showed negative results. A modest benefit of bone marrow cell transplantation was also observed in patients with chronic ischemic heart disease. Despite mixed results reported so far, cell therapy of heart disease still is in its infancy and has considerable room for improvement.

Vehicle Traffic Map, 2012

Vehicle Traffic Map produced by the Iowa Department of Transportation.

Truck Traffic Map, 2012

Vehicle Traffic Map produced by the Iowa Department of Transportation.

Iowa Calibration of MEPDG Performance Prediction Models, 2013

This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.

Iowa Calibration of MEPDG Performance Prediction Models: Tech Transfer Summary

This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.

Prediction of resting energy expenditure from fat-free mass and fat mass.

On the basis of literature values, the relationship between fat-free mass (FFM), fat mass (FM), and resting energy expenditure [REE (kJ/24 h)] was determined for 213 adults (86 males, 127 females). The objectives were to develop a mathematical model to predict REE based on body composition and to evaluate the contribution of FFM and FM to REE. The following regression equations were derived: 1) REE = 1265 + (93.3 x FFM) (r2 = 0.727, P < 0.001); 2) REE = 1114 + (90.4 x FFM) + (13.2 x FM) (R2 = 0.743, P < 0.001); and 3) REE = (108 x FFM) + (16.9 x FM) (R2 = 0.986, P < 0.001). FM explained only a small part of the variation remaining after FFM was accounted for. The models that include both FFM and FM are useful in examination of the changes in REE that occur with a change in both the FFM and FM. To account for more of the variability in REE, FFM will have to be divided into organ mass and skeletal muscle mass in future analyses.

Iowa State Capitol Interior Floors Map, 2013

Iowa State Capitol Interior Floors Map with cell phone audio information that can be used with a smartphone audio and video.

Iowa State Capitol Monuments and Memorials Map, 2013

Iowa State Capitol Monuments and Memorials Map

Ruling out coronary heart disease in primary care: external validation of a clinical prediction rule.

BACKGROUND: The Marburg Heart Score (MHS) aims to assist GPs in safely ruling out coronary heart disease (CHD) in patients presenting with chest pain, and to guide management decisions. AIM: To investigate the diagnostic accuracy of the MHS in an independent sample and to evaluate the generalisability to new patients. DESIGN AND SETTING: Cross-sectional diagnostic study with delayed-type reference standard in general practice in Hesse, Germany. METHOD: Fifty-six German GPs recruited 844 males and females aged ≥ 35 years, presenting between July 2009 and February 2010 with chest pain. Baseline data included the items of the MHS. Data on the subsequent course of chest pain, investigations, hospitalisations, and medication were collected over 6 months and were reviewed by an independent expert panel. CHD was the reference condition. Measures of diagnostic accuracy included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, likelihood ratios, and predictive values. RESULTS: The AUC was 0.84 (95% confidence interval [CI] = 0.80 to 0.88). For a cut-off value of 3, the MHS showed a sensitivity of 89.1% (95% CI = 81.1% to 94.0%), a specificity of 63.5% (95% CI = 60.0% to 66.9%), a positive predictive value of 23.3% (95% CI = 19.2% to 28.0%), and a negative predictive value of 97.9% (95% CI = 96.2% to 98.9%). CONCLUSION: Considering the diagnostic accuracy of the MHS, its generalisability, and ease of application, its use in clinical practice is recommended.