Protein aggregation in the brain: the molecular basis for Alzheimer's and Parkinson's diseases.

Developing effective treatments for neurodegenerative diseases is one of the greatest medical challenges of the 21st century. Although many of these clinical entities have been recognized for more than a hundred years, it is only during the past twenty years that the molecular events that precipitate disease have begun to be understood. Protein aggregation is a common feature of many neurodegenerative diseases, and it is assumed that the aggregation process plays a central role in pathogenesis. In this process, one molecule (monomer) of a soluble protein interacts with other monomers of the same protein to form dimers, oligomers, and polymers. Conformation changes in three-dimensional structure of the protein, especially the formation of beta-strands, often accompany the process. Eventually, as the size of the aggregates increases, they may precipitate as insoluble amyloid fibrils, in which the structure is stabilized by the beta-strands interacting within a beta-sheet. In this review, we discuss this theme as it relates to the two most common neurodegenerative conditions-Alzheimer's and Parkinson's diseases.

Impact of cough across different chronic respiratory diseases: comparison of two cough-specific health-related quality of life questionnaires

Background: Cough is a prominent symptom across a range of common chronic respiratory diseases and impacts considerably on patient health status.

Methods: We undertook a cross-sectional comparison of scores from two cough-specific health-related quality of life (HRQoL) questionnaires, the Leicester Cough Questionnaire (LCQ), and the Cough Quality of Life Questionnaire (CQLQ), together with a generic HRQoL measure, the EuroQol. Questionnaires were administered to and spirometry performed on 147 outpatients with chronic cough (n = 83), COPD (n = 18), asthma (n = 20), and bronchiectasis (n = 26).

Results: There was no significant difference in the LCQ and CQLQ total scores between groups (p = 0.24 and p = 0.26, respectively). Exploratory analyses of questionnaire subdomains revealed differences in psychosocial issues and functional impairment between the four groups (p = 0.01 and p = 0.05, respectively). CQLQ scores indicated that chronic coughers have more psychosocial issues than patients with bronchiectasis (p = 0.03) but less functional impairment than COPD patients (p = 0.04). There was a significant difference in generic health status across the four disease groups (p = 0.04), with poorest health status in COPD patients. A significant inverse correlation was observed between CQLQ and LCQ in each disease group (chronic cough r = - 0.56, p < 0.001; COPD r = - 0.49, p = 0.04; asthma r = - 0.94, p < 0.001; and bronchiectasis r = - 0.88, p < 0.001). There was no correlation between cough questionnaire scores and FEV1 in any group, although a significant correlation between EuroQol visual analog scale component and FEV1 (r = 0.639, p = 0.004) was observed in COPD patients.

Conclusion: Cough adversely affects health status across a range of common respiratory diseases. The LCQ and CQLQ can each provide important additional information concerning the impact of cough.

Involvement of Nox2 NADPH oxidase in adverse cardiac remodeling after myocardial infarction.

Oxidative stress plays an important role in the development of cardiac remodeling after myocardial infarction (MI), but the sources of oxidative stress remain unclear. We investigated the role of Nox2-containing reduced nicotinamide-adenine dinucleotide phosphate oxidase in the development of cardiac remodeling after MI. Adult Nox2(-/-) and matched wild-type (WT) mice were subjected to coronary artery ligation and studied 4 weeks later. Infarct size after MI was similar in Nox2(-/-) and WT mice. Nox2(-/-) mice exhibited significantly less left ventricular (LV) cavity dilatation and dysfunction after MI than WT mice (eg, echocardiographic LV end-diastolic volume: 75.7+/-5.8 versus 112.4+/-12.3 microL; ejection fraction: 41.6+/-3.7 versus 32.9+/-3.2%; both P

Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78-0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1-6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI. © Springer-Verlag London Limited 2008.