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.

Raman microscopy in the diagnosis and prognosis of surgically resected nonsmall cell lung cancer

The main curative therapy for patients with nonsmall cell lung cancer is surgery. Despite this, the survival rate is only 50%, therefore it is important to more efficiently diagnose and predict prognosis for lung cancer patients. Raman spectroscopy is useful in the diagnosis of malignant and premalignant lesions. The aim of this study is to investigate the ability of Raman microscopy to diagnose lung cancer from surgically resected tissue sections, and predict the prognosis of these patients. Tumor tissue sections from curative resections are mapped by Raman microscopy and the spectra analzsed using multivariate techniques. Spectra from the tumor samples are also compared with their outcome data to define their prognostic significance. Using principal component analysis and random forest classification, Raman microscopy differentiates malignant from normal lung tissue. Principal component analysis of 34 tumor spectra predicts early postoperative cancer recurrence with a sensitivity of 73% and specificity of 74%. Spectral analysis reveals elevated porphyrin levels in the normal samples and more DNA in the tumor samples. Raman microscopy can be a useful technique for the diagnosis and prognosis of lung cancer patients receiving surgery, and for elucidating the biochemical properties of lung tumors. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3323088]

Critical reading of science-based news reports: Establishing a knowledge skills and attitudes framework

A recognised aim of science education is to promote critical engagement with science in the media. Evidence would suggest that this is challenging for both teachers and pupils and that at science education does not yet adequately prepare young people for this task. Furthermore, in the absence of clear guidance as to what this means and how this may be achieved it is difficult for teachers to develop approaches and resources that address the matter and that systematically promote such critical engagement within their teaching programmes. Twenty-six individuals with recognised expertise or interest in science in the media, drawn from a range of disciplines and areas of practice, constituted a specialist panel in this study. The question this research sought to answer was ‘what are the elements of knowledge, skill and attitude which underpin critical reading of science based news reports’? During in-depth individual interviews the panel were asked to explore what they considered to be essential elements of knowledge, skills and attitude which people need to enable them to respond critically to news reports with a science component. Analysis of the data revealed fourteen fundamental elements which together contribute to an individual’s capacity to engage critically with science-based news. These are classified in five categories ‘knowledge of science’, ‘knowledge of writing and language’, ‘knowledge about news, newspapers and journalism’, ‘skills’ and ‘attitudes’. Illustrative profiles of each category along with indicators of critical engagement are presented. The implications for curriculum planning and pedagogy are considered.

Moving window kernel PCA for adaptive monitoring of nonlinear processes

This paper discusses the monitoring of complex nonlinear and time-varying processes. Kernel principal component analysis (KPCA) has gained significant attention as a monitoring tool for nonlinear systems in recent years but relies on a fixed model that cannot be employed for time-varying systems. The contribution of this article is the development of a numerically efficient and memory saving moving window KPCA (MWKPCA) monitoring approach. The proposed technique incorporates an up- and downdating procedure to adapt (i) the data mean and covariance matrix in the feature space and (ii) approximates the eigenvalues and eigenvectors of the Gram matrix. The article shows that the proposed MWKPCA algorithm has a computation complexity of O(N2), whilst batch techniques, e.g. the Lanczos method, are of O(N3). Including the adaptation of the number of retained components and an l-step ahead application of the MWKPCA monitoring model, the paper finally demonstrates the utility of the proposed technique using a simulated nonlinear time-varying system and recorded data from an industrial distillation column.

Kids’ Life and Times: using an Internet survey to measure children’s health-related quality of life

Objective
To examine the psychometric properties of an internet version of a children and young person's quality of life measure originally designed as a paper questionnaire.

Methods
Participants were 3,440 10 and 11 year old children in Northern Ireland who completed the KIDSCREEN-27 online as part of a general attitudinal survey. The questionnaire was animated using cartoon characters that are familiar to most children and the questions appeared on screen and were read aloud by actors.

Results
Exploratory principal component analysis of the online version of the questionnaire supported the existence of five components in line with the paper version. The items loaded on the components that would be expected based on previous findings with five domains - physical well-being,psychological well-being, autonomy and parents, social support and peers and school environment.Internal consistency reliability of the five domains was measured using Cronbach's alpha and the results suggested that the scale scores were reliable. The domain scores were similar to those reported in the literature for the paper version.

Conclusions
These results suggest that the factor structure and internal consistency reliability scores of the KIDSCREEN-27 embedded within an online survey are comparable to those reported in the literature for the paper version.

Live-Cell Tracking Using SIFT Features in DIC Microscopic Videos

In this paper, a novel motion-tracking scheme using scale-invariant features is proposed for automatic cell motility analysis in gray-scale microscopic videos, particularly for the live-cell tracking in low-contrast differential interference contrast (DIC) microscopy. In the proposed approach, scale-invariant feature transform (SIFT) points around live cells in the microscopic image are detected, and a structure locality preservation (SLP) scheme using Laplacian Eigenmap is proposed to track the SIFT feature points along successive frames of low-contrast DIC videos. Experiments on low-contrast DIC microscopic videos of various live-cell lines shows that in comparison with principal component analysis (PCA) based SIFT tracking, the proposed Laplacian-SIFT can significantly reduce the error rate of SIFT feature tracking. With this enhancement, further experimental results demonstrate that the proposed scheme is a robust and accurate approach to tackling the challenge of live-cell tracking in DIC microscopy.

Metabolic profile changes in the testes of mice with streptozotocin-induced type 1 diabetes mellitus

Contrary to the traditional view, recent studies suggest that diabetes mellitus has an adverse influence on male reproductive function. Our aim was to determine the effect of diabetes on the testicular environment by identifying and then assessing perturbations in small molecule metabolites. Testes were obtained from control and streptozotocin-induced diabetic C57BL/6 mice, 2, 4 and 8 weeks post-treatment. Diabetic status was confirmed by glycated haemoglobin, non-fasting blood glucose, physiological condition and body weight. A novel extraction procedure was utilized to obtain protein free, low-molecular weight, water soluble extracts which were then assessed using H-1 nuclear magnetic resonance spectroscopy. Principal component analysis of the derived profiles was used to classify any variations, and specific metabolites were identified based on their spectral pattern. Characteristic metabolite profiles were identified for control and type 1 diabetic animals with the most distinctive being from mice with the largest physical deterioration and loss of body weight. Eight streptozotocin-treated animals did not develop diabetes and displayed profiles similar to controls. Diabetic mice had decreases in creatine, choline and carnitine and increases in lactate, alanine and myo-inositol. Betaine levels were found to be increased in the majority of diabetic mice but decreased in a few animals with severe loss of body weight and physical condition. The association between perturbations in a number of small molecule metabolites known to be influential in sperm function, with diabetic status and physiological condition, adds further impetus to the proposal that diabetes influences important spermatogenic pathways and mechanisms in a subtle and previously unrecognized manner.

Molecular-assisted immunohistochemical optimization

Immunohistochemistry (IHC) is an essential tool in diagnostic surgical pathology, allowing analysis of protein subcellular localization The use of IHC by different laboratories has lead to inconsistencies in published literature for several antibodies, due to either interpretative (inter-observer venation) or technical reasons These disparities have major implications in both clinical and research settings In this study, we report our experience conducting an IHC optimization of antibodies against five proteins previously identified by proteomic analysis to be breast cancer biomarkers, namely 6PGL (PGLS), CAZ2 (CAPZA2), PA2G4 (EBP1) PSD2 and TKT Large variations in the immunolocalizations and intensities were observed when manipulating the antigen retrieval method and primary antibody incubation concentration However, the use of an independent molecular analysis method provided a clear indication in choosing the appropriate biologically and functionally relevant

Application of Nonlinear PCA for Fault Detection in Polymer Extrusion Processes

This paper describes the application of an improved nonlinear principal component analysis (PCA) to the detection of faults in polymer extrusion processes. Since the processes are complex in nature and nonlinear relationships exist between the recorded variables, an improved nonlinear PCA, which incorporates the radial basis function (RBF) networks and principal curves, is proposed. This algorithm comprises two stages. The first stage involves the use of the serial principal curve to obtain the nonlinear scores and approximated data. The second stage is to construct two RBF networks using a fast recursive algorithm to solve the topology problem in traditional nonlinear PCA. The benefits of this improvement are demonstrated in the practical application to a polymer extrusion process.

Dietary patterns and bone mineral status in young adults: the Northern Ireland Young Hearts Project

Studies of individual nutrients or foods have revealed much about dietary influences on bone. Multiple food or nutrient approaches, such as dietary pattern analysis, could offer further insight but research is limited and largely confined to older adults. We examined the relationship between dietary patterns, obtained by a posteriori and a priori methods, and bone mineral status (BMS; collective term for bone mineral content (BMC) and bone mineral density (BMD)) in young adults (20-25 years; n 489). Diet was assessed by 7 d diet history and BMD and BMC were determined at the lumbar spine and femoral neck (FN). A posteriori dietary patterns were derived using principal component analysis (PCA) and three a priori dietary quality scores were applied (dietary diversity score (DDS), nutritional risk score and Mediterranean diet score). For the PCA-derived dietary patterns, women in the top compared to the bottom fifth of the 'Nuts and Meat' pattern had greater FN BMD by 0.074 g/cm(2) (P=0.049) and FN BMC by 0.40 g (P=0.034) after adjustment for confounders. Similarly, men in the top compared to the bottom fifth of the 'Refined' pattern had lower FN BMC by 0.41 g (P-0.049). For the a priori DDS, women in the top compared to the bottom third had lower FN BMD by 0.05 g/cm(2) after adjustments (P=0.052), but no other relationships with BMS were identified. In conclusion, adherence to a 'Nuts and Meat' dietary pattern may be associated with greater BMS in young women and a 'Refined' dietary pattern may be detrimental for bone health in young men.

2D silhouette and 3D skeletal models for human detection and tracking

In this paper we propose a statistical model for detection and tracking of human silhouette and the corresponding 3D skeletal structure in gait sequences. We follow a point distribution model (PDM) approach using a Principal Component Analysis (PCA). The problem of non-lineal PCA is partially resolved by applying a different PDM depending of pose estimation; frontal, lateral and diagonal, estimated by Fisher's linear discriminant. Additionally, the fitting is carried out by selecting the closest allowable shape from the training set by means of a nearest neighbor classifier. To improve the performance of the model we develop a human gait analysis to take into account temporal dynamic to track the human body. The incorporation of temporal constraints on the model increase reliability and robustness.

A posteriori-derived dietary patterns and retinal vessel caliber in an elderly population

Purpose. To examine the association between a posteriori–derived dietary patterns (DP) and retinal vessel caliber in an elderly population.

Methods. This was a cross-sectional study of 288 elderly adults (>65 years) who participated in the European Eye study (EUREYE) Northern Irish cohort. DP were extracted using principal component analysis from completed food frequency questionnaires. Semi-automated computer grading was used to determine the mean retinal vessel diameters (central retinal arteriole equivalent [CRAE] and central retinal venule equivalent [CRVE]) from digitized visual field one images using a standard measurement protocol.

Results. Three major DP were identified in this population, which accounted for 21% of the total variance: a “healthy” pattern with high factor loadings for oily fish, fruits and vegetables, and olive oil; an “unhealthy” pattern with high factor loadings for red and processed meat, refined grains, eggs, butter, sugar and sweets; and a “snack and beverage” pattern with high factor loading for pizza, nuts, and coffee. Multivariable linear regression analysis indicated no significant association between major identified DP and mean CRAE or CRVE in all models.

Conclusions. This is the first study to investigate associations between a posteriori–derived DP and retinal vessel caliber. There was no evidence of a relationship between extracted DP and retinal vessel measurements in this population. However, it is possible that potentially important relationships exist between single nutrients or foods and vessel diameters that cannot be identified using a DP approach. Further studies to examine the role of dietary factors in the microcirculation are required.

Fault Diagnostics for Internal Combustion Engines – Current and Future Techniques

The adoption of each new level of automotive emissions legislation often requires the introduction of additional emissions reduction techniques or the development of existing emissions control systems. This, in turn, usually requires the implementation of new sensors and hardware which must subsequently be monitored by the on-board fault detection systems. The reliable detection and diagnosis of faults in these systems or sensors, which result in the tailpipe emissions rising above the progressively lower failure thresholds, provides enormous challenges for OBD engineers. This paper gives a review of the field of fault detection and diagnostics as used in the automotive industry. Previous work is discussed and particular emphasis is placed on the various strategies and techniques employed. Methodologies such as state estimation, parity equations and parameter estimation are explained with their application within a physical model diagnostic structure. The utilization of symptoms and residuals in the diagnostic process is also discussed. These traditional physical model based diagnostics are investigated in terms of their limitations. The requirements from the OBD legislation are also addressed. Additionally, novel diagnostic techniques, such as principal component analysis (PCA) are also presented as a potential method of achieving the monitoring requirements of current and future OBD legislation.

Profiling the ionome of rice and its use in discriminating geographical origins at the regional scale, China

Element profile was investigated for their use to trace the geographical origin of rice (Oryza sativa L.) samples. The concentrations of 13 elements (calcium (Ca), potassium (K), magnesium (Mg), phosphorus (P), boron (B), manganese (Mn), iron (Fe), nickel (Ni), copper (Cu), arsenic (As), selenium (Se), molybdenum (Mo), and cadmium (Cd)) were determined in the rice samples by inductively coupled plasma optical emission and mass spectrometry. Most of the essential elements for human health in rice were within normal ranges except for Mo and Se. Mo concentrations were twice as high as those in rice from Vietnam and Spain. Meanwhile, Se concentrations were three times lower in the whole province compared to the Chinese average level of 0.088 mg/kg. About 12% of the rice samples failed the Chinese national food safety standard of 0.2 mg/kg for Cd. Combined with the multi-elemental profile in rice, the principal component analysis (PCA), discriminant function analysis (DFA) and Fibonacci index analysis (FIA) were applied to discriminate geographical origins of the samples. Results indicated that the FIA method could achieve a more effective geographical origin classification compared with PCA and DFA, due to its efficiency in making the grouping even when the elemental variability was so high that PCA and DFA showed little discriminatory power. Furthermore, some elements were identified as the most powerful indicators of geographical origin: Ca, Ni, Fe and Cd. This suggests that the newly established methodology of FIA based on the ionome profile can be applied to determine the geographical origin of rice.

Chemometric techniques in multivariate statistical modelling of process plant

The techniques of principal component analysis (PCA) and partial least squares (PLS) are introduced from the point of view of providing a multivariate statistical method for modelling process plants. The advantages and limitations of PCA and PLS are discussed from the perspective of the type of data and problems that might be encountered in this application area. These concepts are exemplified by two case studies dealing first with data from a continuous stirred tank reactor (CSTR) simulation and second a literature source describing a low-density polyethylene (LDPE) reactor simulation.