Feasibility of infrared spectroscopy with pattern recognition techniques to identify a subpopulation of mares at risk of producing foals diagnosed with failure of transfer of passive immunity.

Objective: To assess the feasibility of a serum-based test using infrared spectroscopy to identify a subpopulation of mares at risk of producing foals susceptible to failure of passive transfer of immunity (FPT) because of mare-associated factors.

Materials And Methods: Serum was collected from post-parturient mares (n = 126) and their foals at 24-72 h of age. A radial immunodiffusion IgG test was used to determine each foal's serum IgG concentration.

Class proximity measures--dissimilarity-based classification and display of high-dimensional data.

For two-class problems, we introduce and construct mappings of high-dimensional instances into dissimilarity (distance)-based Class-Proximity Planes. The Class Proximity Projections are extensions of our earlier relative distance plane mapping, and thus provide a more general and unified approach to the simultaneous classification and visualization of many-feature datasets. The mappings display all L-dimensional instances in two-dimensional coordinate systems, whose two axes represent the two distances of the instances to various pre-defined proximity measures of the two classes.

Potential of magnetic resonance spectroscopy in assessing the effect of fatty acids on inflammatory bowel disease in an animal model.

People with inflammatory bowel disease (IBD) are at risk for developing colorectal cancer, and this risk increases at a rate of 1% per year after 8-10 years of having the disease. Saturated and omega-6 polyunsaturated fatty acids (PUFAs) have been implicated in its causation. Conversely, omega-3 PUFAs may have the potential to confer therapeutic benefit.

Potential of mid-infrared spectroscopy to aid the triage of patients with acute chest pain.

A total of 1,429 serum samples from 389 consecutive patients with acute chest pain were analyzed with the goal to aid the rapid diagnosis of acute myocardial infarction. To the best of our knowledge this is the largest and most comprehensive study on mid-infrared spectroscopy in cardiology. We were able to identify those signatures in the mid-infrared spectra of the samples, which were specific to either acute myocardial infarction or chest pain of other origin (angina pectoris, oesophagitis, etc).

Rapid etiological classification of meningitis by NMR spectroscopy based on metabolite profiles and host response.

Bacterial meningitis is an acute disease with high mortality that is reduced by early treatment. Identification of the causative microorganism by culture is sensitive but slow. Large volumes of cerebrospinal fluid (CSF) are required to maximise sensitivity and establish a provisional diagnosis.

Detecting colorectal cancer by 1H magnetic resonance spectroscopy of fecal extracts.

Colorectal cancer is one of the most common cancers in the western world. Its early detection has been found to improve the prognosis of the patient, providing a wide window of opportunity for successful therapeutic interventions. However, current diagnostic techniques all have some limitations; there is a need to develop a better technique for routine screening purposes.

Metabolomic biomarkers in a model of asthma exacerbation: urine nuclear magnetic resonance.

Rationale: Airway obstruction in patients with asthma is associated with airway dysfunction and inflammation. Objective measurements including sputum analysis can guide therapy, but this is often not possible in typical clinical settings. Metabolomics is the study of molecules generated by metabolic pathways.

Detection of cholangiocarcinoma with magnetic resonance spectroscopy of bile in patients with and without primary sclerosing cholangitis.

Background: Early detection of cholangiocarcinoma (CC) is very difficult, especially in patients with primary sclerosing cholangitis (PSC) who are at increased risk of developing CC.

Purpose: To evaluate 1H magnetic resonance spectroscopy ((1)H-MRS) of bile as a diagnostic marker for CC in patients with and without PSC.

Material And Methods: The institutional review board approved the study, and all patients gave informed consent.

Disease pattern recognition in infrared spectra of human sera with diabetes mellitus as an example.

To benefit from the full information content of the mid-IR spectra of human sera, we directly related the overall shape of the spectra to the donors' disease states. For this approach of disease pattern recognition we applied cluster analysis and discriminant analysis to the example of the disease states diabetes type 1, diabetes type 2, and healthy. In a binary, supervised classification of any pair of these disease states we achieved specificities and sensitivities of approximately 80% within our data set.

Detection of inflammatory bowel disease by proton magnetic resonance spectroscopy (1H MRS) using an animal model.

Background: The aim of this study was to analyze the potential of proton magnetic resonance spectroscopy (1H MRS) in diagnosing early inflammatory bowel disease (IBD).

Methods: Thirty male Sprague Dawley rats were fed 2% carrageenan in their diet for either 1 or 2 weeks. 1H MRS was performed ex-vivo on colonic mucosal samples (n = 123) and the spectra were analyzed by a multivariate method of analysis.

Direct classification of high-dimensional data in low-dimensional projected feature spaces--comparison of several classification methodologies.

Previously, we introduced a distance (similarity)-based mapping for the visualization of high-dimensional patterns and their relative relationships. The mapping preserves exactly the original distances from all points to any two reference patterns in a special two-dimensional coordinate system, the relative distance plane (RDP). We extend the RDP mapping's applicability from visualization to classification.

Magnetic resonance spectroscopy detects biochemical changes in the brain associated with chronic low back pain: a preliminary report.

Magnetic resonance (MR) spectroscopy is a noninvasive technique that can be used to detect and measure the concentration of metabolites and neurotransmitters in the brain and other organs. We used in vivo (1)H MR spectroscopy in subjects with low back pain compared with control subjects to detect alterations in biochemistry in three brain regions associated with pain processing. A pattern recognition approach was used to determine whether it was possible to discriminate accurately subjects with low back pain from control subjects based on MR spectroscopy.

Melanoma metastases in regional lymph nodes are accurately detected by proton magnetic resonance spectroscopy of fine-needle aspirate biopsy samples.

Background: Nonsurgical assessment of sentinel nodes (SNs) would offer advantages over surgical SN excision by reducing morbidity and costs. Proton magnetic resonance spectroscopy (MRS) of fine-needle aspirate biopsy (FNAB) specimens identifies melanoma lymph node metastases. This study was undertaken to determine the accuracy of the MRS method and thereby establish a basis for the future development of a nonsurgical technique for assessing SNs.

A rapid screening test to distinguish between Candida albicans and Candida dubliniensis using NMR spectroscopy.

Nuclear magnetic resonance (NMR) spectroscopy combined with a statistical classification strategy (SCS) successfully distinguished between Candida albicans and Candida dubliniensis. 96% of the isolates from an independent test set were identified correctly. This proves that this rapid approach is a valuable method for the identification and chemotaxonomic characterisation of closely related taxa.

Diagnosis of cerebral cryptococcoma using a computerized analysis of 1H NMR spectra in an animal model.

Viable cryptococci load in biopsy material from an animal model of cerebral cryptococcoma were correlated with 1H NMR spectra and metabolite profiles. A statistical classification strategy was applied to distinguish among high-resolution 1H NMR spectra acquired from cryptococcomas, glioblastomas, and normal brain tissue. The overall classification accuracy was 100% when a genetic-algorithm-based optimal region selection preceded the development of linear discriminant analysis-based classifiers.

Identification of Staphylococcus aureus brain abscesses: rat and human studies with 1H MR spectroscopy.

Purpose: To determine the feasibility of a statistical classification strategy (SCS) and the identity of metabolites of bacterial and host origins that potentially contributed to the most discriminatory regions of magnetic resonance (MR) spectra from Staphylococcus aureus abscesses of biopsy material from controls, gliomas, and staphylococcal abscesses.

Materials And Methods: Human and animal study received ethics committee approval, and informed patient consent was obtained. A rat model of S aureus brain abscess was developed.

Determination of grade and receptor status from the primary breast lesion by magnetic resonance spectroscopy.

Magnetic resonance spectra (MRS) from fine needle aspiration biopsies (FNAB) from primary breast lesions were analysed using a pattern recognition method, Statistical Classification Strategy, to assess tumor grade and oestrogen receptor (ER) and progesterone receptor (PgR) status. Grade 1 and 2 breast cancers were separated from grade 3 cancers with a sensitivity and specificity of 96% and 95%, respectively. The ER status was predicted with a sensitivity of 91% and a specificity of 90%, and the PgR status with a sensitivity of 91% and a specificity of 86%.

Molecular classification of scrapie strains in mice using gene expression profiling.

Transmissible spongiform encephalopathy strains demonstrate specific prion characteristics, each with specific incubation times, and strain-specific patterns of deposition of the misfolded isoform of prion, PrPSc, in the brains of infected individuals. Different biochemical properties, including glycosylation profiles and the degree of proteinase resistance, have been shown to be strain-specific. However, no relationship between these properties and the phenotypic differences in the subsequent diseases has as yet been determined.

Mapping high-dimensional data onto a relative distance plane--an exact method for visualizing and characterizing high-dimensional patterns.

We introduce a distance (similarity)-based mapping for the visualization of high-dimensional patterns and their relative relationships. The mapping preserves exactly the original distances between points with respect to any two reference patterns in a special two-dimensional coordinate system, the relative distance plane (RDP). As only a single calculation of a distance matrix is required, this method is computationally efficient, an essential requirement for any exploratory data analysis.

Classification of signatures of Bovine Spongiform Encephalopathy in serum using infrared spectroscopy.

Signatures of Bovine Spongiform Encephalopathy (BSE) have been identified in serum by means of "Diagnostic Pattern Recognition (DPR)". For DPR-analysis, mid-infrared spectroscopy of dried films of 641 serum samples was performed using disposable silicon sample carriers and a semi-automated DPR research system operating at room temperature. The combination of four mathematical classification approaches (principal component analysis plus linear discriminant analysis, robust linear discriminant analysis, artificial neural network, support vector machine) allowed for a reliable assignment of spectra to the class "BSE-positive" or "BSE-negative".

Class prediction and discovery using gene microarray and proteomics mass spectroscopy data: curses, caveats, cautions.

Motivation: Two practical realities constrain the analysis of microarray data, mass spectra from proteomics, and biomedical infrared or magnetic resonance spectra. One is the 'curse of dimensionality': the number of features characterizing these data is in the thousands or tens of thousands. The other is the 'curse of dataset sparsity': the number of samples is limited.

Rapid identification of Candida species by using nuclear magnetic resonance spectroscopy and a statistical classification strategy.

Nuclear magnetic resonance (NMR) spectra were acquired from suspensions of clinically important yeast species of the genus Candida to characterize the relationship between metabolite profiles and species identification. Major metabolites were identified by using two-dimensional correlation NMR spectroscopy. One-dimensional proton NMR spectra were analyzed by using a staged statistical classification strategy.

Pathology of Barrett's esophagus by proton magnetic resonance spectroscopy and a statistical classification strategy.

Background: Barrett's esophagus is thought to be a precursor of adenocarcinoma. The incidence of adenocarcinoma of the lower esophagus in the Western world is rising and accounts for more than 40% of esophageal carcinomas in males. It is not possible to identify which Barrett's patients are at high risk of developing malignancy.

Pathology of hepatocellular carcinoma and its precursors using proton magnetic resonance spectroscopy and a statistical classification strategy.

Aim: Apply the statistical classification strategy (SCS) to magnetic resonance spectroscopy (MRS) data from liver biopsies and test its potential to discriminate between normal liver, cirrhotic nodules and nodules of hepatocellular carcinoma with a high degree of accuracy.

Methods: Liver tissue specimens from 54 patients undergoing either partial (hemi) or total hepatectomy were analysed by one-dimensional proton MRS at 8.5 Tesla.

Diagnosis and prognosis of breast cancer by magnetic resonance spectroscopy of fine-needle aspirates analysed using a statistical classification strategy.

Background: The aim was to develop robust classifiers to analyse magnetic resonance spectroscopy (MRS) data of fine-needle aspirates taken from breast tumours. The resulting data could provide computerized, classification-based diagnosis and prognostic indicators.

Methods: Fine-needle aspirate biopsies obtained at the time of surgery for both benign and malignant breast diseases were analysed by one-dimensional proton MRS at 8.