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Biomedical subjects

Angela Harris

Publications and source records attributed to Angela Harris.

4 recordsLinked to original sources

Foetal alcohol syndrome: a cephalometric analysis of patients and controls.

Foetal alcohol syndrome (FAS) consists of multi-system abnormalities and is caused by the excessive intake of alcohol during pregnancy. The teratogenic effect of alcohol on the human foetus has now been established beyond reasonable doubt and FAS is the most important human teratogenic condition known today. The purpose of this study was to analyse the craniofacial parameters of children with FAS and compare them with matched controls. Ninety children diagnosed with FAS (45 males, 45 females) and 90 controls were matched for age, gender, and social class. The mean age of the FAS children was 8.9 years with the controls slightly older at 9.1 years. This age difference was not significant (P = 0.34). A standard lateral cephalometric radiograph of each subject was taken. The radiographs were digitized for 20 linear and 17 angular measurements. These 37 variables were formulated to assess the size, shape, and relative position of three craniofacial complexes: (1) the cranial base, (2) midface, and (3) mandible. In addition, nine variables were computed to compare the soft tissue profiles. The study showed that measurements related to face height and mandibular size appear to be the most important features when distinguishing FAS children. Overall, the FAS children in the present study presented with vertically and horizontally underdeveloped maxillae, together with features of long face syndrome with large gonial angles and a short ramus in relation to total face height. There was also a tendency for the development of an anterior open bite, which appears to be compensated for by an increase in the vertical dimension of the anterior alveolar process to bring the incisor teeth into occlusion. The latter adaptation occurred mainly in the mandible.

Age Factors↗

Development of public toxicogenomics software for microarray data management and analysis.

A robust bioinformatics capability is widely acknowledged as central to realizing the promises of toxicogenomics. Successful application of toxicogenomic approaches, such as DNA microarray, inextricably relies on appropriate data management, the ability to extract knowledge from massive amounts of data and the availability of functional information for data interpretation. At the FDA's National Center for Toxicological Research (NCTR), we are developing a public microarray data management and analysis software, called ArrayTrack. ArrayTrack is Minimum Information About a Microarray Experiment (MIAME) supportive for storing both microarray data and experiment parameters associated with a toxicogenomics study. A quality control mechanism is implemented to assure the fidelity of entered expression data. ArrayTrack also provides a rich collection of functional information about genes, proteins and pathways drawn from various public biological databases for facilitating data interpretation. In addition, several data analysis and visualization tools are available with ArrayTrack, and more tools will be available in the next released version. Importantly, gene expression data, functional information and analysis methods are fully integrated so that the data analysis and interpretation process is simplified and enhanced. ArrayTrack is publicly available online and the prospective user can also request a local installation version by contacting the authors.

Databases, Genetic↗

Median-of-subsets normalization of intensities for cDNA array data.

cDNA arrays allow quantitative measurement of expression levels for thousands of genes simultaneously. The measurements are affected by many sources of variation, and substantial improvements in the precision of estimated effects accompany adjustments for these effects. Two generic nuisance variations, one associated with the magnitude of expression and the other associated with array location, are common in data from filter arrays. Procedures, like normalization using lowess regression, are effective at reducing variation associated with magnitude, and they have been widely adopted. However, variation associated with location has received less attention. Here, a simple, but effective method based on localized median is expounded for dealing with these nuisance effects, and its properties are discussed. The proposed methodology handles location-dependent variation ("splotches") and magnitude-dependent variation (background and/or saturation) effectively. The procedure is related to lowess when implemented to adjust magnitude-dependent variation, and it performs similarly. The proposed methodology is illustrated with data from the National Center for Toxicological Research (NCTR), where treatment differences in levels of mRNA from rat hepatocytes were assessed using 33P-labeled samples hybridized to cDNA spotted arrays. Normalizing intensities by the median-of-subsets removes systematic variation associated with the location of a gene on the array and/or the level of its expression. This procedure is easy to implement using iteratively reweighted least-squares algorithms. Although less sophisticated than lowess, this procedure works nearly as well for normalizing intensities based upon their magnitude. Unlike lowess, it can adjust for location-dependent effects.

DNA, Complementary↗

ArrayTrack--supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research.

The mapping of the human genome and the determination of corresponding gene functions, pathways, and biological mechanisms are driving the emergence of the new research fields of toxicogenomics and systems toxicology. Many technological advances such as microarrays are enabling this paradigm shift that indicates an unprecedented advancement in the methods of understanding the expression of toxicity at the molecular level. At the National Center for Toxicological Research (NCTR) of the U.S. Food and Drug Administration, core facilities for genomic, proteomic, and metabonomic technologies have been established that use standardized experimental procedures to support centerwide toxicogenomic research. Collectively, these facilities are continuously producing an unprecedented volume of data. NCTR plans to develop a toxicoinformatics integrated system (TIS) for the purpose of fully integrating genomic, proteomic, and metabonomic data with the data in public repositories as well as conventional (Italic)in vitro(/Italic) and (Italic)in vivo(/Italic) toxicology data. The TIS will enable data curation in accordance with standard ontology and provide or interface a rich collection of tools for data analysis and knowledge mining. In this article the design, practical issues, and functions of the TIS are discussed through presenting its prototype version, ArrayTrack, for the management and analysis of DNA microarray data. ArrayTrack is logically constructed of three linked components: a) a library (LIB) that mirrors critical data in public databases; b) a database (MicroarrayDB) that stores microarray experiment information that is Minimal Information About a Microarray Experiment (MIAME) compliant; and c) tools (TOOL) that operate on experimental and public data for knowledge discovery. Using ArrayTrack, we can select an analysis method from the TOOL and apply the method to selected microarray data stored in the MicroarrayDB; the analysis results can be linked directly to gene information in the LIB.

Databases, Factual↗