Biomedical subjects

James D Malley

Publications and source records attributed to James D Malley.

9 recordsLinked to original sources

PubMed2003

Multiple neural network classification scheme for detection of colonic polyps in CT colonography data sets.

RATIONALE AND OBJECTIVES: A new classification system for colonic polyp detection, designed to increase sensitivity and reduce the number of false-positive findings with computed tomographic colonography, was developed and tested in this study. MATERIALS AND METHODS: The system involves classification by a committee of neural networks (NNs), each using largely distinct subsets of features selected from a general set. Back-propagation NNs trained with the Levenberg-Marquardt algorithm were used as primary classifiers (committee members). The set of features included region density, Gaussian and mean curvature and sphericity, lesion size, colon wall thickness, and the means and standard deviations of all of these values. Subsets of variables were initially selected because of their effectiveness according to training and test sample misclassification rates. The final decision for each case is based on the majority vote across the networks and reflects the weighted votes of all networks. The authors also introduce a smoothed cross-validation method designed to improve estimation of the true misclassification rates by reducing bias and variance. RESULTS: This committee method reduced the false-positive rate by 36%, a clinically meaningful reduction, and improved sensitivity by an average of 6.9% compared with decisions made by any single NN. The overall sensitivity and specificity were 82.9% and 95.3%, respectively, when sensitivity was estimated by means of smoothed cross-validation. CONCLUSION: The proposed method of using multiple classifiers and majority voting is recommended for classification tasks with large sets of input features, particularly when selected feature subsets may not be equally effective and do not provide satisfactory true- and false-positive rates. This approach reduces variance in estimates of misclassification rates.

Algorithms↗

PubMed2003

Autobiographical memory in schizophrenia: an examination of the distribution of memories.

Patients with schizophrenia display numerous memory impairments. Examination of autobiographical memory distribution across the life span can constrain theories of how schizophrenia affects memory. Previously, schizophrenic patients were shown to produce fewer memories from early adulthood than from childhood or the recent past (A. Feinstein, T. E. Goldberg, B. Nowlin, & D. R. Weinberger, 1998), this temporal paucity corresponding with illness onset. The current study examined this issue further using a different (noncued) method. Age-matched schizophrenic patients (n = 21) and controls (n = 21) were to freely generate 50 episodes, after which they dated these memories. Patients generated fewer memories than did controls, especially from the recent decade. When the overall lower production of memories was controlled for, the groups displayed equivalent recency effects. It was concluded that patients' paucity of memories generated from the recent decade reflects encoding or acquisition problems, which may be associated with the illness period.

Adult↗

PubMed2003

Computer-assisted detection of colonic polyps with CT colonography using neural networks and binary classification trees.

Detection of colonic polyps in CT colonography is problematic due to complexities of polyp shape and the surface of the normal colon. Published results indicate the feasibility of computer-aided detection of polyps but better classifiers are needed to improve specificity. In this paper we compare the classification results of two approaches: neural networks and recursive binary trees. As our starting point we collect surface geometry information from three-dimensional reconstruction of the colon, followed by a filter based on selected variables such as region density, Gaussian and average curvature and sphericity. The filter returns sites that are candidate polyps, based on earlier work using detection thresholds, to which the neural nets or the binary trees are applied. A data set of 39 polyps from 3 to 25 mm in size was used in our investigation. For both neural net and binary trees we use tenfold cross-validation to better estimate the true error rates. The backpropagation neural net with one hidden layer trained with Levenberg-Marquardt algorithm achieved the best results: sensitivity 90% and specificity 95% with 16 false positives per study.

Algorithms↗

PubMed2002

New genes involved in cancer identified by retroviral tagging.

Retroviral insertional mutagenesis in BXH2 and AKXD mice induces a high incidence of myeloid leukemia and B- and T-cell lymphoma, respectively. The retroviral integration sites (RISs) in these tumors thus provide powerful genetic tags for the discovery of genes involved in cancer. Here we report the first large-scale use of retroviral tagging for cancer gene discovery in the post-genome era. Using high throughput inverse PCR, we cloned and analyzed the sequences of 884 RISs from a tumor panel composed primarily of B-cell lymphomas. We then compared these sequences, and another 415 RIS sequences previously cloned from BXH2 myeloid leukemias and from a few AKXD lymphomas, against the recently assembled mouse genome sequence. These studies identified 152 loci that are targets of retroviral integration in more than one tumor (common retroviral integration sites, CISs) and therefore likely to encode a cancer gene. Thirty-six CISs encode genes that are known or predicted to be genes involved in human cancer or their homologs, whereas others encode candidate genes that have not yet been examined for a role in human cancer. Our studies demonstrate the power of retroviral tagging for cancer gene discovery in the post-genome era and indicate a largely unrecognized complexity in mouse and presumably human cancer.

Animals↗

PubMed2002

Comparison of vaccine strategies using recombinant env-gag-pol MVA with or without an oligomeric Env protein boost in the SHIV rhesus macaque model.

Rhesus macaques were immunized with a replication-deficient vaccinia virus (MVA) expressing human immunodeficiency virus type 1 89.6 envelope (env) and SIV gagpol (MVA/SHIV89.6) with or without a protein boost consisting of soluble 89.6 env (gp140). Immunization with MVA/SHIV89.6 alone elicited binding antibodies in all animals and neutralizing antibodies in 5 of 15 animals. Both types of antibodies were enhanced by protein boosting. In addition, CD8 cells exhibiting CM9 tetramer binding were detected in the subset of animals that were Mamu-A*01 positive. Animals were challenged intravenously with either SHIV-89.6 (Study 1) or the more pathogenic derivative SHIV-89.6P (Study 2). In Study 1, all control and vaccinated animals except one became infected. However, the levels of viremia were as follows: controls > rMVA alone > rMVA + protein. The differences were statistically significant between immunized and control groups but not between the two immunized groups. In Study 2, all animals became infected; however, the vaccinated group exhibited a 5-fold reduction in peak viremia and a 10-fold reduction in the postacute phase viremia in comparison to the controls. All of the controls required euthanasia by 10 months after challenge. A relationship between vaccine-induced antibody titers and reduction in virus burden was observed in both studies. Thus, immunization with MVA/SHIV89.6 alone or with a protein boost stimulated both arms of the immune system and resulted in significant control of viremia and delayed progression to disease after challenge with SHIV-89.6P.

AIDS Vaccines↗

PubMed2002

Differences in idiopathic inflammatory myopathy phenotypes and genotypes between Mesoamerican Mestizos and North American Caucasians: ethnogeographic influences in the genetics and clinical expression of myositis.

OBJECTIVE: As part of a larger, worldwide study of the ethnogeography of myositis, we evaluated the clinical, serologic, and immunogenetic features of Mestizo (Mexican and Guatemalan) and North American Caucasian patients with idiopathic inflammatory myopathy (IIM). METHODS: Clinical manifestations, autoantibodies, HLA-DRB1 and DQA1 alleles, and immunoglobulin Gm/Km allotypes were compared between 138 Mestizos with IIM and 287 Caucasians with IIM, using the same classification criteria and standardized questionnaires. RESULTS: IIM in Mestizo patients was characterized by a higher proportion of dermatomyositis (69% of adult Mestizos versus 35% of adult Caucasians; P < 0.001) and anti-Mi-2 autoantibodies (30% versus 7% of adults, respectively, and 32% versus 4% of children, respectively; P < 0.01). Genetic risk factors also differed in these populations. Whereas Mestizos had no HLA risk factors for IIM, HLA-DRB1*0301, the linked allele DQA1*0501, and DRB1 alleles sharing the first hypervariable region motif (9)EYSTS(13) were major risk factors in Caucasian patients with IIM. Furthermore, different HLA-DRB1 and DQA1 alleles were associated with anti-Mi-2 autoantibodies (DRB1*04 and DQA1*03 in Mestizos and DRB1*07 and DQA1*02 in Caucasians). Immunoglobulin gamma-chain allotypes Gm(1), Gm(17) (odds ratio for both 11.3, P = 0.008), and Gm(21) (odds ratio 7.3, P = 0.005) and kappa-chain allotype Km(3) (odds ratio 7.3, P = 0.005) were risk factors for IIM in Mestizos; however, no Gm or Km allotypes were risk or protective factors in Caucasians. In addition, Gm and Km phenotypes were unique risk factors (Gm 1,3,17 5,13,21 and Gm 1,17 23 21 and Km 3,3) or protective factors (Km 1,1) for the development of myositis and anti-Mi-2 autoantibodies (Gm 1,2,3,17 23 5,13,21) in adult Mestizos. CONCLUSION: IIM in Mesoamerican Mestizos differs from IIM in North American Caucasians in the frequency of phenotypic features and in the immune-response genes predisposing to and protecting from myositis and anti-Mi-2 autoantibodies at 4 chromosomal loci. These and other data suggest the likelihood that the expression of IIM is modulated by different genes and environmental exposures around the world.

Adult↗

PubMed2002

Colonic polyps: complementary role of computer-aided detection in CT colonography.

PURPOSE: To apply a computer-aided detection (CAD) algorithm to supine and prone multisection helical computed tomographic (CT) colonographic images to confirm if there is any added benefit provided by CAD over that of standard clinical interpretation. MATERIALS AND METHODS: CT colonography (with patients in both supine and prone positions) was performed with a multisection helical CT scanner in 40 asymptomatic high-risk patients. There were two consecutive series of patients, 20 of whom had at least one polyp 1.0 cm in size or larger and 20 of whom had normal colons at conventional colonoscopy performed the same day. The CT colonographic images were interpreted with an automated CAD algorithm and by two radiologists who were blinded to colonoscopy findings. RESULTS: For 25 polyps at least 1.0 cm in size ("large" polyps), sensitivity for detection by at least one radiologist was 48% (12 of 25). The sensitivity of CAD for detecting large polyps was also 48% (12 of 25), but the CAD algorithm detected four of 13 large polyps that were not detected by either radiologist (31%, 95% two-sided CI: 9, 61), increasing the potential sensitivity to 64% (16 of 25). For polyps identifiable retrospectively, sensitivity of CAD was 67% (12 of 18), and sensitivity of the combination of detection with the CAD algorithm or by at least one radiologist was 89% (16 of 18). There were an average of 11 false-positive detections per patient for CAD. CONCLUSION: In this series of patients in whom radiologists had difficulties detecting polyps (compared with sensitivities of 75%-90% reported in the literature), this CAD algorithm played a complementary role to conventional interpretation of CT colonographic images by detecting a number of large polyps missed by trained observers.

Aged↗

PubMed2002

A comprehensive method for genome scans.

In applications involving the use of genome scans the problem of correcting for multiple testing figures prominently. A frequently used approach is the Bonferroni adjustment, but this is known to be often severely conservative. As an alternative we use the method of importance sampling to accurately and efficiently obtain required exceedance probabilities. This method is comprehensive in the sense that it has application to exceedance probabilities for other classes of test statistics, such as those for linkage disequilibrium or Hardy-Weinberg equilibrium at multiple loci. We illustrate the importance sampling technique by focusing on affected sib pair tests done at a large number of fully informative markers. We demonstrate how our approach can be used to obtain exceedance probabilities for arbitrary marker spacings, and we compare our approach with that of Feingold et al. [1993], which uses the method of large deviations and does not provide the means for adjusting for unequal marker spacing.

Genetic Linkage↗

PubMedDate not supplied

Habit and skill learning in schizophrenia: evidence of normal striatal processing with abnormal cortical input.

Different forms of nondeclarative learning involve regionally specific striatal circuits. The motor circuit (involving the putamen) has been associated with motor-skill learning and the dorsolateral prefrontal cortex (DLPFC) circuit (involving the caudate) has been associated with cognitive-habit learning. Efforts to differentiate functional striatal circuits within patient samples have been limited. Previous studies have provided mixed results regarding striatal-dependent nondeclarative learning deficits in patients with schizophrenia. In this study, a cognitive-habit learning task (probabilistic weather prediction) was used to assess the DLPFC circuit and a motor-skill learning task (pursuit rotor) was used to assess the motor circuit in 35 patients with schizophrenia and 35 normal controls. Patients with schizophrenia displayed significant performance differences from controls on both nondeclarative tasks; however, cognitive-habit learning rate in patients did not differ from controls. There were performance and learning-rate differences on the motor-skill learning task between the whole sample of patients and controls, however, analysis of a subset of patients and controls matched on general intellectual level eliminated learning rate differences between groups. The abnormal performance offset between patients with schizophrenia and controls in the absence of learning rate differences suggests that abnormal cortical processing provides altered input to normal striatal circuitry.

Adult↗