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Articles 1 - 20 of 20
Full-Text Articles in Life Sciences
Genotype-Phenotype Diversity Of Beta-Thalassemia In Malaysia: Treatment Options And Emerging Therapies, Maryanne Jin Ai Tan Maryanne
Genotype-Phenotype Diversity Of Beta-Thalassemia In Malaysia: Treatment Options And Emerging Therapies, Maryanne Jin Ai Tan Maryanne
Mary Anne Tan Jin Ai
The haemoglobinopathies and thalassemias represent the most common inherited monogenic disorders in the world1. Beta-thalassaemia major is an ongoing public health problem in Malaysia2. Prior to 2004, the country had no national policy for screening and registry for thalassemia. In the absence of a national audit, the true figure of the extent of thalassemia in the Malaysian population was largely presumptive from micro-mapping studies from various research workers in the country. The estimated carrier rate for beta-thalassemia in Malaysia is 3.5-4%. There were 4768 transfusion dependent thalassemia major patients as of May 2010 (Data from National Thalassemia Registry).
A Novel Totivirus And Piscine Reovirus (Prv) In Atlantic Salmon (Salmo Salar) With Cardiomyopathy Syndrome (Cms), Torstein Tengs
A Novel Totivirus And Piscine Reovirus (Prv) In Atlantic Salmon (Salmo Salar) With Cardiomyopathy Syndrome (Cms), Torstein Tengs
Dr. Torstein Tengs
BACKGROUNDCardiomyopathy syndrome (CMS) is a severe disease affecting large farmed Atlantic salmon. Mortality often appears without prior clinical signs, typically shortly prior to slaughter. We recently reported the finding and the complete genomic sequence of a novel piscine reovirus (PRV), which is associated with another cardiac disease in Atlantic salmon; heart and skeletal muscle inflammation (HSMI). In the present work we have studied whether PRV or other infectious agents may be involved in the etiology of CMS.RESULTSUsing high throughput sequencing on heart samples from natural outbreaks of CMS and from fish experimentally challenged with material from fish diagnosed with CMS …
Heart And Skeletal Muscle Inflammation Of Farmed Salmon Is Associated With Infection With A Novel Reovirus, Torstein Tengs
Heart And Skeletal Muscle Inflammation Of Farmed Salmon Is Associated With Infection With A Novel Reovirus, Torstein Tengs
Dr. Torstein Tengs
Atlantic salmon (Salmo salar L.) mariculture has been associated with epidemics of infectious diseases that threaten not only local production, but also wild fish coming into close proximity to marine pens and fish escaping from them. Heart and skeletal muscle inflammation (HSMI) is a frequently fatal disease of farmed Atlantic salmon. First recognized in one farm in Norway in 1999, HSMI was subsequently implicated in outbreaks in other farms in Norway and the United Kingdom. Although pathology and disease transmission studies indicated an infectious basis, efforts to identify an agent were unsuccessful. Here we provide evidence that HSMI is associated …
Non-Prejudiced Detection And Characterization Of Genetic Modifications, Torstein Tengs
Non-Prejudiced Detection And Characterization Of Genetic Modifications, Torstein Tengs
Dr. Torstein Tengs
The application of gene technology is becoming widespread much thanks to the rapid increase in technology, resource, and knowledge availability. Consequently, the diversity and number of genetically modified organisms (GMOs) that may find their way into the food chain or the environment, intended or unintended, is rapidly growing. From a safety point of view the ability to detect and characterize in detail any GMO, independent of publicly available information, is fundamental. Pre-release risk assessments of GMOs are required in most jurisdictions and are usually based on application of technologies with limited ability to detect unexpected rearrangements and insertions. We present …
Comparison Of Nine Different Real-Time Pcr Chemistries For Qualitative And Quantitative Applications In Gmo Detection, Torstein Tengs
Comparison Of Nine Different Real-Time Pcr Chemistries For Qualitative And Quantitative Applications In Gmo Detection, Torstein Tengs
Dr. Torstein Tengs
Several techniques have been developed for detection and quantification of genetically modified organisms, but quantitative real-time PCR is by far the most popular approach. Among the most commonly used realtime PCR chemistries are TaqMan probes and SYBR green, but many other detection chemistries have also been developed. Because their performance has never been compared systematically, here we present an extensive evaluation of some promising chemistries: sequenceunspecific DNA labeling dyes (SYBR green), primer-based technologies (AmpliFluor, Plexor, Lux primers), and techniques involving double-labeled probes, comprising hybridization (molecular beacon) and hydrolysis (TaqMan, CPT, LNA, and MGB) probes, based on recently published experimental data. …
Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull
Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull
Jeffrey S. Morris
Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient …
Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris
Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris
Jeffrey S. Morris
A recent article published in The Annals of Applied Statistics (AOAS) by two MD Anderson researchers—Keith Baggerly and Kevin Coombes—dissects results from a highly-influential series of medical papers involving genomics-driven personalized cancer therapy, and outlines a series of simple yet fatal flaws that raises serious questions about the veracity of the original results. Having immediate and strong impact, this paper, along with related work, is providing the impetus for new standards of reproducibility in scientific research.
Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes
Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes
Jeffrey S. Morris
Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the …
Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang
Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang
Jeffrey S. Morris
Whilst recent progress in ‘shotgun’ peptide separation by integrated liquid chromatography and mass spectrometry (LC/MS) has enabled its use as a sensitive analytical technique, proteome coverage and reproducibility is still limited and obtaining enough replicate runs for biomarker discovery is a challenge. For these reasons, recent research demonstrates the continuing need for protein separation by two-dimensional gel electrophoresis (2-DE). However, with traditional 2-DE informatics, the digitized images are reduced to symbolic data though spot detection and quantification before proteins are compared for differential expression by spot matching. Recently, a more robust and automated paradigm has emerged where gels are directly …
Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris
Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris
Jeffrey S. Morris
Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. …
Quantitative Comparison Of Genomic-Wide Protein Domain Distributions, Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
Quantitative Comparison Of Genomic-Wide Protein Domain Distributions, Arli A. Parikesit, Peter F. Stadler, Sonja J. Prohaska
Arli A Parikesit
Investigations into the origins and evolution of regulatory mechanisms require quantitative estimates of the abundance and co-occurrence of functional protein domains among distantly related genomes. Currently available databases, such as the SUPERFAMILY, are not designed for quantitative comparisons since they are built upon transcript and protein annotations provided by the various different genome annotation projects. Large biases are introduced by the differences in genome annotation protocols, which strongly depend on the availability of transcript information and well-annotated closely related organisms. Here we show that the combination of de novo gene predictors and subsequent HMM-based annotation of SCOP domains in the …
Paraoxonase 1 Activity As A Predictor Of Cardiovascular Disease In Type 2 Diabetes, Rozaida @ Poh Yuen Ying
Paraoxonase 1 Activity As A Predictor Of Cardiovascular Disease In Type 2 Diabetes, Rozaida @ Poh Yuen Ying
Rozaida @ Poh Yuen Ying
The role of paraoxonase 1 in cardiovascular disease complications in type 2 diabetes mellitus is not fully understood. We studied paraoxonase activity towards paraoxon in 188 non-diabetic and 140 diabetic subjects using general linear models and univariate analysis. Adjusting for age revealed a reduction in activity towards paraoxon was associated with a significant increase in risk (p=0.023) for cardiovascular disease complications in diabetic patients. Multivariate analysis of two plasma measures of paraoxonase activity using paraoxon and diazoxon also showed reduced paraoxonase activity towards paraoxon was associated with a significant increase in risk (p=0.045) for cardiovascular disease complications in diabetic patients. …
Dispersal Of Stable Flies (Diptera: Muscidae) From Larval Developmental Sites., David B. Taylor, Roger D. Moon, Jack B. Campbell, Dennis R. Berkebile, Philip J. Scholl, Alberto B. Broce, Jerome A. Hogsette
Dispersal Of Stable Flies (Diptera: Muscidae) From Larval Developmental Sites., David B. Taylor, Roger D. Moon, Jack B. Campbell, Dennis R. Berkebile, Philip J. Scholl, Alberto B. Broce, Jerome A. Hogsette
David B Taylor
Seven mark-recapture studies were conducted over 3 yr to assess dispersal of newly emerging adult stable flies, Stomoxys calcitrans L., from larval development sites in a mixed agricultural environment in northeastern Nebraska. Infested hay debris piles were marked by dusting their surfaces with fluorescent pigments, adults were captured with surrounding grids of Alsynite sticky traps, and specimens were dissected to determine feeding histories and reproductive age. Distances and directions of 3,889 marked specimens indicated males and females dispersed equally and in all directions. Midguts of males and females were equally likely to contain blood-meal remnants. Percentage with blood remnants and …
Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh
Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh
Debashis Ghosh
In high-throughput studies involving genetic data such as from gene expression mi- croarrays, dierential expression analysis between two or more experimental conditions has been a very common analytical task. Much of the resulting literature on multiple comparisons has paid relatively little attention to the choice of test statistic. In this article, we focus on the issue of choice of test statistic based on a special pattern of dierential expression. The approach here is based on recasting multiple comparisons procedures for assessing outlying expression values. A major complication is that the resulting p-values are discrete; some theoretical properties of sequential testing …
Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh
Detecting Outlier Genes From High-Dimensional Data: A Fuzzy Approach, Debashis Ghosh
Debashis Ghosh
A recent nding in cancer research has been the characterization of previously undis- covered chromosomal abnormalities in several types of solid tumors. This was found based on analyses of high-throughput data from gene expression microarrays and motivated the development of so-called `outlier' tests for dierential expression. One statistical issue was the potential discreteness of the test statistics. Using ideas from fuzzy set theory, we develop fuzzy outlier detection algorithms that have links to ideas in multiple comparisons. Two- and K-sample extensions are considered. The methodology is illustrated by application to two microarray studies.
Links Between Analysis Of Surrogate Endpoints And Endogeneity, Debashis Ghosh, Jeremy M. Taylor, Michael R. Elliott
Links Between Analysis Of Surrogate Endpoints And Endogeneity, Debashis Ghosh, Jeremy M. Taylor, Michael R. Elliott
Debashis Ghosh
There has been substantive interest in the assessment of surrogate endpoints in medical research. These are measures which could potentially replace \true" endpoints in clinical trials and lead to studies that require less follow-up. Recent research in the area has focused on assessments using causal inference frameworks. Beginning with a simple model for associating the surrogate and true endpoints in the population, we approach the problem as one of endogenous covariates. An instrumental variables estimator and general two-stage algorithm is proposed. Existing surrogacy frameworks are then evaluated in the context of the model. A numerical example is used to illustrate …
Meta-Analysis For Surrogacy: Accelerated Failure Time Models And Semicompeting Risks Modelling, Debashis Ghosh, Jeremy M. Taylor, Daniel J. Sargent
Meta-Analysis For Surrogacy: Accelerated Failure Time Models And Semicompeting Risks Modelling, Debashis Ghosh, Jeremy M. Taylor, Daniel J. Sargent
Debashis Ghosh
There has been great recent interest in the medical and statistical literature in the assessment and validation of surrogate endpoints as proxies for clinical endpoints in medical studies. More recently, authors have focused on using meta-analytical methods for quanti cation of surrogacy. In this article, we extend existing procedures for analysis based on the accelerated failure time model to this setting. An advantage of this approach relative to proportional hazards model is that it allows for analysis in the semi-competing risks setting, where we constrain the surrogate endpoint to occur before the true endpoint. A novel principal components procedure is …
Spline-Based Models For Predictiveness Curves, Debashis Ghosh, Michael Sabel
Spline-Based Models For Predictiveness Curves, Debashis Ghosh, Michael Sabel
Debashis Ghosh
A biomarker is dened to be a biological characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. The use of biomarkers in cancer has been advocated for a variety of purposes, which include use as surrogate endpoints, early detection of disease, proxies for environmental exposure and risk prediction. We deal with the latter issue in this paper. Several authors have proposed use of the predictiveness curve for assessing the capacity of a biomarker for risk prediction. For most situations, it is reasonable to assume monotonicity of …
Combining Multiple Models With Survival Data: The Phase Algorithm, Debashis Ghosh, Zheng Yuan
Combining Multiple Models With Survival Data: The Phase Algorithm, Debashis Ghosh, Zheng Yuan
Debashis Ghosh
In many scientic studies, one common goal is to develop good prediction rules based on a set of available measurements. This paper proposes a model averaging methodology using proportional hazards regression models to construct new estimators of predicted survival probabilities. A screening step based on an adaptive searching algorithm is used to handle large numbers of covariates. The nite-sample properties of the proposed methodology is assessed using simulation studies. Application of the method to a cancer biomarker study is also given.
Data Sharing, Latency Variables And The Science Commons, Jorge L. Contreras
Data Sharing, Latency Variables And The Science Commons, Jorge L. Contreras
Jorge L Contreras
Over the past decade, the rapidly decreasing cost of computer storage and the increasing prevalence of high-speed Internet connections have fundamentally altered the way in which scientific research is conducted. Led by scientists in disciplines such as genomics, the rapid sharing of data sets and cross-institutional collaboration promise to increase scientific efficiency and output dramatically. As a result, an increasing number of public “commons” of scientific data are being created: aggregations intended to be used and accessed by researchers worldwide. Yet, the sharing of scientific data presents legal, ethical and practical challenges that must be overcome before such science commons …