Annotation and query of tissue microarray data using the NCI Thesaurus

<p>Abstract</p> <p>Background</p> <p>The Stanford Tissue Microarray Database (TMAD) is a repository of data serving a consortium of pathologists and biomedical researchers. The tissue samples in TMAD are annotated with multiple free-text fields, specifying the pathological diagnoses for each sample. These text annotations are not structured according to any ontology, making future integration of this resource with other biological and clinical data difficult.</p> <p>Results</p> <p>We developed methods to map these annotations to the NCI thesaurus. Using the NCI-T we can effectively represent annotations for about 86% of the samples. We demonstrate how this mapping enables ontology driven integration and querying of tissue microarray data. We have deployed the mapping and ontology driven querying tools at the TMAD site for general use.</p> <p>Conclusion</p> <p>We have demonstrated that we can effectively map the diagnosis-related terms describing a sample in TMAD to the NCI-T. The NCI thesaurus terms have a wide coverage and provide terms for about 86% of the samples. In our opinion the NCI thesaurus can facilitate integration of this resource with other biological data.</p

Intricacies in the surgical management of appendiceal mucinous cystadenoma: a case report and review of the literature

<p>Abstract</p> <p>Introduction</p> <p>Mucinous cystadenoma is a type of mucocele of the appendix that is rarely encountered in clinical practice. Dogmatic consensus on the optimal surgical modus operandi of appendicular mucocele is lacking in the literature and this remains a subject of controversy. There is little agreement with regard to the best procedure (right hemicolectomy versus appendectomy) or the best surgical approach (laparoscopic versus laparotomy).</p> <p>Case presentation</p> <p>We report the case of a 70-year-old Asian woman from Karachi who presented with pain in the right iliac fossa for 15 days. On physical examination, a mobile and firm mass was palpable in the right iliac fossa. A colonoscopy was performed which showed external compression of the cecum. A biopsy of the mucosa was normal. Computed tomography scan showed a mucocele of the appendix with minimal periappendiceal fat stranding. She underwent an initial diagnostic laparoscopy to evaluate any mucin spillage in the peritoneal cavity. Once no spillage was identified, an open appendectomy was then performed. Intra-operatively, a frozen section of the appendiceal sample was sent to ascertain the need for an extension of surgery to a right hemicolectomy. Absence of any malignancy on the frozen section obviated the need for a surgical extension. The final histopathological examination showed a mucinous cystadenoma of the appendix. The patient was symptom-free at one year after surgery.</p> <p>Conclusion</p> <p>It is important to distinguish between mucinous cystadenomas and mucinous cystadenocarcinomas. However, this distinction remains elusive in the pre-operative setting. A simple appendectomy using an intra-operative frozen section appears to be a reasonable surgical approach for selected cases with an intact mucocele of the appendix. However, long-term follow-up is warranted in such patients to evaluate the risks of using this approach.</p

Using GeneReg to construct time delay gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>Understanding gene expression and regulation is essential for understanding biological mechanisms. Because gene expression profiling has been widely used in basic biological research, especially in transcription regulation studies, we have developed GeneReg, an easy-to-use R package, to construct gene regulatory networks from time course gene expression profiling data; More importantly, this package can provide information about time delays between expression change in a regulator and that of its target genes.</p> <p>Findings</p> <p>The R package GeneReg is based on time delay linear regression, which can generate a model of the expression levels of regulators at a given time point against the expression levels of their target genes at a later time point. There are two parameters in the model, time delay and regulation coefficient. Time delay is the time lag during which expression change of the regulator is transmitted to change in target gene expression. Regulation coefficient expresses the regulation effect: a positive regulation coefficient indicates activation and negative indicates repression. GeneReg was implemented on a real Saccharomyces cerevisiae cell cycle dataset; more than thirty percent of the modeled regulations, based entirely on gene expression files, were found to be consistent with previous discoveries from known databases.</p> <p>Conclusions</p> <p>GeneReg is an easy-to-use, simple, fast R package for gene regulatory network construction from short time course gene expression data. It may be applied to study time-related biological processes such as cell cycle, cell differentiation, or causal inference.</p

Body fat mass and the proportion of very large adipocytes in pregnant women are associated with gestational insulin resistance.

Pregnancy is accompanied by fat gain and insulin resistance. Changes in adipose tissue morphology and function during pregnancy and factors contributing to gestational insulin resistance are incompletely known. We sought to characterize adipose tissue in trimesters 1 and 3 (T1/T3) in normal weight (NW) and obese pregnant women, and identify adipose tissue-related factors associated with gestational insulin resistance

Estimating total body water content in suckling and lactating llamas (Lama glama) by isotope dilution

Total body water (TBW) in 17 suckling and six lactating llamas was estimated from isotope dilution at three different post natum and lactation stages using both 18O and deuterium oxide (D2O). In total, 69 TBW measurements were undertaken. While TBW in lactating dams, expressed in kilogram, remained stable during the three measurement periods (91.8 ± 15.0 kg), the body water fraction (TBW expressed in percent of body mass) increased slightly (P = 0.042) from 62.9% to 65.8%. In contrast, TBW (kilogram) in suckling llamas increased significantly (P < 0.001) with age and decreased slightly when expressed as a percentage of body mass (P = 0.016). Relating TBW to body mass across all animals yielded a highly significant regression equation (TBW in kilogram = 2.633 + 0.623 body mass in kilogram, P < 0.001, n = 69) explaining 99.5% of the variation. The water fraction instead decreased in a curve linear fashion with increasing body mass (TBW in percent of body mass = 88.23 body mass in kilogram−0.064, P < 0.001, R2 = 0.460). The present results on TBW can serve as reference values for suckling and lactating llamas, e.g., for the evaluation of fluid losses during disease. Additionally, the established regression equations can be used to predict TBW from body mass, providing that the body masses fall inside the range of masses used to derive the equations

Human Disease-Drug Network Based on Genomic Expression Profiles

BACKGROUND: Drug repositioning offers the possibility of faster development times and reduced risks in drug discovery. With the rapid development of high-throughput technologies and ever-increasing accumulation of whole genome-level datasets, an increasing number of diseases and drugs can be comprehensively characterized by the changes they induce in gene expression, protein, metabolites and phenotypes. METHODOLOGY/PRINCIPAL FINDINGS: We performed a systematic, large-scale analysis of genomic expression profiles of human diseases and drugs to create a disease-drug network. A network of 170,027 significant interactions was extracted from the approximately 24.5 million comparisons between approximately 7,000 publicly available transcriptomic profiles. The network includes 645 disease-disease, 5,008 disease-drug, and 164,374 drug-drug relationships. At least 60% of the disease-disease pairs were in the same disease area as determined by the Medical Subject Headings (MeSH) disease classification tree. The remaining can drive a molecular level nosology by discovering relationships between seemingly unrelated diseases, such as a connection between bipolar disorder and hereditary spastic paraplegia, and a connection between actinic keratosis and cancer. Among the 5,008 disease-drug links, connections with negative scores suggest new indications for existing drugs, such as the use of some antimalaria drugs for Crohn's disease, and a variety of existing drugs for Huntington's disease; while the positive scoring connections can aid in drug side effect identification, such as tamoxifen's undesired carcinogenic property. From the approximately 37K drug-drug relationships, we discover relationships that aid in target and pathway deconvolution, such as 1) KCNMA1 as a potential molecular target of lobeline, and 2) both apoptotic DNA fragmentation and G2/M DNA damage checkpoint regulation as potential pathway targets of daunorubicin. CONCLUSIONS/SIGNIFICANCE: We have automatically generated thousands of disease and drug expression profiles using GEO datasets, and constructed a large scale disease-drug network for effective and efficient drug repositioning as well as drug target/pathway identification

Metabolic acceleration and the evolution of human brain size and life history.

Humans are distinguished from the other living apes in having larger brains and an unusual life history that combines high reproductive output with slow childhood growth and exceptional longevity. This suite of derived traits suggests major changes in energy expenditure and allocation in the human lineage, but direct measures of human and ape metabolism are needed to compare evolved energy strategies among hominoids. Here we used doubly labelled water measurements of total energy expenditure (TEE; kcal day(-1)) in humans, chimpanzees, bonobos, gorillas and orangutans to test the hypothesis that the human lineage has experienced an acceleration in metabolic rate, providing energy for larger brains and faster reproduction without sacrificing maintenance and longevity. In multivariate regressions including body size and physical activity, human TEE exceeded that of chimpanzees and bonobos, gorillas and orangutans by approximately 400, 635 and 820 kcal day(-1), respectively, readily accommodating the cost of humans' greater brain size and reproductive output. Much of the increase in TEE is attributable to humans' greater basal metabolic rate (kcal day(-1)), indicating increased organ metabolic activity. Humans also had the greatest body fat percentage. An increased metabolic rate, along with changes in energy allocation, was crucial in the evolution of human brain size and life history

Quantitative Epistasis Analysis and Pathway Inference from Genetic Interaction Data

Inferring regulatory and metabolic network models from quantitative genetic interaction data remains a major challenge in systems biology. Here, we present a novel quantitative model for interpreting epistasis within pathways responding to an external signal. The model provides the basis of an experimental method to determine the architecture of such pathways, and establishes a new set of rules to infer the order of genes within them. The method also allows the extraction of quantitative parameters enabling a new level of information to be added to genetic network models. It is applicable to any system where the impact of combinatorial loss-of-function mutations can be quantified with sufficient accuracy. We test the method by conducting a systematic analysis of a thoroughly characterized eukaryotic gene network, the galactose utilization pathway in Saccharomyces cerevisiae. For this purpose, we quantify the effects of single and double gene deletions on two phenotypic traits, fitness and reporter gene expression. We show that applying our method to fitness traits reveals the order of metabolic enzymes and the effects of accumulating metabolic intermediates. Conversely, the analysis of expression traits reveals the order of transcriptional regulatory genes, secondary regulatory signals and their relative strength. Strikingly, when the analyses of the two traits are combined, the method correctly infers ∼80% of the known relationships without any false positives

Body mass index, adiposity rebound and early feeding in a longitudinal cohort (Raine study)

Objective: This study examined the influence of type and duration of infant feeding on adiposity rebound and the tracking of body mass index (BMI) from birth to 14 years. Methods: A sample of 1330 individuals over eight follows-ups was drawn from the Western Australian Pregnancy Cohort (Raine) Study. Trajectories of BMI from birth to adolescence using linear mixed model (LMM) analysis investigated the influence of age breastfeeding stopped and age other milk introduced (binomial 4-month cut-point). A sub-sample of LMM predicted BMI was used to determine BMI and age at nadir for early infant feeding groups. Results: Chi square analysis between early feeding and weight status (normal weight, overweight and obese) groups found a significant difference between age breastfeeding stopped (p Conclusions: Early infant feeding was important in the timing and BMI at adiposity rebound. The relationship between infant feeding and BMI remained up to age 14 years. Although confounding factors cannot be excluded, these findings support the importance of exclusive breastfeeding for longer than four months as a protective behaviour against the development of adolescent obesity

Study of Women, Infant feeding, and Type 2 diabetes mellitus after GDM pregnancy (SWIFT), a prospective cohort study: methodology and design

<p>Abstract</p> <p>Background</p> <p>Women with history of gestational diabetes mellitus (GDM) are at higher risk of developing type 2 diabetes within 5 years after delivery. Evidence that lactation duration influences incident type 2 diabetes after GDM pregnancy is based on one retrospective study reporting a null association. The Study of Women, Infant Feeding and Type 2 Diabetes after GDM pregnancy (SWIFT) is a prospective cohort study of postpartum women with recent GDM within the Kaiser Permanente Northern California (KPNC) integrated health care system. The primary goal of SWIFT is to assess whether prolonged, intensive lactation as compared to formula feeding reduces the 2-year incidence of type 2 diabetes mellitus among women with GDM. The study also examines whether lactation intensity and duration have persistent favorable effects on blood glucose, insulin resistance, and adiposity during the 2-year postpartum period. This report describes the design and methods implemented for this study to obtain the clinical, biochemical, anthropometric, and behavioral measurements during the recruitment and follow-up phases.</p> <p>Methods</p> <p>SWIFT is a prospective, observational cohort study enrolling and following over 1, 000 postpartum women diagnosed with GDM during pregnancy within KPNC. The study enrolled women at 6-9 weeks postpartum (baseline) who had been diagnosed by standard GDM criteria, aged 20-45 years, delivered a singleton, term (greater than or equal to 35 weeks gestation) live birth, were not using medications affecting glucose tolerance, and not planning another pregnancy or moving out of the area within the next 2 years. Participants who are free of type 2 diabetes and other serious medical conditions at baseline are screened for type 2 diabetes annually within the first 2 years after delivery. Recruitment began in September 2008 and ends in December 2011. Data are being collected through pregnancy and early postpartum telephone interviews, self-administered monthly mailed questionnaires (3-11 months postpartum), a telephone interview at 6 months, and annual in-person examinations at which a 75 g 2-hour OGTT is conducted, anthropometric measurements are obtained, and self- and interviewer-administered questionnaires are completed.</p> <p>Discussion</p> <p>This is the first, large prospective, community-based study involving a racially and ethnically diverse cohort of women with recent GDM that rigorously assesses lactation intensity and duration and examines their relationship to incident type 2 diabetes while accounting for numerous potential confounders not assessed previously.</p