Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network

Joint Modeling and Registration of Cell Populations in Cohorts of High-Dimensional Flow Cytometric Data

In systems biomedicine, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multi-variable network-level responses. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simultaneous modeling and registration of populations across a cohort. JCM models every population with a robust multivariate probability distribution. Simultaneously, JCM fits a random-effects model to construct an overall batch template -- used for registering populations across samples, and classifying new samples. By tackling systems-level variation, JCM supports practical biomedical applications involving large cohorts

An experienced physiotherapist prescribing and administering corticosteroid and local anaesthetic injections to the shoulder in an Australian orthopaedic service, a non-inferiority randomised controlled trial and economic analysis: study protocol for a ra

Background: The early management of orthopaedic outpatients by physiotherapists may be useful in reducing public hospital waiting lists. Physiotherapists in Australia are prevented by legislation and funding models from investigating, prescribing, injecting and referring autonomously. This gap in service is particularly noticeable in the management of shoulder pain in early-access physiotherapy services, as patients needing corticosteroid injection face delays or transfer to other services for this procedure. This trial will investigate the clinical (decision making and outcomes) and economic feasibility of a physiotherapist prescribing and delivering corticosteroid and local anaesthetic injections for shoulder pain in an Australian public hospital setting. Methods/Design: A double-blinded (patient and assessor) non-inferiority randomised controlled trial will compare an orthopaedic surgeon and a physiotherapist prescribing and delivering corticosteroid injections to the shoulder. Agreement in decision making between the two clinicians will be investigated, and economic information will be obtained for estimating disease burden and an economic evaluation. The surgeon and the physiotherapist will independently assess patients, and 64 eligible participants will be randomised to receive subacromial injection of corticosteroid and local anaesthetic from either the surgeon or the physiotherapist. Post-injection, all participants will receive physiotherapy. The primary outcome measure will be the Shoulder Pain and Disability Index measured at baseline, and at 6 and 12 weeks post-injection. Analysis will be conducted on an intention-to-treat basis and compared to a per-protocol analysis. A cost-utility analysis will be undertaken from the perspective of the health funder. Discussion: Findings will assist policy makers and services in improving access for orthopaedic patients

Characterization of aldehyde dehydrogenase isozymes in ovarian cancer tissues and sphere cultures

BACKGROUND: Aldehyde dehydrogenases belong to a superfamily of detoxifying enzymes that protect cells from carcinogenic aldehydes. Of the superfamily, ALDH1A1 has gained most attention because current studies have shown that its expression is associated with human cancer stem cells. However, ALDH1A1 is only one of the 19 human ALDH subfamilies currently known. The purpose of the present study was to determine if the expression and activities of other major ALDH isozymes are associated with human ovarian cancer and ovarian cancer sphere cultures. METHODS: Immunohistochemistry was used to delineate ALDH isozyme localization in clinical ovarian tissues. Western Blot analyses were performed on lysates prepared from cancer cell lines and ovarian cancer spheres to confirm the immunohistochemistry findings. Quantitative reverse transcription-polymerase chain reactions were used to measure the mRNA expression levels. The Aldefluor® assay was used to measure ALDH activity in cancer cells from the four tumor subtypes. RESULTS: Immunohistochemical staining showed significant overexpression of ALDH1A3, ALDH3A2, and ALDH7A1 isozymes in ovarian tumors relative to normal ovarian tissues. The expression and activity of ALDH1A1 is tumor type-dependent, as seen from immunohistochemisty, Western blot analysis, and the Aldefluor® assay. The expression was elevated in the mucinous and endometrioid ovarian epithelial tumors than in serous and clear cell tumors. In some serous and most clear cell tumors, ALDH1A1 expression was found in the stromal fibroblasts. RNA expression of all studied ALDH isozymes also showed higher expression in endometrioid and mucinous tumors than in the serous and clear cell subtypes. The expression of ALDH enzymes showed tumor type-dependent induction in ovarian cancer cells growing as sphere suspensions in serum-free medium. CONCLUSIONS: The results of our study indicate that ALDH enzyme expression and activity may be associated with specific cell types in ovarian tumor tissues and vary according to cell states. Elucidating the function of the ALDH isozymes in lineage differentiation and pathogenesis may have significant implications for ovarian cancer pathophysiology

Epithelialization of mouse ovarian tumor cells originating in the fallopian tube stroma

Epithelial ovarian carcinoma accounts for 90% of all ovarian cancer and is the most deadly gynecologic malignancy. Recent studies have suggested that fallopian tube fimbriae can be the origin of cells for high-grade serous subtype of epithelial ovarian carcinoma (HGSOC). A mouse HGSOC model with conditional Dicer-Pten double knockout (Dicer-Pten DKO) developed primary tumors, intriguingly, from the fallopian tube stroma. We examined the growth and epithelial phenotypes of the Dicer-Pten DKO mouse tumor cells contributable by each gene knockout. Unlike human ovarian epithelial cancer cells that expressed full-length E-cadherin, the Dicer-Pten DKO stromal tumor cells expressed cleaved E-cadherin fragments and metalloproteinase 2, a mixture of epithelial and mesenchymal markers. Although the Dicer-Pten DKO tumor cells lost the expression of mature microRNAs as expected, they showed high levels of tRNA fragment expression and enhanced AKT activation due to the loss of PTEN function. Introduction of a Dicer1-expressing construct into the DKO mouse tumor cells significantly reduced DNA synthesis and the cell growth rate, with concurrent diminished adhesion and ZO1 epithelial staining. Hence, it is likely that the loss of Dicer promoted mesenchymal-epithelial transition in fallopian tube stromal cells, and in conjunction with Pten loss, further promoted cell proliferation and epithelial-like tumorigenesis

Poverty, Dietary Intake, Intestinal Parasites, and Nutritional Status among School-Age Children in the Rural Philippines

Intestinal helminths are endemic throughout the Philippines; however, there is limited evidence with respect to their prevalence, intensity, and impact on children’s nutritional status. A cross-sectional survey was carried out on 693 children from five rural villages in Northern Samar, the Philippines. Data on dietary intake, nutritional status, and intestinal parasites were collected. Infection with Schistosoma japonicum, Ascaris lumbricoides, Trichuris trichiura, and hookworm was evident in 20.1, 54.4, 71.4, and 25.3% of the children. The majority (84.7%) was infected with one or more helminth species, with about one-quarter of the sample (24.7%) infected with three or more. About half (49.2%, n = 341) of the children were stunted and 27.8% (n = 193) were wasted. A lower prevalence of normal height-for-age (48.3%) appeared in those with polyparasitism, while the prevalence of stunted children increased with infection (46.7% monoparasitism and 51.7% polyparasitism). There was a decreasing trend between infection intensity and the mean values of HAZ and BAZ identified for T. trichiura or hookworm infections. Stunted children were more likely to be male (AOR = 1.58; 95% CI: 1.05–2.39; p = 0.028), older in age (10–14 years) (AOR = 1.93; 95% CI: 1.29–2.88; p = 0.001), and living in poorer households with palm leaves/nipa roof (AOR = 1.85; 95% CI: 1.14–3.01; p = 0.013). Intestinal parasitic treatment needs to be combined with nutrient supplements and health education in order to interrupt the parasite life cycle and achieve sustainable control.We thank the Australian National Health and Medical Research Council for providing financial support for this research in the Philippines

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer

Mucinous epithelial ovarian cancers are clinically and morphologically distinct from the other histopathologic subtypes of ovarian cancer. Unlike other ovarian subtypes, epidemiologic studies have indicated that tobacco exposure is a significant risk factor for developing mucinous ovarian cancer. Detection of autoantibody reactivity is useful in biomarker discovery and for explaining the role of important pathophysiologic pathways in disease. In order to study if there are specific antibody biomarkers in the plasma samples of mucinous ovarian cancer patients, we have initiated a screen by employing a “reverse capture antibody microarray” platform that uses native host antigens derived from mucinous ovarian tissues as “baits” for the capture of differentially labeled patient and control autoantibodies. 35 autoantibodies that were significantly elevated in the cancer plasma samples compared with healthy controls, and six autoantibodies that segregated smoking and nonsmoking patients were identified. Functional annotation of the antibody targets has identified nine target antigens involved in integrin and Wnt signaling pathways. Immunohistochemistry of archived ovarian specimens showed significant overexpression of eight of the nine target antigens in mucinous ovarian tumor tissues, suggesting that plasma autoantibodies from mucinous ovarian cancer patients might have heightened reactivities with epitopes presented by these overexpressed antigens. Autoantibody profiling may have an unexpected utility in uncovering key signaling pathways that are dysregulated in the system of interest