Postpartum Screening for Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus: A Cost-Effectiveness Analysis in Singapore.

Objectives: In Singapore, diabetes imposes a huge population health and economic burden. Despite that, there is paucity of evidence on the health economics of screening programs for type 2 diabetes, especially in the context of screening after gestational diabetes (GDM). The objective of this study is to assess cost-effectiveness of universal lifelong screening for type 2 diabetes after GDM, which is supported by current guidelines, compared with elective screening where 54% of mothers with GDM undertake one-off screening.

Patient-derived acellular ascites fluid affects drug responses in ovarian cancer cell lines through the activation of key signalling pathways.

Malignant ascites is commonly produced in advanced epithelial ovarian cancer (EOC) and serves as unique microenvironment for tumour cells. Acellular ascites fluid (AAF) is rich in signalling molecules and has been proposed to play a role in the induction of chemoresistance. Through in vitro testing of drug sensitivity and by assessing intracellular phosphorylation status in response to mono- and combination treatment of five EOC cell lines after incubation with AAFs derived from 20 different patients, we investigated the chemoresistance-inducing potential of ascites.

Joint modeling of association networks and longitudinal biomarkers: An application to childhood obesity.

The prevalence of chronic non-communicable diseases such as obesity has noticeably increased in the last decade. The study of these diseases in early life is of paramount importance in determining their course in adult life and in supporting clinical interventions. Recently, attention has been drawn to approaches that study the alteration of metabolic pathways in obese children.

Perinatal Trajectories of Maternal Depressive Symptoms in Prospective, Community-Based Cohorts Across 3 Continents.

Importance: Depressive symptoms during pregnancy influence the development and health of the offspring, underscoring the need for timely intervention. However, the course of depressive symptoms across the perinatal period remains unclear, thus complicating screening and referral guidelines.

Objective: To examine the course and stability of depressive symptoms across the perinatal period in multiple, ethnically diverse independent observational cohorts.

Bayesian clustering of multiple zero-inflated outcomes.

Several applications involving counts present a large proportion of zeros (excess-of-zeros data). A popular model for such data is the hurdle model, which explicitly models the probability of a zero count, while assuming a sampling distribution on the positive integers. We consider data from multiple count processes.

Bayesian modelling of response to therapy and drug-sensitivity in acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is a heterogeneous haematologic malignancy involving the abnormal proliferation of immature lymphocytes and accounts for most paediatric cancer cases. The management of ALL in children has seen great improvement in the last decades thanks to greater understanding of the disease leading to improved treatment strategies evidenced through clinical trials. Common therapy regimens involve a first course of chemotherapy (induction phase), followed by treatment with a combination of anti-leukemia drugs.

Bayesian dynamic network modelling: an application to metabolic associations in cardiovascular diseases.

We propose a novel approach to the estimation of multiple Graphical Models to analyse temporal patterns of association among a set of metabolites over different groups of patients. Our motivating application is the Southall And Brent REvisited (SABRE) study, a tri-ethnic cohort study conducted in the UK. We are interested in identifying potential ethnic differences in metabolite levels and associations as well as their evolution over time, with the aim of gaining a better understanding of different risk of cardio-metabolic disorders across ethnicities.

Ex vivo drug sensitivity screening in multiple myeloma identifies drug combinations that act synergistically.

The management of multiple myeloma (MM) is challenging: An assortment of available drug combinations adds complexity to treatment selection, and treatment resistance frequently develops. Given the heterogeneous nature of MM, personalized testing tools are required to identify drug sensitivities. To identify drug sensitivities in MM cells, we established a drug testing pipeline to examine ex vivo drug responses.

A Bayesian nonparametric approach to dynamic item-response modeling: An application to the GUSTO cohort study.

Statistical analysis of questionnaire data is often performed employing techniques from item-response theory. In this framework, it is possible to differentiate respondent profiles and characterize the questions (items) included in the questionnaire via interpretable parameters. These models are often crosssectional and aim at evaluating the performance of the respondents.

bayesynergy: flexible Bayesian modelling of synergistic interaction effects in in vitro drug combination experiments.

The effect of cancer therapies is often tested pre-clinically via in vitro experiments, where the post-treatment viability of the cancer cell population is measured through assays estimating the number of viable cells. In this way, large libraries of compounds can be tested, comparing the efficacy of each treatment. Drug interaction studies focus on the quantification of the additional effect encountered when two drugs are combined, as opposed to using the treatments separately.

Hierarchical Normalized Completely Random Measures for Robust Graphical Modeling.

Gaussian graphical models are useful tools for exploring network structures in multivariate normal data. In this paper we are interested in situations where data show departures from Gaussianity, therefore requiring alternative modeling distributions. The multivariate -distribution, obtained by dividing each component of the data vector by a gamma random variable, is a straightforward generalization to accommodate deviations from normality such as heavy tails.

An in vitro assay for biomarker discovery and dose prediction applied to ibrutinib plus venetoclax treatment of CLL.

Recently, several small molecule drugs were approved for treatment of chronic lymphocytic leukemia (CLL), significantly improving patient management. However, knowledge about how to combine these therapies for optimal effects and what patients will best benefit from them is lacking. Here, we show that drug synergies can be identified by single cell signaling analyses.

Single cell profiling of phospho-protein levels in chronic lymphocytic leukemia.

Chronic lymphocytic leukemia (CLL) has a high incidence and a steeply growing prevalence in the Western world. The heterogeneity of the disease necessitates individual mapping of biology and predicted drug response in each patient as basis for administration of tailored treatments. Cell signaling aberrations may serve as biological indicators for suitable therapy.

Nut-cracking behaviour in wild-born, rehabilitated bonobos (Pan paniscus): a comprehensive study of hand-preference, hand grips and efficiency.

There has been an enduring interest in primate tool-use and manipulative abilities, most often with the goal of providing insight into the evolution of human manual dexterity, right-hand preference, and what behaviours make humans unique. Chimpanzees (Pan troglodytes) are arguably the most well-studied tool-users amongst non-human primates, and are particularly well-known for their complex nut-cracking behaviour, which has been documented in several West African populations. However, their sister-taxon, the bonobos (Pan paniscus), rarely engage in even simple tool-use and are not known to nut-crack in the wild.