Understanding the basic biology underlying the flavor world of children

Health organizations worldwide recommend that adults and children minimize intakes of excess energy and salty, sweet, and fatty foods (all of which are highly preferred tastes) and eat diets richer in whole grains, low- and non- fat dairy products, legumes, fish, lean meat, fruits, and vegetables (many of which taste bitter). Despite such recommendations and the well-established benefits of these foods to human health, adults are not complying, nor are their children. A primary reason for this difficulty is...     

Reference concentrations of cholecalciferol in animals: a basis for establishing non-target exposure

Abstract

Cholecalciferol (vitamin D₃) is widely used as a vertebrate pesticide in New Zealand. However, cholecalciferol also occurs naturally in animals. Therefore, when trying to determine whether a non-target animal has been exposed to cholecalciferol baits, knowledge of the baseline cholecalciferol concentrations in the animal's plasma and tissue is required. We analysed cattle, sheep, pig, deer, dog and cat plasma and liver samples for the vitamin D₃ metabolite 25-hydroxycholecalciferol (25-OHD), a sensitive biomarker for cholecalciferol. Based on these data and a literature search we present 25-OHD reference ranges. We also examined the literature for 25-OHD concentrations in poisoned animals and compared these to the reference ranges. Where plasma and liver samples have 25-OHD concentrations at least four times higher than our reference ranges it is likely that the animal has been exposed to cholecalciferol baits. 25-OHD concentrations 10 times higher than the reference range indicate ingestion of abnormally high amounts of cholecalciferol.     

The Gene Expression Profile of CD11c+CD8α? Dendritic Cells in the Pre-Diabetic Pancreas of the NOD Mouse

Two major dendritic cell (DC) subsets have been described in the pancreas of mice: The CD11c⁺CD8α⁻ DCs (strong CD4+ T cell proliferation inducers) and the CD8α⁺CD103⁺ DCs (T cell apoptosis inducers). Here we analyzed the larger subset of CD11c⁺CD8α⁻ DCs isolated from the pancreas of pre-diabetic NOD mice for genome-wide gene expression (validated by Q-PCR) to elucidate abnormalities in underlying gene expression networks. CD11c⁺CD8α⁻ DCs were isolated from 5 week old NOD and control C57BL/6 pancreas. The steady state pancreatic NOD CD11c⁺CD8α⁻ DCs showed a reduced expression of several gene networks important for the prime functions of these cells, i.e. for cell renewal, immune tolerance induction, migration and for the provision of growth factors including those for beta cell regeneration. A functional in vivo BrdU incorporation test showed the reduced proliferation of steady state pancreatic DC. The reduced expression of tolerance induction genes (CD200R, CCR5 and CD24) was supported on the protein level by flow cytometry. Also previously published functional tests on maturation, immune stimulation and migration confirm the molecular deficits of NOD steady state DC. Despite these deficiencies NOD pancreas CD11c⁺CD8α⁻ DCs showed a hyperreactivity to LPS, which resulted in an enhanced pro-inflammatory state characterized by a gene profile of an enhanced expression of a number of classical inflammatory cytokines. The enhanced up-regulation of inflammatory genes was supported by the in vitro cytokine production profile of the DCs. In conclusion, our data show that NOD pancreatic CD11c⁺CD8α⁻ DCs show various deficiencies in steady state, while hyperreactive when encountering a danger signal such as LPS.     

Vertical inhibition of the MAPK pathway enhances therapeutic responses in NRAS‐mutant melanoma

The MEK inhibitor MEK162 is the first targeted therapy agent with clinical activity in patients whose melanomas harbor NRAS mutations; however, median PFS is 3.7 months, suggesting the rapid onset of resistance in the majority of patients. Here, we show that treatment of NRAS‐mutant melanoma cell lines with the MEK inhibitors AZD6244 or trametinib resulted in a rebound activation of phospho‐ERK (pERK). Functionally, the recovery of signaling was associated with the maintenance of cyclin‐D1 expression and therapeutic escape. The combination of a MEK inhibitor with an ERK inhibitor suppressed the recovery of cyclin‐D1 expression and was associated with a significant enhancement of apoptosis and the abrogation of clonal outgrowth. The MEK/ERK combination strategy induced greater levels of apoptosis compared with dual MEK/CDK4 or MEK/PI3K inhibition across a panel of cell lines. These data provide the rationale for further investigation of vertically co‐targeting the MAPK pathway as a potential treatment option for NRAS‐mutant melanoma patients.     

Optimising predictive modelling of Ross River virus using meteorological variables

BackgroundStatistical models are regularly used in the forecasting and surveillance of infectious diseases to guide public health. Variable selection assists in determining factors associated with disease transmission, however, often overlooked in this process is the evaluation and suitability of the statistical model used in forecasting disease transmission and outbreaks. Here we aim to evaluate several modelling methods to optimise predictive modelling of Ross River virus (RRV) disease notifications and outbreaks in epidemiological important regions of Victoria and Western Australia.Methodology/Principal findingsWe developed several statistical methods using meteorological and RRV surveillance data from July 2000 until June 2018 in Victoria and from July 1991 until June 2018 in Western Australia. Models were developed for 11 Local Government Areas (LGAs) in Victoria and seven LGAs in Western Australia. We found generalised additive models and generalised boosted regression models, and generalised additive models and negative binomial models to be the best fit models when predicting RRV outbreaks and notifications, respectively. No association was found with a model’s ability to predict RRV notifications in LGAs with greater RRV activity, or for outbreak predictions to have a higher accuracy in LGAs with greater RRV notifications. Moreover, we assessed the use of factor analysis to generate independent variables used in predictive modelling. In the majority of LGAs, this method did not result in better model predictive performance.Conclusions/SignificanceWe demonstrate that models which are developed and used for predicting disease notifications may not be suitable for predicting disease outbreaks, or vice versa. Furthermore, poor predictive performance in modelling disease transmissions may be the result of inappropriate model selection methods. Our findings provide approaches and methods to facilitate the selection of the best fit statistical model for predicting mosquito-borne disease notifications and outbreaks used for disease surveillance.