Comparison of smoking-related DNA methylation between newborns from prenatal exposure and adults from personal smoking.

Aim: Cigarette smoking influences DNA methylation genome wide, in newborns from pregnancy exposure and in adults from personal smoking. Whether a unique methylation signature exists for in utero exposure in newborns is unknown. Materials & methods: We separately meta-analyzed newborn blood DNA methylation (assessed using Illumina450k Beadchip), in relation to sustained maternal smoking during pregnancy (9 cohorts, 5648 newborns, 897 exposed) and adult blood methylation and personal smoking (16 cohorts, 15907 participants, 2433 current smokers). Results & conclusion: Comparing meta-analyses, we identified numerous signatures specific to newborns along with many shared between newborns and adults. Unique smoking-associated genes in newborns were enriched in xenobiotic metabolism pathways. Our findings may provide insights into specific health impacts of prenatal exposure on offspring

Informative Models for the Joint Distribution of a Vector from Its Marginal Distributions – An Application to the Spina Bifida Condition

<p>We propose a model, which has information on the joint distribution of the vector from its marginal distributions. We outline a method of extracting information on the joint distribution from the marginal distributions. </p&gt

Reliability of Systematic and Targeted Biopsies versus Prostatectomy

Systematic Biopsy (SBx) has been and continues to be the standard staple for detecting prostate cancer. The more expensive MRI guided biopsy (MRITBx) is a better way of detecting cancer. The prostatectomy can provide an accurate condition of the prostate. The goal is to assess how reliable SBx and MRITBx are vis à vis prostatectomy. Graded Gleason scores are used for comparison. Cohen’s Kappa index and logistic regression after binarization of the graded Gleason scores are some of the methods used to achieve our goals. Machine learning methods, such as classification trees, are employed to improve predictability clinically. The Cohen’s Kappa index is 0.31 for SBx versus prostatectomy, which means a fair agreement. The index is 0.34 for MRITBx versus prostatectomy, which again means a fair agreement. A direct comparison of SBx versus prostatectomy via binarized graded scores gives sensitivity 0.83 and specificity 0.50. On the other hand, a direct comparison of MRITBx versus prostatectomy gives sensitivity 0.78 and specificity 0.67, putting MRITBx on a higher level of accuracy. The SBx and MRITBx do not yet match the findings of prostatectomy completely, but they are useful. We have developed new biomarkers, considering other pieces of information from the patients, to improve the accuracy of SBx and MRITBx. From a clinical point of view, we provide a prediction model for prostatectomy Gleason grades using classification tree methodology

Sample Size Calculations in Simple Linear Regression: A New Approach

The problem tackled is the determination of sample size for a given level and power in the context of a simple linear regression model. The standard approach deals with planned experiments in which the predictor X is observed for a number n of times and the corresponding observations on the response variable Y are to be drawn. The statistic that is used is built on the least squares’ estimator of the slope parameter. Its conditional distribution given the data on the predictor X is utilized for sample size calculations. This is problematic. The sample size n is already presaged and the data on X is fixed. In unplanned experiments, in which both X and Y are to be sampled simultaneously, we do not have data on the predictor X yet. This conundrum has been discussed in several papers and books with no solution proposed. We overcome the problem by determining the exact unconditional distribution of the test statistic in the unplanned case. We have provided tables of critical values for given levels of significance following the exact distribution. In addition, we show that the distribution of the test statistic depends only on the effect size, which is defined precisely in the paper

How trade affects the US produce industry: the case of fresh tomatoes

The US produce industry faces intensifying competition from imports, particularly those from Mexico, the largest exporter of produce to the United States. Fresh produce imports from Mexico have grown dramatically in recent years. This study examines the impact of increasing fresh tomato imports from Mexico on market price and revenue of US growers. Results show that tomato prices are highly sensitive to supply, suggesting a saturated market. Imports from Mexico have significant negative impacts on the prices of US domestic tomatoes. A scenario of 50% increase in tomato imports from Mexico could result in a $252 million (27%) revenue loss for American growers, thus posing great challenges to the sustainability of the declining US tomato industry

The U.S. Sweet Potato Market: Price Response and Impact of Supply Shocks

Sweet potatoes have become increasingly popular among consumers due to their health benefits, and, as a result, sweet potato production has been growing rapidly over the last decade in the United States. However, the industry is facing major challenges, including the risk of disease outbreaks and adverse weather events, which could potentially have a significant impact on the market. However, the economic literature on the sweet potato commodity is limited. This study models the U.S. sweet potato market price response to supply changes and derives elasticity estimates. This information is essential for understanding the sweet potato market and for simulating the impacts of potential supply shocks, given the challenges that the industry is facing. We found that prices are highly sensitive to supply. North Carolina, the largest sweet potato producer in the country, dominates the domestic market and exerts significantly larger influences on market prices than other producing states