[health Protection For Rural Workers: The Need To Standardize Techniques For Quantifying Dermal Exposure To Pesticides].

Quantification of dermal exposure to pesticides in rural workers, used in risk assessment, can be performed with different techniques such as patches or whole body evaluation. However, the wide variety of methods can jeopardize the process by producing disparate results, depending on the principles in sample collection. A critical review was thus performed on the main techniques for quantifying dermal exposure, calling attention to this issue and the need to establish a single methodology for quantification of dermal exposure in rural workers. Such harmonization of different techniques should help achieve safer and healthier working conditions. Techniques that can provide reliable exposure data are an essential first step towards avoiding harm to workers' health.

Microfluidic Paper-based Devices For Bioanalytical Applications.

Paper has become increasingly recognized as a very interesting substrate for the construction of microfluidic devices, with potential application in a variety of areas, including health diagnosis, environmental monitoring, immunoassays and food safety. The aim of this review is to present a short history of analytical systems constructed from paper, summarize the main advantages and disadvantages of fabrication techniques, exploit alternative methods of detection such as colorimetric, electrochemical, photoelectrochemical, chemiluminescence and electrochemiluminescence, as well as to take a closer look at the novel achievements in the field of bioanalysis published during the last 2 years. Finally, the future trends for production of such devices are discussed.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.