Implications of Mexican Health Care Reform on the Health Coverage of Nonmigrants and Returning Migrants

Objectives. To assess health coverage among Mexicans with US migration experience, before and after the implementation of Mexico’s universal health care program, Seguro Popular

Uninsured migrants: Health insurance coverage and access to care among Mexican return migrants

Background: Despite an expansive body of research on health and access to medical care among Mexican immigrants in the United States, research on return migrants focuses primarily on their labor market mobility and contributions to local development. Objective: Motivated by recent scholarship that documents poor mental and physical health among Mexican return migrants, this study investigates return migrants' health insurance coverage and access to medical care. Methods: I use descriptive and multivariate techniques to analyze data from the 2009 and 2014 rounds of Mexico's National Survey of Demographic Dynamics (ENADID, combined n=632,678). Results: Analyses reveal a large and persistent gap between recent return migrants and non-migrants, despite rising overall health coverage in Mexico. Multivariate analyses suggest that unemployment among recent arrivals contributes to their lack of insurance. Relative to non-migrants, recently returned migrants rely disproportionately on private clinics, pharmacies, self-medication, or have no regular source of care. Mediation analysis suggests that returnees' high rate of uninsurance contributes to their inadequate access to care. Conclusion: This study reveals limited access to medical care among the growing population of Mexican return migrants, highlighting the need for targeted policies to facilitate successful reintegration and ensure access to vital resources such as health care

E-BioFlow: Different Perspectives on Scientific Workflows

We introduce a new type of workflow design system called\ud e-BioFlow and illustrate it by means of a simple sequence alignment workflow. E-BioFlow, intended to model advanced scientific workflows, enables the user to model a workflow from three different but strongly coupled perspectives: the control flow perspective, the data flow perspective, and the resource perspective. All three perspectives are of\ud equal importance, but workflow designers from different domains prefer different perspectives as entry points for their design, and a single workflow designer may prefer different perspectives in different stages of workflow design. Each perspective provides its own type of information, visualisation and support for validation. Combining these three perspectives in a single application provides a new and flexible way of modelling workflows

Change in Nutritional Status Modulates the Abundance of Critical Pre-initiation Intermediate Complexes During Translation Initiation \u3cem\u3ein Vivo\u3c/em\u3e

In eukaryotic translation initiation, eIF2∙GTP–Met-tRNAiMet ternary complex (TC) interacts with eIF3–eIF1–eIF5 complex to form the multifactor complex (MFC), while eIF2∙GDP associates with eIF2B for guanine nucleotide exchange. Gcn2p phosphorylates eIF2 to inhibit eIF2B. Here we evaluate the abundance of eIFs and their pre-initiation intermediate complexes in gcn2 deletion mutant grown under different conditions. We show that ribosomes are three times as abundant as eIF1, eIF2 and eIF5, while eIF3 is half as abundant as the latter three and hence, the limiting component in MFC formation. By quantitative immunoprecipitation, we estimate that ∼ 15% of the cellular eIF2 is found in TC during rapid growth in a complex rich medium. Most of the TC is found in MFC, and important, ∼ 40% of the total eIF2 is associated with eIF5 but lacks tRNAiMet. When the gcn2Δ mutant grows less rapidly in a defined complete medium, TC abundance increases threefold without altering the abundance of each individual factor. Interestingly, the TC increase is suppressed by eIF5 overexpression and Gcn2p expression. Thus, eIF2B-catalyzed TC formation appears to be fine-tuned by eIF2 phosphorylation and the novel eIF2/eIF5 complex lacking tRNAiMet

ExpertiSZe, a tool for determining the effects of social security legislation

Social security legislation plays an important role in the Dutch society. In view of this, the effects of social security legislation have to be analysed carefully before new legislation can be made. Due to the growing complexity of legislation on the social security domain, this analysis has become a demanding task. ExpertiSZe is a knowledge-based system developed to support the process of analysing juridical and socio-economic effects of social security legislation. The ExpertiSZe system consists of three modules: a consultation module, a consistency module and a simulation module. These modules, which all work on the basis of the same rule-based model, provide the legislator with more insight into the impact of legislation. This article describes the potential of ExpertiSZe to support the analysis of effects of legislation

Normalisation to Blood Activity Is Required for the Accurate Quantification of Na/I Symporter Ectopic Expression by SPECT/CT in Individual Subjects

The utilisation of the Na/I symporter (NIS) and associated radiotracers as a reporter system for imaging gene expression is now reaching the clinical setting in cancer gene therapy applications. However, a formal assessment of the methodology in terms of normalisation of the data still remains to be performed, particularly in the context of the assessment of activities in individual subjects in longitudinal studies. In this context, we administered to mice a recombinant, replication-incompetent adenovirus encoding rat NIS, or a human colorectal carcinoma cell line (HT29) encoding mouse NIS. We used 99mTc pertechnetate as a radiotracer for SPECT/CT imaging to determine the pattern of ectopic NIS expression in longitudinal kinetic studies. Some animals of the cohort were culled and NIS expression was measured by quantitative RT-PCR and immunohistochemistry. The radioactive content of some liver biopsies was also measured ex vivo. Our results show that in longitudinal studies involving datasets taken from individual mice, the presentation of non-normalised data (activity expressed as %ID/g or %ID/cc) leads to ‘noisy’, and sometimes incoherent, results. This variability is due to the fact that the blood pertechnetate concentration can vary up to three-fold from day to day. Normalisation of these data with blood activities corrects for these inconsistencies. We advocate that, blood pertechnetate activity should be determined and used to normalise the activity measured in the organ/region of interest that expresses NIS ectopically. Considering that NIS imaging has already reached the clinical setting in the context of cancer gene therapy, this normalisation may be essential in order to obtain accurate and predictive information in future longitudinal clinical studies in biotherapy

A genome-wide scan for common alleles affecting risk for autism

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C