Importance of the First Postoperative Year in the Prognosis of Elderly Colorectal Cancer Patients

Surgical oncolog

The absence of MyD88 has no effect on the induction of alternatively activated macrophage during Fasciola hepatica infection

<p>Abstract</p> <p>Background</p> <p>Alternatively activated macrophages (AAMϕ) play important roles in allergies and responses to parasitic infections. However, whether signaling through toll-like receptors (TLRs) plays any role in AAMϕ induction when young <it>Fasciola hepatica </it>penetrates the liver capsule and migrates through the liver tissue is still unclear.</p> <p>Results</p> <p>The data show that the lack of myeloid differentiation factor 88 (MyD88) has no effect on the AAMϕ derived from the bone marrow (BMMϕ) <it>in vitro </it>and does not impair the mRNA expression of arginase-1, resistin-like molecule (RELMα), and Ym1 in BMMϕs. The Th2 cytokine production bias in splenocytes was not significantly altered in <it>F. hepatica</it>-infected mice in the absence of MyD88 <it>in vitro </it>and in the pleural cavity lavage <it>in vivo</it>. In addition, MyD88-deficiency has no effect on the arginase production of the <it>F. hepatica </it>elicited macrophages (Fe Mϕs), production of RELMα and Ym1 proteins and mRNA expression of Ym1 and RELMα of macrophages in the peritoneal cavity 6 weeks post <it>F. hepatica </it>infection.</p> <p>Conclusions</p> <p>The absence of MyD88 has no effect on presence of AAMϕ 6 weeks post <it>F. hepatica </it>infection.</p

The National Longitudinal Study of Adolescent to Adult Health (Add Health) Sibling Pairs Genome-Wide Data

Here we provide a detailed description of the genome-wide information available on the National Longitudinal Study of Adolescent to Adult Health (Add Health) sibling pair subsample (Harris et al., 2012). A total of 2020 samples were genotyped (including duplicates) arising from 1946 Add Health individuals from the sibling pairs subsample. After various steps for quality control (QC) and quality assurance (QA), we have high quality genome-wide data available on 1,888 individuals. In this report, we first highlight theQC and QA steps that were taken to prune the data of poorly performing samples and genetic markers. We further estimate the pairwise biological relationships using genome-wide data and compare those estimates to the assumed relationships in Add Health. Additionally, using genome-wide data from knownregional reference populations from Europe, West Africa, North and South America, Japan and China, weestimate the relative genetic ancestry of the respondents. Finally, rather than conducting a traditional cross-sectional genome-wide association study (GWAS) of body mass index (BMI), we opted to utilize the extensivepublicly available genome-wide information to conduct a weighted genome-wide association study (GWAS) of longitudinal BMI while accounting for both family and ethnic variation