Results show that morphology developed during the process influences the diffusion of water molecules through the polymer matrix. Liproxstatin-1 inhibitor In particular, a direct influence of crystalline degree on the sorption and diffusion parameters was identified. (C) 2010 Wiley Periodicals, Inc. J Appl Polym Sci 117: 2831-2838, 2010″
“Fruits and nuts from the North and Northeast regions of Brazil were collected to determine their phytosterol and tocopherol content. The species studied were Cotia nut (Aptandra spruceana M.), Brazil nut (Bertholletia excelsa H.B.K.), Mucaja (Couma rigida M.), Red
Acai (Euterpe oleracea M.), Inaja (Maximiliana maripa D.), Jenipapo (Genipa Americana L), Buriti (Mauritia flexuosa L) and Uxi (Endopleura uchi C.). Phytosterols were analyzed by GC-FID using beta-cholestanol as an internal standard, while tocopherols were determined by RP-HPLC-DAD. The pulps of Mucaja (26-236 mg 100 g(-1)), Inaja (119-285 mg 100 g(-1)) and Jenipapo (216 mg 100 g(-1)) showed the highest total phytosterol contents. Considering alpha-tocopherol equivalents, the pulps of Buriti (346.72 mu g g(-1)) and Uxi (200.92 mu g g(-1)) contained the highest vitamin E activity. Therefore, the results indicate that these fruits Selleckchem Galardin and nuts have great potential to be cultivated and marketed as alternative dietary sources for these bioactive compounds. (C) 2010 Elsevier Ltd. All rights reserved.”
“Background-
Fetal hemoglobin (HbF)
is the major modifier of the clinical course of sickle cell anemia. Its levels are highly heritable, and its interpersonal variability is modulated in part by 3 quantitative trait loci that affect HbF gene expression. Genome-wide association studies have identified single-nucleotide polymorphisms (SNPs) in these quantitative trait loci that are highly associated with HbF but explain only 10% to 12% of the variance of HbF. Combining SNPs into a genetic risk score can help to explain a larger amount of the variability of HbF level, but the challenge Rabusertib of this approach is to select the optimal number of SNPs to be included
in the genetic risk score.
Methods and Results-
We developed a collection of 14 models with genetic risk score composed of different numbers of SNPs and used the ensemble of these models to predict HbF in patients with sickle cell anemia. The models were trained in 841 patients with sickle cell anemia and were tested in 3 independent cohorts. The ensemble of 14 models explained 23.4% of the variability in HbF in the discovery cohort, whereas the correlation between predicted and observed HbF in the 3 independent cohorts ranged between 0.28 and 0.44. The models included SNPs in BCL11A, the HBS1L-MYB intergenic region, and the site of the HBB gene cluster, quantitative trait loci previously associated with HbF.
Conclusions-
An ensemble of 14 genetic risk models can predict HbF levels with accuracy between 0.28 and 0.44, and the approach may also prove useful in other applications.