Lead exposure in adult males in urban Transvaal Province, South Africa during the apartheid era

Human exposure to lead is a substantial public health hazard worldwide and is particularly problematic in the Republic of South Africa given the country’s late cessation of leaded petrol. Lead exposure is associated with a number of serious health issues and diseases including developmental and cognitive deficiency, hypertension and heart disease. Understanding the distribution of lifetime lead burden within a given population is critical for reducing exposure rates. Femoral bone from 101 deceased adult males living in urban Transvaal Province (now Gauteng Province), South Africa between 1960 and 1998 were analyzed for lead concentration by Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Of the 72 black and 29 white individuals sampled, chronic lead exposure was apparent in nearly all individuals. White males showed significantly higher median bone lead concentration (ME = 10.04 µg·g−1), than black males (ME = 3.80 µg·g−1) despite higher socioeconomic status. Bone lead concentration covaries significantly, though weakly, with individual age. There was no significant temporal trend in bone lead concentration. These results indicate that long-term low to moderate lead exposure is the historical norm among South African males. Unexpectedly, this research indicates that white males in the sample population were more highly exposed to lead

Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers

Background: At the current price, the use of high-density single nucleotide polymorphisms (SNP) genotyping assays in genomic selection of dairy cattle is limited to applications involving elite sires and dams. The objective of this study was to evaluate the use of low-density assays to predict direct genomic value (DGV) on five milk production traits, an overall conformation trait, a survival index, and two profit index traits (APR, ASI). Methods. Dense SNP genotypes were available for 42,576 SNP for 2,114 Holstein bulls and 510 cows. A subset of 1,847 bulls born between 1955 and 2004 was used as a training set to fit models with various sets of pre-selected SNP. A group of 297 bulls born between 2001 and 2004 and all cows born between 1992 and 2004 were used to evaluate the accuracy of DGV prediction. Ridge regression (RR) and partial least squares regression (PLSR) were used to derive prediction equations and to rank SNP based on the absolute value of the regression coefficients. Four alternative strategies were applied to select subset of SNP, namely: subsets of the highest ranked SNP for each individual trait, or a single subset of evenly spaced SNP, where SNP were selected based on their rank for ASI, APR or minor allele frequency within intervals of approximately equal length. Results: RR and PLSR performed very similarly to predict DGV, with PLSR performing better for low-density assays and RR for higher-density SNP sets. When using all SNP, DGV predictions for production traits, which have a higher heritability, were more accurate (0.52-0.64) than for survival (0.19-0.20), which has a low heritability. The gain in accuracy using subsets that included the highest ranked SNP for each trait was marginal (5-6%) over a common set of evenly spaced SNP when at least 3,000 SNP were used. Subsets containing 3,000 SNP provided more than 90% of the accuracy that could be achieved with a high-density assay for cows, and 80% of the high-density assay for young bulls. Conclusions: Accurate genomic evaluation of the broader bull and cow population can be achieved with a single genotyping assays containing ∼ 3,000 to 5,000 evenly spaced SNP

Localized-Statistical Quantification of Human Serum Proteome Associated with Type 2 Diabetes

BACKGROUND: Recent advances in proteomics have shed light to discover serum proteins or peptides as biomarkers for tracking the progression of diabetes as well as understanding molecular mechanisms of the disease. RESULTS: In this work, human serum of non-diabetic and diabetic cohorts was analyzed by proteomic approach. To analyze total 1377 high-confident serum-proteins, we developed a computing strategy called localized statistics of protein abundance distribution (LSPAD) to calculate a significant bias of a particular protein-abundance between these two cohorts. As a result, 68 proteins were found significantly over-represented in the diabetic serum (p<0.01). In addition, a pathway-associated analysis was developed to obtain the overall pathway bias associated with type 2 diabetes, from which the significant over-representation of complement system associated with type 2 diabetes was uncovered. Moreover, an up-stream activator of complement pathway, ficolin-3, was observed over-represented in the serum of type 2 diabetic patients, which was further validated with statistic significance (p = 0.012) with more clinical samples. CONCLUSIONS: The developed LSPAD approach is well fit for analyzing proteomic data derived from biological complex systems such as plasma proteome. With LSPAD, we disclosed the comprehensive distribution of the proteins associated with diabetes in different abundance levels and the involvement of ficolin-related complement activation in diabetes

Investigation of surface related leakage current in AlGaN/GaN High Electron Mobility Transistors

This paper reports the study of surface-related mechanisms to explain the high reverse leakage current observed in the in-house fabricated Si3N4 passivated AlGaN/GaN High Electron Mobility Transistors. We propose that the Si3N4/AlGaN interface in the un-gated regions provides an additional leakage path between the gate and source/drain and may constitute a large component of reverse current. This surface related leakage component of current exhibits both temperature and electric field dependence and its Arrhenius behavior has been experimentally verified using Conductance Deep Level Transient Spectroscopy and temperature dependent reverse leakage current measurements. A thin interfacial amorphous semiconductor layer formed due to inter diffusion at Si3N4/AlGaN interface has been presumed as the source for this surface related leakage. We, therefore, conclude that optimum Si3N4 deposition conditions and careful surface preparation prior to passivation can limit the extent of surface leakage and can thus vastly improve the device performance. (C) 2016 Elsevier B.V. All rights reserved

Comparison of PLS algorithms when number of objects is much larger than number of variables

High-dimensional data, Kernel matrix, Multicollinearity, Multiple linear regression, NIPALS, Partial least squares, SIMPLS,