Sequence context analysis of 8.2 million single nucleotide polymorphisms in the human genome

We analyzed n-mers (n=3-8) in the local environment of 8,249,446 human SNPs and compared their distribution with that in the genome reference sequences. The results revealed that the short sequences, which contained at least one CpG dinucleotide, occurred

Amplified immunoassay of human IgG using real-time biomolecular interaction analysis (BIA) technology

An automated biomolecular interaction analysis instrument (BI-Acore) based on surface plasmon resonance (SPR) has been used to determine human immunoglobulin G (IgG) in real time. Polyclonal anti-human IgG antibody was covalently immobilized to a carboxymethyldextran modified gold film surface. The samples of human IgG prepared in HBS buffer were poured over the immobilized surface. The signal amplification antibody was applied to amplify the response signal. After each measurement, the surface was regenerated with 0.1 mol/L H3PO4. The assay was rapid, requiring only 30 min for antibody immobilization and 20 min for each subsequent process of immune binding, antibody amplification and regeneration. The antibody immobilized surface had good response to human IgG in the range of 0.12-60 nmol/L with a detection limit of 60 pmol/L. The same antibody immobilized surface could be used for more than 110 cycles of binding, amplification and regeneration. The results demonstrate that the sensitivity, specificity and reproducibility of amplified immunoassay using real-time BIA technology are satisfactory.

Fractionation and analysis of Artemisia capillaris Thunb. by affinity chromatography with human serum albumin as stationary phase

A method for the screening and analysis of biologically active compounds in traditional Chinese medicine is proposed. Affinity chromatography using a human serum albumin (HSA) stationary phase was applied to separate and analyze the bioactive compounds from Artemisia capillaris Thunb. Five major peaks and several minor peaks were resolved based on their affinity to HSA, two of them were identified as scoparone (SCO, 6,7-dimethoxycoumarin) and capillarisin (CAP). CAP shows a much higher affinity to HSA than SCO. The effects of acetonitrile concentration, eluent pH, phosphate concentration and temperature on the retention behaviors of several major active components were also investigated, and it was found that hydrophobicity and eluent pH play major roles in changing retention values. The results demonstrate that the affinity chromatography with a HSA stationary phase is an effective way for analyzing and screening biologically active compounds in traditional Chinese medicine. (C) 2000 Elsevier Science B.V. All rights reserved.

Human plasma proteome analysis by multidimensional chromatography prefractionation and linear ion trap mass spectrometry identification

A resurgence of interest in the human plasma proteome has occurred in recent years because it holds great promise of revolution in disease diagnosis and therapeutic monitoring. As one of the most powerful separation techniques, multidimensional liquid chromatography has attracted extensive attention, but most published works have focused on the fractionation of tryptic peptides. In this study, proteins from human plasma were prefractionated by online sequential strong cation exchange chromatography and reversed-phase chromatography. The resulting 30 samples were individually digested by trypsin, and analyzed by capillary reversed-phase liquid chromatography coupled with linear ion trap mass spectrometry. After meeting stringent criteria, a total of 1292 distinct proteins were successfully identified in our work, among which, some proteins known to be present in serum in < 10 ng/mL were detected. Compared with other works in published literatures, this analysis offered a more full-scale list of the plasma proteome. Considering our strategy allows high throughput of protein identification in serum, the prefractionation of proteins before MS analysis is a simple and effective method to facilitate human plasma proteome research.

Exploring human resource development: a level of analysis approach.

Levels of analysis perform an important function in framing research and practice in human resource development (HRD). The purpose of this paper is to examine the concept of HRD from the individual, organizational and community/societal levels of analysis. The paper highlights both the distinctiveness and usefulness of each level of analysis, identifies tensions within and between them, and outlines differences in underpinning assumptions, characteristics of HRD provision and delivery of HRD interventions. By adopting this approach, the paper draws attention to variations in meaning, intent, content and practice with implications for developing both the theory and practice of HRD.

Functional metagenomic analysis of the human gut microbiome to identify novel salt tolerance genes

The ability to adapt to and respond to increases in external osmolarity is an important characteristic that enables bacteria to survive and proliferate in different environmental niches. When challenged with increased osmolarity, due to sodium chloride (NaCl) for example, bacteria elicit a phased response; firstly via uptake of potassium (K+), which is known as the primary response. This primary response is followed by the secondary response which is characterised by the synthesis or uptake of compatible solutes (osmoprotectants). The overall osmotic stress response is much broader however, involving many diverse cellular systems and processes. These ancillary mechanisms are arguably more interesting and give a more complete view of the osmotic stress response. The aim of this thesis was to identify novel genetic loci from the human gut microbiota that confer increased tolerance to osmotic stress using a functional metagenomic approach. Functional metagenomics is a powerful tool that enables the identification of novel genes from as yet uncultured bacteria from diverse environments through cloning, heterologous expression and phenotypic identification of a desired trait. Functional metagenomics does not rely on any previous sequence information to known genes and can therefore enable the discovery of completely novel genes and assign functions to new or known genes. Using a functional metagenomic approach, we have assigned a novel function to previously annotated genes; murB, mazG and galE, as well as a putative brp/blh family beta-carotene 15,15’-monooxygenase. Finally, we report the identification of a completely novel salt tolerance determinant with no current known homologues in the databases. Overall the genes identified originate from diverse taxonomic and phylogenetic groups commonly found in the human gastrointestinal (GI) tract, such as Collinsella and Eggerthella, Akkermansia and Bacteroides from the phyla Actinobacteria, Verrucomicrobia and Bacteroidetes, respectively. In addition, a number of the genes appear to have been acquired via lateral gene transfer and/or encoded on a prophage. To our knowledge, this thesis represents the first investigation to identify novel genes from the human gut microbiota involved in the bacterial osmotic stress response.

Latent factor analysis to discover pathway-associated putative segmental aneuploidies in human cancers.

Tumor microenvironmental stresses, such as hypoxia and lactic acidosis, play important roles in tumor progression. Although gene signatures reflecting the influence of these stresses are powerful approaches to link expression with phenotypes, they do not fully reflect the complexity of human cancers. Here, we describe the use of latent factor models to further dissect the stress gene signatures in a breast cancer expression dataset. The genes in these latent factors are coordinately expressed in tumors and depict distinct, interacting components of the biological processes. The genes in several latent factors are highly enriched in chromosomal locations. When these factors are analyzed in independent datasets with gene expression and array CGH data, the expression values of these factors are highly correlated with copy number alterations (CNAs) of the corresponding BAC clones in both the cell lines and tumors. Therefore, variation in the expression of these pathway-associated factors is at least partially caused by variation in gene dosage and CNAs among breast cancers. We have also found the expression of two latent factors without any chromosomal enrichment is highly associated with 12q CNA, likely an instance of "trans"-variations in which CNA leads to the variations in gene expression outside of the CNA region. In addition, we have found that factor 26 (1q CNA) is negatively correlated with HIF-1alpha protein and hypoxia pathways in breast tumors and cell lines. This agrees with, and for the first time links, known good prognosis associated with both a low hypoxia signature and the presence of CNA in this region. Taken together, these results suggest the possibility that tumor segmental aneuploidy makes significant contributions to variation in the lactic acidosis/hypoxia gene signatures in human cancers and demonstrate that latent factor analysis is a powerful means to uncover such a linkage.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

An analysis of human behaviour during aircraft evacuation situations using the AASK v3.0 database

The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes recent developments with the database leading to the development of AASK v3.0. These include significantly increasing the number of passenger accounts in the database, the introduction of cabin crew accounts, the introduction of fatality information, improved functionality through the seat plan viewer utility and improved ease of access to the database via the internet. In addition, the paper demonstrates the use of the database by investigating a number of important issues associated with aircraft evacuation. These include issues associated with social bonding and evacuation, the relationship between the number of crew and evacuation efficiency, frequency of exit/slide failures in accidents and exploring possible relationships between seating location and chances of survival. Finally, the passenger behavioural trends described in analysis undertaken with the earlier database are confirmed with the wider data set.

An analysis of human behaviour during the WTC disaster of 9/11 based on published survivor accounts

This paper presents an analysis of survivor experiences from the World Trade Centre (WTC) evacuation of 11 September 2001. The experiences were collected from published accounts appearing in the print and electronic mass media and are stored in a relational database specifically developed for this purpose.

An Analysis of Human Behavior during Evacuation

The World Trade Center Evacuation: The evacuation of the WTC complex represents one of the largest full-scale evacuations of people in modern times.

Investigation of the permeation of model formulations and a commercial ibuprofen formulation in Carbosil® and human skin using ATR-FTIR and multivariate spectral analysis

The purpose of the present study was to use attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) and target factor analysis (TFA) to investigate the permeation of model drugs and formulation components through Carbosil® membrane and human skin. Diffusion studies of saturated solutions in 50:50 water/ethanol of methyl paraben (MP), ibuprofen (IBU) and caffeine (CF) were performed on Carbosil® membrane. The spectroscopic data were analysed by target factor analysis, and evolution profiles of the signal for each component (i.e. the drug, water, ethanol and membrane) over time were obtained. Results showed that the data were successfully deconvoluted as correlations between factors from the data and reference spectra of the components, were above 0.8 in all cases. Good reproducibility over three runs for the evolution profiles was obtained. From the evolution profiles it was observed that water diffused better through the Carbosil® membrane than ethanol, confirming the hydrophilic properties of the Carbosil® membrane used. IBU diffused slower compared with MP and CF. The evolution profile of CF was very similar to that of water, probably because of the high solubility of CF in water, indicating that both compounds are diffusing concurrently. The second part of the work involved a study of the evolution profiles of the components of a commercial topical gel containing 5% (w/w) of ibuprofen as it permeated through human skin. Although the system was much more complex, data were still successfully deconvoluted and the different components of the formulation identified except for benzyl alcohol which might be attributed to the low concentrations of benzyl alcohol used in topical formulations. (C) 2009 Elsevier B.V. All rights reserved.