Root Cause Analysis of Encumbrances Faced by Indigenous Building Contractors during Bidding in Nigeria

This paper intends to address one problem that is yet to be systematically examined. The focus is on the causal factors underlying the encumbrances faced by indigenous building contractors during bidding in Nigeria with a view to mitigating the hindrances and resultant effect of enhancing their business. To achieve this, data were collected via in-depth interviews and validated via secondary sources. Epistemology type of philosophical paradigm and random purposive sampling technique was adopted.Thematic analysis was adopted for the qualitative research and 2 themes were generated. Lagos State and Federal Capital Territory (FCT) were the locations covered. The participants were key practitioners (management and senior staff in procurement/estimating/tendering/bidding/contract administration department) in the contracting firms interviewed. A total of 16 firms were interviewed, eight from small and medium firms respectively. From the findings, all the participants agree that inability to bid for many projects, size of the project, location of the project, type of project, limited available personnel, the competition environment, lack of construction fund availability, and uncertainty of getting the job were identified as the major challenges facing indigenous building contractors in bidding performance. The study identified the root cause of each of the challenges and recommended that contractors should formulate right strategic plans, develop professionalism and innovative business strategies. Also, there is the need for building contractors to invest in talented staff, advanced construction technology, among others

Functional Dyadicity and Heterophilicity of Gene-Gene Interactions in Statistical Epistasis Networks

Background: The interaction effect among multiple genetic factors, i.e. epistasis, plays an important role in explaining susceptibility on common human diseases and phenotypic traits. The uncertainty over the number of genetic attributes involved in interactions poses great challenges in genetic association studies and calls for advanced bioinformatics methodologies. Network science has gained popularity in modeling genetic interactions thanks to its structural characterization of large numbers of entities and their complex relationships. However, little has been done on functionally interpreting statistically inferred epistatic interactions using networks. Results: In this study, we propose to characterize gene functional properties in the context of interaction network structure. We used Gene Ontology (GO) to functionally annotate genes as vertices in a statistical epistasis network, and quantitatively characterize the correlation between the distribution of gene functional properties and the network structure by measuring dyadicity and heterophilicity of each functional category in the network. These two parameters quantify whether genetic interactions tend to occur more frequently for genes from the same functional category, i.e. dyadic effect, or more frequently for genes from across different functional categories, i.e. heterophilic effect. Conclusions: By applying this framework to a population-based bladder cancer dataset, we were able to identify several GO categories that have significant dyadicity or heterophilicity associated with bladder cancer susceptibility. Thus, our informatics framework suggests a new methodology for embedding functional analysis in network modeling of statistical epistasis in genetic association studies

Genomic and proteomic profiling of responses to toxic metals in human lung cells.

Examining global effects of toxic metals on gene expression can be useful for elucidating patterns of biological response, discovering underlying mechanisms of toxicity, and identifying candidate metal-specific genetic markers of exposure and response. Using a 1,200 gene nylon array, we examined changes in gene expression following low-dose, acute exposures of cadmium, chromium, arsenic, nickel, or mitomycin C (MMC) in BEAS-2B human bronchial epithelial cells. Total RNA was isolated from cells exposed to 3 M Cd(II) (as cadmium chloride), 10 M Cr(VI) (as sodium dichromate), 3 g/cm2 Ni(II) (as nickel subsulfide), 5 M or 50 M As(III) (as sodium arsenite), or 1 M MMC for 4 hr. Expression changes were verified at the protein level for several genes. Only a small subset of genes was differentially expressed in response to each agent: Cd, Cr, Ni, As (5 M), As (50 M), and MMC each differentially altered the expression of 25, 44, 31, 110, 65, and 16 individual genes, respectively. Few genes were commonly expressed among the various treatments. Only one gene was altered in response to all four metals (hsp90), and no gene overlapped among all five treatments. We also compared low-dose (5 M, noncytotoxic) and high-dose (50 M, cytotoxic) arsenic treatments, which surprisingly, affected expression of almost completely nonoverlapping subsets of genes, suggesting a threshold switch from a survival-based biological response at low doses to a death response at high doses

Detecting Gene-Gene Interactions Using a Permutation-Based Random Forest Method

Identifying gene-gene interactions is essential to understand disease susceptibility and to detect genetic architectures underlying complex diseases. Here, we aimed at developing a permutation-based methodology relying on a machine learning method, random forest (RF), to detect gene-gene interactions. Our approach called permuted random forest (pRF) which identified the top interacting single nucleotide polymorphism (SNP) pairs by estimating how much the power of a random forest classification model is influenced by removing pairwise interactions

A neuronal network of mitochondrial dynamics regulates metastasis.

The role of mitochondria in cancer is controversial. Using a genome-wide shRNA screen, we now show that tumours reprogram a network of mitochondrial dynamics operative in neurons, including syntaphilin (SNPH), kinesin KIF5B and GTPase Miro1/2 to localize mitochondria to the cortical cytoskeleton and power the membrane machinery of cell movements. When expressed in tumours, SNPH inhibits the speed and distance travelled by individual mitochondria, suppresses organelle dynamics, and blocks chemotaxis and metastasis, in vivo. Tumour progression in humans is associated with downregulation or loss of SNPH, which correlates with shortened patient survival, increased mitochondrial trafficking to the cortical cytoskeleton, greater membrane dynamics and heightened cell invasion. Therefore, a SNPH network regulates metastatic competence and may provide a therapeutic target in cancer

Drinking-Water Arsenic Exposure Modulates Gene Expression in Human Lymphocytes from a U.S. Population

Background: Arsenic exposure impairs development and can lead to cancer, cardiovascular disease, and diabetes. The mechanism underlying these effects remains unknown. Primarily because of geologic sources of contamination, drinking-water arsenic levels are above the current recommended maximum contaminant level of 10 μg/L in the northeastern, western, and north central regions of the United States. Objectives: We investigated the effects of arsenic exposure, defined by internal biomarkers at levels relevant to the United States and similarly exposed populations, on gene expression. Methods: We conducted separate Affymetrix microarray-based genomewide analyses of expression patterns. Peripheral blood lymphocyte samples from 21 controls interviewed (1999–2002) as part of a case–control study in New Hampshire were selected based on high- versus low-level arsenic exposure levels. Results: The biologic functions of the transcripts that showed statistically significant abundance differences between high- and low-arsenic exposure groups included an overrepresentation of genes involved in defense response, immune function, cell growth, apoptosis, regulation of cell cycle, T-cell receptor signaling pathway, and diabetes. Notably, the high-arsenic exposure group exhibited higher levels of several killer cell immunoglobulin-like receptors that inhibit natural killer cell activity. Conclusions: These findings define biologic changes that occur with chronic arsenic exposure in humans and provide leads and potential targets for understanding and monitoring the pathogenesis of arsenic-induced diseases

Drinking-Water Arsenic Exposure Modulates Gene Expression in Human Lymphocytes from a U.S. Population

Background: Arsenic exposure impairs development and can lead to cancer, cardiovascular disease, and diabetes. The mechanism underlying these effects remains unknown. Primarily because of geologic sources of contamination, drinking-water arsenic levels are above the current recommended maximum contaminant level of 10 μg/L in the northeastern, western, and north central regions of the United States. Objectives: We investigated the effects of arsenic exposure, defined by internal biomarkers at levels relevant to the United States and similarly exposed populations, on gene expression. Methods: We conducted separate Affymetrix microarray-based genomewide analyses of expression patterns. Peripheral blood lymphocyte samples from 21 controls interviewed (1999–2002) as part of a case–control study in New Hampshire were selected based on high- versus low-level arsenic exposure levels. Results: The biologic functions of the transcripts that showed statistically significant abundance differences between high- and low-arsenic exposure groups included an overrepresentation of genes involved in defense response, immune function, cell growth, apoptosis, regulation of cell cycle, T-cell receptor signaling pathway, and diabetes. Notably, the high-arsenic exposure group exhibited higher levels of several killer cell immunoglobulin-like receptors that inhibit natural killer cell activity. Conclusions: These findings define biologic changes that occur with chronic arsenic exposure in humans and provide leads and potential targets for understanding and monitoring the pathogenesis of arsenic-induced diseases

Genetic Population Structure Analysis in New Hampshire Reveals Eastern European Ancestry

Genetic structure due to ancestry has been well documented among many divergent human populations. However, the ability to associate ancestry with genetic substructure without using supervised clustering has not been explored in more presumably homogeneous and admixed US populations. The goal of this study was to determine if genetic structure could be detected in a United States population from a single state where the individuals have mixed European ancestry. Using Bayesian clustering with a set of 960 single nucleotide polymorphisms (SNPs) we found evidence of population stratification in 864 individuals from New Hampshire that can be used to differentiate the population into six distinct genetic subgroups. We then correlated self-reported ancestry of the individuals with the Bayesian clustering results. Finnish and Russian/Polish/ Lithuanian ancestries were most notably found to be associated with genetic substructure. The ancestral results were further explained and substantiated using New Hampshire census data from 1870 to 1930 when the largest waves of European immigrants came to the area. We also discerned distinct patterns of linkage disequilibrium (LD) between the genetic groups in the growth hormone receptor gene (GHR). To our knowledge, this is the first time such an investigation has uncovered a strong link between genetic structure and ancestry in what would otherwise be considered a homogenous US population

Lung Cancer in a U.S. Population with Low to Moderate Arsenic Exposure

BackgroundLittle is known about the carcinogenic potential of arsenic in areas with low to moderate concentrations of arsenic (< 100 microg/L) in drinking water.ObjectivesWe examined associations between arsenic and lung cancer.MethodsA population-based case-control study of primary incident lung cancer was conducted in 10 counties in two U.S. states, New Hampshire and Vermont. The study included 223 lung cancer cases and 238 controls, each of whom provided toenail clippings for arsenic exposure measurement by inductively coupled-plasma mass spectrometry. We estimated odds ratios (ORs) of the association between arsenic exposure and lung cancer using unconditional logistic regression with adjustment for potential confounders (age, sex, race/ethnicity, smoking pack-years, education, body mass index, fish servings per week, and toenail selenium level).ResultsArsenic exposure was associated with small-cell and squamous-cell carcinoma of the lung [OR = 2.75; 95% confidence interval (CI), 1.00-7.57] for toenail arsenic concentration > or = 0.114 microg/g, versus < 0.05 microg/g. A history of lung disease (bronchitis, chronic obstructive pulmonary disease, or fibrosis) was positively associated with lung cancer (OR = 2.86; 95% CI, 1.39-5.91). We also observed an elevated risk of lung cancer among participants with a history of lung disease and toenail arsenic > or = 0.05 microg/g (OR = 4.78; 95% CI, 1.87-12.2) than among individuals with low toenail arsenic and no history of lung disease.ConclusionAlthough this study supports the possibility of an increased risk of specific lung cancer histologic types at lower levels of arsenic exposure, we recommend large-scale population-based studies