33 research outputs found

    An Evaluation of exposures to respirable particulates, environmental PM2.5, PAHs and metal compounds in Western Australia

    Get PDF
    It has been well established that air pollution is associated with health impacts. This study investigated the relationship between exposure to air pollutants and potential biomarkers of health effects. The research project was conducted in 2 separate study locations and cohorts. Study 1: An Evaluation of Children’s Exposures to Respirable Particulates, Environmental PM2.5, PAHs and Metal Compounds in The South West of Western Australia. A cross sectional study to evaluate the exposures of children (n=18), and controls (n=15) to respirable particulates PAHs and metal compounds in the South West of Australia during 2011. Ambient particulate matter (PM2.5) samples were found to be significantly higher in Collie as compared to Dalyellup. However, personal PM2.5 concentrations between locations were not significantly different and both PAH and heavy metals were below the levels of detection. Urinary levels of 1-hydroxypyrene (1-OHpy) were below the level of detection. Copper, selenium and nickel were present in urine samples and these were not significantly different between locations, nor was there any correlation with residential areas within study locations. Urinary nickel concentrations were higher than expected for nonoccupational cohorts and although statistically insignificant, mean values of urinary nickel were highest for homes using gas as a fuel source. These data endorse current views that the reconstruction of PM2.5 exposures and related respiratory health effects based simply on the mass of airborne particulate matter alone is not sufficient in providing an insight to the respiratory health of susceptible subgroups such as children. The presence of certain urinary heavy metals suggests possible accumulation in participants via alternative routes of entry, probably a dietary source. Studies that rely purely on data accrued from ambient PM2.5 mass, and/or general health data might not detect or underestimate significant relationships between certain components of PM2.5. Study 2: Urinary levels of malondialdehyde and 8-deoxyguanosine as biomarkers of oxidative DNA damage induced by exposure to nickel and cobalt in metal refinery workers. Metal mining and refinery workers in Australia have the potential to be occupationally exposed to quantities of heavy metals that may be associated with health impacts affecting major organ and immune systems. Current regulatory and internal company policies and guidelines require regular monitoring of occupational exposures of employees through a combination of air borne sampling as well as biological monitoring for heavy metals. Toxic levels of heavy metals accumulated in the body have been shown to elicit inflammatory responses linked to exacerbated health effects impacting the respiratory, cardiovascular and nervous systems. There are many studies that have established a significant link between heavy metal exposure and increased oxidative stress. In light of these observations, this study investigated urinary levels of nickel (Ni) and cobalt (Co) and Malondialdehyde (MDA) and 8-hydroxy-2’deoxyguanosine (8-OHdG) which are oxidative stress markers indicative of cellular and DNA damage. A positive correlation between urinary Ni and Co exposure and oxidative stress markers among refinery workers was established. This finding has implications for occupational health management as individual responses to exposures can now be identified. In addition to implementing a global mean air borne exposure standard, individual variation and sensitivity can be accommodated through the use of urinary oxidative stress marker

    Contourlet textual features: Improving the diagnosis of solitary pulmonary nodules in two dimensional ct images

    Get PDF
    Materials and Methods: A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data.Results: Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93.Objective: To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer. Copyright:Conclusion: Our results indicate that the combined contourlet textural features of solitary pulmonary nodules in CT images with patient profile information could potentially improve the diagnosis of lung cancer

    Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk

    Get PDF
    In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.Peer reviewe

    The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer

    Get PDF
    Abstract: Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors

    Screening for potential serum-based proteomic biomarkers for human type 2 diabetes mellitus using MALDI-TOF MS

    No full text
    Background Type 2 diabetes mellitus (T2DM) is a complex, pandemic disease contributing towards the global burden of health issues. To date, there are no simple clinical tests for the early detection of T2DM. Method To identify potential peptide biomarkers for such applications, 406 sera of T2DM patients (n = 206) and healthy controls (n = 200) are analyzed by using MALDI-TOF MS with a cross-sectional case-control design. Result Six peptides (peaks m/z 1452.9, 1692.8, 1946.0, 2115.1, 2211.0 and 4053.6) are identified as candidate biomarkers for T2DM. A diagnostic model constructed with six peptides is able to discriminate T2DM patients from healthy controls, with an accuracy of 82.20%, sensitivity of 82.50%, and specificity of 77.80% in the validation set. Peptide peaks m/z 1452.9 and 1692.8 are identified as fragments of the complement C3f, while peptide peaks m/z 1946.0, 2115.1, and 2211.0 are identified as the fragments of kininogen 1 isoform 1 precursor. Conclusion This study reinforces proteomic analyses as a potential technique for defining significant clinical peptide biomarkers, providing a simple and convenient diagnostic model for T2DM in clinical examination.
    corecore