Occupational exposure and markers of genetic damage, systemic inflammation and lung function: a Danish cross-sectional study among air force personnel

Air force ground crew personnel are potentially exposed to fuels and lubricants, as raw materials, vapours and combustion exhaust emissions, during operation and maintenance of aircrafts. This study investigated exposure levels and biomarkers of effects for employees at a Danish air force military base. We enrolled self-reported healthy and non-smoking employees (n = 79) and grouped them by exposure based on job function, considered to be potentially exposed (aircraft engineers, crew chiefs, fuel operators and munition specialists) or as reference group with minimal occupational exposure (avionics and office workers). We measured exposure levels to polycyclic aromatic hydrocarbons (PAHs) and organophosphate esters (OPEs) by silicone bands and skin wipes (PAHs only) as well as urinary excretion of PAH metabolites (OH-PAHs). Additionally, we assessed exposure levels of ultrafine particles (UFPs) in the breathing zone for specific job functions. As biomarkers of effect, we assessed lung function, plasma levels of acute phase inflammatory markers, and genetic damage levels in peripheral blood cells. Exposure levels of total PAHs, OPEs and OH-PAHs did not differ between exposure groups or job functions, with low correlations between PAHs in different matrices. Among the measured job functions, the UFP levels were higher for the crew chiefs. The exposure level of the PAH fluorene was significantly higher for the exposed group than the reference group (15.9 +/- 23.7 ng/g per 24 h vs 5.28 +/- 7.87 ng/g per 24 h, p = 0.007), as was the OPE triphenyl phosphate (305 +/- 606 vs 19.7 +/- 33.8 ng/g per 24 h, p = 0.011). The OPE tris(1, 3-dichlor-2-propyl)phosphate had a higher mean in the exposed group (60.7 +/- 135 ng/g per 24 h) compared to the reference group (8.89 +/- 15.7 ng/g per 24 h) but did not reach significance. No evidence of effects for biomarkers of systemic inflammation, genetic damage or lung function was found. Overall, our biomonitoring study show limited evidence of occupational exposure of air force ground crew personnel to UFPs, PAHs and OPEs. Furthermore, the OH-PAHs and the assessed biomarkers of early biological effects did not differ between exposed and reference groups

Assessing and selecting gene expression signals based upon the quality of the measured dynamics

<p>Abstract</p> <p>Background</p> <p>One of the challenges with modeling the temporal progression of biological signals is dealing with the effect of noise and the limited number of replicates at each time point. Given the rising interest in utilizing predictive mathematical models to describe the biological response of an organism or analysis such as clustering and gene ontology enrichment, it is important to determine whether the dynamic progression of the data has been accurately captured despite the limited number of replicates, such that one can have confidence that the results of the analysis are capturing important salient dynamic features.</p> <p>Results</p> <p>By pre-selecting genes based upon quality before the identification of differential expression via algorithm such as EDGE, it was found that the percentage of statistically enriched ontologies (p < .05) was improved. Furthermore, it was found that a majority of the genes found via the proposed technique were also selected via an EDGE selection though the reverse was not necessarily true. It was also found that improvements offered by the proposed algorithm are anti-correlated with improvements in the various microarray platforms and the number of replicates. This is illustrated by the fact that newer arrays and experiments with more replicates show less improvement when the filtering for quality is first run before the selection of differentially expressed genes. This suggests that the increase in the number of replicates as well as improvements in array technologies are increase the confidence one has in the dynamics obtained from the experiment.</p> <p>Conclusion</p> <p>We have developed an algorithm that quantifies the quality of temporal biological signal rather than whether the signal illustrates a significant change over the experimental time course. Because the use of these temporal signals, whether it is in mathematical modeling or clustering, focuses upon the entire time series, it is necessary to develop a method to quantify and select for signals which conform to this ideal. By doing this, we have demonstrated a marked and consistent improvement in the results of a clustering exercise over multiple experiments, microarray platforms, and experimental designs.</p

The role of parental achievement goals in predicting autonomy-supportive and controlling parenting

Although autonomy-supportive and controlling parenting are linked to numerous positive and negative child outcomes respectively, fewer studies have focused on their determinants. Drawing on achievement goal theory and self-determination theory, we propose that parental achievement goals (i.e., achievement goals that parents have for their children) can be mastery, performance-approach or performance-avoidance oriented and that types of goals predict mothers' tendency to adopt autonomy-supportive and controlling behaviors. A total of 67 mothers (aged 30-53 years) reported their goals for their adolescent (aged 13-16 years; 19.4 % girls), while their adolescent evaluated their mothers' behaviors. Hierarchical regression analyses showed that parental performance-approach goals predict more controlling parenting and prevent acknowledgement of feelings, one autonomy-supportive behavior. In addition, mothers who have mastery goals and who endorse performance-avoidance goals are less likely to use guilt-inducing criticisms. These findings were observed while controlling for the effect of maternal anxiety

Particulate air pollution and survival in a COPD cohort

<p>Abstract</p> <p>Background</p> <p>Several studies have shown cross-sectional associations between long term exposure to particulate air pollution and survival in general population or convenience cohorts. Less is known about susceptibility, or year to year changes in exposure. We investigated whether particles were associated with survival in a cohort of persons with COPD in 34 US cities, eliminating the usual cross-sectional exposure and treating PM₁₀as a within city time varying exposure.</p> <p>Methods</p> <p>Using hospital discharge data, we constructed a cohort of persons discharged alive with chronic obstructive pulmonary disease using Medicare data between 1985 and 1999. 12-month averages of PM₁₀were merged to the individual annual follow up in each city. We applied Cox's proportional hazard regression model in each city, with adjustment for individual risk factors.</p> <p>Results</p> <p>We found significant associations in the survival analyses for single year and multiple lag exposures, with a hazard ratio for mortality for an increase of 10 μg/m³PM₁₀over the previous 4 years of 1.22 (95% CI: 1.17–1.27).</p> <p>Conclusion</p> <p>Persons discharged alive for COPD have substantial mortality risks associated with exposure to particles. The risk is evident for exposure in the previous year, and higher in a 4 year distributed lag model. These risks are significantly greater than seen in time series analyses.</p

Difference-based clustering of short time-course microarray data with replicates

<p>Abstract</p> <p>Background</p> <p>There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically.</p> <p>Results</p> <p>We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods.</p> <p>Conclusions</p> <p>Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.</p

Acoustic Cues for Sound Source Distance and Azimuth in Rabbits, a Racquetball and a Rigid Spherical Model

There are numerous studies measuring the transfer functions representing signal transformation between a source and each ear canal, i.e., the head-related transfer functions (HRTFs), for various species. However, only a handful of these address the effects of sound source distance on HRTFs. This is the first study of HRTFs in the rabbit where the emphasis is on the effects of sound source distance and azimuth on HRTFs. With the rabbit placed in an anechoic chamber, we made acoustic measurements with miniature microphones placed deep in each ear canal to a sound source at different positions (10–160 cm distance, ±150° azimuth). The sound was a logarithmically swept broadband chirp. For comparisons, we also obtained the HRTFs from a racquetball and a computational model for a rigid sphere. We found that (1) the spectral shape of the HRTF in each ear changed with sound source location; (2) interaural level difference (ILD) increased with decreasing distance and with increasing frequency. Furthermore, ILDs can be substantial even at low frequencies when distance is close; and (3) interaural time difference (ITD) decreased with decreasing distance and generally increased with decreasing frequency. The observations in the rabbit were reproduced, in general, by those in the racquetball, albeit greater in magnitude in the rabbit. In the sphere model, the results were partly similar and partly different than those in the racquetball and the rabbit. These findings refute the common notions that ILD is negligible at low frequencies and that ITD is constant across frequency. These misconceptions became evident when distance-dependent changes were examined

Exon Array Analysis of Head and Neck Cancers Identifies a Hypoxia Related Splice Variant of LAMA3 Associated with a Poor Prognosis

The identification of alternatively spliced transcript variants specific to particular biological processes in tumours should increase our understanding of cancer. Hypoxia is an important factor in cancer biology, and associated splice variants may present new markers to help with planning treatment. A method was developed to analyse alternative splicing in exon array data, using probeset multiplicity to identify genes with changes in expression across their loci, and a combination of the splicing index and a new metric based on the variation of reliability weighted fold changes to detect changes in the splicing patterns. The approach was validated on a cancer/normal sample dataset in which alternative splicing events had been confirmed using RT-PCR. We then analysed ten head and neck squamous cell carcinomas using exon arrays and identified differentially expressed splice variants in five samples with high versus five with low levels of hypoxia-associated genes. The analysis identified a splice variant of LAMA3 (Laminin α 3), LAMA3-A, known to be involved in tumour cell invasion and progression. The full-length transcript of the gene (LAMA3-B) did not appear to be hypoxia-associated. The results were confirmed using qualitative RT-PCR. In a series of 59 prospectively collected head and neck tumours, expression of LAMA3-A had prognostic significance whereas LAMA3-B did not. This work illustrates the potential for alternatively spliced transcripts to act as biomarkers of disease prognosis with improved specificity for particular tissues or conditions over assays which do not discriminate between splice variants

Quantitative imaging of concentrated suspensions under flow

We review recent advances in imaging the flow of concentrated suspensions, focussing on the use of confocal microscopy to obtain time-resolved information on the single-particle level in these systems. After motivating the need for quantitative (confocal) imaging in suspension rheology, we briefly describe the particles, sample environments, microscopy tools and analysis algorithms needed to perform this kind of experiments. The second part of the review focusses on microscopic aspects of the flow of concentrated model hard-sphere-like suspensions, and the relation to non-linear rheological phenomena such as yielding, shear localization, wall slip and shear-induced ordering. Both Brownian and non-Brownian systems will be described. We show how quantitative imaging can improve our understanding of the connection between microscopic dynamics and bulk flow.Comment: Review on imaging hard-sphere suspensions, incl summary of methodology. Submitted for special volume 'High Solid Dispersions' ed. M. Cloitre, Vol. xx of 'Advances and Polymer Science' (Springer, Berlin, 2009); 22 pages, 16 fig

Signatures of Selection in Fusion Transcripts Resulting From Chromosomal Translocations in Human Cancer

BACKGROUND: The recurrence and non-random distribution of translocation breakpoints in human tumors are usually attributed to local sequence features present in the vicinity of the breakpoints. However, it has also been suggested that functional constraints might contribute to delimit the position of translocation breakpoints within the genes involved, but a quantitative analysis of such contribution has been lacking. METHODOLOGY: We have analyzed two well-known signatures of functional selection, such as reading-frame compatibility and non-random combinations of protein domains, on an extensive dataset of fusion proteins resulting from chromosomal translocations in cancer. CONCLUSIONS: Our data provide strong experimental support for the concept that the position of translocation breakpoints in the genome of cancer cells is determined, to a large extent, by the need to combine certain protein domains and to keep an intact reading frame in fusion transcripts. Additionally, the information that we have assembled affords a global view of the oncogenic mechanisms and domain architectures that are used by fusion proteins. This can be used to assess the functional impact of novel chromosomal translocations and to predict the position of breakpoints in the genes involved