The NIEHS Superfund Research Program: 25 Years of Translational Research for Public Health

BACKGROUND: The Superfund Research Program (SRP) is an academically based, multidisciplinary, translational research program that for 25 years has sought scientific solutions to health and environmental problems associated with hazardous waste sites. SRP is coordinated by the National Institute of Environmental Health Sciences (NIEHS). It supports multi-project grants, undergraduate and postdoctoral training programs, individual research grants, and Small Business Innovation Research (SBIR) and Technology Transfer Research (STTR) grants. RESULTS: SRP has had many successes: discovery of arsenic\u27s toxicity to the developing human central nervous system; documentation of benzene toxicity to hematologic progenitor cells in human bone marrow; development of novel analytic techniques such as the luciferase expression assay and laser fragmentation fluorescence spectroscopy; demonstration that PCBs can cause developmental neurotoxicity at low levels and alter the genomic characteristics of sentinel animals; elucidation of the neurodevelopmental toxicity of organophosphate insecticides; documentation of links between antimicrobial agents and alterations in hormone response; discovery of biological mechanisms through which environmental chemicals may contribute to obesity, atherosclerosis, diabetes, and cancer; tracking the health and environmental effects of the attacks on the World Trade Center and Hurricane Katrina; and development of novel biological and engineering techniques to facilitate more efficient and lower-cost remediation of hazardous waste sites. CONCLUSION: SRP must continue to address the legacy of hazardous waste in the United States, respond to new issues caused by rapid advances in technology, and train the next generation of leaders in environmental health science while recognizing that most of the world\u27s worst toxic hot spots are now located in low- and middle-income countries

Visualisation tool for peptide fractionation data in proteomics: application to OFFGEL isoelectric focussing

<p>Abstract</p> <p>Background</p> <p>OFFGEL isoelectric focussing (IEF) has become a popular tool in proteomics to fractionate peptides or proteins. As a consequence there is a need for software solutions supporting data mining, interpretation and characterisation of experimental quality.</p> <p>Results</p> <p>We can assess performance characteristics of OFFGEL IEF peptide fractionation in proteomics by generating plots of the overall fractionation patterns and the pairwise comparisons of adjacent fractions.</p> <p>Conclusions</p> <p>A visualisation tool for peptide fractionation has been developed to support the evaluation of IEF data quality and can be implemented in proteomics research.</p

Inference with interference between units in an fMRI experiment of motor inhibition

An experimental unit is an opportunity to randomly apply or withhold a treatment. There is interference between units if the application of the treatment to one unit may also affect other units. In cognitive neuroscience, a common form of experiment presents a sequence of stimuli or requests for cognitive activity at random to each experimental subject and measures biological aspects of brain activity that follow these requests. Each subject is then many experimental units, and interference between units within an experimental subject is likely, in part because the stimuli follow one another quickly and in part because human subjects learn or become experienced or primed or bored as the experiment proceeds. We use a recent fMRI experiment concerned with the inhibition of motor activity to illustrate and further develop recently proposed methodology for inference in the presence of interference. A simulation evaluates the power of competing procedures.Comment: Published by Journal of the American Statistical Association at http://www.tandfonline.com/doi/full/10.1080/01621459.2012.655954 . R package cin (Causal Inference for Neuroscience) implementing the proposed method is freely available on CRAN at https://CRAN.R-project.org/package=ci

Simplicity in Visual Representation: A Semiotic Approach

Simplicity, as an ideal in the design of visual representations, has not received systematic attention. High-level guidelines are too general, and low-level guidelines too ad hoc, too numerous, and too often incompatible, to serve in a particular design situation. This paper reviews notions of visual simplicity in the literature within the analytical framework provided by Charles Morris' communication model, specifically, his trichotomy of communication levels—the syntactic, the semantic, and the pragmatic. Simplicity is ultimate ly shown to entail the adjudication of incompatibilities both within, and between, levels.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68281/2/10.1177_105065198700100103.pd

Using ELISPOT to Expose False Positive Skin Test Conversion in Tuberculosis Contacts

BACKGROUND: Repeat tuberculin skin tests may be false positive due to boosting of waned immunity to past mycobacterial exposure. We evaluated whether an ELISPOT test could identify tuberculosis (TB) contacts with boosting of immunity to non-tuberculous mycobacterial exposure. METHODOLOGY/PRINCIPAL FINDINGS: We conducted tuberculin and ELISPOT tests in 1665 TB contacts: 799 were tuberculin test negative and were offered a repeat test after three months. Those with tuberculin test conversion had an ELISPOT, chest X-ray and sputum analysis if appropriate. We compared converters with non-converters, assessed the probability of each of four combinations of ELISPOT results over the two time points and estimated boosting with adjustment for ELISPOT sensitivity and specificity. 704 (72%) contacts had a repeat tuberculin test; 176 (25%) had test conversion, which increased with exposure to a case (p = 0.002), increasing age (p = 0.0006) and BCG scar (p = 0.06). 114 tuberculin test converters had ELISPOT results: 16(14%) were recruitment positive/follow-up positive, 9 (8%) positive/negative, 34 (30%) negative/positive, and 55 (48%) were negative/negative. There was a significant non-linear effect of age for ELISPOT results in skin test converters (p = 0.038). Estimates of boosting ranged from 32%–41% of skin test converters with increasing age. Three converters were diagnosed with TB, two had ELISPOT results: both were positive, including one at recruitment. CONCLUSIONS/SIGNIFICANCE: We estimate that approximately one third of tuberculin skin test conversion in Gambian TB case contacts is due to boosting of immunity to non-tuberculous mycobacterial exposure. Further longitudinal studies are required to confirm whether ELISPOT can reliably identify case contacts with tuberculin test conversion that would benefit most from prophylactic treatment

'It's Reducing a Human Being to a Percentage'; Perceptions of Justice in Algorithmic Decisions

Data-driven decision-making consequential to individuals raises important questions of accountability and justice. Indeed, European law provides individuals limited rights to 'meaningful information about the logic' behind significant, autonomous decisions such as loan approvals, insurance quotes, and CV filtering. We undertake three experimental studies examining people's perceptions of justice in algorithmic decision-making under different scenarios and explanation styles. Dimensions of justice previously observed in response to human decision-making appear similarly engaged in response to algorithmic decisions. Qualitative analysis identified several concerns and heuristics involved in justice perceptions including arbitrariness, generalisation, and (in)dignity. Quantitative analysis indicates that explanation styles primarily matter to justice perceptions only when subjects are exposed to multiple different styles---under repeated exposure of one style, scenario effects obscure any explanation effects. Our results suggests there may be no 'best' approach to explaining algorithmic decisions, and that reflection on their automated nature both implicates and mitigates justice dimensions.Comment: 14 pages, 3 figures, ACM Conference on Human Factors in Computing Systems (CHI'18), April 21--26, Montreal, Canad

The role of left ventricular deformation in the assessment of microvascular obstruction and intramyocardial haemorrhage

In the setting of acute ST-elevation myocardial infarction (STEMI), it remains unclear which strain parameter most strongly correlates with microvascular obstruction (MVO) or intramyocardial haemorrhage (IMH). We aimed to investigate the association of MVO, IMH and convalescent left ventricular (LV) remodelling with strain parameters measured with cardiovascular magnetic resonance (CMR). Forty-three patients with reperfused STEMI and 10 age and gender matched healthy controls underwent CMR within 3-days and at 3-months following reperfused STEMI. Cine, T2-weighted, T2*-imaging and late gadolinium enhancement (LGE) imaging were performed. Infarct size, MVO and IMH were quantified. Peak global longitudinal strain (GLS), global radial strain (GRS), global circumferential strain (GCS) and their strain rates were derived by feature tracking analysis of LV short-axis, 4-chamber and 2-chamber cines. All 43 patients and ten controls completed the baseline scan and 34 patients completed 3-month scans. In multivariate regression, GLS demonstrated the strongest association with MVO or IMH (beta = 0.53, p 20%). Baseline GLS also demonstrated the strongest diagnostic performance in predicting adverse LV remodelling (AUC = 0.79; 95% CI 0.60–0.98; p = 0.03). Post-reperfused STEMI, baseline GLS was most closely associated with the presence of MVO or IMH. Baseline GLS was more strongly associated with adverse LV remodelling than other CMR parameters

Blended Clustering for Health Data Mining

Exploratory data analysis using data mining techniques is becoming more popular for investigating subtle relationships in health data, for which direct data collection trials would not be possible. Health data mining involving clustering for large complex data sets in such cases is often limited by insufficient key indicative variables. When a conventional clustering technique is then applied, the results may be too imprecise, or may be inappropriately clustered according to expectations. This paper suggests an approach which can offer greater range of choice for generating potential clusters of interest, from which a better outcome might in turn be obtained by aggregating the results. An example use case based on health services utilization characterization according to socio-demographic background is discussed and the blended clustering approach being taken for it is described