496 research outputs found

    Risky Reform

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    Predictive models for nanotoxicology: current challenges and future opportunities.

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    Characterizing the risks posed by nanomaterials is extraordinarily complex because these materials can have a wide range of sizes, shapes, chemical compositions and surface modifications, all of which may affect toxicity. There is an urgent need for a testing strategy that can rapidly and efficiently provide a screening approach for evaluating the potential hazard of nanomaterials and inform the prioritization of additional toxicological testing where necessary. Predictive toxicity models could form an integral component of such an approach by predicting which nanomaterials, as a result of their physico-chemical characteristics, have potentially hazardous properties. Strategies for directing research towards predictive models and the ancillary benefits of such research are presented here

    Genomic differences between nasal Staphylococcus aureus from hog slaughterhouse workers and their communities.

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    New human pathogens can emerge from the livestock-human interface and spread into human populations through many pathways including livestock products. Occupational contact with livestock is a risk factor for exposure to those pathogens and may cause further spreading of those pathogens in the community. The current study used whole genome sequencing to explore nasal Staphylococcus aureus obtained from hog slaughterhouse workers and their community members, all of whom resided in a livestock-dense region in rural North Carolina. Sequence data were analyzed for lineage distribution, pathogenicity-related genomic features, and mobile genetic elements. We observed evidence of nasal S. aureus differences between hog workers and non-workers. Nasal S. aureus from hog workers showed a greater lineage diversity than nasal S. aureus from community residents. Hog worker isolates were less likely to carry the φSa3 prophage and human-specific immune evasion cluster genes than community resident isolates (φSa3 prophage: 54.5% vs. 91.7%, Benjamini-Hochberg (BH) corrected p = 0.035; immune evasion cluster genes: 66.7% vs. 100%, BH p = 0.021). Hog worker isolates had a lower prevalence and diversity of enterotoxins than community resident isolates, particularly lacking the enterotoxin gene cluster (39.4% vs. 70.8%, BH p = 0.125). Moreover, hog worker isolates harbored more diverse antibiotic resistance genes, with a higher prevalence of carriage of multiple resistance genes, than community resident isolates (75.8% vs. 29.2%, BH p = 0.021). Phylogenetic analysis of all ST5 isolates, the most abundant lineage in the collection, further supported separation of isolates from hog workers and non-workers. Together, our observations suggest impact of occupational contact with livestock on nasal S. aureus colonization and highlight the need for further research on the complex epidemiology of S. aureus at the livestock-human interface

    Arsenic Exposure and Type 2 Diabetes: A Systematic Review of the Experimental and Epidemiologic Evidence

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    Chronic arsenic exposure has been suggested to contribute to diabetes development. We performed a systematic review of the experimental and epidemiologic evidence on the association of arsenic and type 2 diabetes. We identified 19 in vitro studies of arsenic and glucose metabolism. Five studies reported that arsenic interfered with transcription factors involved in insulin-related gene expression: upstream factor 1 in pancreatic β-cells and peroxisome proliferative-activated receptor γ in preadipocytes. Other in vitro studies assessed the effect of arsenic on glucose uptake, typically using very high concentrations of arsenite or arsenate. These studies provide limited insight on potential mechanisms. We identified 10 in vivo studies in animals. These studies showed inconsistent effects of arsenic on glucose metabolism. Finally, we identified 19 epidemiologic studies (6 in high-arsenic areas in Taiwan and Bangladesh, 9 in occupational populations, and 4 in other populations). In studies from Taiwan and Bangladesh, the pooled relative risk estimate for diabetes comparing extreme arsenic exposure categories was 2.52 (95% confidence interval, 1.69–3.75), although methodologic problems limit the interpretation of the association. The evidence from occupational studies and from general populations other than Taiwan or Bangladesh was inconsistent. In summary, the current available evidence is inadequate to establish a causal role of arsenic in diabetes. Because arsenic exposure is widespread and diabetes prevalence is reaching epidemic proportions, experimental studies using arsenic concentrations relevant to human exposure and prospective epidemiologic studies measuring arsenic biomarkers and appropriately assessing diabetes should be a research priority

    Multidrug-resistant and methicillin-resistant Staphylococcus aureus (MRSA) in hog slaughter and processing plant workers and their community in North Carolina (USA)

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    Background: Use of antimicrobials in industrial food-animal production is associated with the presence of antimicrobial resistant Staphylococcus aureus among animals and humans. Hog slaughter/processing plants process large numbers of animals from industrial animal operations, and are environments conducive to the exchange of bacteria between animals and workers. Objectives: To compare the prevalence of methicillin-resistant S. aureus (MRSA) and multidrug resistant S. aureus(MDRSA) carriage between processing plant workers, their household members, and community residents. Methods: We conducted a cross-sectional study of hog slaughter/processing plant workers, their household members, and community residents in North Carolina. Participants responded to a questionnaire and provided a nasal swab. Swabs were tested for S. aureus, and isolates tested for antimicrobial susceptibility and subjected to multilocus sequence typing. Results: The prevalence of S. aureus was 21.6%, 30.2%, and 22.5% among 162 workers, 63 household members, and 111 community residents, respectively. The overall prevalence of MRSA and MDRSA tested by disk diffusion was 4.8% and 6.9%, respectively. The adjusted prevalence of MDRSA among workers was 1.96 times (95% CI: 0.71, 5.45) the prevalence in community residents. The adjusted average number of antimicrobial classes to which S. aureus isolates from workers were resistant was 2.54 times (95% CI: 1.16, 5.56) the number among isolates from community residents. One MRSA isolate and two MDRSA isolates from workers were identified as sequence type 398, a type associated with exposure to livestock. Conclusions: Although the prevalence of S. aureus and MRSA was similar in hog slaughter/processing plant workers and their household and community members, S. aureus isolates from workers were resistant to a greater number of antimicrobial classes. These findings may be related to the non-therapeutic use of antimicrobials in food-animal production

    Lead inhibits secretion of osteonectin/SPARC without significantly altering collagen or Hsp47 production in osteoblast-like ROS 17/2.8 cells

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    In an effort to better understand the consequences of lead (Pb2+) on skeletal growth, the effects of Pb2+ were investigated using ROS 17/2.8 bone-like cells in vitro. These studies revealed that Pb2+ (4.5 x 10-6 - 4.5 x 10-7 ) has little or no effect on cell shape except when added immediately following seeding of the cells. However, proliferation of ROS cells was inhibited, in the absence of serum, at concentrations of 4.5 x 10-6 Pb2+. Protein production was generally increased, however, the major structural protein of bone, type I collagen, production was only slightly altered. Following treatment of ROS cells with Pb2+, intracellular levels of the calcium-binding protein osteonectin/SPARC were increased. Osteonectin/SPARC secretion into the media was delayed or inhibited. Coincident with retention of osteonectin/SPARC there was a decrease in the levels of osteonectin/SPARC mRNA as determined by Northern analysis. These studies suggest that processes associated with osteonectin/SPARC translation and secretion are sensitive to Pb2+.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/29805/1/0000151.pd

    Stress as a Potential Modifier of the Impact of Lead Levels on Blood Pressure: The Normative Aging Study

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    BACKGROUND. Lead exposure and psychological stress have been independently associated with hypertension in various populations, and animal studies suggest that when they co-occur, their effects may be exacerbated. OBJECTIVES. We examined whether psychological stress modifies the impact of cumulative lead exposure (measured as bone lead levels) on hypertension and blood pressure in Boston-area community-exposed men participating in the Normative Aging Study. METHODS. We evaluated the modifying effect of stress on lead exposure on baseline hypertension status (513 participants) and on blood pressure in those without hypertension (237 participants), cross-sectionally. In baseline nonhypertensives, we examined the same risk factors in relation to prospective risk of developing hypertension. RESULTS. Cross-sectional analysis revealed a positive interaction between stress and tibia lead on systolic blood pressure, after adjusting for age, body mass index, family history of high blood pressure, education, smoking, alcohol consumption, physical activity, and nutritional factors. In prospective multivariate analyses, high stress also modified the effect of tibia lead and patella lead on the risk of developing hypertension. Those reporting high stress had 2.66 [95% confidence interval (CI), 1.43-4.95] times the risk of developing hypertension per standard deviation increase in tibia lead and had 2.64 (95% CI, 1.42-4.92) times the risk per standard deviation increase in patella lead. CONCLUSION. To our knowledge, these are the first analyses to look at interactive effects of stress and lead on hypertension in humans. These results suggest that the effect of lead on hypertension is most pronounced among highly stressed individuals, independent of demographic and behavioral risk factors.National Institutes of Health (R01-ES05257, P20-MD000501, P42-ES05947, GCRC M01-RR02635, ES03918-02); United States Department of Veterans Affair
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