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1.
Environ Health ; 23(1): 8, 2024 Jan 22.
Artigo em Inglês | MEDLINE | ID: mdl-38254105

RESUMO

BACKGROUND: Environmental health research in the US has shown that racial and ethnic minorities and members of low-socioeconomic groups, are disproportionately burdened by harmful environmental exposures, in their homes, workplace, and neighborhood environments that impact their overall health and well-being. Systemic racism is a fundamental cause of these disproportionate exposures and associated health effects. To invigorate and inform current efforts on environmental justice and to raise awareness of environmental racism, the National Institute of Environmental Health Sciences (NIEHS) hosted a workshop where community leaders, academic researchers, and NIEHS staff shared perspectives and discussed ways to inform future work to address health disparities. OBJECTIVES: To share best practices learned and experienced in partnerships between academic researchers and communities that are addressing environmental racism across the US; and to outline critical needs and future actions for NIEHS, other federal agencies, and anyone who is interested in conducting or funding research that addresses environmental racism and advances health equity for all communities. DISCUSSION: Through this workshop with community leaders and researchers funded by NIEHS, we learned that partnerships between academics and communities hold great promise for addressing environmental racism; however, there are still profound obstacles. To overcome these barriers, translation of research into plain language and health-protective interventions is needed. Structural changes are also needed in current funding mechanisms and training programs across federal agencies. We also learned the importance of leveraging advances in technology to develop creative solutions that can protect public health.


Assuntos
Racismo , Humanos , Justiça Ambiental , Saúde Pública , Exposição Ambiental , Saúde Ambiental
2.
PLoS One ; 4(9): e7024, 2009 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-19753116

RESUMO

BACKGROUND: The nematode Caenorhabditis elegans is being assessed as an alternative model organism as part of an interagency effort to develop better means to test potentially toxic substances. As part of this effort, assays that use the COPAS Biosort flow sorting technology to record optical measurements (time of flight (TOF) and extinction (EXT)) of individual nematodes under various chemical exposure conditions are being developed. A mathematical model has been created that uses Biosort data to quantitatively and qualitatively describe C. elegans growth, and link changes in growth rates to biological events. Chlorpyrifos, an organophosphate pesticide known to cause developmental delays and malformations in mammals, was used as a model toxicant to test the applicability of the growth model for in vivo toxicological testing. METHODOLOGY/PRINCIPAL FINDINGS: L1 larval nematodes were exposed to a range of sub-lethal chlorpyrifos concentrations (0-75 microM) and measured every 12 h. In the absence of toxicant, C. elegans matured from L1s to gravid adults by 60 h. A mathematical model was used to estimate nematode size distributions at various times. Mathematical modeling of the distributions allowed the number of measured nematodes and log(EXT) and log(TOF) growth rates to be estimated. The model revealed three distinct growth phases. The points at which estimated growth rates changed (change points) were constant across the ten chlorpyrifos concentrations. Concentration response curves with respect to several model-estimated quantities (numbers of measured nematodes, mean log(TOF) and log(EXT), growth rates, and time to reach change points) showed a significant decrease in C. elegans growth with increasing chlorpyrifos concentration. CONCLUSIONS: Effects of chlorpyrifos on C. elegans growth and development were mathematically modeled. Statistical tests confirmed a significant concentration effect on several model endpoints. This confirmed that chlorpyrifos affects C. elegans development in a concentration dependent manner. The most noticeable effect on growth occurred during early larval stages: L2 and L3. This study supports the utility of the C. elegans growth assay and mathematical modeling in determining the effects of potentially toxic substances in an alternative model organism using high-throughput technologies.


Assuntos
Caenorhabditis elegans/efeitos dos fármacos , Clorpirifos/farmacologia , Inseticidas/farmacologia , Animais , Clorpirifos/toxicidade , Relação Dose-Resposta a Droga , Regulação da Expressão Gênica no Desenvolvimento/efeitos dos fármacos , Inseticidas/toxicidade , Cadeias de Markov , Modelos Estatísticos , Modelos Teóricos , Análise de Regressão , Fatores de Tempo
3.
PLoS One ; 4(9): e7018, 2009 Sep 15.
Artigo em Inglês | MEDLINE | ID: mdl-19753303

RESUMO

BACKGROUND: As part of a program to predict the toxicity of environmental agents on human health using alternative methods, several in vivo high- and medium-throughput assays are being developed that use C. elegans as a model organism. C. elegans-based toxicological assays utilize the COPAS Biosort flow sorting system that can rapidly measure size, extinction (EXT) and time-of-flight (TOF), of individual nematodes. The use of this technology requires the development of mathematical and statistical tools to properly analyze the large volumes of biological data. METHODOLOGY/PRINCIPAL FINDINGS: Findings A Markov model was developed that predicts the growth of populations of C. elegans. The model was developed using observations from a 60 h growth study in which five cohorts of 300 nematodes each were aspirated and measured every 12 h. Frequency distributions of log(EXT) measurements that were made when loading C. elegans L1 larvae into 96 well plates (t = 0 h) were used by the model to predict the frequency distributions of the same set of nematodes when measured at 12 h intervals. The model prediction coincided well with the biological observations confirming the validity of the model. The model was also applied to log(TOF) measurements following an adaptation. The adaptation accounted for variability in TOF measurements associated with potential curling or shortening of the nematodes as they passed through the flow cell of the Biosort. By providing accurate estimates of frequencies of EXT or TOF measurements following varying growth periods, the model was able to estimate growth rates. Best model fits showed that C. elegans did not grow at a constant exponential rate. Growth was best described with three different rates. Microscopic observations indicated that the points where the growth rates changed corresponded to specific developmental events: the L1/L2 molt and the start of oogenesis in young adult C. elegans. CONCLUSIONS: Quantitative analysis of COPAS Biosort measurements of C. elegans growth has been hampered by the lack of a mathematical model. In addition, extraneous matter and the inability to assign specific measurements to specific nematodes made it difficult to estimate growth rates. The present model addresses these problems through a population-based Markov model.


Assuntos
Caenorhabditis elegans/metabolismo , Animais , Estudos de Coortes , Modelos Animais de Doenças , Genoma Helmíntico , Crescimento/genética , Humanos , Cadeias de Markov , Modelos Biológicos , Modelos Genéticos , Modelos Estatísticos , Modelos Teóricos , Oogênese , Fatores de Tempo
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