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Biomedical subjects

M A Shirazi

Publications and source records attributed to M A Shirazi.

10 recordsLinked to original sources
PubMed1994

An interpretation of toxicity response of bobwhite quail with respect to duration of exposure.

Avian dietary toxicity tests were conducted with seven pesticides, two age groups (2 and 16 weeks old) of northern bobwhite (Colinus virginianus) and two durations (5 and 28 days) of exposure. Results were analyzed with an emphasis placed upon comparing mortalities on similar test conditions. An analysis that used the entire dose-time-response results led to the calculation of a common measure (asymptotic rate e) of temporal development of the response surface and served as a basis of comparison of diverse test results. The asymptotic median lethal concentrations were designated by ALC50 and the median lethal concentrations at the end of a test period by LC50. It was found that: (1) Young birds in 5- and 28-day tests were more sensitive to incremental increases in the duration of exposure than adults. (2) Young birds were less sensitive to incremental increases of dietary concentration than adults only in the 5-day test and displayed delayed response patterns in six of seven chemicals in those tests. (3) LC50 values of 5-day tests of young birds were greater than LC50 values of 28-day tests, but the corresponding ALC50s were smaller in 5-day tests than 28-day tests. (4) ALC50s for 28-day tests were lower for young birds than for adults.(ABSTRACT TRUNCATED AT 250 WORDS)

Animal Feed↗
PubMed1991

Developmental malformation of frog embryos: an analysis of teratogenicity of chemical mixtures.

Chemical compounds known to be teratogenic to frog embryos were tested singly and in binary mixtures and Weibull functions were used to model their concentration-response relationships. A separate Weibull function with an additive concentration variable modeled the mixtures using only single chemical test data. Seven chemicals in five binary mixtures at 3/1, 1/1, and 1/3 mixture proportions each were tested. The ratios of measured and calculated model parameters and median concentrations were estimated for comparing the results. The ratios ranged from 0.72 and 1.44 with an average at 0.99, an agreement that was qualitatively similar to modeling mixtures of narcotic chemicals which are known to produce additive concentration effects. The model reliability in determining mixture response classes and prediction of effects based on single chemical data was quantified. The model is useful for environmental risk assessment of chemical mixtures in hazardous waste sites and for the design of mixture experiments.

Animals↗
PubMed1991

A model of additive effects of mixtures of narcotic chemicals.

Biological effects data with single chemicals are far more abundant than with mixtures. Yet, environmental exposures to chemical mixtures, for example near hazardous waste sites or non point sources, are very common and using test data from single chemicals to approximate effects of mixtures can be useful in environmental risk assessment. To facilitate the linkage, the Weibull function was used as a common model to link responses of single chemicals with the response of their mixtures. The present paper addresses the response of fish to mixtures of narcotic chemicals and a second paper addresses the developmental malformation of frog embryos when exposed to defined mixtures of teratogenic chemicals. Biological effects data with singly tested chemicals cannot be used directly to predict effects of mixtures. However, narcotic chemicals are known to produce an additive concentration effects in fish and the Weibull function with an additive concentration variable was used to model the effects of mixtures of these chemicals. The model produced good agreement with data over a wide range of chemicals and mixture ratios and provides a useful initial assessment of environmental effects of mixtures of narcotic chemicals.

Animals↗
PubMedDate not supplied

An analysis of risk from exposure to aldicarb using immune response of nonuniform populations of mice.

The immunomodulation response of mice to low levels of aldicarb in drinking water was investigated in four series of studies. The splenic plaque forming cell (PFC) response to red sheep cells were measured for treatment levels of 0.01 to 1,000 ppb (micrograms/kg). Based on their beginning and end body weights, the animal populations were uniform in all series of tests, but based on their net body weights and PFC counts they were highly nonuniform in the 30 and 60 day tests and uniform in the 90 and 180 day tests. The mean PFC counts for animals in each treatment were calculated and compared with the mean PFC counts for animals in the controls in all four series of tests. This approach ignores the variability and nonuniformity in the animal population. The outcomes using this approach were stimulatory for the 30 and 60 day tests and inhibitory for the 90 and 180 day tests. An alternative approach was developed based on the analysis of the distributions of the relative PFC counts of each animal in a treatment with each animal in a control, and specifically addresses the variability and nonuniformity in animal population as integral parts of the analysis. The distribution peaks were estimated by maximum likelihood and kernel/bootstrap procedures and were used to summarize the tests. The outcomes were consistently inhibitory, indicating immune suppression. The outcome of this approach converged to the outcome of the mean PFC approach for the 90 and 180 day tests where the animal populations were uniform.

Aldicarb↗
PubMedDate not supplied

A probabilistic statement of the structure activity relationship for environmental risk analysis.

In this paper, we define a mode of biological response of an organism to a chemical in terms of a general mathematical model of the response surface. The model describes the combined effects of dose-level exposure and time-duration exposure using 570 96-hr toxicity tests with fathead minnows. The response surface along the dose and time axes for each chemical in these tests were completely defined by two scale factors, one for dose and one for time, and two form factors, one for dose and one for time. The scale factors for dose and time are proportional with the inverse of LC50 and Lt50, respectively. The form factors measure the relative response strategies with respect to dose and time exposures. Only the scale factor for the dose is correlated with the logarithm of the octanol water partition coefficient (log P) and molecular weight (Mw). Additional and independent observations beyond log P and Mw are needed to correlate various modes of chemical action with the form factors. It is shown that narcosis-producing chemicals can be distinguished from other classes of chemicals by the dominance of the response strategy with respect to the dose over time exposures.

Environmental Pollution↗
PubMedDate not supplied

Spatial extrapolation of soil characteristics using whole-soil particle size distributions.

Soils support ecosystem functions such as plant growth and water quality because of certain physical, chemical, and biological properties. These properties have been studied at different spatial scales, including point scales to satisfy basic research needs, and regional scales to satisfy monitoring needs. Recently, soil property data for the entire USA have become available in the State Soil Geographic Data Base (STATSGO), which is appropriate for regional-scale research. We analyzed and created models of STATSGO data in this study to serve as a research tool, for example, for linking the soil to regional water quality monitoring data in our companion paper. Map units in STATSGO define geographic land areas by soil characteristics (SCs) of similar soil series. We selected 27 SCs that influenced water properties (in varying degrees), aggregated the layer and component SCs to map unit SCs, and used SCs to calculate relationships among map units. The relationships were defined by equations of conditional mean for the qth SC (SCq), while using the remaining 26 SCs as predictors. The relative standard errors for 22 of the 27 SCs were less than 10%, and less than 22% for the remaining five. We conclude that spatial extrapolation of SCs is feasible and the procedures are a first step toward extrapolating information across a region using SC-water property relationships. Although our procedure is for regional scale monitoring, it is also applicable to finer spatial scales commensurate with available soil data.

Ecosystem↗
PubMedDate not supplied

Predicting physical and chemical water properties from relationships with watershed soil characteristics.

The Surface Waters component of the Environmental Monitoring and Assessment Program (EMAPSW) was developed by the USEPA to evaluate the extent and condition of lakes and streams over national and regional scales. Realistically, chemical or physical water properties (WPs) such as acidity or turbidity can be field-sampled for only a small portion of all lakes and streams. However, soil characteristics (SCs) affect WPs and broad-scale soil survey data have become available in the State Soil Geographic Data Base (STATSGO). We developed models relating observed WPs to SCs to extrapolate the sampled WPs to a region, potentially reducing extensive monitoring needs. Our study region consisted of 13 northeastern and Mid-Atlantic states and contained 882 STATSGO soil map units. We used map units as the spatial component of WP analysis. The WPs were sampled in 721 randomly selected EMAPSW study sites. The watersheds of these sites represent 7.1% of the region's total area and spatially intersect 400 of its soil map units. Each intersected map unit was assigned the weighted average WPs from the corresponding watersheds. Conditional expectation models were used to extrapolate sampled WPs to 882 map units. The relative standard errors ranged from low for pH (0.8%), intermediate for total P (12.1%), and very high for chloride (54.8%). The high extrapolation errors indicate outlier conditions from natural, non-soil, or anthropogenic sources.

Ecosystem↗