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Relative Dose Measurements
Published in W. P. M. Mayles, A. E. Nahum, J.-C. Rosenwald, Handbook of Radiotherapy Physics, 2021
The absolute dose (or reference dose) determination in reference conditions is based on published codes of practice discussed in Chapter 19. It is important to stick closely to the recommendations of these codes of practice, because they guarantee accuracy and consistency of the dose determination throughout the world. The reference conditions are chosen to provide a point at a depth of clinical interest where electronic equilibrium can be relied on (for photon beams) and where the dose gradient is not too steep.
Hormesis
Published in T. D. Luckey, Radiation Hormesis, 2020
Hormesis is readily seen in a typical dose-response curve (Figure 2.1 A). The dose is usually plotted on the abscissa using a logarithmic scale. This allows both low and high doses to be evaluated. Generally the reference dose represents the background radiation to which the control group is exposed, not an absolute zero nor a defined dose of radiation. This provides a convenient starting point for the rainbow curve obtained. This curve may look different when the connection between the lowest dose and control values is not made (Figure 2.1B). Note that the curve is inverted when opposite parameters are used, e.g., survival and mortality.
Detectors for Reference Dosimetry
Published in Ben Mijnheer, Clinical 3D Dosimetry in Modern Radiation Therapy, 2017
There is room for further confusion, since the measurement conditions specified in a reference dosimetry protocol would normally be referred to as “reference” conditions, and any measurement following the protocol would normally be referred to as a “reference” dose measurement. The confusion arises if an absolute measurement, whether or not it is made using a primary standard, is made under nonreference conditions. Such a measurement may be “absolute,” and is possible provided that an appropriate correction is made for the change in sensitivity of a dosimeter when it is used under nonreference conditions rather than reference conditions; however, it is not a “reference” measurement.
Potential toxic elements in sediment and fishes of an important fish breeding river in Bangladesh: a preliminary study for ecological and health risks assessment
Published in Toxin Reviews, 2022
Y. N. Jolly, Md. Refat Jahan Rakib, Md. Saiful Islam, S. Akter, Abubakr M. Idris, Khamphe Phoungthong
Target hazard quotients (THQs) were estimated by the ratio of EDI and oral reference dose (RfD). If the THQ is higher than 1 then the exposed population may possibly experience adverse health effects (Abtahi et al.2017; Traina et al.2019). The THQ formula is expressed as follows: years) (USEPA 1991); EFr is the exposure frequency (365days/year); FIR is the rate of food ingestion (g/person/day); C is the metal concentration in fish (mg/kg); RfD is the oral reference dose (mg/kg/day); BW is the average body weight; AT is the average time for non-carcinogens (365days/year × number of exposure years, assuming 30years). The oral reference doses of elements were 1.5, 0.14, 0.03, 0.04, 0.3, 0.0003, and 0.004 Cr, Mn, Co, Cu, Zn, Hg, and Pb, respectively (USEPA 2010).
Using existing knowledge for the risk evaluation of crop protection products in order to guide exposure driven data generation strategies and minimise unnecessary animal testing
Published in Critical Reviews in Toxicology, 2021
Paul Parsons, Elaine Freeman, Ryan Weidling, Gary L. Williams, Philip Gill, Neil Byron
There are different ways in which the distribution of reference dose values can be derived and used to contextualise exposure. In this study we chose to derive values by region separating data from US EPA, EU and JMPR and also separating the data by pesticide indication for fungicides, insecticides and herbicides. Whilst this may be viewed as creating a data set that is more relevant to the exposure scenario and the regulatory framework under which it will be evaluated, it does reduce the number of data points. This becomes more apparent when further refining the data set for a specific pesticide mode of action as was the case for the SDHI use scenario. An alternative approach would be to pool a larger data set and include, for example, all insecticide ARfDs from each region into a single data set giving a much larger number of data points.
Using the Matrix to bridge the epidemiology/risk assessment gap: a case study of 2,4-D
Published in Critical Reviews in Toxicology, 2021
Carol J. Burns, Judy S. LaKind
The fields of environmental epidemiology and exposure science have provided consequential data for use in meta-analyses, systematic reviews, and ultimately, public health decision-making. Yet while activities such as the development of reference doses have been based on data from epidemiology studies, it is often the case that these data are secondary to toxicological data or are judged to be insufficient to examine exposure-outcome associations (Nachman et al. 2011; EFSA Panel on Plant Protection Products et al. 2017; Deener et al. 2018). While calls have been made for improving the utility of epidemiology for risk assessment, hurdles remain (Burns et al. 2014; Christensen et al. 2015; Birnbaum et al. 2016). In an effort to move the needle on this issue, an international, multi-sector group with expertise in risk assessment, toxicology, epidemiology, and exposure science developed the Matrix (Table 1), a structured approach to bridging the risk assessment-epidemiology gap (Burns et al. 2019).