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Singh, N.P.; McCoy, M.T.; Tice, R.R. & Schneider, E.L. (1988). A simpletechnique for quantitation of low levels of DNA damage in individuals cells, Exp.Cell. Res, 175, 1, 184-191, ISSN 0014-4827.Singh, N.P.; Muller, C.H. & Berger, R.E. (2003) Effects of age on DNA doublestrandbreaks and apoptosis in human sperm, Ferti. Steril., 0, 6, 1420–30.Singh, V.K.; Jyoti; Krishna Reddy, M.M.; Kesavachandran, C.; Rastogi, S.K. &Siddiqui, M.K.J. (2007). Biomonitoring of organochlorines, glutathione, lipidperoxidation and cholinesterase activity among pesticide sprayers in mangoorchards, Clin. Chim. Acta, 377, 268–272.Souza Casadinho, O. & Bocero, S. (2008). Agrotóxicos: Condiciones de utilizaciónen la horticultura de la Provincia de Buenos Aires (Argentina), RevistaIberoamericana de Economía Ecológica, 9, 87-101.Sturzenegger, A., & M. Salazni. 2008. “Distortions to Agricultural Incentives inArgentina.” In Chapter 2 of Distortions to Agricultural Incentives in Latin America,K. Anderson and A.Valdes, eds. Washington, DC: World Bank, pp. 59-85.Vaghef, H.; Nygren, P.; Edling, C.; Bergh, J. & Hellman, B. (1997). Alkalinesingle-cell gel electrophoresis and human biomonitoring for genotoxicity: a pilotstudy on breast cancer patients undergoing chemotherapy includingcyclophosphamide, Mutat. Res, 395, 2–3, 127–138.Valverde, M.; Lopez, M.; Lopez, I.; Sanchez, I.; Fortoul, T.; Ostrosky-Wegman P.& Rojas, E. (1997). DNA damage in leukocytes and buccal and nasal epithelial cellsof individuals exposed to air pollution in Mexico City, Environ. Mol. Mutagen., 30,147–152.WHO, World Health Organization, 2004. Recommended classification of pesticidesby hazard and guidelines to classification. World Health Organization, Geneva.(http://www.int/ipcs/publications/pesticides_hazards/en)World Bank. 2006. Argentina Agriculture and Rural Development: Selected Issues.Report No. 32763-AR. Washington, DC: World Bank.Zeljezic, D. & Garaj-Vrhovac, V. (2001). Chromosomal aberration and single cellgel electrophoresis (comet) assay in the longitudinal risk assessment of occupationalexposure to pesticides, Mutagenesis, 16, 4, 359–363.AcademyPublish.org - The Impact of Pesticides104
Using a Toxicokinetic Modeling Approach to DetermineBiological Reference Values (BRVs) and to Assess HumanExposure to PesticidesAurélie Berthet, Michèle Bouchard, Mathieu Valcke, Roberto Heredia-OrtizABSTRACTExposure to various pesticides has been characterized in workers and the generalpopulation, but interpretation and assessment of biomonitoring data from a healthrisk perspective remains an issue. For workers, a Biological Exposure Index (BEI ® )has been proposed for some substances, but most BEIs are based on urinarybiomarker concentrations at Threshold Limit Value - Time Weighted Average(TLV-TWA) airborne exposure while occupational exposure can potentially occursthrough multiple routes, particularly by skin contact (i.e.captan, chlorpyrifos,malathion). Similarly, several biomonitoring studies have been conducted to assessenvironmental exposure to pesticides in different populations, but dose estimates orhealth risks related to these environmental exposures (mainly through the diet), wererarely characterized. Recently, biological reference values (BRVs) in the form ofurinary pesticide metabolites have been proposed for both occupationally exposedworkers and children. These BRVs were established using toxicokinetic modelsdeveloped for each substance, and correspond to safe levels of absorption inhumans, regardless of the exposure scenario. The purpose of this chapter is topresent a review of a toxicokinetic modeling approach used to determine biologicalreference values. These are then used to facilitate health risk assessments anddecision-making on occupational and environmental pesticide exposures. Suchmodels have the ability to link absorbed dose of the parent compound to exposurebiomarkers and critical biological effects. To obtain the safest BRVs for the studiedpopulation, simulations of exposure scenarios were performed using a conservativereference dose such as a no-observed-effect level (NOEL). The various examplesdiscussed in this chapter show the importance of knowledge on urine collections(i.e. spot samples and complete 8-h, 12-h or 24-h collections), sampling strategies,metabolism, relative proportions of the different metabolites in urine, absorptionfraction, route of exposure and background contribution of prior exposures. Theyalso show that relying on urinary measurements of specific metabolites appearsmore accurate when applying this approach to the case of occupational exposures.Conversely, relying on semi-specific metabolites (metabolites common to acategory of pesticides) appears more accurate for the health risk assessment ofenvironmental exposures given that the precise pesticides to which subjects areexposed are often unknown. In conclusion, the modeling approach to define BRVsfor the relevant pesticides may be useful for public health authorities for managingissues related to health risks resulting from environmental and occupationalexposures to pesticides.AcademyPublish.org - The Impact of Pesticides105
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The Impactof PesticidesEdited by:Pr
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Other access free resources from Ac
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The Impact of PesticidesPrepared an
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Table of Contentsp.203-p.224 Behavi
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About authorspublished by Elsevier.
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About authorsof medical researchers
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About authorsdifferent spatial scal
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About authorsEducation:Bachelor’s
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About authorsSensors - A Nanotechno
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Section 1HUMAN EXPOSURE TO PESTICID
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ecently explored on preliminary stu
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individuals within 1 day (Jokanovic
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occupational environmental health r
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must be considered, since effective
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Jensen BH, Petersen A, and Christen
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Ragas AMJ, and Huijbregts MAJ (1998
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Weichenthal S, Moase C, and Chan P
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human poisoning, general acute symp
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Management of the cholinergic syndr
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1982; Lotti, 1992; Jokanović et al
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exposed populations, revealed high
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DiazepamBenzodiazepines are CNS dep
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Among the many classes of oximes in
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inhibited by dichlorvos (a dimethox
Page 54 and 55: Dawson, 1995). It appears that the
Page 56 and 57: Eddleston M, Eyer P, Worek F, Moham
Page 58 and 59: Jokanović M, Kosanović M (2010b).
Page 60 and 61: Ray DE (1998). Chronic effects of l
Page 62 and 63: Worek F, Eyer P, Kiderlen D, Thierm
Page 64 and 65: developing countries is due to suic
Page 66 and 67: count and morphology, as well as se
Page 68 and 69: PON1 modulation of genetic damageFe
Page 70 and 71: elationship between OP exposure and
Page 72 and 73: Blatter-Garin MC, James RW, Dussoix
Page 74 and 75: Hung RJ, Hall J, Brennan P, Boffett
Page 76 and 77: Rojas-García AE., Solís-Heredia M
Page 78 and 79: Occupational Exposure to Pesticides
Page 80 and 81: considered as conditions typical of
Page 82 and 83: observed adverse health outcome. Su
Page 84 and 85: within cells can oxidize biomolecul
Page 86 and 87: of the study. A face-to-face questi
Page 88 and 89: PesticidesFungicideInsecticide-Nema
Page 90 and 91: Table 4. Mixtures of pesticides use
Page 92 and 93: In pesticide applicators, Table 7 s
Page 94 and 95: DISCUSSIONThe agricultural workers
Page 96 and 97: changes in the antioxidant enzyme C
Page 98 and 99: Bajpayee, M.; Pandey, A. K.; Parmar
Page 100 and 101: Environmental health criteria 155.
Page 102 and 103: Palus, J.; Rydzynski, K.; Dziubalto
Page 106 and 107: INTRODUCTIONPopulations may be occu
Page 108 and 109: exposure scenarios on the basis of
Page 110 and 111: not present adverse health effects
Page 112 and 113: greenhouse workers exposed to malat
Page 114 and 115: Paraoxon is then either metabolized
Page 116 and 117: cyclohexene-1,2-dicarboximide, CAS
Page 118 and 119: metabolite of phthalates, such that
Page 120 and 121: scenarios were simulated, assuming
Page 122 and 123: Table 2. Biological reference value
Page 124 and 125: References N a urinarybiomarkeStudi
Page 126 and 127: Figure 2. Representation of a BRV d
Page 128 and 129: Figure 4. Conceptual representation
Page 130 and 131: Figure 6 Conceptual representation
Page 132 and 133: REFERENCESACGIH, 2011. Documentatio
Page 134 and 135: Bradway, D.E., Shafik, T.M., 1977.
Page 136 and 137: EPA, 1999b. Registration Eligibilit
Page 138 and 139: Hines, C.J., Deddens, J.A., Jaycox,
Page 140 and 141: McCollister, S.B., Kociba, R.J., Hu
Page 142 and 143: Verberk, M.M., Brouwer, D.H., Brouw
Page 144 and 145: important IGFBP for binding IGF-1 i
Page 146 and 147: secretion of IGF-1 (Tannheimer et a
Page 148 and 149: FIGURESFig. 1. An “hormetic” ef
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Page 152 and 153: Smith WJ, Underwood LE, Clemmons DR
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Section 2PESTICIDES IN THEENVIRONME
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vicinity of subsoil waters and ther
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Hieracium pilosella, southernwood -
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formed clusters (Figure 3). Ultrast
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Fig. 5. Fragment of hepatocyte of t
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Szarek, J, Skibniewska, K, Wojtacka
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negative effects (ZALUCKI et al., 2
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Figure 2. Appropriated sampling pro
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Figure 4. Illustration of the conse
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(HAILE et al., 1998). Earlier resul
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Table 1. Distribution of the applic
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Means followed by the same letter i
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(involving pests and natural enemie
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efore the pest emergence and their
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Table 3 (continuation)…AcademyPub
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Table 5. Effect of different fungic
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Table 6. Magament used including do
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adopted by Brazilian soybean grower
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Pickle, C.S.; Caviness, C.E. Yield
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This chapter reports on Dutch surfa
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several different occasions at any
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The greatest number of pesticides a
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Accumulated ExceedanceIt is useful
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For the years 2003-2009 the calcula
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Bonzini S, Verro R, Otto S, Lazzaro
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atios of the pesticide amounts in t
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Table 1. (Cont.) Runoff ratios of p
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mefenacet and simetrin were observe
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Table 2. (Cont.)Pesticide concentra
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Table 2. (Cont.)Pesticide concentra
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Fig. 3. Typical weekly variation of
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(BAM) in water (Pukkila et al. 2009
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Table 5. Concentrations of pesticid
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Table 6. Maximum concentrations of
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Iwafune, T, Inao, K, Horio, T, Iwas
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Suzuki, M, Takemine, S, Yoshida, M,
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factor, etc. Levels of pesticides i
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factor of 10 above ambient sea wate
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weight sample. Minimum were shown f
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Figure 3. DDTs in mussel samples fo
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Figure 5. HCB in mussel samples for
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Figure 8. Methoxychlor in mussel sa
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ACKNOWLEDGEMENTAuthors thank UNEP/M
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Pesticide Risk Index of Del Azul Wa
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on that presented in Swanson et al.
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eference value for that substance.
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predict the aquatic toxicity of a s
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Calculation Model of Aggravating Fa
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To estimate the values of Human Hea
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water in comparison with the durati
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Cypermethrin (95 th percentile (P 9
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Table 8 shows the results of the De
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are many ranking systems of dangero
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REFERENCESAres J. (2004). “Estima
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Mackay D. and Paterson S. (1991).
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Long-term Monitoring of Pesticides
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Sampling sites of the survey in 200
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than those in Lake Biwa and Seta Ri
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Fig. 7 Detection of fungicides in R
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Fig. 11 Detection of herbicides in
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Monitoring of pesticides in Yanamun
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A measured volume (1000 mL) of the
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SimetrynePretilachlorConcentration
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Fig. 18 Maximum concentrations of t
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Ecological risk assessmentFig. 20 Y
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REFERENCESAgradi E, Baga R, Cillo F
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Time Trend Variation of Selected Pe
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Table 1. Physical and chemical prop
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marketed under variety of trade nam
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Figure 3. Long-term trends of globa
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laboratory animals fed or injected
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fed for a lifespan at 5-1,600 mg/kg
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Soil samplingSoil sampling was foll
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Figure 5. Map showing sampling area
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concentration (MAC) in surface soil
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Table 7. Concentrations of HCH isom
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Shanghai and Guanting Reservoir (Ch
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Contrary to the results of ΣDDT, t
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DDT metabolites, the ratio of (p,p
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2001). Therefore, the predominance
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Mean concentration (ng g -1 dw)3002
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CONCLUSIONSAn evaluation of selecte
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Hung, D.Q., Thiemann, W., (2002),
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Viet, P.H., Hoai, P.M., Minh, N.H.,
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found in tissues or fluids samples
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Study area and SamplingThis study w
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the liver, mainly to p,p'-DDE and p
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33,370 ha, whilst that of woody cro
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Increase in crops area (x1000)Ha)25
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Table 1. Blood concentrations of or
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Council Directive 90/533/EEC of 15
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Konstantinou, IK, Goutner, V, Alban
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Smith, AG (2004). “Toxicology of
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Pesticides are used in order to pro
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EXPERIMENTALMaterialsIsoproturon wa
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RESULTS AND DISCUSIONEquilibrium is
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As seen in Table 4, as the concentr
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Fig.4. Breakthrough curves of isopr
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Fig.6. Breakthrough curves of isopr
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Fig.8. Experimental and theoretical
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Section 3PESTICIDE ANALYSISAcademyP
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scandal’ are familiar to the gene
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ecoveries (>70%) for certain pH-dep
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Due the versatility of the QuEChERS
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of application, with some still sca
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The main supercritical solvent used
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extracting the pesticides from the
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would be appropriate for the routin
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chromatography with negative-ion el
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GPC was applied as a nondestructive
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Charlton A.J.A., Stuckey, V. (2009)
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Lehotay, S.J., Mastvoska, K. & Yun,
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Rodrigues, F. M., Mesquita, P. R. R
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Analytical methods to assess the im
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acetylcholine, a neurotransmitter t
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1.3 to 22.3% for all pesticides. Li
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Malathion, parathion, fenitrothion,
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Fuller, BH and Berger, GMB (1990).
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Table 1. Largest exporters of coffe
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Fig. 1: Structures of (a) Phosphate
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ELECTROCHEMICAL BIOSENSORBiosensors
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inorganic and organic species a lar
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surface area and be easily modified
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Acetylcholine + H 2 O AChE Choline
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Wang, 2010) and tetracyanoquinodime
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PDDA/AChE/PDDA/CNT/GCAChE-Au-PPy/GC
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ng/mL and good precision (RSD ) 5.3
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FUTURE PERSPECTIVESThe detection of
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Du, D; Wang, M; Cai, J; Qin, Y; Zha
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Martorell, D; Cespedes, F; Fabreaga
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The Pesticide Action Network (PAN).
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About EditorMilan JokanovićProfess
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THE IMPACT OF PESTICIDESPesticides
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