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Relationship: 2335

Title

The title of the KER should clearly define the two KEs being considered and the sequential relationship between them (i.e., which is upstream and which is downstream). Consequently all KER titles take the form “upstream KE leads to downstream KE”.  More help

AchE Inhibition leads to Hyperglycemia

Upstream event
Upstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help
Downstream event
Downstream event in the Key Event Relationship. On the KER page, clicking on the Event name under Upstream Relationship will bring the user to that individual KE page. More help

Key Event Relationship Overview

The utility of AOPs for regulatory application is defined, to a large extent, by the confidence and precision with which they facilitate extrapolation of data measured at low levels of biological organisation to predicted outcomes at higher levels of organisation and the extent to which they can link biological effect measurements to their specific causes. Within the AOP framework, the predictive relationships that facilitate extrapolation are represented by the KERs. Consequently, the overall WoE for an AOP is a reflection in part, of the level of confidence in the underlying series of KERs it encompasses. Therefore, describing the KERs in an AOP involves assembling and organising the types of information and evidence that defines the scientific basis for inferring the probable change in, or state of, a downstream KE from the known or measured state of an upstream KE. More help

AOPs Referencing Relationship

This table is automatically generated upon addition of a KER to an AOP. All of the AOPs that are linked to this KER will automatically be listed in this subsection. Clicking on the name of the AOP in the table will bring you to the individual page for that AOP. More help
AOP Name Adjacency Weight of Evidence Quantitative Understanding Point of Contact Author Status OECD Status
Acetylcholine esterase inhibition leading to type 2 diabetes non-adjacent Moderate Low Arthur Author (send email) Under development: Not open for comment. Do not cite

Taxonomic Applicability

Select one or more structured terms that help to define the biological applicability domain of the KER. In general, this will be dictated by the more restrictive of the two KEs being linked together by the KER. Authors can indicate the relevant taxa for this KER in this subsection. The process is similar to what is described for KEs (see pages 30-31 and 37-38 of User Handbook) More help
Term Scientific Term Evidence Link
humans Homo sapiens High NCBI
mouse Mus musculus High NCBI
rat Rattus norvegicus High NCBI

Sex Applicability

Authors can indicate the relevant sex for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of the User Handbook). More help
Sex Evidence
Male High
Female Moderate

Life Stage Applicability

Authors can indicate the relevant life stage for this KER in this subsection. The process is similar to what is described for KEs (see pages 31-32 of User Handbook). More help
Term Evidence
All life stages Moderate

Key Event Relationship Description

Provide a brief, descriptive summation of the KER. While the title itself is fairly descriptive, this section can provide details that aren’t inherent in the description of the KEs themselves (see page 39 of the User Handbook). This description section can be viewed as providing the increased specificity in the nature of upstream perturbation (KEupstream) that leads to a particular downstream perturbation (KEdownstream), while allowing the KE descriptions to remain generalised so they can be linked to different AOPs. The description is also intended to provide a concise overview for readers who may want a brief summation, without needing to read through the detailed support for the relationship (covered below). Careful attention should be taken to avoid reference to other KEs that are not part of this KER, other KERs or other AOPs. This will ensure that the KER is modular and can be used by other AOPs. More help

Acetylcholine esterase (AChE) is an enzyme that metabolizes acetylcholine into choline and acetate. Organophosphate pesticides (OPPs) are well establish acetylcholine esterase (AChE) inhibitors (6, 23). Human exposure to OPPs, be it acute high-dose (e.g., a poisoning) or chronic low-dose (e.g., general population), is associated with AChE inhibition and hyperglycemia. These findings are supported by in vitro/ex vivo and in vivo data using a variety of exposure models and different OPPs.

Evidence Supporting this KER

Assembly and description of the scientific evidence supporting KERs in an AOP is an important step in the AOP development process that sets the stage for overall assessment of the AOP (see pages 49-56 of the User Handbook). To do this, biological plausibility, empirical support, and the current quantitative understanding of the KER are evaluated with regard to the predictive relationships/associations between defined pairs of KEs as a basis for considering WoE (page 55 of User Handbook). In addition, uncertainties and inconsistencies are considered. More help
Biological Plausibility
Define, in free text, the biological rationale for a connection between KEupstream and KEdownstream. What are the structural or functional relationships between the KEs? For example, there is a functional relationship between an enzyme’s activity and the product of a reaction it catalyses. Supporting references should be included. However, it is recognised that there may be cases where the biological relationship between two KEs is very well established, to the extent that it is widely accepted and consistently supported by so much literature that it is unnecessary and impractical to cite the relevant primary literature. Citation of review articles or other secondary sources, like text books, may be reasonable in such cases. The primary intent is to provide scientifically credible support for the structural and/or functional relationship between the pair of KEs if one is known. The description of biological plausibility can also incorporate additional mechanistic details that help inform the relationship between KEs, this is useful when it is not practical/pragmatic to represent these details as separate KEs due to the difficulty or relative infrequency with which it is likely to be measured (see page 40 of the User Handbook for further information).   More help

A review by Rahimi and Abdollahi supports the association between OPP exposure and decreased glycogenesis, increased glycogenolysis, and decreased glycolysis (39). Importantly, the authors highlighted that these changes were observed across multiple tissues including brain, hepatic, and muscle. These data suggest that OPP-induced hyperglycemia is the result of global changes to glucose metabolism and storage that point towards an increase in blood glucose. Other reviews have commented on the association between OPP exposure and hyperglycemia in humans (7, 54) and in research animals (7, 18). Overall, the exact mechanism(s) of action remain to be elucidated.

Uncertainties and Inconsistencies
In addition to outlining the evidence supporting a particular linkage, it is also important to identify inconsistencies or uncertainties in the relationship. Additionally, while there are expected patterns of concordance that support a causal linkage between the KEs in the pair, it is also helpful to identify experimental details that may explain apparent deviations from the expected patterns of concordance. Identification of uncertainties and inconsistencies contribute to evaluation of the overall WoE supporting the AOPs that contain a given KER and to the identification of research gaps that warrant investigation (seep pages 41-42 of the User Handbook).Given that AOPs are intended to support regulatory applications, AOP developers should focus on those inconsistencies or gaps that would have a direct bearing or impact on the confidence in the KER and its use as a basis for inference or extrapolation in a regulatory setting. Uncertainties that may be of academic interest but would have little impact on regulatory application don’t need to be described. In general, this section details evidence that may raise questions regarding the overall validity and predictive utility of the KER (including consideration of both biological plausibility and empirical support). It also contributes along with several other elements to the overall evaluation of the WoE for the KER (see Section 4 of the User Handbook).  More help

Though some biochemical pathways have been elucidated, the mechanism(s) of action that associate OPP-induced AChE inhibition with hyperglycemia are not fully understood. Further, AChE knock-out mice are normoglycemic relative to wildtype mice (8), suggesting possible compensatory glucose homeostatic mechanism(s) in these transgenic mice.

The in vivo rodent exposure data reviewed highlighted two studies that found that co-exposure to an AChR antagonist prevented OPP-induced hyperglycemia (15, 16). These data are difficult to interpret as they implicate the cholinergic system, a known modulator of pancreatic insulin secretion (27), which modulates blood glucose concentrations.

Though most of the in vivo rodent exposure data is consistent, one study found that exposure to a high dose of malathion (100 mg/kg/day) for >30 days did not cause hyperglycemia (41). However, these must be interpreted with caution as it was a single measurement that was not done under fasting conditions.

Relative to other organic pollutants, most OPPs have short half-lives (14) making it difficult to measure in human serum. This impedes the accurate modeling of human OPP exposure for in vivo and in vitro/ex vivo exposure studies.

Response-response Relationship
This subsection should be used to define sources of data that define the response-response relationships between the KEs. In particular, information regarding the general form of the relationship (e.g., linear, exponential, sigmoidal, threshold, etc.) should be captured if possible. If there are specific mathematical functions or computational models relevant to the KER in question that have been defined, those should also be cited and/or described where possible, along with information concerning the approximate range of certainty with which the state of the KEdownstream can be predicted based on the measured state of the KEupstream (i.e., can it be predicted within a factor of two, or within three orders of magnitude?). For example, a regression equation may reasonably describe the response-response relationship between the two KERs, but that relationship may have only been validated/tested in a single species under steady state exposure conditions. Those types of details would be useful to capture.  More help
Time-scale
This sub-section should be used to provide information regarding the approximate time-scale of the changes in KEdownstream relative to changes in KEupstream (i.e., do effects on KEdownstream lag those on KEupstream by seconds, minutes, hours, or days?). This can be useful information both in terms of modelling the KER, as well as for analyzing the critical or dominant paths through an AOP network (e.g., identification of an AO that could kill an organism in a matter of hours will generally be of higher priority than other potential AOs that take weeks or months to develop). Identification of time-scale can also aid the assessment of temporal concordance. For example, for a KER that operates on a time-scale of days, measurement of both KEs after just hours of exposure in a short-term experiment could lead to incorrect conclusions regarding dose-response or temporal concordance if the time-scale of the upstream to downstream transition was not considered. More help
Known modulating factors
This sub-section presents information regarding modulating factors/variables known to alter the shape of the response-response function that describes the quantitative relationship between the two KEs (for example, an iodine deficient diet causes a significant increase in the slope of the relationship; a particular genotype doubles the sensitivity of KEdownstream to changes in KEupstream). Information on these known modulating factors should be listed in this subsection, along with relevant information regarding the manner in which the modulating factor can be expected to alter the relationship (if known). Note, this section should focus on those modulating factors for which solid evidence supported by relevant data and literature is available. It should NOT list all possible/plausible modulating factors. In this regard, it is useful to bear in mind that many risk assessments conducted through conventional apical guideline testing-based approaches generally consider few if any modulating factors. More help
Known Feedforward/Feedback loops influencing this KER
This subsection should define whether there are known positive or negative feedback mechanisms involved and what is understood about their time-course and homeostatic limits? In some cases where feedback processes are measurable and causally linked to the outcome, they should be represented as KEs. However, in most cases these features are expected to predominantly influence the shape of the response-response, time-course, behaviours between selected KEs. For example, if a feedback loop acts as compensatory mechanism that aims to restore homeostasis following initial perturbation of a KE, the feedback loop will directly shape the response-response relationship between the KERs. Given interest in formally identifying these positive or negative feedback, it is recommended that a graphical annotation (page 44) indicating a positive or negative feedback loop is involved in a particular upstream to downstream KE transition (KER) be added to the graphical representation, and that details be provided in this subsection of the KER description (see pages 44-45 of the User Handbook).  More help

Domain of Applicability

As for the KEs, there is also a free-text section of the KER description that the developer can use to explain his/her rationale for the structured terms selected with regard to taxonomic, life stage, or sex applicability, or provide a more generalizable or nuanced description of the applicability domain than may be feasible using standardized terms. More help

Taxonomy: AChE and blood glucose are present in vertebrates and their functional equivalents in invertebrates. However, only human, mouse, and rat data was reviewed.

Life Stage: AChE and blood glucose are present throughout all life stages. However, almost all of the data reviewed was in adults.

Sex Applicability: AChE and blood glucose are present in males and females. However, most of the data reviewed was from male rodents.

References

List of the literature that was cited for this KER description using the appropriate format. Ideally, the list of references should conform, to the extent possible, with the OECD Style Guide (OECD, 2015). More help

1.        Abdollahi M, Donyavi M, Pournourmohammadi S, Saadat M. Hyperglycemia associated with increased hepatic glycogen phosphorylase and phosphoenolpyruvate carboxykinase in rats following subchronic exposure to malathion. Comp Biochem Physiol - C Toxicol Pharmacol 137: 343–347, 2004. doi: 10.1016/j.cca.2004.03.009.

2.        Ather N, Ara J, Khan E, Sattar R, Durrani R. Acute organophosphate insecticide poisoning. J Surg Pakistan 13: 71–74, 2008.

3.        Badrane N, Askour M, Berechid K, Abidi K, Dendane T, Zeggwagh AA. Severe oral and intravenous insecticide mixture poisoning with diabetic  ketoacidosis: a case report. BMC Res Notes 7: 485, 2014. doi: 10.1186/1756-0500-7-485.

4.        Coban A, Carr RL, Chambers HW, Willeford KO, Chambers JE. Comparison of inhibition kinetics of several organophosphates, including some nerve agent surrogates, using human erythrocyte and rat and mouse brain acetylcholinesterase. Toxicol Lett 248: 39–45, 2016. doi: 10.1016/j.toxlet.2016.03.002.

5.        Çolak Ş, Erdoğan MÖ, Baydin A, Afacan MA, Kati C, Duran L. Epidemiology of organophosphate intoxication and predictors of intermediate  syndrome. Turkish J Med Sci 44: 279–282, 2014. doi: 10.3906/sag-1211-31.

6.        Costa LG. Organophosphorus Compounds at 80: Some Old and New Issues. Toxicol Sci 162: 24–35, 2018. doi: 10.1093/toxsci/kfx266.

7.        Czajka M, Matysiak-Kucharek M, Jodłowska-Jędrych B, Sawicki K, Fal B, Drop B, Kruszewski M, Kapka-Skrzypczak L. Organophosphorus pesticides can influence the development of obesity and type 2 diabetes with concomitant metabolic changes. Environ Res 178: 108685, 2019. doi: https://doi.org/10.1016/j.envres.2019.108685.

8.        Duysen EG, Stribley JA, Fry DL, Hinrichs SH, Lockridge O. Rescue of the acetylcholinesterase knockout mouse by feeding a liquid diet; phenotype of the adult acetylcholinesterase deficient mouse. Dev Brain Res 137: 43–54, 2002. doi: https://doi.org/10.1016/S0165-3806(02)00367-X.

9.        Faiz MS, Mughal S, Memon AQ. Acute and late complications of organophosphate poisoning. J Coll Physicians Surg Pak 21: 288–290, 2011.

10.      Ghafour-Rashidi Z, Dermenaki-Farahani E, Aliahmadi A, Esmaily H, Mohammadirad A, Ostad SN, Abdollahi M. Protection by cAMP and cGMP phosphodiesterase inhibitors of diazinon-induced hyperglycemia and oxidative/nitrosative stress in rat Langerhans islets cells: Molecular evidence for involvement of non-cholinergic mechanisms. Pestic Biochem Physiol 87: 261–270, 2007. doi: 10.1016/j.pestbp.2006.08.007.

11.      Gifford RM, Chathuranga U, Lamb T, Verma V, Sattar MA, Thompson A, Siribaddana S, Ghose A, Forbes S, Reynolds RM, Eddleston M. Short-term glucose dysregulation following acute poisoning with organophosphorus insecticides but not herbicides, carbamate or pyrethroid insecticides in South Asia. Clin Toxicol 57: 254–264, 2019. doi: 10.1080/15563650.2018.1515438.

12.      Hagar HH, Fahmy AH. A biochemical, histochemical, and ultrastructural evaluation of the effect of dimethoate intoxication on rat pancreas. Toxicol Lett 133: 161–170, 2002. doi: 10.1016/S0378-4274(02)00128-5.

13.      Hayes MMM, Van Der Westhuizen NG, Gelfand M. Organophosphate poisoning in Rhodesia. A study of the clinical features and management of 105 patients. South African Med J 54: 230–234, 1978.

14.      Hoffmann U, Papendorf T. Organophosphate poisonings with parathion and dimethoate. Intensive Care Med 32: 464–468, 2006. doi: 10.1007/s00134-005-0051-z.

15.      Husain K, Ansari RA. Influence of cholinergic and adrenergic blocking drugs on hyperglycemia and brain glycogenolysis in diazinon-treated animals. Can J Physiol Pharmacol 66: 1144–1147, 1988. doi: 10.1139/y88-188.

16.      Joshi AKR, Nagaraju R, Rajini PS. Insights into the mechanisms mediating hyperglycemic and stressogenic outcomes in rats treated with monocrotophos, an organophosphorus insecticide. Toxicology 294: 9–16, 2012. doi: 10.1016/j.tox.2012.01.009.

17.      Joshi AKR, Rajini PS. Hyperglycemic and stressogenic effects of monocrotophos in rats: Evidence for the involvement of acetylcholinesterase inhibition. Exp Toxicol Pathol 64: 115–120, 2012. doi: 10.1016/j.etp.2010.07.003.

18.      Joshi AKR, Sukumaran BO. Metabolic dyshomeostasis by organophosphate insecticides: insights from experimental and human studies. EXCLI J 18: 479–484, 2019. doi: 10.17179/excli2019-1492.

19.      Kamath V, Rajini PS. Altered glucose homeostasis and oxidative impairment in pancreas of rats subjected to dimethoate intoxication. Toxicology 231: 137–146, 2007. doi: 10.1016/j.tox.2006.11.072.

20.      Kempegowda P. Glycemic changes in acute anticholinesterase insecticide poisoning. West Lond Med J 5: 27–33, 2013.

21.      Lasram MM, Annabi AB, Rezg R, Elj N, Slimen S, Kamoun A, El-Fazaa S, Gharbi N. Effect of short-time malathion administration on glucose homeostasis in Wistar rat. Pestic Biochem Physiol 92: 114–119, 2008. doi: 10.1016/j.pestbp.2008.06.006.

22.      Leonel Javeres MN, Raza S, Judith N, Anwar F, Habib R, Batool S, Nurulain SM. Mixture of Organophosphates Chronic Exposure and Pancreatic Dysregulations in Two Different Population Samples. Front public Heal 8: 534902, 2020. doi: 10.3389/fpubh.2020.534902.

23.      Marrs TC. Organophosphate poisoning. Pharmacol Ther 58: 51–66, 1993. doi: 10.1016/0163-7258(93)90066-M.

24.      Matin MA, Husain K, Khan SN. Modification of diazinon-induced changes in carbohydrate metabolism by adrenalectomy in rats. Biochem Pharmacol 39: 1781–1786, 1990. doi: 10.1016/0006-2952(90)90125-5.

25.      Matin MA, Siddiqui RA. Effect of diacetylmonoxime and atropine on malathion-induced changes in blood glucose level and glycogen content of certain brain structures of rats. Biochem Pharmacol 31: 1801–1803, 1982. doi: 10.1016/0006-2952(82)90692-X.

26.      Meller D, Fraser I, Kryger M. Hyperglycemia in anticholinesterase poisoning. Can Med Assoc J 124: 745–748, 1981.

27.      Molina J, Rodriguez-Diaz R, Fachado A, Jacques-Silva MC, Berggren PO, Caicedo A. Control of insulin secretion by cholinergic signaling in the human pancreatic islet. Diabetes 63: 2714–2726, 2014. doi: 10.2337/db13-1371.

28.      Moore PG, James OF. Acute pancreatitis induced by acute organophosphate poisoning. Postgrad Med J 57: 660–662, 1981. doi: 10.1136/pgmj.57.672.660.

29.      Nagaraju R, Kumar A, Joshi R, Rajini PS. Organophosphorus insecticide, monocrotophos, possesses the propensity to induce insulin resistance in rats on chronic exposure. J Diabetes 7: 47–59, 2015. doi: 10.1111/1753-0407.12158.

30.      Nagaraju R, Rajini PS. Adaptive response of rat pancreatic β -cells to insulin resistance induced by monocrotophos : Biochemical evidence. YPEST 134: 39–48, 2016. doi: 10.1016/j.pestbp.2016.04.009.

31.      Nili-Ahmadabadi A, Pourkhalili N, Fouladdel S, Pakzad M, Mostafalou S, Hassani S, Baeeri M, Azizi E, Ostad SN, Hosseini R, Sharifzadeh M, Abdollahi M. On the biochemical and molecular mechanisms by which malathion induces dysfunction in pancreatic islets in vivo and in vitro. Pestic Biochem Physiol 106: 51–60, 2013. doi: 10.1016/j.pestbp.2013.04.003.

32.      Oztürk MA, Keleştimur F, Kurtoğlu S, Güven K, Arslan D. Anticholinesterase poisoning in Turkey--clinical, laboratory and radiologic  evaluation of 269 cases. Hum Exp Toxicol 9: 273–279, 1990. doi: 10.1177/096032719000900503.

33.      Pakzad M, Fouladdel S, Nili-Ahmadabadi A, Pourkhalili N, Baeeri M, Azizi E, Sabzevari O, Ostad SN, Abdollahi M. Sublethal exposures of diazinon alters glucose homostasis in Wistar rats: Biochemical and molecular evidences of oxidative stress in adipose tissues. Pestic Biochem Physiol 105: 57–61, 2013. doi: 10.1016/j.pestbp.2012.11.008.

34.      Panahi P, Vosough-Ghanbari S, Pournourmohammadi S, Ostad SN, Nikfar S, Minaie B, Abdollahi M. Stimulatory effects of malathion on the key enzymes activities of insulin secretion in Langerhans islets, glutamate dehydrogenase and glucokinase. Toxicol Mech Methods 16: 161–167, 2006. doi: 10.1080/15376520500191623.

35.      Panda S, Nanda R, Mangaraj M, Rathod PK, Mishra PK. Glycemic Status in Organophosphorus Poisoning. J Nepal Health Res Counc 13: 214–219, 2015.

36.      Pournourmohammadi S, Farzami B, Ostad SN, Azizi E, Abdollahi M. Effects of malathion subchronic exposure on rat skeletal muscle glucose metabolism. Environ Toxicol Pharmacol 19: 191–196, 2005. doi: 10.1016/j.etap.2004.07.002.

37.      Pournourmohammadi S, Ostad SN, Azizi E, Ghahremani MH, Farzami B, Minaie B, Larijani B, Abdollahi M. Induction of insulin resistance by malathion: Evidence for disrupted islets cells metabolism and mitochondrial dysfunction. Pestic Biochem Physiol 88: 346–352, 2007. doi: 10.1016/j.pestbp.2007.02.001.

38.      Raafat N, Abass MA, Salem HM. Malathion exposure and insulin resistance among a group of farmers in Al-Sharkia governorate. Clin Biochem 45: 1591–1595, 2012. doi: 10.1016/j.clinbiochem.2012.07.108.

39.      Rahimi R, Abdollahi M. A review on the mechanisms involved in hyperglycemia induced by organophosphorus pesticides. 88: 115–121, 2007. doi: 10.1016/j.pestbp.2006.10.003.

40.      Rao R, Raju G. Random blood sugar levels and pseudocholinesterase levels their relevance in organophosphorus compound poisoning. Int J Community Med Public Heal 3: 2757–2761, 2016.

41.      Rezg R, Mornagui B, El-Arbi M, Kamoun A, El-Fazaa S, Gharbi N. Effect of subchronic exposure to malathion on glycogen phosphorylase and hexokinase activities in rat liver using native PAGE. Toxicology 223: 9–14, 2006. doi: 10.1016/j.tox.2006.02.020.

42.      Rivera JA, Rivera M. Organophosphate poisoning. Bol Asoc Med P R 82: 419–422, 1990.

43.      Sarin S, Gill KD. Dichlorvos induced alterations in glucose homeostasis: Possible implications on the state of neuronal function in rats. Mol Cell Biochem 199: 87–92, 1999. doi: 10.1023/A:1006930511459.

44.      Seifert J. Toxicologic Significance of the Hyperglycemia Caused by Organophosphorous Insecticides. Bull Environ Contam Toxicol 67: 0463–0469, 2001. doi: 10.1007/s00128-001-0146-3.

45.      Singh S, Bhardwaj U, Verma SK, Bhalla A, Gill K. Hyperamylasemia and acute pancreatitis following anticholinesterase poisoning. Hum Exp Toxicol 26: 467–471, 2007. doi: 10.1177/0960327107076814.

46.      Sungur M, Güven M. Intensive care management of organophosphate insecticide poisoning. Crit Care 5: 211–215, 2001. doi: 10.1186/cc1025.

47.      Swaminathan K, Sundaram M, Prakash P, Subbiah S. Diabetic ketoacidosis: an uncommon manifestation of pesticide poisoning. Diabetes Care 36: e4–e4, 2013. doi: 10.2337/dc12-1251.

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49.      Teimouri F, Amirkabirian N, Esmaily H, Mohammadirad A, Aliahmadi A, Abdollahi M. Alteration of hepatic cells glucose metabolism as a non-cholinergic detoxication mechanism in counteracting diazinon-induced oxidative stress. Hum Exp Toxicol 25: 697–703, 2006. doi: 10.1177/0960327106075064.

50.      Tuzcu K, Alp H, Ozgur T, Karcioglu M, Davarci I, Evliyaoglu O, Karakus A, Hakimoglu S. Oral intralipid emulsion use: A novel therapeutic approach to pancreatic β-cell injury caused by malathion toxicity in rats. Drug Chem Toxicol 37: 261–267, 2014. doi: 10.3109/01480545.2013.838780.

51.      Wang C, Murphy SD. Kinetic analysis of species difference in acetylcholinesterase sensitivity to organophosphate insecticides. Toxicol Appl Pharmacol 66: 409–419, 1982. doi: https://doi.org/10.1016/0041-008X(82)90307-6.

52.      Weizman Z, Sofer S. Acute pancreatitis in children with anticholinesterase insecticide intoxication. Pediatrics 90: 204–206, 1992.

53.      Wiesner J, Kriz Z, Kuca K, Jun D, Koca J. Acetylcholinesterases--the structural similarities and differences. J Enzyme Inhib Med Chem 22: 417–424, 2007. doi: 10.1080/14756360701421294.

54.      Xiao X, Clark JM, Park Y. Potential contribution of insecticide exposure and development of obesity and type 2 diabetes. Food Chem Toxicol 105: 456–474, 2017. doi: 10.1016/j.fct.2017.05.003.

55.      Yanagisawa N, Morita H, Nakajima T. Sarin experiences in Japan: acute toxicity and long-term effects. J Neurol Sci 249: 76–85, 2006. doi: 10.1016/j.jns.2006.06.007.

56.      Yurumez Y, Durukan P, Yavuz Y, Ikizceli I, Avsarogullari L, Ozkan S, Akdur O, Ozdemir C. Acute Organophosphate Poisoning in University Hospital Emergency Room Patients. Intern Med 46: 965–969, 2007. doi: 10.2169/internalmedicine.46.6304.

57.      Zadik Z, Blachar Y, Barak Y, Levin S. Organophosphate poisoning presenting as diabetic ketoacidosis. J Toxicol Clin Toxicol 20: 381–385, 1983. doi: 10.3109/15563658308990606.