Subchronic toxicity of chlorpropham (CIPC) in ICR mice

Fujitani, Tomoko; Tada, Yasunori; Fujii, A; Kimura, Mamoru; Yoneyama, M.

doi:10.1016/s0278-6915(00)00043-0

Cited by 7 publications

(4 citation statements)

References 19 publications

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“…Cabagna showed that toads (Bufo arenarum) exposed to pesticides in the acetochlor class displayed evidence of normochromic, normocytic anemia (Cabagna 2005). Fujitani et al studied the effects of chlorpropham in rats including splenotoxicity, anemia and methemoglobinemia (Fujitani, Tada et al 1997, Fujitani, Tada et al 2000, Fujitani, Tada et al 2001, Fujitani, Tada et al 2004. They found that some of these effects were reversible, but that hemosiderin deposition and fibrosis in the spleen were not.…”

Section: Discussionmentioning

confidence: 99%

“…REG=regenerative; nonREG=non-regenerative; NEG=negative for anemia; MIX=both regenerative and non-regenerative studies. (Fujitani, Tada et al 1997, Fujitani, Tada et al 2000, Fujitani, Tada et al 2004 105512-06-9 Clodinafop-propargyl 3 nonREG nonREG NEG nonREG (Leet, Lindberg et al 2014) 1702 (Zhang, Cai et al 2002, Tchounwou, Patlolla et al 2003, Cheng, Li et al 2004 122-39-4 Diphenylamine 4 REG REG REG REG , Yoshida, Shimoji et al 1989 80844-07-1 (Wu, Lin et al 2010, Park, Kim et al 2011, Jung, Lee et al 2013, Leet, Lindberg et al 2014 77501-63-4 (Pinkhas, Djaldetti et al 1963) Judson et al Page 48 Comparison of predicted and experimental metabolite information…”

Section: Supplementary Materialsmentioning

confidence: 99%

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Retrospective mining of toxicology data to discover multispecies and chemical class effects: Anemia as a case study

Judson

Martin

Patlewicz

et al. 2017

Regulatory Toxicology and Pharmacology

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Predictive toxicity models rely on large amounts of accurate in vivo data. Here, we analyze the quality of in vivo data from the U.S. EPA Toxicity Reference Database (ToxRefDB), using chemical-induced anemia as an example. Considerations include variation in experimental conditions, changes in terminology over time, distinguishing negative from missing results, observer and diagnostic bias, and data transcription errors. Within ToxRefDB, we use hematological data on 658 chemicals tested in one or more of 1738 studies (subchronic rat or chronic rat, mouse, or dog). Anemia was reported most frequently in the rat subchronic studies, followed by chronic studies in dog, rat, and then mouse. Concordance between studies for a positive finding of anemia (same chemical, different laboratories) ranged from 90% (rat subchronic predicting rat chronic) to 40% (mouse chronic predicting rat chronic). Concordance increased with manual curation by 20% on average. We identified 49 chemicals that showed an anemia phenotype in at least two species. These included 14 aniline moiety-containing compounds that were further analyzed for their potential to be metabolically transformed into substituted anilines, which are known anemia-causing chemicals. This analysis should help inform future use of in vivo databases for model development.

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Section: Discussionmentioning

confidence: 99%

Section: Supplementary Materialsmentioning

confidence: 99%

Retrospective mining of toxicology data to discover multispecies and chemical class effects: Anemia as a case study

Judson

Martin

Patlewicz

et al. 2017

Regulatory Toxicology and Pharmacology

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“…Although it has been reported that typical compounds causing methemoglobinemia were accompanied by a hemolytic anemia (Nair et al, 1986;Cattley et al, 1994;Hejtmancik et al, 2002), not all compounds are hemolytic, such as chlorpropham (Fujitani et al, 2000) and sodium nitrite (National Toxicology Program, 2001). …”

Section: List Of Genes That Were Exclusively Up-regulated In the Splementioning

confidence: 99%

Methemoglobinemia Induced by 1,2-Dichloro-4-nitrobenzene in Mice with a Disrupted Glutathione S-Transferase Mu 1 Gene

Arakawa¹,

Maejima²,

Kiyosawa³

et al. 2010

Drug Metab Dispos

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ABSTRACT:A specific substrate to Mu class glutathione S-transferase (GST), 1,2-dichloro-4-nitrobenzene (DCNB), was administered to mice with a disrupted GST Mu 1 gene (Gstm1-null mice) to investigate the in vivo role of murine Gstm1 in toxicological responses to DCNB. A single oral administration of DCNB at doses of 500 and 1000 mg/kg demonstrated a marked increase in blood methemoglobin (MetHB) in Gstm1-null mice but not in wild-type mice. Therefore, Gstm1-null mice were considered to be more predisposed to methemoglobinemia induced by a single dosing of DCNB. In contrast, 14-day repeated-dose studies of DCNB at doses up to 600 mg/kg demonstrated a marked increase in blood MetHB in both wild-type and Gstm1-null mice. However, marked increases in the blood reticulocyte count, relative spleen weight, and extramedullary hematopoiesis in the spleen were observed in Gstm1-null mice compared with wild-type mice. In addition, microarray and quantitative reverse transcription-polymerase chain reaction analyses in the spleen showed exclusive up-regulation of hematopoiesisrelated genes in Gstm1-null mice. These changes were considered to be adaptive responses to methemoglobinemia and attenuated the higher predisposition to methemoglobinemia observed in Gstm1-null mice in the single-dose study. In toxicokinetics monitoring, DCNB concentrations in plasma and blood cells were higher in Gstm1-null mice than those in wild-type mice, resulting from the Gstm1 disruption. In conclusion, it is suggested that the higher exposure to DCNB due to Gstm1 disruption was reflected in methemoglobinemia in the single-dose study and in adaptive responses in the 14-day repeated-dose study.

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“…Acetamiprid has been reported to mainly target the liver , where it may cause, at least in rodents, oxidative stress leading to mitochondrial dysfunction (EL-Hak et al, 2022;Siwen Li et al, 2021). Exposure to chlorpropham rather leads to adverse effects on the hematopoietic system (Arena et al, 2017;Fujitani et al, 2000Fujitani et al, , 2004. Hemotoxicity such as hemolytic anemia, however, is considered to be due 123 Pesticide mixtures in five European countries by suspect screening • Chapter 5 Chapter 5 to oxidative stress (Rokushima et al, 2007;Sivilotti, 2004).…”

Section: Co-occurrencementioning

confidence: 99%

Approaches to identify exposure to real-life chemical mixtures in the general population

Ottenbros

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Humans are exposed to large number of chemicals from various sources in their environment. Current risk assessment approaches often focus on single chemicals, sources or routes, not accounting for possible combinations of chemicals and overlooking potential additional risks associated with chemical mixtures. This thesis focusses on how to accurately measure and describe exposure patterns of chemical mixtures in the general population. Measuring exposure to chemical mixtures in real-life situations at a population level is a complex task. The preferably individual measurements can be obtained either externally (e.g. silicone wristbands) or internally (human biomonitoring). In my thesis, chemical mixtures are described as combinations of manufactured chemicals that co-occur within the same individual or sample. My thesis revolves around three different approaches to identify chemical mixtures in the general population. 1) The first approach focusses on describing co-occurrence patterns of chemicals in existing human biomonitoring datasets, combining a graphical correlation network model with a clustering algorithm. This method visualizes and summarizes these co-occurrence patterns by identifying highly correlated groups or clusters of chemicals. We demonstrated that presenting biomonitoring data in networks facilitates the identification of exposure patterns that contribute to the observed exposure levels in the samples. The application of community detection with a clustering algorithm was instrumental in identifying patterns within and between chemical families. 2) The second approach involves measuring chemical mixtures at individual level, employing external and internal measurements. 3) The third approach refers to the analytical measurement of chemical mixtures in urine samples, for which a suspect screening approach based on high resolution mass spectrometry was applied, enabling detection of a broad range of biomarkers in a single sample. The second and third approach were applied on pesticides, as an example of a mixture of chemicals. By utilization of wristbands we were able to detect multiple pesticides over a longer period of time, reflecting highly individual exposure profiles. It was demonstrated that a harmonized pan-European sample collection, combined with suspect screening provided valuable new insights into the presence of pesticide mixture exposure in the European population. Forty pesticide biomarkers corresponding to 29 different pesticides were confidently identified across six countries. Some variation but no consistent pattern in the probability of detection of pesticide biomarkers was observed based on residential location or season of urine sampling. Pesticide mixture patterns in the adult populations of the Netherlands and Switzerland were analyzed by their semi-quantitative levels. Urinary concentrations of the two most frequently detected pesticides (acetamiprid and chlorpropham) showed an inverse association with high organic vegetable and fruit consumption. In both countries, detection rates and co-occurrence of pesticides in the same urine sample were typically low. This thesis highlights the importance of understanding and measuring the mixture of chemicals we encounter. Knowledge of what these mixtures are helps us to figure out the risks to human health. I recommend to incorporate the approaches of this thesis in future studies to learn more about human exposure to chemical mixtures, and that research and sharing data is conducted in a harmonized way.

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Subchronic toxicity of chlorpropham (CIPC) in ICR mice

Cited by 7 publications

References 19 publications

Retrospective mining of toxicology data to discover multispecies and chemical class effects: Anemia as a case study

Retrospective mining of toxicology data to discover multispecies and chemical class effects: Anemia as a case study

Methemoglobinemia Induced by 1,2-Dichloro-4-nitrobenzene in Mice with a Disrupted Glutathione S-Transferase Mu 1 Gene

Approaches to identify exposure to real-life chemical mixtures in the general population

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