Category: 637-07-0

Lewis, Robert W. published the artcileA set of six Gene expression biomarkers and their thresholds identify rat liver tumorigens in short-term assays, Safety of Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, the publication is Toxicology (2020), 152547, database is CAplus and MEDLINE.

Traditional methods for cancer risk assessment are retrospective, resource-intensive, and not feasible for the vast majority of environmental chems. In earlier studies, we used a set of six biomarkers to accurately identify liver tumorigens in transcript profiles derived from chem.-treated rats using either a Toxicol. Priority Index (ToxPi) approach or using derived biomarker thresholds for cancer. The biomarkers consisting of 7-113 genes are used to predict the most common liver cancer mol. initiating events: genotoxicity, cytotoxicity and activation of the xenobiotic receptors AhR, CAR, ER, and PPARα. In the present study, we apply and evaluate the performance of these methods for cancer prediction in an independent rat liver study of 44 chems. (6 h-7d exposures) examined by Affymetrix arrays. In the first approach, ToxPi ranking of biomarker scores consistently gave the highest scores to tumorigenic chem.-dose pairs; balanced accuracies for identification of liver tumorigenic chems. were up to 89 %. The second approach used tumorigenic thresholds derived in the present study or from our earlier study that were set at the maximum value for chem.-dose exposures without detectable liver tumor outcomes. Using these thresholds, balanced accuracies were up to 90 %. Both approaches identified all tumorigenic chems. Almost all of the tumorigenic chems. activated more than one MIE. We also compared biomarker responses between two types of profiling platforms (Affymetrix full-genome array, TempO-Seq 1500+ array containing ∼2600 genes) and found that the lack of the full set of biomarker genes on the 1500+ array resulted in decreased ability to identify chems. that activate the MIEs. Overall, these results demonstrate that predictive approaches based on the 6 biomarkers could be used in short-term assays to identify chems. and their doses that induce liver tumors, the most common endpoint in rodent bioassays.

Toxicology published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C12H15ClO3, Safety of Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Corton, J. Christopher published the artcileA set of six gene expression biomarkers identify rat liver tumorigens in short-term assays, Category: chlorides-buliding-blocks, the publication is Toxicological Sciences (2020), 177(1), 11-26, database is CAplus and MEDLINE.

Chem.-induced liver cancer occurs in rodents through well-characterized adverse outcome pathways. We hypothesized that measurement of the 6 most common mol. initiating events (MIEs) in liver cancer adverse outcome pathways in short-term assays using only gene expression will allow early identification of chems. and their associated doses that are likely to be tumorigenic in the liver in 2-yr bioassays. We tested this hypothesis using transcript data from a rat liver microarray compendium consisting of 2013 comparisons of 146 chems. administered at doses with previously established effects on rat liver tumor induction. Five MIEs were measured using previously characterized gene expression biomarkers composed of gene sets predictive for genotoxicity and activation of 1 or more xenobiotic receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Because chronic injury can be important in tumorigenesis, we also developed a biomarker for cytotoxicity that had a 96% balanced accuracy. Characterization of the genes in each biomarker set using the unsupervised TXG-MAP network model demonstrated that the genes were associated with distinct functional coexpression modules. Using the Toxicol. Priority Index to rank chems. based on their ability to activate the MIEs showed that chems. administered at tumorigenic doses clearly gave the highest ranked scores. Balanced accuracies using thresholds derived from either TG-GATES or DrugMatrix data sets to predict tumorigenicity in independent sets of chems. were up to 93%. These results show that a MIE-directed approach using only gene expression biomarkers could be used in short-term assays to identify chems. and their doses that cause tumors.

Toxicological Sciences published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C12H15ClO3, Category: chlorides-buliding-blocks.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Ahmed, Marawan published the artcileGPCR_LigandClassify.py; a rigorous machine learning classifier for GPCR targeting compounds, Computed Properties of 637-07-0, the publication is Scientific Reports (2021), 11(1), 9510, database is CAplus and MEDLINE.

The current study describes the construction of various ligand-based machine learning models to be used for drug-repurposing against the family of G-Protein Coupled Receptors (GPCRs). In building these models, we collected > 500,000 data points, encompassing exptl. measured mol. association data of > 160,000 unique ligands against > 250 GPCRs. These data points were retrieved from the GPCR-Ligand Association (GLASS) database. We have used diverse mol. featurization methods to describe the input mols. Multiple supervised ML algorithms were developed, tested and compared for their accuracy, F scores, as well as for their Matthews correlation coefficient scores (MCC). Our data suggest that combined with mol. fingerprinting, ensemble decision trees and gradient boosted trees ML algorithms are on the accuracy border of the rather sophisticated deep neural nets (DNNs)-based algorithms. On a test dataset, these models displayed an excellent performance, reaching a �90% classification accuracy. Addnl., we showcase a few examples where our models were able to identify interesting connections between known drugs from the Drug-Bank database and members of the GPCR family of receptors. Our findings are in excellent agreement with previously reported exptl. observations in the literature. We hope the models presented in this paper synergize with the currently ongoing interest of applying machine learning modeling in the field of drug repurposing and computational drug discovery in general.

Scientific Reports published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C12H15ClO3, Computed Properties of 637-07-0.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Li, Xuefei published the artcileUsing Chlorotrifluoroethane for Trifluoroethylation of (Hetero)aryl Bromides and Chlorides via Nickel Catalysis, Application of Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, the publication is Organic Letters (2021), 23(4), 1400-1405, database is CAplus and MEDLINE.

A nickel-catalyzed reductive cross-coupling between industrial chem. CF₃CH₂Cl and (hetero)aryl bromides and chlorides was reported. The reaction was synthetically simple without the preparation of arylmetals and exhibits high functional group tolerance. The utility of this protocol was demonstrated by the late-stage modification of pharmaceuticals, providing a facile route for medicinal chem.

Organic Letters published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C12H15ClO3, Application of Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Zhu, Yuting published the artcileAntidiabetic activity and metabolite profiles of ascidian Halocynthia roretzi, Safety of Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, the publication is Journal of Functional Foods (2022), 105095, database is CAplus.

Halocynthia roretzi has been cultured and utilized as a nutritious seafood in Southeastern Asia for many years because of its abundance active mols. Here, we reported that feeding of H. roretzi tissues resulted in improving oral glucose tolerance in rats. To screen the active components, we identified 950 chem. compounds from H. roretzi metabolome. Furthermore, 11 mols. with the activity of regulating blood glucose and lipids were selected based on structural identity. Among them, two natural products, hesperetin and astaxanthin were selected for further quant. detection. The results showed that concentrations of hesperetin and astaxanthin in the tissues of H. roretzi were calculated to be 13.7 ± 9.5 and 167.9 ± 48.4μg/100 g, resp. The high content of astaxanthin in H. roretzi indicates its potential roles and functions in anti-diabetes activity. Taken together, our results showed that H. roretzi could be used as a functional food supplement for regulating lipid/glucose metabolism

Journal of Functional Foods published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C15H23BO2, Safety of Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Kisui, Fumiya published the artcileStrain and sex differences in drug hydrolase activities in rodent livers, Related Products of chlorides-buliding-blocks, the publication is European Journal of Pharmaceutical Sciences (2020), 105143, database is CAplus and MEDLINE.

Carboxylesterase (CES) 1, CES2, and arylacetamide deacetylase (AADAC) are the major drug hydrolases in humans, and they have different substrate preferences. Because rodents are widely used in preclin. studies, we aimed to clarify the extent of the species, strain, and sex differences in hydrolase activity in rats and mice. Hydrolase activities for 24 compounds were evaluated in Fischer 344, Sprague-Dawley, and Wistar-Imamichi rat liver microsomes (RLM) and Balb/c, C3H/He, C57BL/6J, and ddY mouse liver microsomes (MLM) by comparing the results with the activities in human liver microsomes (HLM). Imidapril hydrolase activities in RLM from all strains were substantially higher than those in MLM and HLM, whereas oseltamivir was hardly hydrolyzed in rodents, although both are specific substrates of CES1 in humans. In rats, males tended to show higher hydrolase activities for most human CES1 substrates than females. Hydrolase activities for irinotecan and procaine, which are CES2 substrates in humans, tended to be higher in RLM and MLM than in HLM. Rifamycins, substrates of human AADAC, were not hydrolyzed in RLM and MLM. The results of this study provide important information about the species, strain, and sex differences in hydrolase activities in rats and mice.

European Journal of Pharmaceutical Sciences published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C12H15ClO3, Related Products of chlorides-buliding-blocks.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Honda, Shiori published the artcileHydrolase activities of cynomolgus monkey liver microsomes and recombinant CES1, CES2, and AADAC, COA of Formula: C12H15ClO3, the publication is European Journal of Pharmaceutical Sciences (2021), 105807, database is CAplus and MEDLINE.

The cynomolgus monkey is a nonhuman primate that is often used for pharmacokinetic and toxicokinetic studies of new chem. entities. Species differences in drug metabolism are obstacles for the extrapolation of animal data to humans. This study aimed to characterize hydrolase activities for typical compounds by cynomolgus monkey liver microsomes and recombinant monkey carboxylesterases (CES1 and CES2) and arylacetamide deacetylase (AADAC) compared with the activities in humans. To estimate the contribution of each hydrolase, the ratios of the expression level of each hydrolase in the liver microsomes and recombinant systems were used. For almost all of the tested human CES1 substrates, hydrolase activities in cynomolgus monkey liver microsomes tended to be lower than those in human liver microsomes, and recombinant cynomolgus monkey CES1 showed catalytic activity, but not for all substrates. For human CES2 substrates, hydrolase activities in cynomolgus monkey liver were higher than those in human liver microsomes, and recombinant monkey CES2 was responsible for their hydrolysis. Among human AADAC substrates, phenacetin was mainly hydrolyzed by monkey AADAC, whereas indiplon and ketoconazole were hydrolyzed by AADAC and other unknown enzymes. Flutamide was hydrolyzed by monkey CES2, not by AADAC. Rifamycins were hardly hydrolyzed in monkey liver microsomes. In conclusion, this study characterized the hydrolase activities of cynomolgus monkeys compared with those in humans. The findings would be helpful for pharmacokinetic or toxicokinetic studies of new chem. entities whose main metabolic pathway is hydrolysis.

European Journal of Pharmaceutical Sciences published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C12H15ClO3, COA of Formula: C12H15ClO3.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Honda, Shiori published the artcileDifferences in hydrolase activities in the liver and small intestine between marmosets and humans, Recommanded Product: Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, the publication is Drug Metabolism & Disposition (2021), 49(9), 718-728, database is CAplus and MEDLINE.

For drug development, species differences in drug-metabolism reactions present obstacles for predicting pharmacokinetics in humans. We characterized the species differences in hydrolases among humans and mice, rats, dogs, and cynomolgus monkeys. In this study, to expand the series of such studies, we attempted to characterize marmoset hydrolases. We measured hydrolase activities for 24 compounds using marmoset liver and intestinal microsomes, as well as recombinant marmoset carboxylesterase (CES) 1, CES2, and arylacetamide deacetylase (AADAC). The contributions of CES1, CES2, and AADAC to hydrolysis in marmoset liver microsomes were estimated by correcting the activities by using the ratios of hydrolase protein levels in the liver microsomes and those in recombinant systems. For six out of eight human CES1 substrates, the activities in marmoset liver microsomes were lower than those in human liver microsomes. For two human CES2 substrates and three out of seven human AADAC substrates, the activities in marmoset liver microsomes were higher than those in human liver microsomes. Notably, among the three rifamycins, only rifabutin was hydrolyzed by marmoset tissue microsomes and recombinant AADAC. The activities for all substrates in marmoset intestinal microsomes tended to be lower than those in liver microsomes, which suggests that the first-pass effects of the CES and AADAC substrates are due to hepatic hydrolysis. In most cases, the sums of the values of the contributions of CES1, CES2, and AADAC were below 100%, which indicated the involvement of other hydrolases in marmosets. In conclusion, we clarified the substrate preferences of hydrolases in marmosets.

Drug Metabolism & Disposition published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C12H15ClO3, Recommanded Product: Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Zorn, Kimberley M. published the artcileMachine Learning Models for Estrogen Receptor Bioactivity and Endocrine Disruption Prediction, Computed Properties of 637-07-0, the publication is Environmental Science & Technology (2020), 54(19), 12202-12213, database is CAplus and MEDLINE.

The U. S. Environmental Protection Agency (EPA) periodically releases in vitro data across a variety of targets, including the estrogen receptor (ER). In 2015, the EPA used this data to construct math. models of ER agonist and antagonist pathways to prioritize chems. for endocrine disruption testing. However, math. models require in vitro data prior to predicting estrogenic activity, but machine learning methods are capable of prospective prediction from mol. structure alone. The current study describes the generation and evaluation of Bayesian machine learning models grouped by the EPA’s ER agonist pathway model, using multiple data types with proprietary software, Assay Central. External predictions with three test sets of in vitro and in vivo reference chems. with agonist activity classifications were compared to previous math. model publications. Training datasets were subjected to addnl. machine learning algorithms and compared with rank normalized scores of internal five-fold cross-validation statistics. External predictions were found to be comparable or superior to previous studies published by the EPA. When assessing six addnl. algorithms for the training datasets, Assay CentralTM performed similarly at a reduced computational cost. This study demonstrates machine learning can prioritize chems. for future in vitro and in vivo testing of ER agonism.

Environmental Science & Technology published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C3H8N2S, Computed Properties of 637-07-0.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics

Harrill, Joshua A. published the artcileHigh-throughput transcriptomics platform for screening environmental chemicals, HPLC of Formula: 637-07-0, the publication is Toxicological Sciences (2021), 181(1), 68-89, database is CAplus and MEDLINE.

New approach methodologies (NAMs) that efficiently provide information about chem. hazard without using whole animals are needed to accelerate the pace of chem. risk assessments. Technol. advancements in gene expression assays have made in vitro high-throughput transcriptomics (HTTr) a feasible option for NAMs-based hazard characterization of environmental chems. In this study, we evaluated the Templated Oligo with Sequencing Readout (TempO-Seq) assay for HTTr concentration-response screening of a small set of chems. in the human-derived MCF7 cell model. Our exptl. design included a variety of reference samples and reference chem. treatments in order to objectively evaluate TempO-Seq assay performance. To facilitate anal. of these data, we developed a robust and scalable bioinformatics pipeline using open-source tools. We also developed a novel gene expression signature-based concentration-response modeling approach and compared the results to a previously implemented workflow for concentration-response anal. of transcriptomics data using BMDExpress. Anal. of reference samples and reference chem. treatments demonstrated highly reproducible differential gene expression signatures. In addition, we found that aggregating signals from individual genes into gene signatures prior to concentration-response modeling yielded in vitro transcriptional biol. pathway altering concentrations (BPACs) that were closely aligned with previous ToxCast high-throughput screening assays. Often these identified signatures were associated with the known mol. target of the chems. in our test set as the most sensitive components of the overall transcriptional response. This work has resulted in a novel and scalable in vitro HTTr workflow that is suitable for high-throughput hazard evaluation of environmental chems.

Toxicological Sciences published new progress about 637-07-0. 637-07-0 belongs to chlorides-buliding-blocks, auxiliary class Inhibitor,Cell Cycle,PPAR, name is Ethyl 2-(4-chlorophenoxy)-2-methylpropanoate, and the molecular formula is C12H15ClO3, HPLC of Formula: 637-07-0.

Referemce:
https://en.wikipedia.org/wiki/Chloride,
Chlorides – an overview | ScienceDirect Topics