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Differential Specificity of the Human and Mouse Multidrug Resistance Protein 4 (MRP4) Orthologs for Arsenic Metabolites

2016· article· en· W2554006468 on OpenAlexafffundabout
Brayden D. Whitlock, Diane P. Swanlund, X. Chris Le, John D. Schuetz, Susan P.C. Cole, Elaine M. Leslie

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsQueen's UniversityUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsArsenicMetaboliteGlutathioneCarcinogenEffluxArseniteArsenateArsenic toxicityChemistryCytotoxicityBiochemistryXenobioticPharmacologyBiologyIn vitroEnzyme

Abstract

fetched live from OpenAlex

An estimated 160 million people world‐wide are exposed to levels of arsenic in their drinking water higher than the limit of 10 ppb (10 μg/L) set by the World Health Organization. Arsenic is a Group 1 (proven) human carcinogen which causes skin, lung, and bladder tumors, and is associated with numerous other adverse health effects, including neuropathy and cardiovascular dysfunctions. Multidrug resistance proteins (MRPs/ABCCs) mediate the cellular efflux of a chemically diverse array of endogenous and xenobiotic metabolites. Substrates include glutathione (GSH) conjugates of inorganic and methylated arsenic species and dimethylarsinic acid (DMA V ). Unlike in humans, arsenic is a poor carcinogen in rodents, requiring at least 100‐fold higher doses for tumour induction. Differences in toxicokinetics between humans and other species are also well documented. We have shown that human MRP4 (hMRP4) reduces the cytotoxicity and cellular accumulation of inorganic and methylated arsenic species, and hMRP4‐enriched membrane vesicle transport studies identified the GSH conjugate of the highly toxic methylated arsenic metabolite monomethylarsonous acid (MMA III ), MMA(GS) 2 , and the major human urinary metabolite DMA V as the transported forms. The objective of the current study was to determine if mouse Mrp4 (mMrp4) conferred resistance to and/or transported the same arsenic species as hMRP4. HEK293 clonal cell lines stably expressing mMrp4 were established and used in cytotoxicity assays. Our results showed that mMrp4 did not confer resistance to any of the arsenic species tested [arsenite (As III ), arsenate (As V ), MMA III , monomethylarsonic acid (MMA V ), dimethylarsinous acid (DMA III ) or DMA V ]. Studies with mMrp4‐enriched membrane vesicles showed that unlike hMRP4, mMrp4 did not transport MMA(GS) 2 or DMA V . Thus, under the conditions tested, arsenicals are not substrates for mMrp4. These results suggest that hMRP4/mMrp4 could contribute to differences in arsenic toxicokinetics between humans and mice. Furthermore, Mrp4/Abcc4(−/−) mice are unlikely to be a relevant model for understanding the in vivo contribution of hMRP4 to arsenic detoxification and elimination. Support or Funding Information Canadian Institutes of Health Research, Alberta Innovates Health Solutions, Faculty of Medicine and Dentistry, University of Alberta

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.226
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes3
Has abstractyes

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