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Record W2080801424 · doi:10.1139/o08-120

Iron regulatory protein 1 is not an early target of cadmium toxicity in mice, but it is sensitive to cadmium stress in a human epithelial cell line

2008· article· en· W2080801424 on OpenAlexvenueno aff
Estelle Rousselet, Jean‐Marc Moulis

Bibliographic record

VenueBiochemistry and Cell Biology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsnot available
Fundersnot available
KeywordsCadmiumHomeostasisTransferrinToxicityChemistryErythropoiesisCell biologyMetallothioneinTransferrin receptorCadmium poisoningDMT1FerroportinHeLaBiologyBiochemistryCellTransporterAnemiaIron homeostasisMetabolismInternal medicineGene

Abstract

fetched live from OpenAlex

Disruption of iron homeostasis at the levels of intestinal absorption or erythropoiesis contributes to cadmium toxicity. Cellular iron homeostasis in metazoans is maintained by the iron regulatory proteins (IRPs) that regulate the synthesis of proteins involved in the transport, use, and storage of iron. The effect of cadmium intoxication on this regulatory system has been investigated in a cellular model of human epithelium. Cadmium exposure of HeLa cells did not activate the IRPs; rather, the amount of these proteins relative to that of housekeeping proteins decreased. Accordingly, the transferrin receptor mRNA level decreased upon cadmium insult. In a more integrated investigation, separate groups of mice had free access to different doses of cadmium in drinking water for 3 weeks. Cadmium accumulated in all analyzed organs, but its concentration in mouse tissues did not correlate with changes of the activity of the IRPs. The intoxicated mice did not show any sign of anemia, indicating that iron homeostasis was not immediately disrupted after the onset of cadmium accumulation. These data establish that cadmium destabilizes IRPs in mammalian cells, but that iron imbalance is not an early event of cadmium intoxication.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.002
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.228
Teacher spread0.217 · 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 teacher head, 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".

Quick stats

Citations3
Published2008
Admission routes1
Has abstractyes

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