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Record W2152888391 · doi:10.1002/jat.1448

Assessment of hair and bone accumulation of beryllium by mice exposed to contaminated dusts

2009· article· en· W2152888391 on OpenAlexafffund
Katherine Drolet‐Vives, Joseph Zayed, Sébastien Sauvé

Bibliographic record

VenueJournal of Applied Toxicology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsUniversité de Montréal
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du TravailPolytechnique Montréal
KeywordsChemistryExcretionToxicityInhalationInhalation exposureAnimal scienceInternal medicineEndocrinologyAnatomyMedicineBiologyBiochemistry

Abstract

fetched live from OpenAlex

This study looks at the accumulation of Be in the hair and bones of mice to understand both the use of hair as a bioindicator of exposure to Be and accumulation in bones as a means to evaluate the translocation of Be. We exposed two groups of mice (C3H/HeJ) to 250 microg m(-3) of two different particles sizes of Be metal (fine and intermediate; Be-F and Be-I) during 3 weeks of nose-only inhalation exposure. A control group was exposed to HEPA-filtered air. Mice were sacrificed either 1 or 3 weeks after the end of exposure. Mice were shaved and the bones were extracted. For washed hair, the results of mice sacrificed one week after the end of exposure were 8.3 + or - 1.4 microg kg(-1) hair for the control group, 114 + or - 42 microg kg(-1 )hair for the Be-I group, and 159 + or - 65 microg kg(-1) hair for the Be-F group. Results for Be-F mice sacrificed 3 weeks after the end of exposure showed an average Be concentration in washed hair of 419 + or - 100 microg kg(-1), thus suggesting that excretion of Be in hair increases with time. Be concentration in bones was 6 + or - 3 microg kg(-1) dry bone tissues for the control group, compared with 24 + or - 7 microg kg(-1) for Be-I and 34 + or - 6 or 43 + or - 8 microg kg(-1) for Be-F in mice sacrificed 1 or 3 weeks after the end of exposure. These results demonstrate the potential of using hair and bone as bioindicators of Be exposure.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.305
Teacher spread0.284 · 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

Citations9
Published2009
Admission routes2
Has abstractyes

Explore more

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