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Record W2315354643 · doi:10.1021/es304226h

Selenomethionine Protects against Neuronal Degeneration by Methylmercury in the Developing Rat Cerebrum

2013· article· en· W2315354643 on OpenAlexaff
Mineshi Sakamoto, Akira Yasutake, Akiyoshi Kakita, Masae Ryufuku, Hing Man Chan, Megumi Yamamoto, Sanae Oumi, Sayaka Kobayashi, Chiho Watanabe

Bibliographic record

VenueEnvironmental Science & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMethylmercurySeleniumCerebrumNeurotoxicityToxicityChemistryCerebral cortexPharmacologyEndocrinologyInternal medicineCentral nervous systemBiologyMedicine

Abstract

fetched live from OpenAlex

Although many experimental studies have shown that selenium protects against methylmercury (MeHg) toxicity at different end points, the direct interactive effects of selenium and MeHg on neurons in the brain remain unknown. Our goal is to confirm the protective effects of selenium against neuronal degeneration induced by MeHg in the developing postnatal rat brain using a postnatal rat model that is suitable for extrapolating the effects of MeHg to the fetal brain of humans. As an exposure source of selenium, we used selenomethionine (SeMet), a food-originated selenium. Wistar rats of postnatal days 14 were orally administered with vehicle (control), MeHg (8 mg Hg/kg/day), SeMet (2 mg Se/kg/day), or MeHg plus SeMet coexposure for 10 consecutive days. Neuronal degeneration and reactive astrocytosis were observed in the cerebral cortex of the MeHg-group but the symptoms were prevented by coexposure to SeMet. These findings serve as a proof that dietary selenium can directly protect neurons against MeHg toxicity in the mammalian brain, especially in the developing cerebrum.

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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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".

Quick stats

Citations73
Published2013
Admission routes1
Has abstractyes

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