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Record W4401933617 · doi:10.1016/j.etap.2024.104545

Morphological changes in the fetal kidney induced by exposure to fluoride during pregnancy

2024· article· en· W4401933617 on OpenAlexaff
Esaú Montañez-Rodriguez, Sabino Hazael Avila-Rojas, Ariana Guadalupe Jimenez-Dorantes, Juan Carlos León‐Contreras, Rogélio Hernández‐Pando, José Manuel Arreola‐Guerra, Casimiro Gerarduzzi, María Estela Meléndez-Camargo, Luz M. Del Razo, Olivier Barbier

Bibliographic record

VenueEnvironmental Toxicology and Pharmacology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsFluoridePregnancyFetusKidneyAndrologyPhysiologyObstetricsMedicineChemistryToxicologyInternal medicineEndocrinologyBiologyGeneticsInorganic chemistry

Abstract

fetched live from OpenAlex

To determine if fluoride's established negative impact on adult kidney health begins during gestation, an intergenerational model of Wistar rats was exposed to two doses of fluoride (2.5 or 5.0 mg/kg/day via gavage) 20 days before mating and during gestation (20 days). The results revealed that fluoride was distributed to the amniotic fluid and fetus, resulting in lower weight, more pronounced fetal restriction, and decreased creatinine, osmolarity, and amniotic fluid volume. At the kidney level, less development in the nephrogenic and cortical zones was observed in the fluoride treatment groups, with an imbalance in the number of glomeruli and "S" shaped bodies, an increase in the immunoexpression of the marker of proliferation Ki-67 in the nephrogenic zone, an increase in the expression of Wnt4 and more maturation of the renal tubules, indicating that fluoride exposure during pregnancy alters kidney development and promotes early maturation of tubular segments.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

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)0.0010.000

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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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 designObservational
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

Citations6
Published2024
Admission routes1
Has abstractyes

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