MétaCan
Menu
Back to cohort
Record W4394691928 · doi:10.1080/07435800.2024.2337758

Comparison of in vitro Toxicities of 8-Prenylnaringenin, Tartrazine and 17β-Estradiol, Representatives of Natural and Synthetic Estrogens, in Rat and Human Hepatoma Cell Lines

2024· article· en· W4394691928 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEndocrine Research · 2024
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicHops Chemistry and Applications
Canadian institutionsDalhousie University
Fundersnot available
KeywordsXenoestrogenPhytoestrogensCytotoxicityEstrogenGenotoxicityMicronucleus testIn vitroCell growthCell cultureBiologyChemistryPharmacologyEndocrinologyToxicityInternal medicineBiochemistryEstrogen receptorMedicineGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Phytoestrogens have been praised for their beneficial health effects, whereas synthetic xenoestrogens have been connected to ailments. AIMS: To ascertain whether the toxicities of natural and synthetic estrogens differ, we examined the potent phytoestrogen 8-prenylnaringenin (8-PN), the common synthetic xenoestrogen tartrazine, and the physiological estrogen 17β-estradiol (E2). METHODS: These three compounds were tested for cytotoxicity, cell proliferation and genotoxicity in human HepG2 and rat H4IIE hepatoma cells. RESULTS: All three estrogens elicited cytotoxicity at high concentrations in both cell lines. They also inhibited cell proliferation, with E2 being the most effective. They all tended to increase micronuclei formation. CONCLUSION: Natural estrogens were no less toxic than a synthetic one.

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.

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 score0.094
Threshold uncertainty score0.426

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.163
GPT teacher head0.541
Teacher spread0.378 · 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