Expression of Concern: Laccase treatment impairs bisphenol A‐induced cancer cell proliferation affecting estrogen receptor α‐dependent rapid signals
Bibliographic record
Abstract
A wide variety of environmental contaminants exert estrogenic actions in wildlife, laboratory animals, and in human beings through binding to nuclear estrogen receptors (ERs). Here, the mechanism(s) of bisphenol A (BPA) to induce cell proliferation and the occurrence of its bioremediation by treatment with laccase are reported. BPA, highly present in natural world and considered as a model of environmental estrogen action complexity, promotes human cancer cell proliferation via ERalpha-dependent signal transduction pathways. Similar to 17beta-estradiol, BPA increases the phosphorylation of both extracellular regulated kinase and AKT. Specific inhibitors of these kinase completely block the BPA effect on cancer cell proliferation. Notably, high BPA concentrations (i.e., 0.1 and 1 mM) are cytotoxic even in ERalpha-devoid cancer cells, indicating that an ERalpha-independent mechanism participates to BPA-induced cytotoxicity. On the other hand, BPA oxidation by laccase impairs the binding of this environmental estrogen to ERalpha loosing at all ERalpha-dependent effect on cancer cell proliferation. Moreover, the laccase-catalyzed oxidation of BPA reduces the BPA cytotoxic effect. Thus, laccase appears to impair BPA action(s), representing an invaluable bioremediation enzyme.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".