Differential effects of selenite and selenate on human melanocytes, keratinocytes, and melanoma cells
Bibliographic record
Abstract
Among the substances that attracted the attention of oncologists in recent years are selenium-containing compounds, both inorganic and organic. Several epidemiological studies have shown an inverse correlation between selenium intake and cancer incidence. In the experiments reported here, we compared the effects of 2 inorganic selenium-containing salts that differed in the level of selenium oxidation, selenite IV and selenate VI. We tested the effects of these 2 compounds on cell survival and growth, cell cycle processing, cell morphology, cytoskeleton, and lipid peroxidation in 3 human skin cell types: normal keratinocytes, melanocytes, and human melanoma cell line HTB140. The different effects of selenite and selenate on the viability, growth, and morphology of normal cells and tumor cells are reported and provide a base for future research and treatment of some neoplastic diseases. The attention is paid to cell apoptosis induced by selenite and not by selenate, and the effects of tested substances on thioredoxin reductase system are postulated.
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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".