Influence of zinc and zinc chelator on HT-29 colorectal cell line
Bibliographic record
Abstract
Trace elements are involved in many key pathways involving cell cycle control. The influence of zinc and zinc chelator (TPEN) on transcription levels of the main zinc transporters (ZnT1 and ZIP1) in the HT-29 colorectal cell line has not been reported. Proliferation of HT-29 cells was measured using the methylene blue assay after exposure to zinc (two concentrations), TPEN (two concentrations), or a combination of zinc and TPEN (simultaneously and sequentially) for 4 h, 8 h, and 24 h. The transcription levels of ZnT1, ZIP1, vascular endothelial growth factor (VEGF), and caspase-3 were determined using reverse transcriptase real-time polymerase chain reaction (RT-PCR) after exposure of cells to zinc and TPEN. The zinc content in the substrate (medium used for culture) was determined using atomic absorption spectrometry. TPEN decreased cellular proliferation causing complete cell death by 8 h. Zinc had a protective effect against short periods of exposure to TPEN. There was no correlation between the transcripts of main zinc transporters and the zinc content in the substrate. The zinc content in the substrate remained constant after varying periods of cell culture. TPEN decreased the transcript levels of caspase-3 and VEGF, which are surrogate markers for apoptosis and angiogenesis. Zinc chelation of HT-29 cells causes cell death. Zinc appears to be protective for short periods of exposure to TPEN but has no protective effect on prolonged exposure. HT-29 cells are not able to counteract the effect of intracellular chelation of zinc by altering zinc transport. Further research into the mechanisms of these findings is necessary and may lead to novel therapeutic options. © 2010 Springer Science+Business Media, LLC.
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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) | 0.001 | 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 | 0.001 |
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".