Bibliographic record
Abstract
Background. Bacterial ribosomes have been considered the principal targets of tetracyclines. Recently, new clinical data has shown how other biomacromolecules are involved in the cellular damage of bacteria. Researchers are now reconsidering the pharmacological classification of tetracyclines, not only based on their semisynthetic or synthetic generations but also following the new mechanisms of action that are progressively being discovered. Materials and Methods. The toxicity properties of seven tetracycline derivatives (tetracycline, oxytetracycline, demeclocycline, chlortetracycline, doxycycline, minocycline, and meclocycline) were investigated in vitro using a cell line of human keratinocytes. Cells were irradiated in the presence of tetracyclines for different durations and at three different intensities of light. The investigation of protein oxidation was set up using model proteins to quantify the formation of carbonyl groups. Results. After incubation and irradiation with UV light, the viability of keratinocytes was assessed with half the maximal inhibitory concentration for doxycycline, demeclocycline, chlortetracycline, and tetracycline. No phototoxicity was observed for oxytetracycline, meclocycline, and minocycline. Conclusions. This study provides evidence that tetracycline’s derivatives show different photobehaviour according to their chemical properties due to different reactive groups on the same molecular skeleton.
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".