Bibliographic record
Abstract
Biological functions of folic acid (FA) have been reported in various cells to include syn¬thesis and repair of DNA. We have shown that over-dosage of FA causes blood haemolysis, leading to progressive anaemia. It is reported that 200 – 400 μg/ml of FA increases the size of blood cells within 2h of treatment leading to abnormal cell division and necrosis. This observation suggests early cellular aging or senescence. We hypothesized that FA may play a vital role in cellular senescence. Kidney fibro¬blast (cos7) cells were treated with 200 μg of FA in combination with an anti-neoplastic agent, nocodazole prior to FA treatment. FA affected the expression of fibronectin (protein marker for aging) after nocodazole exposure. Further¬more, fibronectin expression was higher in FA-treated cells of the 14th generation compared to the 8th generation. 14th generation cells also showed a decrease in cell size when exposed to FA treatment. Contrasting previous results, treating cancer cells with FA showed in fact cell-beneficial effects as FA over-dosage has a noticeable effect on cell aging. However, these effects may be cell type or tissue-specific. L’espèce copépode, Tigriopus californicus, est une des espèces les plus thermiquement adapt¬ables de la biosphère. On les trouve dans les bâches depuis la côte de l’Alaska jusqu’à la côte sud de la Californie. Toutefois, comme tous les autres organ¬ismes, les Tigriopus californicus ont des limites et ne peuvent pas tolérer des températures supérieures à 34oC. En comparant l’expression génétique entre les spécimens exposés à des températures élevées et ceux exposés à des températures optimales, nous avons identifié les gènes responsables de la tolérance à des températures en hausse. Après avoir testé l’expression génétique entre les copépodes à 20oC et à 34oC, nous avons déterminé que le gène hsp70 et les récepteurs de type Toll du T. californicus jouent tous deux un rôle dans la tolérance aux variations de température.
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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) | 0.000 | 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".