Comparison of black, green and rooibos tea on osteoblast activity
Bibliographic record
Abstract
Globally, tea is the second most consumed beverage after water. Habitual tea intake has been associated with higher bone mineral density, particularly in postmenopausal women. This association may be due to its polyphenols and resulting protective antioxidant effects. While in vivo studies have shown improved bone outcomes with a consumption of individual purified tea polyphenols, it is unclear if a particular tea - due to its different profiles of polyphenols - is more beneficial than others. Therefore, we compared three different types of commercially available teas on osteoblasts: green, black and rooibos tea. Tea was normalized to 1 or 10 μg per mL gallic acid equivalents to assess differences in outcomes based on tea profiles rather than the quantity of polyphenol naturally present. The lower level of polyphenols (1 μg per mL gallic acid equivalents) - regardless of tea type and thus polyphenol profile - resulted in greater mineral content as well as cellular and alkaline phosphatase activity in Saos2 cells. Moreover, this was associated with higher markers of differentiation (osteopontin, sclerostin) and reduced cellular toxicity and pro-inflammatory markers (IL6, TNFα). Green, black and rooibos tea improved osteoblast activity at the low level and support epidemiological evidence suggesting tea consumption may benefit bone heath.
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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) | 0.002 | 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".