The Effect of Gu-Sui-Bu (Drynaria fortunei) on Bone Cell Activity
Bibliographic record
Abstract
We investigated the effects of Gu-Sui-Bu using in vitro bone cell cultures. Primary rabbit and mouse marrow cells were cultured with or without five different concentrations of Gu-Sui-Bu extract. Osteoclast numbers were assessed using tartrate-resistant acid phosphatase (TRAP) positive cell counts and for function, osteoclast resorption pits on bovine bone slices were performed. Alkaline phosphatase (AP) positive cell counts and mineralized nodule formation were examined to assess osteoblast function with Gu-Sui-Bu. TRAP+ osteoclast numbers increased, as did the number and size of resorption pits with 0.001 mg/ml of extract. Low doses of extract did not alter AP+ colony number or mineralized nodule formation, but both were inhibited by doses of 0.1 mg/ml or higher. The highest dose of extract (10 mg/ml) inhibited proliferation of all cell types. At 0.01 and 0.001 mg/ml doses, RANKL increased over time; however, osteoprotegerin levels only increased at doses > or = 0.1 mg/ml. Resorption pit formation was decreased without alteration in mature multinucleated (TRAP+) cell counts only at the highest dose of the putative active ingredient of Gu-Sui-Bu. In summary, lower concentrations of Gu-Sui-Bu extract had positive effects on osteoclast proliferation, survival and resorptive activity that may be mediated through enhanced prostaglandin secretion. However, high doses of extract proved detrimental to osteoclast and osteoblast survival. No effect of low doses of Gu-Sui-Bu extract was seen in osteoblast cultures. High doses of the putative active ingredient of Gu-Sui-Bu showed mild inhibition of mouse osteoclast function.
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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) | 0.001 | 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".