INFLUENCE OF BETALAIN-RICH EXTRACT ON REDUCTION OF DISCOMFORT ASSOCIATED WITH OSTEOARTHRITIS**
Why this work is in the frame
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Bibliographic record
Abstract
Summary Introduction. Osteoarthritis (OA) subjects typically experience progressive discomfort related to pain, joint stiffness, and general tiredness. The most common treatment of these conditions includes use of non-steroidal anti-inflammatory drugs (NSAIDS). However, efficacy of NSAID treatment is generally not completely satisfactory. Therefore, further improvements in management of OA-associated discomfort are needed. Aim. The aim was to verify whether a betalain-rich red beet extract at dose range of 35-100 mg twice per day could reduce discomfort associated with osteoarthritis (OA) conditions. Materials and methods. Study participants experiencing OA symptoms were treated with red beet extract (RBE) twice per day for exactly ten days. McGill and Energy Score data were evaluated at days 1, 5 and 10. The serum levels of advanced oxidation protein products (AOPP) were measured using a commercial kit (Cell Biolabs, Inc., #STA318). Sera from volunteers treated with RBE were subjected to a cytokines and chemokines array as offered by Qynsys Inc. Results. Collected data showed that ingestion of RBE for 10 days reduced McGill scores in a time- and dose-dependent manner with maximum 33% reduction as compared to the first day of the treatment. Interestingly, due to the treatment, serum levels of TNF-alpha were reduced in subjects whose serum TNF-alpha was greater than 1 pg/mL prior to initiation of the treatment. It was also found that serum levels of AOPP (proteins oxidized by hypochlorous acid/hypochlorites) were reduced by up to 48% after 10 days of the treatment. Conclusions. This study showed that ingestion of RBE, at dosages greater than 35 mg, had a beneficial effect on pain associated with OA conditions. RBE may act by inhibiting protein oxidation typically induced by hypochlorous acid released from active neutrophils.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it