Response of cartilage explants to LPS cultured in normoxic and hypoxic conditions is modulated by Spirulina: implications for exercise recovery in vivo
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Exercise-induced inflammation and free radical production are crucial for recovery, yet excess inflammation poses risks to equine athletes, leading to conditions like arthritis. Spirulina, recognized for its antioxidant and anti-inflammatory properties, could mitigate degenerative diseases without hindering post-exercise recovery. This study investigates Spirulina’s direct impact on cartilage responses to LPS-induced inflammation in normoxic and hypoxic conditions, focusing on outcomes relevant to cartilage matrix turnover and exercise-induced inflammation. Spirulina underwent simulated digestion and liver metabolism, yielding a simulated biological extract (SPsim). In the normoxic experiment, porcine cartilage explants were cultured with SPsim (0, 30, or 90 μg/mL) for 72 h after 24 h in basal media, with LPS (0 or 10 μg/mL) added for the final 48 h. The hypoxic experiment mirrored this, with explants transferred to a hypoxia chamber for the final 48 h. Media samples collected at 0, 24, and 48 h were analyzed for biomarkers related to cartilage turnover (GAG), and exercise-induced inflammation (IL-6 and NO). Cell viability, assessed by live:dead staining, remained > 97% and unaffected by oxygen tension. In normoxic conditions, SPsim (30 μg/mL) significantly reduced GAG release at 48 h. Under hypoxia, SPsim (30 and 90 μg/mL) inhibited LPS-induced GAG release. SPsim (90 μg/mL) increased IL-6 and NO production in LPS-stimulated explants in normoxia, and a similar effect was observed with the lower SPsim dose (30 μg/mL) in hypoxic conditions. These results suggest that Spirulina may enhance cartilage mediators, potentially promoting healthy cartilage turnover during exercise recovery.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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