Non-invasive electroarthrography measures cartilage in live horses and correlates to direct measurements of cartilage streaming potentials in weight bearing regions of equine metacarpophalangeal joints
Bibliographic record
Abstract
OBJECTIVE: To perform non-invasive Electroarthrography (EAG) on live horses and establish relationships between EAG and direct measurements of cartilage streaming potentials in weight bearing areas of the equine metacarpophalangeal joint. DESIGN: EAG was performed bilaterally on the metacarpophalangeal joints of live horses (n = 3). Separate experiments used metacarpophalangeal joint explants (n = 11) to measure EAG obtained during simulated loading followed by direct measurements of cartilage streaming potentials on joint surfaces using the Arthro-BST probe. Joints were assigned to relatively normal (n = 5) and mildly degraded (n = 6) groups based on histological scoring of Safranin-O/Fast Green stained sections. RESULTS: EAG, involving application of electrodes to skin surrounding the joint and repeated weight shifting, was well-tolerated in live horses. One pair of distal forelimbs were available for analogous ex vivo EAG testing and measurements were strongly correlated to in vivo EAG measurements obtained on the same joints (r = 0.804, p = 0.016, n = 8). Both indirect (EAG) and direct (Arthro-BST) measurements of cartilage streaming potentials distinguished between normal and mildly degraded cartilage with statistically significant differences at 5 of 6 and 4 of 6 electrodes during simulated standing and walking, respectively. Strong and moderate correlations for weight bearing regions on the dorsal phalanx and central metacarpus were detected during both standing and walking. At the metacarpus/sesamoid interface a moderate correlation occurred during walking. CONCLUSION: Non-invasive EAG was used successfully in a clinical scenario and correlated to direct measurements of streaming potentials in weight bearing cartilage. These data support the potential of EAG to contribute to the diagnosis and treatment of degenerative joint diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".