Topographical variations of the strain-dependent zonal properties of tibial articular cartilage by microscopic MRI
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
The topographical variations of the zonal properties of canine articular cartilage over the medial tibia were evaluated as the function of external loading by microscopic magnetic resonance imaging (µMRI). T2 and T1 relaxation maps and GAG (glycosaminoglycan) images from a total of 70 specimens were obtained with and without the mechanical loading at 17.6 µm depth resolution. In addition, mechanical modulus and water content were measured from the tissue. For the bulk without loading, the means of T2 at magic angle (43.6 ± 8.1 ms), absolute thickness (907.6 ± 187.9 µm) and water content (63.3 ± 9.3%) on the meniscus-covered area were significantly lower than the means of T2 at magic angle (51.1 ± 8.5 ms), absolute thickness (1251.6 ± 218.4 µm) and water content (73.2 ± 5.6%) on the meniscus-uncovered area. However GAG (86.0 ± 15.3 mg/ml) on the covered area was significantly higher than GAG (70.0 ± 8.8 mg/ml) on the uncovered area. Complex relationships were found in the tissue properties as the function of external loading. The tissue parameters in the superficial zone changed more profoundly than the same properties in the radial zone. The tissue parameters in the meniscus-covered areas changed differently when comparing with the same parameters in the uncovered areas. This project confirms that the load-induced changes in the molecular distribution and structure of cartilage are both depth-dependent and topographically distributed. Such detailed knowledge of the tibial layer could improve the early detection of the subtle softening of the cartilage that will eventually lead to the clinical diseases such as osteoarthritis.
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.
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 | 0.001 |
| 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 | 0.000 |
| 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