Contrast-enhanced x-ray microscopy of bovine articular cartilage
Bibliographic record
Abstract
Osteoarthritis (OA) is a common chronic disease of joints typically characterized by degenerative changes of articular cartilage, which is comprised of chondrocytes embedded in a composite of water-imbibing proteoglycans restrained by fibrillar collagen network. Early diagnosis of OA requires sensitive imaging, ideally at the cellular-molecular level. Whereas cartilage histopathology is destructive, time-consuming and limited to 2D views, contrast-enhanced x-ray microscopy (XRM) brings the possibility to non-destructively image the cartilage collagen network in 3D at high resolution. This study establishes a correlation between contrast-enhanced XRM and the gold-standard histology for the evaluation of the cartilage collagen network. Cartilage with subchondral bone was excised in 3 x 3 mm<sup>2</sup> cross-sectional area from healthy bovine knees and stained in phosphotungstic acid (PTA) for 0, 4, 8, 12, 16, 20, 24, 28 and 32 hours. XRM imaging was performed after each staining time, analyzed and determined an optimal staining time of 16 hrs and a saturated staining time of 24 hrs for this sample. Polarized light microscopy and second harmonic generation dual-photon microscopy of a histology section from the same sample were analyzed and compared with the matching XRM slice. Cartilage collagen network from PTA-enhanced XRM was well correlated with histology. We validated the PTAenhanced XRM for the evaluation of the cartilage collagen network non-destructively. The 3D cartilage volume from this technique will provide a non-destructive approach to investigate OA pathology.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".