Osteolytic and mixed cancer metastasis modulates collagen and mineral parameters within rat vertebral bone matrix
Bibliographic record
Abstract
Metastatic involvement in vertebral bone diminishes the mechanical integrity of the spine; however minimal data exist on the potential impact of metastases on the intrinsic material characteristics of the bone matrix. Thirty-four (34) female athymic rats were inoculated with HeLa (N = 17) or Ace-1 (N = 17) cancer cells lines producing osteolytic or mixed (osteolytic and osteoblastic) metastases, respectively. A maximum of 21 days was allowed between inoculation and rat sacrifice for vertebrae extraction. High performance liquid chromatography (HPLC) was utilized to determine modifications in collagen-I parameters such as proline hydroxylation and the formation of specific enzymatic and non-enzymatic (pentosidine) cross-links. Raman spectroscopy was used to determine relative changes in mineral crystallinity, mineral carbonation, mineral/collagen matrix ratio, collagen quality ratio, and proline hydroxylation. HPLC results showed significant increase in the formation of pentosidine and decrease in the formation of the enzymatic cross-link deoxy-pryridinoline within osteolytic bone compared to mixed bone. Raman results showed decreased crystallinity, increased carbonation, and collagen quality (aka 1660/1690 sub-band) ratio with osteolytic bone compared to mixed bone and healthy controls along with an observed increase in proline hydroxylation with metastatic involvement. The mineral/matrix ratio decreased in both osteolytic and mixed bone compared to healthy controls. Quantifying modifications within the intrinsic characteristics of bone tissue will provide a foundation to assess the impact of current therapies on the material behavior of bone tissue in the metastatic spine and highlight targets for the development of new therapeutics and approaches for treatment. © 2016 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 34:2126-2136, 2016.
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 | 0.002 | 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 | 0.000 |
| 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 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".