Analysis of Human Bone Sialoprotein in Normal and Pathological Tissues using a Monoclonal Antibody (BSP 1.2 mab)
Bibliographic record
Abstract
Bone sialoprotein (BSP), a phosphorylated and sulphated glycoprotein that is expressed by mineralized connective tissues is also produced in tumors that metastasize to bone. To facilitate studies of BSP expression in normal and pathological human tissues a monoclonal antibody (BSP 1.2 mab) was raised against human bone BSP. BSP 1.2 mab was shown by ELISA assays to recognize the epitope "DEYSY" (amino acids 279-283) that is conserved in mammalian BSP sequences. However, whereas the antibody recognized recombinant BSPs expressed in bacteria, it did not recognize native forms of rat or pig BSP in which the first tyrosine of the DEYSY peptide sequence appears to be modified. Immunostaining of embryonic human tibiae and calvariae with BSP 1.2 mab showed strong reaction in osteoblasts and osteocytes with relatively weak staining of the bone matrix, suggesting that the BSP 1.2 mab epitope is partially masked in the bone matrix. BSP 1.2 mab also stained osteosarcoma cells and normal trophoblastic cells in the placenta in areas of microcrystalline deposits. Cancer cells in primary breast tumors, lymph nodes, and secondary bone metastases from individual patients were stained strongly by BSP 1.2 mab. Although BSP 1.2 mab also stained breast cancer carcinoma cell lines and SaOS2 osteosarcoma cells, biosynthesis of radiolabelled BSP could not be demonstrated in breast cancer cells. Notably, the staining of BSP in the breast cancer cells was diffuse contrasting the punctate staining, typical of secreted proteins, in SaOS2 cells. These studies, therefore, have identified a unique epitope in human BSP recognized by a monoclonal antibody, BSP 1.2 mab, which can be used for the unequivocal identification of BSP in normal and pathological human tissues.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 0.001 |
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".