Targeting Systemically Administered Proteins to Bone by Bisphosphonate Conjugation
Bibliographic record
Abstract
To develop a methodology for bone-specific delivery of proteins, a bone-seeking aminobisphosphonate (aminoBP) was previously conjugated to a model protein, bovine serum albumin (BSA). The conjugates were shown to exhibit a high affinity to bone in vitro and in vivo. This study was conducted to determine whether the systemic delivery of proteins to bone can be increased by aminoBP conjugation. Two model proteins used for this study were BSA and lysozyme (LYZ). For each protein, an unmodified (i.e., control) and aminoBP-conjugated protein were (125)I-labeled and injected into rats, and the organ delivery of the proteins were determined. Intravenous (IV) injection of aminoBP-BSA resulted in a 2.0- to 3.7-fold increased delivery to bones as compared to the control protein in young rats. In osteopenic, ovariectomized rats, aminoBP conjugation enhanced the bone delivery of BSA by 2.2- to 7.5-fold. A 3.7- to 5.6-fold increased delivery was also observed for LYZ after IV injection in normal rats. In addition to IV route of administration, subcutaneous injection was also effective in delivering a higher amount of aminoBP-conjugated proteins to bone. We conclude that conjugating bone-seeking aminoBPs to proteins improved their delivery to mineralized tissues. The proposed targeting approach has the potential to improve the efficacy of recombinant proteins capable of stimulating bone formation by enhancing their localization to bones.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".