Protease-Activatable Porphyrin Molecular Beacon for Osteoarthritis Management
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Despite the substantial burden posed by osteoarthritis (OA) globally, difficult challenges remain in achieving early OA diagnosis and adopting effective disease-modifying treatments. In this study, we use a biomolecular approach to address these limitations by creating an inherently theranostic molecular beacon whose imaging and therapeutic capabilities are activated by early pathological changes in OA. This platform comprised (1) a peptide linker substrate for metalloproteinase-13 (MMP-13), a pathological protease upregulated in OA, which was conjugated to (2) a porphyrin moiety with inherent multimodal imaging, photodynamic therapy, and drug delivery capabilities, and (3) a quencher that silences the porphyrin’s endogenous fluorescence and photoreactivity when the beacon is intact. In diseased OA tissue with upregulated MMP-13 expression, this porphyrin molecular beacon (PP MMP13 B) was expected to undergo sequence-specific cleavage, yielding porphyrin fragments with restored fluorescence and photoreactivity that could, respectively, be used as a readout of MMP-13 activity within the joint for early OA imaging and disease-targeted photodynamic therapy. This study focused on the synthesis and characterization of PP MMP13 B, followed by a proof-of-concept evaluation of its OA imaging and drug delivery potential. In solution, PP MMP13 B demonstrated 90% photoactivity quenching in its intact form and robust MMP-13 activation, yielding a 13-fold increase in fluorescence post-cleavage. In vitro, PP MMP13 B was readily uptaken and activated in an MMP-13 cell expression-dependent manner in primary OA synoviocytes without exuding significant cytotoxicity. This translated into effective intra-articular cartilage (to a 50 μm depth) and synovial uptake and activation of PP MMP13 B in a destabilization of the medial meniscus OA mouse model, yielding strong fluorescence contrast (7-fold higher signal than background) at the diseased joint site. These results provide the foundation for further exploration of porphyrin molecular beacons for image-guided OA disease stratification, effective articular delivery of disease-modify agents, and OA photodynamic therapy.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".