Imaging of Homeostatic, Neoplastic, and Injured Tissues by HA-Based Probes
Bibliographic record
Abstract
An increase in hyaluronan (HA) synthesis, cellular uptake, and metabolism occurs during the remodeling of tissue microenvironments following injury and during disease processes such as cancer. We hypothesized that multimodality HA-based probes selectively target and detectably accumulate at sites of high HA metabolism, thus providing a flexible imaging strategy for monitoring disease and repair processes. Kinetic analyses confirmed favorable available serum levels of the probe following intravenous (i.v.) or subcutaneous (s.c.) injection. Nuclear (technetium-HA, (99m)Tc-HA, and iodine-HA, (125)I-HA), optical (fluorescent Texas Red-HA, TR-HA), and magnetic resonance (gadolinium-HA, Gd-HA) probes imaged liver ((99m)Tc-HA), breast cancer cells/xenografts (TR-HA, Gd-HA), and vascular injury ((125)I-HA, TR-HA). Targeting of HA probes to these sites appeared to result from selective HA receptor-dependent localization. Our results suggest that HA-based probes, which do not require polysaccharide backbone modification to achieve favorable half-life and distribution, can detect elevated HA metabolism in homeostatic, injured, and diseased tissues.
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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 | 0.000 | 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 | 0.000 | 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".