PulmoBind, an Adrenomedullin-Based Molecular Lung Imaging Tool
Bibliographic record
Abstract
UNLABELLED: Previous studies showed that adrenomedullin (AM) could be a promising agent for molecular imaging of the pulmonary circulation, with abundant specific binding sites at the pulmonary vascular endothelium. The purpose of this work was to design an AM-based compound that encompasses the desired imaging properties without posing safety issues for clinical applications. METHODS: AM analogs were synthesized through solid-phase peptide synthesis. They were evaluated for (99m)Tc labeling efficiency and in vivo lung uptake. Biodistribution and hemodynamic characteristics of the lead compound were determined in anesthetized dogs as well as by a dosimetric analysis. Lung perfusion was evaluated in the monocrotaline model of pulmonary arterial hypertension in rats. RESULTS: A cyclic AM (residues 22-52) analog encompassing a polyethylene glycol spacer and a tetrapeptide chelating moiety was found to possess the desired characteristics, with 90.7% ± 0.3% (mean ± SD) labeling efficiency, 40% lung uptake at 10 min after injection, and a favorable safety profile. Lung uptake of the (99m)Tc-labeled compound was markedly reduced in rats with pulmonary arterial hypertension. CONCLUSION: This lead compound could be a suitable clinical imaging agent for the molecular diagnosis of disorders of the pulmonary circulation.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".