Direct mapping of kidney function by DCE-MRI urography using a tetrazinanone organic radical contrast agent
Bibliographic record
Abstract
Chronic kidney disease (CKD) and acute kidney injury (AKI) are ongoing global health burdens. Glomerular filtration rate (GFR) is the gold standard measure of kidney function, with clinical estimates providing a global assessment of kidney health without spatial information of kidney- or region-specific dysfunction. The addition of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) to the anatomical imaging already performed would yield a 'one-stop-shop' for renal assessment in cases of suspected AKI and CKD. Towards urography by DCE-MRI, we evaluated a class of nitrogen-centered organic radicals known as verdazyls, which are extremely stable even in highly reducing environments. A glucose-modified verdazyl, glucoverdazyl, provided contrast limited to kidney and bladder, affording functional kidney evaluation in mouse models of unilateral ureteral obstruction (UUO) and folic acid-induced nephropathy (FAN). Imaging outcomes correlated with histology and hematology assessing kidney dysfunction, and glucoverdazyl clearance rates were found to be a reliable surrogate measure of GFR.
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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) | 0.001 | 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".