Microvascular aberrations found in human polycystic kidneys are an early feature in a <i>Pkd1</i> mutant mouse model
Bibliographic record
Abstract
Therapies targeting blood vessels hold promise for autosomal dominant polycystic kidney disease (ADPKD), the most common inherited disorder causing kidney failure. However, the onset and nature of kidney vascular abnormalities in ADPKD are poorly defined. Accordingly, we employed a combination of single-cell transcriptomics; three-dimensional imaging with geometric, topological and fractal analyses; and multimodal magnetic resonance imaging with arterial spin labelling to investigate aberrant microvasculature in ADPKD kidneys. Within human ADPKD kidneys with advanced cystic pathology and excretory failure, we identified a molecularly distinct blood microvascular subpopulation, characterised by impaired angiogenic signalling and metabolic dysfunction, differing from endothelial injury profiles observed in non-cystic human kidney diseases. Next, Pkd1 mutant mouse kidneys were examined postnatally, when cystic pathology is well established, but before excretory failure. An aberrant endothelial subpopulation was also detected, concurrent with reduced cortical blood perfusion. Disorganised kidney cortical microvasculature was also present in Pkd1 mutant mouse fetal kidneys when tubular dilation begins. Thus, aberrant features of cystic kidney vasculature are harmonised between human and mouse ADPKD, supporting early targeting of the vasculature as a strategy to ameliorate ADPKD progression.
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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".