Podocytes Contribute to the Formation of Glomerular Crescents
Bibliographic record
Abstract
The cellular composition of crescents in glomerular disease is controversial. The role of podocytes in crescent formation has been especially difficult to study because podocytes typically lose their characteristic terminally differentiated phenotype under disease conditions, making them difficult to identify. We reasoned that the intermediate filament protein nestin, a marker of progenitor cells that has recently been identified in podocytes, may allow the investigation of podocyte involvement in glomerular crescents. In a series of 35 biopsies with crescentic glomerular disease, all showed nestin-positive cells in the crescents, ranging in number from occasional to approximately 50% of crescent cells. Other podocyte markers, such as podocin and WT1, failed to identify cells in crescents, and no contribution by endothelial or myogenic cells was noted. CD68-positive cells were observed in 80% of cases but were never as numerous as the nestin-positive cells. Nestin and CD68 were not coexpressed by the same cells, providing no evidence of trans-differentiation of podocytes into a macrophage phenotype. Keratin-positive cells were found in crescents in 51% of cases, but only as occasional cells. Up to one third of crescent cells were cycling in 48% of biopsies, and double immunostaining identified these cells as a mixture of nestin-positive cells and "null" cells (negative for nestin, CD68, and keratin). In addition to our observations in human disease, we also identified nestin-positive proliferating podocytes in the crescents of 2 mouse models of crescentic glomerulonephritis. We conclude that podocytes play a role in the formation of glomerular crescents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".