Urinary Podocyte Microparticles Identify Prealbuminuric Diabetic Glomerular Injury
Bibliographic record
Abstract
Microparticles (MPs) are small (0.1-1.0 µm) vesicles shed from the surface of cells in response to stress. Whether podocytes produce MPs and whether this production reflects glomerular injury are unclear. We examined MP formation in cultured human podocytes (hPODs) and diabetic mice. hPODs were exposed to cyclical stretch, high glucose (HG; 25 mM), angiotensin II, or TGF-β. Urinary podocyte MPs were assessed in three mouse models of diabetic nephropathy: streptozotocin (STZ)-treated, OVE26, and Akita mice. Cyclic stretch and HG increased MP release as assessed by flow cytometry (P<0.01 and P<0.05, respectively, versus controls). Inhibition of Rho-kinase (ROCK) with fasudil blocked HG-induced podocyte MP formation. STZ-treated (8 weeks) mice exhibited increased urinary podocyte MPs compared with age-matched nondiabetic mice. Similarly, 16-week-old OVE26 mice had elevated levels of urinary podocyte MPs compared with wild-type littermates (P<0.01). In 1 week post-STZ-treated and 6- and 12-week-old Akita mice, urinary podocyte MPs increased significantly compared with those MPs in nondiabetic mice, despite normal urinary albumin levels. Our results indicate that podocytes produce MPs that are released into urine. Podocyte-derived MPs are generated by exposure to mechanical stretch and high glucose in vitro and could represent early markers of glomerular injury in diabetic nephropathy.
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".