A Humanized Mouse Model of Idiopathic Nephrotic Syndrome Suggests a Pathogenic Role for Immature Cells
Bibliographic record
Abstract
Idiopathic nephrotic syndrome is characterized by glomerular proteinuria in the absence of infiltrating cells or immunoglobulin deposits. Although it is suspected that T cells secrete a circulating factor that leads to proteinuria by altering the permeability of the glomerular filtration barrier, the precise etiology of this syndrome is unknown. Because an animal model that mimics human idiopathic nephrotic syndrome does not exist, we developed a humanized mouse model of the disease by injecting CD34(+) stem cells or CD34(-) peripheral blood mononuclear cells from afflicted patients into immunocompromised mice. Even though both CD34(+) and CD34(-) cells induced the engraftment of human CD45(+) leukocytes in mice, only the injection of CD34(+) stem cells induced albuminuria. Ultrastructural analysis of glomeruli from the resulting proteinuric mice revealed effacement of podocyte foot processes, similar to the pathology observed in the human disease. Therefore, our data suggest that the cells responsible for the pathogenesis of idiopathic nephrotic syndrome are more likely to be immature differentiating cells rather than mature peripheral T cells.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".