Doxorubicin-induced glomerulosclerosis with proteinuria in GFP-GABARAP transgenic mice
Bibliographic record
Abstract
Autophagy is a process of cellular degradation, and its dysfunction elicits many pathological symptoms. However, the contribution of autophagy to kidney glomerular function has not been fully clarified. We previously reported that LC3, a promising executor of autophagy, played an important role in recovery from podocyte damage in an experimental nephrosis model (Asanuma K, Tanida I, Shirato I, Ueno T, Takahara H, Nishitani T, Kominami E, Tomino Y. FASEB J 17: 1165-1167, 2003). γ-Aminobutyric acid A receptor-associated protein (GABARAP), has recently been characterized as another homolog of LC3, although its precise role in autophagy remains unclear. We recently generated green fluorescent protein (GFP)-GABARAP transgenic mice, in which GFP-GABARAP is abundantly expressed in glomerular podocytes. We found that the transgenic mice showed no obvious phenotype, and podocytes isolated from these mice manifested autophagic activity almost equivalent to that of wild-type mice when measured in vitro. Surprisingly, a single injection of doxorubicin caused a greater increase in proteinuria and sclerotic glomeruli in transgenic mice compared with wild-type mice. Under these conditions, neither GFP-GABARAP nor endogenous GABARAP appeared to be recruited to autophagosomes, and both remained in the cytosol. Moreover, the cytosolic GFP-GABARAP was significantly colocalized with p62 to form aggregates. These results indicate that the GFP-GABARAP/p62 complex is responsible for impairment of glomerular function and that it retards recovery from the effects of doxorubicin.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".