Proteostasis as a therapeutic target in glomerular injury associated with mutant α-actinin-4
Bibliographic record
Abstract
Mutations in α-actinin-4 (actinin-4) result in hereditary focal segmental glomerulosclerosis (FSGS) in humans. Actinin-4 mutants induce podocyte injury because of dysregulation of the cytoskeleton and proteotoxicity. Injury may be associated with endoplasmic reticulum (ER) stress and polyubiquitination of proteins. We assessed if the chemical chaperone 4-phenylbutyrate (4-PBA) can ameliorate the proteotoxicity of an actinin-4 mutant. Actinin-4 K255E, which causes FSGS in humans (K256E in the mouse), showed enhanced ubiquitination, accelerated degradation, aggregate formation, and enhanced association with filamentous (F)-actin in glomerular epithelial cells (GECs). The mutant disrupted ER function and stimulated autophagy. 4-PBA reduced actinin-4 K256E aggregation and its tight association with F-actin. Transgenic mice that express actinin-4 K256E in podocytes develop podocyte injury, proteinuria, and FSGS in association with glomerular ER stress. Treatment of these mice with 4-PBA in the drinking water over a 10-wk period significantly reduced albuminuria and ER stress. Another drug, celastrol, which enhanced expression of ER and cytosolic chaperones in GECs, tended to reduce actinin-4 aggregation but did not decrease the tight association of actinin-4 K256E with F-actin and did not reduce albuminuria in actinin-4 K256E transgenic mice. Thus, chemical chaperones, such as 4-PBA, may represent a novel therapeutic approach to certain hereditary glomerular diseases.
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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 | 0.000 | 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 | 0.001 |
| 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".