Sphingomyelinase-Like Phosphodiesterase 3b Expression Levels Determine Podocyte Injury Phenotypes in Glomerular Disease
Bibliographic record
Abstract
Diabetic kidney disease (DKD) is the most common cause of ESRD in the United States. Podocyte injury is an important feature of DKD that is likely to be caused by circulating factors other than glucose. Soluble urokinase plasminogen activator receptor (suPAR) is a circulating factor found to be elevated in the serum of patients with FSGS and causes podocyte αVβ3 integrin-dependent migration in vitro. Furthermore, αVβ3 integrin activation occurs in association with decreased podocyte-specific expression of acid sphingomyelinase-like phosphodiesterase 3b (SMPDL3b) in kidney biopsy specimens from patients with FSGS. However, whether suPAR-dependent αVβ3 integrin activation occurs in diseases other than FSGS and whether there is a direct link between circulating suPAR levels and SMPDL3b expression in podocytes remain to be established. Our data indicate that serum suPAR levels are also elevated in patients with DKD. However, unlike in FSGS, SMPDL3b expression was increased in glomeruli from patients with DKD and DKD sera-treated human podocytes, where it prevented αVβ3 integrin activation by its interaction with suPAR and led to increased RhoA activity, rendering podocytes more susceptible to apoptosis. In vivo, inhibition of acid sphingomyelinase reduced proteinuria in experimental DKD but not FSGS, indicating that SMPDL3b expression levels determined the podocyte injury phenotype. These observations suggest that SMPDL3b may be an important modulator of podocyte function by shifting suPAR-mediated podocyte injury from a migratory phenotype to an apoptotic phenotype and that it represents a novel therapeutic glomerular disease target.
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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 | 0.001 | 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".