Sex Differences in Glomerular Protein Expression and Effects of Soy-Based Diet on Podocyte Signaling
Bibliographic record
Abstract
Background: Kidney disease is a major public health issue arising from loss of glomerular podocyte function, and there are considerable sex differences in its prognosis. Evidence suggests a renoprotective effect of estrogen and soy diet-derived phytoestrogens, although the molecular basis for this is poorly understood. Objective: Here, we aim to assess sex differences in expression of key proteins associated with podocyte survival and determine the effects of dietary soy on glomerular and podocyte signaling. Methods: and until 100 days of age. Spot urine was collected to measure proteinuria and isolated glomeruli were used to quantify activated and total levels of nephrin, Akt, and ERK1/2. To investigate protective effects of specific soy phytoestrogens, cultured podocytes were treated with or without daidzein and subject to control or high glucose as a model of podocyte injury. Results: Nephrin and Akt were elevated at baseline in glomeruli from females compared to males. Both sexes that were fed 1% and 20% ISP displayed robust increases in total glomerular Akt compared to controls, and these effects were more prominent in females. A similar trend at both doses in both sexes was observed with activated Akt and total nephrin. Notably, males exclusively showed increased phosphorylation of nephrin and extracellular signal-regulated kinase (ERK) at the 1% ISP dose; however, no overt changes in urinary albumin excretion or podocin levels were observed, suggesting that the soy diets did not impair podocyte function. Finally, in cultured male and female podocytes, daidzein treatment suppressed high glucose-induced ERK activation. Conclusions: Together, our findings reveal a putative mechanism to explain the protective influence of sex on kidney disease progression, and they provide further evidence to support a beneficial role for dietary soy in preserving glomerular function.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".