Transcriptional regulation of podocyte specification and differentiation
Bibliographic record
Abstract
Glomerular visceral epithelial cells (podocytes) are highly specialized cells found in the vertebrate and invertebrate kidney and make up a major portion of the filtration barrier between blood and urinary spaces. During development, specification and differentiation of the podocyte lineage must be tightly orchestrated to produce highly specialized characteristics such as foot processes and slit diaphragms. Furthermore, podocytes are poised to direct incoming endothelial and mesangial cells during glomerular development. They express a number of growth factors that likely play a major role in these processes. Recent findings from transgenic and knockout mouse models and the identification of genes responsible for human podocyte disease have provided insight into transcriptional regulation of some of these processes. These transcription factors include Pax2, WT1 (the Wilms tumor suppressor gene), Pod1 (capsulin, epicardin), Kreisler (maf-1), lmx1b, and mf2. Furthermore, regulatory regions from a podocyte-restricted gene, NPHS1 (nephrin) that are required to direct podocyte-specific expression have been identified from both human and murine genes and provide a tool to further dissect the transcriptional regulation of podocyte-specific gene expression. This article reviews the present state of knowledge regarding transcriptional regulation of podocyte specification and differentiation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".