Bibliographic record
Abstract
PURPOSE OF REVIEW: The vascular endothelial growth factor (VEGF) system is a multifarious network and an exemplar of an intraglomerular signalling pathway. Here, we review recent advances that highlight the subtle nature of the renal VEGF system and its influencers. RECENT FINDINGS: The VEGF system is no longer considered as a simple paracrine, ligand-receptor interaction under the regulatory control of a soluble 'decoy', soluble fms-like tyrosine kinase-1 (sFLT1). Rather, the abundantly expressed, podocyte-derived VEGF isoform, VEGF-A, is now recognized to mediate both paracrine effects across the filtration barrier and autocrine actions, functioning to preserve the integrity of the cells from which it arises. Autocrine actions of the podocyte VEGF system extend beyond those of the VEGF-A isoform, however, with sFLT1 itself now appreciated as regulating podocyte morphology by binding to lipid microdomains. These and other functions of the VEGF system are profoundly affected by the presence, nature and abundance of influencers both intrinsic and extrinsic to the pathway, the latter most readily exemplified by the role of the cytokine in the diabetic kidney. SUMMARY: The glomerular VEGF system plays a delicate, yet critical, role in preserving renal homeostasis. It may be intricate, but 'in all things of nature there is something of the marvellous'.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".