Juxtaglomerular apparatus-mediated homeostatic mechanisms: therapeutic implication for chronic kidney disease
Bibliographic record
Abstract
INTRODUCTION: Juxtaglomerular apparatus (JGA)-mediated homeostatic mechanism links to how sodium-glucose cotransporter 2 inhibitors (SGLT2is) slow progression of chronic kidney disease (CKD) and may link to how tolvaptan slows renal function decline in autosomal dominant polycystic kidney disease (ADPKD). AREA COVERED: JGA-mediated homeostatic mechanism has been hypothesized based on investigations of tubuloglomerular feedback and renin-angiotensin system. We reviewed clinical trials of SGLT2is and tolvaptan to assess the relationship between this mechanism and these drugs. EXPERT OPINION: When sodium load to macula densa (MD) increases, MD increases adenosine production, constricting afferent arteriole (Af-art) and protecting glomeruli. Concurrently, MD signaling suppresses renin secretion, increases urinary sodium excretion, and counterbalances reduced sodium filtration. However, when there is marked increase in sodium load per-nephron, as in advanced CKD, MD adenosine production increases, relaxing Af-art and maintaining sodium homeostasis at the expense of glomeruli. The beneficial effects of tolvaptan on renal function in ADPKD may also depend on the JGA-mediated homeostatic mechanisms since tolvaptan inhibits sodium reabsorption in the thick ascending limb.The JGA-mediated homeostatic mechanism regulates Af-arts, constricting to relaxing according to homeostatic needs. Understanding this mechanism may contribute to the development of pharmacotherapeutic compounds and better care for patients with CKD.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".