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Record W4412559155 · doi:10.34067/kid.0000000929

Interplay Between the Mineralocorticoid System, Inflammation, Hypertension, and Kidney Disease

2025· article· en· W4412559155 on OpenAlexafffund
Eviatar Fields, Ernesto L. Schiffrin

Bibliographic record

VenueKidney360 · 2025
Typearticle
Languageen
FieldMedicine
TopicHormonal Regulation and Hypertension
Canadian institutionsJewish General HospitalMcGill University
FundersInstitute of Circulatory and Respiratory HealthCanadian Institutes of Health ResearchMcGill University
KeywordsAldosteroneMineralocorticoid receptorEndocrinologyInternal medicineMineralocorticoidAngiotensin IIKidneyInflammationMedicineReceptorBiology

Abstract

fetched live from OpenAlex

Aldosterone, produced by adrenal glomerulosa cells, stimulated by angiotensin II, adrenocorticotrophin, and potassium, and inhibited by natriuretic peptides, plays a role in hypertension and CKD development and progression. Its effects are mediated by nuclear mineralocorticoid receptors inducing genomic effects and putatively by a membrane G-protein-coupled receptor which could be the G-protein-coupled estrogen receptor, triggering nongenomic actions. The classical effect of aldosterone is on the distal nephron to retain Na + and water and excrete potassium, contributing to electrolyte and extracellular volume control. However, aldosterone also acts by stimulating oxidative stress through different signaling pathways that include tyrosine kinases and mitogen-activated protein kinases to induce inflammation and fibrosis in blood vessels, the kidney, and the heart. The actions of aldosterone also lead to endothelial dysfunction, which participates in its effects on target organs, including progression of hypertension. Blockade of mineralocorticoid receptor or inhibition of aldosterone generation lowers BP and protects target organs, reducing progression of CKD. All these actions are reviewed, with an emphasis on the effects on the kidney.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.269
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes2
Has abstractyes

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