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Renal Medulla in Hypertension

2024· review· en· W4402994526 on OpenAlexaff
Allen W. Cowley, Richard J. Roman, David L. Mattson, Kleber G. Franchini, Paul O’Connor, Ayako Makino, Norman E. Taylor, Louise Evans, Takefumi Mori, Jeffrey G. Dickhout, Chunhua Jin, Noriyuki Miyata, Kazushige Nakanishi, M Szentiványi, Frank Park, M. M. Skelton, Theresa Kurth, Satoshi Shimada

Bibliographic record

VenueHypertension · 2024
Typereview
Languageen
FieldMedicine
TopicRenal function and acid-base balance
Canadian institutionsMcMaster University
FundersNational Heart, Lung, and Blood InstituteNational Institute on Aging
KeywordsRenal medullaNatriuresisMedullary cavityMedicineBlood pressurePathophysiology of hypertensionMedullaRenal blood flowInternal medicineNitric oxideBlood flowEndocrinologyCardiology

Abstract

fetched live from OpenAlex

Studies have found that blood flow to the renal medulla is an important determinant of pressure-natriuresis and the long-term regulation of arterial pressure. First, a brief review of methods developed enabling the study of the medullary circulation is presented. Second, studies performed in rats are presented showing medullary blood flow plays a vital role in the pressure-natriuresis relationship and thereby in hypertension. Third, it is shown that chronic reduction of medullary blood flow results in hypertension and that enhancement of medullary blood flow reduces hypertension hereditary models of both salt-sensitive rats and salt-resistant forms of hypertension. The key role that medullary nitric oxide production plays in protecting this region from ischemic injury associated with circulating vasoconstrictor agents and reactive oxygen species is presented. The studies cited are largely the work of my students, research fellows, and colleagues with whom I have performed these studies dating from the late 1980s to more recent years.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.091
GPT teacher head0.334
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations6
Published2024
Admission routes1
Has abstractyes

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