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Control of potassium excretion: a Paleolithic perspective

2006· review· en· W2335305292 on OpenAlexaff
Mitchell L. Halperin, Surinder Cheema‐Dhadli, Shih‐Hua Lin, Kamel S. Kamel

Bibliographic record

VenueCurrent Opinion in Nephrology & Hypertension · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon Transport and Channel Regulation
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsExcretionEndocrinologyChemistryInternal medicineLoop of HenlePotassiumMedullary cavityBicarbonateNatriuresisHomeostasisRenal physiologyAldosteroneKidneyBiologyMedicineReabsorption

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Regulation of potassium (K) excretion was examined in an experimental setting that reflects the dietary conditions for humans in Paleolithic times (high, episodic intake of K with organic anions; low intake of NaCl), because this is when major control mechanisms were likely to have developed. RECENT FINDINGS: The major control of K secretion in this setting is to regulate the number of luminal K channels in the cortical collecting duct. Following a KCl load, the K concentration in the medullary interstitial compartment rose; the likely source of this medullary K was its absorption by the H/K-ATPase in the inner medullary collecting duct. As a result of the higher medullary K concentration, the absorption of Na and Cl was inhibited in the loop of Henle, and this led to an increased distal delivery of a sufficient quantity of Na to raise K excretion markedly, while avoiding a large natriuresis. In addition, because K in the diet was accompanied by 'future' bicarbonate, a role for bicarbonate in the control of K secretion via 'selecting' whether aldosterone would be a NaCl-conserving or a kaliuretic hormone is discussed. SUMMARY: This way of examining the control of K excretion provides new insights into clinical disorders with an abnormal plasma K concentration secondary to altered K excretion, and also into the pathophysiology of calcium-containing kidney stones.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.048
GPT teacher head0.329
Teacher spread0.281 · 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.

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

Citations21
Published2006
Admission routes1
Has abstractyes

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