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Record W2039873707 · doi:10.1159/000188930

Urea Recycling: An Aid to the Excretion of Potassium during Antidiuresis

2008· review· en· W2039873707 on OpenAlexaff
Mitchell L. Halperin, Manjula Gowrishankar, Jean-Pierre Mallié, H. Sonnenberg, Man S. Oh

Bibliographic record

Venue˜The œNephron journals/Nephron journals · 2008
Typereview
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsUreaExcretionInternal medicineEndocrinologyReabsorptionAldosteroneUrine flow rateRenal physiologyNephronMedicineChemistryKidneyBiochemistry

Abstract

fetched live from OpenAlex

Urea absorption in the inner medullary collecting duct provides a mechanism to elevate the concentration of urea in the papillary interstitial fluid and thereby permit the excretion of urea with as little water as possible. Urea reabsorption may have another important effect - to aid in the excretion of potassium (K). K excretion depends on two processes: first, factors such as aldosterone which cause the concentration of K in the luminal fluid of the cortical distal nephron to be high and, second, factors which augment the flow rate through those nephron segments. Since, the osmolality of the luminal fluid in the cortical collecting duct (CCD) and plasma are equal when antidiuretic hormone acts, the flow rate in the CCD is dependent on solute delivery. Urea is a major solute in the lumen of the CCD and thereby plays an important role in maintaining the CCD flow rate. Since urea and K are often found in the same foods, having urea help the excretion of K is potentially advantageous. If the excretion of urea was low, the flow rate in the terminal CCD would decline. In this circumstance, the luminal K concentration would have to rise in proportion to the fall in flow rate or there would be a diminished rate of excretion of K and, possibly, hyperkalemia.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.066
GPT teacher head0.368
Teacher spread0.303 · 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

Citations9
Published2008
Admission routes1
Has abstractyes

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