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Record W2166119127 · doi:10.25011/cim.v32i1.5085

Inability of healthy subjects to deposit potassium during hypokinesia and potassium supplementation

2009· article· en· W2166119127 on OpenAlexvenueno aff
Yan G. Zorbas, Kostas K. Kakuris, Yuri F. Federenko, Viktor A. Deogenov

Bibliographic record

VenueClinical and investigative medicine · 2009
Typearticle
Languageen
FieldNursing
TopicSodium Intake and Health
Canadian institutionsnot available
Fundersnot available
KeywordsHypokinesiaPotassiumUrineInternal medicineEndocrinologyFecesChemistryAnimal scienceBody weightMedicineBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the effect of potassium (K+) supplementation and hypokinesia (HK; diminished movement) on muscle K+ content and K+ loss. METHODS: Studies were conducted on 40 healthy male volunteers during a pre-experimental period of 30 days and an experimental-period of 364 days. Volunteers were equally divided into four groups: unsupplemented control subjects (UCS), unsupplemented experimental subjects (UES), supplemented control subjects (SCS), and supplemented experimental subjects (SES). A daily supplement of 1.17 mmol potassium-chloride (KCl) per kg body weight was given to the subjects in the SCS and SES groups. RESULTS: Muscle K+ content decreased (P < 0.05), and plasma K+ concentration, and K+ loss in urine and feces increased (P < 0.05) in the SES and UES groups compared with their pre-experimental levels and the values in their respective control groups (SCS and UCS). Muscle K+ content decreased more (P < 0.05), and plasma K+ concentration and K+ loss in urine and feces increased more (P < 0.05) in the SES group than in the UES group. CONCLUSION: Muscle K+ content is not decreased by the K+ deficient diet and K+ loss is not increased by the higher muscle K+ content in the body. Rather it is caused by the inability of the body to use K+ during HK and K+ supplementation.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.109
GPT teacher head0.385
Teacher spread0.276 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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