A modeling analysis of whole-body potassium regulation on a high potassium diet: Proximal tubule and tubuloglomerular feedback effects
Bibliographic record
Abstract
Abstract Potassium (K + ) is an essential electrolyte that plays a key role in many physiological processes, including mineralcorticoid action, systemic blood-pressure regulation, as well as hormone secretion and action. Indeed, maintaining K + balance is critical for normal cell function, as too high or too low K + levels can have serious and potentially deadly health consequences. K + homeostasis is achieved by an intricate balance between the intracellular and extracellular fluid as well as balance between K + intake and excretion. This is achieved via the coordinated actions of regulatory mechanisms such as the gastrointestinal feedforward effect, insulin and aldosterone upregulation of Na + -K + -ATPase uptake, and hormone and electrolyte impacts on renal K + handling. We recently developed a mathematical model of whole-body K + regulation to unravel the individual impacts of regulatory mechanisms. In this study, we extend our mathematical model to incorporate recent experimental findings that showed decreased fractional proximal tubule reabsorption under a high K + diet. We conducted model simulations and sensitivity analyses to unravel how these renal alterations impact whole-body K + regulation. Our results suggest that the reduced proximal tubule K + reabsorption under a high K + diet could achieve K + balance in isolation, but the resulting tubuloglomerular feedback reduces filtration rate and thus K + excretion. Model predictions quantify the sensitivity of K + regulation to various levels of proximal tubule K + reabsorption adaptation and tubuloglomerular feedback. Additionally, we predict that without the hypothesized muscle-kidney cross talk signal, intracellular K + stores can exceed normal range under a high K + diet.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".