Impact of time‐restricted feeding on kidney injury in male rats with experimental metabolic syndrome
Bibliographic record
Abstract
Disruptions to circadian rhythm may be implicated in the pathogenesis of metabolic syndrome (Met-S). For example, eating during an extended period of the day may negatively impact the circadian rhythms governing metabolic control, contributing, therefore, to Met-S and associated end-organ damage. Accordingly, time-restricted eating (TRE)/feeding (TRF) is gaining popularity as a dietary intervention for the treatment and prevention of Met-S. To date, no studies have specifically examined the impact of TRE/TRF on the renal consequences of Met-S. The proposed study seeks to use a model of experimental Met-S-associated kidney disease to address this knowledge gap, disambiguating therein the effects of calorie restriction from the timing of food intake. Spontaneously hypertensive rats will consume a high-fat diet (HFD) for 8 weeks and then be allocated by stratified randomisation according to albuminuria to one of three groups. Rats will have free 24-h access to HFD (Group A), access to HFD during the scheduled hours of darkness (Group B) or access to HFD provided in the form of two rations, one provided during the light phase and one provided during the dark phase, equivalent overall in quantity to that consumed by rats in Group B (Group C). The primary outcome measure will be a change in albuminuria. Changes in food intake, body weight, blood pressure, glucose tolerance, fasting plasma insulin, urinary excretion of C-peptide and renal injury biomarkers, liver and kidney histopathology and inflammation, and fibrosis-related renal gene expression will be assessed as secondary outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".