Effects of 5% Coca-Cola Consumption on Metabolic, Renal, and Hepatic Markers in Adult Balb/c Mice
Bibliographic record
Abstract
The impact of consuming Coca-Cola increases the energy and the weight at the same time, however, the 5% refers to consuming one can of Coca-Cola daily in the long term.The consumption of 5% Coca-Cola increases food intake, body weight, and contributes to various other disorders in young mice.This work aims to find the effect of Coca-Cola consumption on leptin and insulin resistance, lipid profile, and changes in renal and liver functions in adult mice.In this study, 30 adult male Balb/c mice (8-10 weeks old, weighing 25-30g) were used and divided into three groups.Ten mice received tap water and serve as control group, the other 20 mice received 5% Coca-Cola daily instead of water for different durations and served as restricted groups, ten for 10-day (restricted 1) and the other ten for 30-day (restricted 2).Body weight of all mice was measured at the start and end of the experiment, while the food intake was recorded daily.The mice were killed at different time-points.Blood was collected and used to determine the levels of FBG, HbA1c, leptin and insulin hormones, lipid profile, and liver and kidney function parameters.The insulin resistance was also calculated.The results indicate significant increases in food intake, body weight, leptin, insulin, FBG, HbA1c, and insulin resistance in groups exposed to Coca-Cola.Lipid profiles and liver and kidney function markers also deteriorated, particularly in the group with longer exposure.Prolonged consumption led to increased body weight and leptin levels (indicating leptin resistance), insulin resistance with elevated FBG and HbA1C (suggestive of type 2 diabetes), altered lipid profiles (raising cardiovascular risk), elevated kidney (BU and SCr) and liver function markers (GOT, GPT, ALK), with these effects intensifying over 30 days compared to 10 days.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".