Metabolic Effects of Maternal High-Fat Diet on Glucose Regulation and Leptin Resistance in Mice: A Research Protocol
Bibliographic record
Abstract
Introduction: Maternal physiological systems undergo critical adaptations during pregnancy to maintain homeostasis. Leptin, an adipocyte-derived hormone, is a critical regulator of energy balance and metabolism, particularly in the early stages of pregnancy. Previous studies demonstrate that hyperleptinemia induces leptin resistance, suppresses feelings of satiety, and increases the risk of gestational diabetes. This study aims to investigate the role of leptin resistance in maternal obesity with mouse models. By understanding leptin resistance, which remains underexplored, pathways can be identified to reduce the risks of excessive weight gain during pregnancy and transmission of health complications to offspring. Methods: The study will utilize female wild-type (C57BL/6) mice of similar ages, maintained in a controlled environment. The experimental group will receive a high-fat diet (HFD) to elevate leptin levels, while the control group will be fed a standard diet. Initial measurements of body mass, food intake, and plasma leptin levels will be recorded to establish a baseline. These measurements will be taken weekly to examine the relationship between leptin levels and the anthropometric data of the mice. To specifically assess leptin resistance, food intake and body mass will be closely monitored in mice exhibiting hyperleptinemia. Anticipated Results: Results are anticipated to demonstrate that leptin resistance impairs maternal metabolic adaptations during pregnancy, leading to altered glucose homeostasis and increased fat mass. Elevated leptin levels are associated with increased adiposity, increasing the risk of maternal obesity. Mice with hyperleptinemia will exhibit increased food intake and body mass, indicating a state of leptin resistance. Persistent weight gain and increased food consumption in these mice will suggest leptin resistance, contributing to metabolic dysregulation and an increased risk of gestational diabetes and obesity. Offspring may exhibit higher birth weights and metabolic dysfunction, supporting the Developmental Origins of Health and Disease (DOHaD) hypothesis. Conclusion: Understanding the role of leptin in pregnancy can identify pathways involved in gestational disorders. The investigation aims to inform therapeutic strategies targeting leptin signaling to prevent the transmission of health complications to offspring. By elucidating mechanisms of leptin resistance, the study aims to contribute to interventions that mitigate risks associated with maternal obesity during pregnancy.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.011 |
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".