Sucrose consumption alters steroid and dopamine signalling in the female rat brain
Bibliographic record
Abstract
Sucrose consumption is associated with type 2 diabetes, cardiovascular disease, and cognitive deficits. Sucrose intake during pregnancy might have particularly prominent effects on metabolic, endocrine, and neural physiology. It remains unclear how consumption of sucrose affects parous females, especially in brain circuits that mediate food consumption and reward processing. Here, we examine whether a human-relevant level of sucrose before, during, and after pregnancy (17-18 weeks total) influences metabolic and neuroendocrine physiology in female rats. Females were fed either a control diet or a macronutrient-matched, isocaloric sucrose diet (25% of kcal from sucrose). Metabolically, sucrose impairs glucose tolerance, increases liver lipids, and increases a marker of adipose inflammation, but has no effect on body weight or overall visceral adiposity. Sucrose also decreases corticosterone levels in serum but not in the brain. Sucrose increases progesterone levels in serum and in the brain and increases the brain:serum ratio of progesterone in the mesocorticolimbic system and hypothalamus. These data suggest a dysregulation of systemic and local steroid signalling. Moreover, sucrose decreases tyrosine hydroxylase (TH), a catecholamine-synthetic enzyme, in the medial prefrontal cortex. Finally, sucrose consumption alters the expression pattern of FOSB, a marker of phasic dopamine signalling, in the nucleus accumbens. Overall, chronic consumption of sucrose at a human-relevant level alters metabolism, steroid levels, and brain dopamine signalling in a female rat model.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".