A high-fat high-sugar diet and adversity early in life modulate pain outcomes at the behavioural and molecular level in adolescent rats: The role of sex
Bibliographic record
Abstract
Given that adolescence is a significant period of brain plasticity and development, early life factors have the potential to alter long term outcomes. For instance, adversities such as consumption of a high-fat high-sugar (HFHS) diet and adverse childhood experiences (ACEs; e.g., neglect), and their resulting inflammation and microglial activation can influence pain outcomes by priming the neuroimmune system to overrespond to stressors. Chronic pain is highly prevalent amongst the adolescent population, with the prevalence and manifestation being sexually dimorphic. Although clinical studies show that females are twice as likely to report pain problems compared to males, the majority of pre-clinical work uses male rodents. Therefore, our aim was to examine the effects of sex, a HFHS diet, and an ACE on chronic pain outcomes following a stressor in adolescence. Rat dams were randomly assigned to a Standard or HFHS diet, with pups maintained on their respective diets then randomly allocated to a No Stress or ACE paradigm, and a Sham or Injury condition as a stressor. Results showed that early life adversities increased nociceptive sensitivity, inflammation, and microglial activation systemically and within the brain. Behaviourally, pain outcomes were more prominent in females, however the neuroimmune response was exacerbated in males. These results demonstrate the sexual dimorphism of chronic pain outcomes following early life adversities and provide insight into the mechanisms driving these changes, which will inform more targeted and effective treatment strategies for youth living with chronic pain.
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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 | 0.000 | 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".