An intermittent hypercaloric diet alters gut microbiota, prefrontal cortical gene expression and social behaviours in rats
Bibliographic record
Abstract
Objectives: Excessive consumption of high fat and high sugar (HFHS) diets alters reward processing, behaviour, and changes gut microbiota profiles. Previous studies in gnotobiotic mice also provide evidence that these gut microorganisms may influence social behaviour. To further investigate these interactions, we examined the impact of the intermittent access to a HFHS diet on social behaviour, gene expression and microbiota composition in adolescent rats.Methods: Male rats were permitted intermittent daily access (2 h / day) to a palatable HFHS chow diet for 28 days across adolescence. Social interaction, social memory and novel object recognition were assessed during this period. Following testing, RT-PCR was conducted on hippocampal and prefrontal cortex (PFC) samples. 16S ribosomal RNA amplicon sequencing was used for identification and relative quantification of bacterial taxa in faecal samples.Results: We observed reduced social interaction behaviours, impaired social memory and novel object recognition in HFHS diet rats compared to chow controls. RT-PCR revealed reduced levels of monoamine oxidase A (Maoa), catechol-O-methyltransferase (Comt) and brain derived neurotrophic factor (Bdnf) mRNA in the PFC of HFHS diet rats. Faecal microbiota analysis demonstrated that the relative abundance of a number of specific bacterial taxa differed significantly between the two diet groups, in particular, Lachnospiraceae and Ruminoccoceae bacteria.Discussion: Intermittent HFHS diet consumption evoked physiological changes to the brain, particularly expression of mRNA associated with reward and neuroplasticity, and gut microbiome. These changes may underpin the observed alterations to social behaviours.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".