Choline Supplementation Alters Hippocampal Cytokine Levels in Adolescence and Adulthood in an Animal Model of Fetal Alcohol Spectrum Disorders
Bibliographic record
Abstract
Alcohol (ethanol) exposure during pregnancy can adversely affect development, with long-lasting consequences that include neuroimmune, cognitive, and behavioral dysfunction. Alcohol-induced alterations in cytokine levels in the hippocampus may contribute to abnormal cognitive and behavioral outcomes in individuals with fetal alcohol spectrum disorders (FASD). Nutritional intervention with the essential nutrient choline can improve hippocampal-dependent behavioral impairments and may also influence neuroimmune function. Thus, we examined the effects of choline supplementation on hippocampal cytokine levels in adolescent and adult rats exposed to alcohol early in development. From postnatal day (PD) 4-9 (third trimester-equivalent), Sprague-Dawley rat pups received ethanol (5.25 g/kg/day) or sham intubations and were treated with choline chloride (100 mg/kg/day) or saline from PD 10-30; hippocampi were collected at PD 35 or PD 60. Age-specific ethanol-induced increases in interferon gamma (IFN-γ), tumor necrosis factor alpha (TNF-α), and keratinocyte chemoattractant/human growth-regulated oncogene (KC/GRO) were identified in adulthood, but not adolescence, whereas persistent ethanol-induced increases of interleukin-6 (IL-6) levels were present at both ages. Interestingly, choline supplementation reduced age-related changes in interleukin-1 beta (IL-1β) and interleukin-5 (IL-5) as well as mitigating the long-lasting increase in IFN-γ in ethanol-exposed adults. Moreover, choline influenced inflammatory tone by modulating ratios of pro- to -anti-inflammatory cytokines. These results suggest that ethanol-induced changes in hippocampal cytokine levels are more evident during adulthood than adolescence, and that choline can mitigate some effects of ethanol exposure on long-lasting inflammatory tone.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".