Exploring the effects of tetrahydrobiopterin on motivation, dopamine release and acute inflammation in mice
Bibliographic record
Abstract
Inflammation can affect mesodopaminergic system and mediates depressive symptoms related to motivation and locomotion. Precisely, pro-inflammatory cytokines can alter dopamine synthesis and thus availability. Tetrahydrobiopterin (BH4) is the mandatory co-factor for phenylalanine and tyrosine hydroxylase activities and therefore essential for dopamine synthesis. Interestingly, inflammation can decrease BH4 by acting on its synthesis and degradation. So, lower BH4 level could participate to the dopaminergic and motivational deficits that occur frequently in chronic inflammatory conditions. Despite its importance, the effects of BH4 administration on dopamine synthesis and related behaviors have been poorly characterized. We hypothesized that BH4 administration can improve dopaminergic function and motivational processes and could be used to counteract inflammation-induced alterations. We first demonstrated that peripheral administration of BH4 (50mg/kg;intraperitoneally) was sufficient to double BH4 brain content within 3h. Using in-situ brain perfusion, we found that the brain uptake clearance (Clup) of BH4 was approximately 0.08μl/g/sec, consistent with a modest transfer across the blood brain barrier. BH4 injection neither changed the expression of main enzymes involved in BH4 and DA synthesis nor total striatal dopamine content. However, using in vivo microdialysis in freely moving mice, we showed that BH4 administration induced a slight increase in dopamine release in the nucleus accumbens during food presentation and a higher amphetamine-induced DA release (3mg/kg). Furthermore, BH4 injection increased motivation in a progressive ratio task in operant conditioning without affecting sucrose consumption and anhedonia. Surprisingly, BH4 injection led to a moderate decrease in spontaneous locomotion and to a blunted locomotor sensitization after second exposure to amphetamine. Last, BH4 injection reduced brain pro-inflammatory cytokines expression in an acute inflammation model induced by lLipopolysaccharide injection (830μg/kg). Here, we showed that increased BH4 content leads to increased dopamine release and motivation, and reduces the proinflammatory response to an acute inflammatory challenge. This suggests that BH4 could be a promising treatment for behavioral deficits related to dopaminergic disturbances related to inflammatory condition.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".