Poly(I:C) alters placental and fetal brain amino acid transport in a rat model of maternal immune activation
Bibliographic record
Abstract
PROBLEM: Maternal immune activation (MIA) during pregnancy is associated with increased chances of neurodevelopmental disorders including schizophrenia and autism spectrum disorder (ASD). However, the exact mechanism through which MIA contributes to altered neurodevelopment is unknown. Due to the important role that amino acids play in neurodevelopment, altered amino acid transport could play a role in neurodevelopmental disorders. Indeed, altered plasma concentrations of multiple amino acids have been reported in individuals with ASD or schizophrenia. Therefore, our objective was to determine whether virally mediated MIA induces changes in amino acid transporters in the placenta and fetal brain. METHOD OF STUDY: Pregnant rats were administered poly(I:C) on gestational day 14, and placental and fetal tissues were collected 6, 24, and 48 hours later. Amino acid transporter expression was measured in the placenta and fetal brain using qPCR, Western blotting, and Simple Western. Free amino acid concentrations in the fetal brain were quantified using HPLC. RESULTS: Poly(I:C) increased mRNA expression of several amino acid transporters in the placenta and fetal brain over these timepoints. Conversely, poly(I:C) imposed significant decreases in the protein expression of ASCT1 and EAAT2 in placenta and expression of SNAT5, EAAT1, and GLYT1 in fetal brain. Functional consequences of altered transporter expression were demonstrated through widespread changes in the concentrations of free amino acids in the fetal brains. CONCLUSION: Together, these results represent novel findings with the poly(I:C) MIA model and contribute to the understanding of how MIA during pregnancy potentially leads to neurodevelopmental disorders.
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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 | 0.001 |
| 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".