Relationship between insulin and Netrin-1/DCC guidance cue pathway regulation in the prefrontal cortex of rodents exposed to prenatal dietary restriction
Bibliographic record
Abstract
Abstract Fetal restriction (FR) alters insulin sensitivity, but it is unknown how the metabolic profile associated with restriction affects development of the dopamine (DA) system and DA-related behaviors. The Netrin-1/DCC guidance cue system participates in maturation of the mesocorticolimbic DA circuitry. Therefore, our objective was to identify if FR modifies Netrin-1/DCC receptor protein expression in the prefrontal cortex (PFC) at birth and mRNA in adulthood in rodent males. We used cultured HEK293 cells to assess if levels of miR-218, microRNA regulator of DCC, are sensitive to insulin. To assess this, pregnant dams were subjected to a 50% FR diet from gestational day 10 until birth. Medial PFC (mPFC) DCC/Netrin-1 protein expression was measured at P0 at baseline and Dcc/Netrin-1 mRNA levels were quantified in adults 15 min after a saline/insulin injection. miR-218 levels in HEK-293 cells were measured in response to insulin exposure. At P0, Netrin-1 levels are downregulated in FR animals in comparison to controls. In adult rodents, insulin administration results in an increase in Dcc mRNA levels in control but not FR rats. In HEK293 cells, there is a positive correlation between insulin concentration and miR-218 levels. Since miR-218 is a Dcc gene expression regulator and our in vitro results show that insulin regulates miR-218 levels, we suggest that FR-induced changes in insulin sensitivity could be affecting Dcc expression via miR-218, impacting DA system maturation and organization. As fetal adversity is linked to nonadaptive behaviors later in life, this may contribute to early identification of vulnerability to chronic diseases associated with fetal adversity.
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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) | 0.000 | 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 | 0.001 |
| 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".