N-3 PUFA Deficiency Affects the Ultrastructural Organization and Density of White Matter Microglia in the Developing Brain of Male Mice
Bibliographic record
Abstract
Over the last century, westernization of dietary habits has led to a dramatic reduction in dietary intake of n-3 polyunsaturated fatty acids (n-3 PUFAs). In particular, low maternal intake of n-3 PUFAs throughout gestation and lactation causes defects in brain myelination. Microglia are recognized for their critical contribution to neurodevelopmental processes, such as myelination. These cells invade the white matter in the first weeks of the post-natal period, where they participate in oligodendrocyte maturation and myelin production. Therefore, we investigated whether an alteration of white matter microglia accompanies the myelination deficits observed in the brain of n-3 PUFA-deficient animals. Macroscopic imaging analysis shows that maternal n-3 PUFA deficiency decreases the density of white matter microglia around post-natal day 10. Microscopic electron microscopy analyses also revealed alterations of microglial ultrastructure, a decrease in the number of contacts between microglia and myelin sheet, and a decreased amount of myelin debris in their cell body. White matter microglia further displayed increased mitochondrial abundance and network area under perinatal n-3 PUFA deficiency. Overall, our data suggest that maternal n-3 PUFA deficiency alters the structure and function of microglial cells located in the white matter of pups early in life, and this could be the key to understand myelination deficits during neurodevelopment.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".