Cerebral microbleeds in a neonatal rat model
Bibliographic record
Abstract
BACKGROUND: In adult humans, cerebral microbleeds play important roles in neurodegenerative diseases but in neonates, the consequences of cerebral microbleeds are unknown. In rats, a single pro-angiogenic stimulus in utero predisposes to cerebral microbleeds after birth at term, a time when late oligodendrocyte progenitors (pre-oligodendrocytes) dominate in the rat brain. We hypothesized that two independent pro-angiogenic stimuli in utero would be associated with a high likelihood of perinatal microbleeds that would be severely damaging to white matter. METHODS: Pregnant Wistar rats were subjected to intrauterine ischemia (IUI) and low-dose maternal lipopolysaccharide (mLPS) at embryonic day (E) 19. Pups were born vaginally or abdominally at E21-22. Brains were evaluated for angiogenic markers, microhemorrhages, myelination and axonal development. Neurological function was assessed out to 6 weeks. RESULTS: mRNA (Vegf, Cd31, Mmp2, Mmp9, Timp1, Timp2) and protein (CD31, MMP2, MMP9) for angiogenic markers, in situ proteolytic activity, and collagen IV immunoreactivity were altered, consistent with an angiogenic response. Vaginally delivered pups exposed to prenatal IUI+mLPS had spontaneous cerebral microbleeds, abnormal neurological function, and dysmorphic, hypomyelinated white matter and axonopathy. Pups exposed to the same pro-angiogenic stimuli in utero but delivered abdominally had minimal cerebral microbleeds, preserved myelination and axonal development, and neurological function similar to naïve controls. CONCLUSIONS: In rats, pro-angiogenic stimuli in utero can predispose to vascular fragility and lead to cerebral microbleeds. The study of microbleeds in the neonatal rat brain at full gestation may give insights into the consequences of microbleeds in human preterm infants during critical periods of white matter development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".