Adaptive Brain Shut-Down Counteracts Neuroinflammation in the Near-Term Ovine Fetus
Bibliographic record
Abstract
OBJECTIVE: Repetitive umbilical cord occlusions (UCOs) in ovine fetus leading to severe acidemia result in adaptive shut-down of electrocortical activity [electrocorticogram (ECoG)] as well as systemic and brain inflammation. We hypothesized that the fetuses with earlier ECoG shut-down as a neuroprotective mechanism in response to repetitive UCOs will show less brain inflammation and, moreover, that chronic hypoxia will impact this relationship. METHODS: Near-term fetal sheep were chronically instrumented with ECoG leads, vascular catheters, and a cord occluder and then underwent repetitive UCOs for up to 4 h or until fetal arterial pH was <7.00. Eight animals, hypoxic prior to the UCOs (SaO2 <55%), were allowed to recover 24 h post insult, while 14 animals, 5 of whom also were chronically hypoxic, were allowed to recover 48 h post insult, after which brains were perfusion-fixed. Time of ECoG shut-down and corresponding pH were noted, as well as time to then reach pH <7.00 (ΔT). Microglia (MG) were counted as a measure of inflammation in gray matter layers 4-6 (GM4-6) where most ECoG activity is generated. RESULTS are reported as mean ± SEM for p < 0.05. RESULTS: Repetitive UCOs resulted in worsening acidosis over 3-4 h with arterial pH decreasing to 6.97 ± 0.02 all UCO groups' animals, recovering to baseline by 24 h. ECoG shut-down occurred 52 ± 7 min before reaching pH <7.00 at pH 7.23 ± 0.02 across the animal groups. MG counts were inversely correlated to ΔT in 24 h recovery animals (R = -0.84), as expected. This was not the case in normoxic 48 h recovery animals, and, surprisingly, in hypoxic 48 h recovery animals, this relationship was reversed (R = 0.90). CONCLUSION: Adaptive brain shut-down during labor-like worsening acidemia counteracts neuroinflammation in a hypoxia- and time-dependent manner.
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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 | 0.000 |
| 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".