Selective Vulnerability of Late Oligodendrocyte Progenitors to Hypoxia–Ischemia
Bibliographic record
Abstract
In the premature infant, hypoxic-ischemic damage to the cerebral white matter [periventricular leukomalacia (PVL)] is a common and leading cause of brain injury that often results in chronic neurologic disability from cerebral palsy. The cellular basis for the propensity of white matter injury to occur in the developing brain and the greater resistance of the adult white matter to similar injury remains unknown. By using a neonatal rat model of hypoxic-ischemic injury, we found that the mechanism of perinatal white matter injury involved maturation-dependent vulnerability in the oligodendroctye (OL) lineage. The timing of appearance of late OL progenitors was the major developmental factor that accounted for the susceptibility of the neonatal white matter to injury. Late OL progenitors were the major OL lineage stage killed by apoptosis, whereas early OL progenitors and more mature OLs were highly resistant. The density of pyknotic late OL progenitors was significantly increased in the ischemic hemisphere (67 +/- 31 cells/mm2) versus the control hemisphere (2.2 +/- 0.4 cells/mm2; mean +/- SEM; p = 0.05), which resulted in the death of 72 +/- 6% of this OL stage. Surviving late OL progenitors displayed a reactive response in which an increase in cell density was accompanied by accelerated maturation to a P27/kip1-positive oligodendrocyte. Because we showed recently that late OL progenitors populate human cerebral white matter during the high risk period for PVL (Back et al., 2001), maturation-dependent vulnerability of OL progenitors to hypoxia-ischemia may underlie the selective vulnerability to PVL of the white matter in the premature infant.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".