Ghost cells: Wilder Penfield and the characterization of glia and glial pathology, 1924–1932
Bibliographic record
Abstract
Wilder Penfield is known for his contributions to the structure-function relationship of the brain and for the surgical treatment of focal epilepsy. Less well known are his contributions to the study of glial cells and his investigation of their role in human neuropathology. Penfield learned the gold and silver methods for staining neurons, glial cells, and their projections from Charles Sherrington and Pío del Río-Hortega. He and his colleague William Cone established a laboratory for the study of glial cells and human neuropathology using metallic stains, initially at the Presbyterian Hospital in New York City in 1925, and then at the Montreal Neurological Institute in 1928. Penfield, Cone, and their research fellows, building on the findings of Río-Hortega, confirmed the existence of oligodendrocytes and their relationship with myelin, and investigated the putative mesodermal origin of microglia. They discovered the reaction of oligodendrocytes to pathological stressors, and the phagocytic activity of microglia in human gliomas. In this article, we argue that Penfield's studies of astrocytes, oligodendrocytes, and microglia, and their responses to craniocerebral trauma, epilepsy, malignant brain tumors, and other pathologies of the central nervous system inaugurated a new era in clinical neurocytology and neuropathology.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".