Innate Immune-Mediated Neuronal Injury Consequent to Loss of Astrocytes
Bibliographic record
Abstract
Neuronal injury and loss are recognized features of neuroinflammatory disorders, including acute and chronic encephalitides and multiple sclerosis; destruction of astrocytes has been demonstrated in cases of Rasmussen encephalitis. Here, we show that innate immune cells (i.e. natural killer [NK] and gammadelta T cells) cause loss of neurons from primary human neuron-enriched cultures by destroying the supporting astrocytes. Interleukin 2-activated NK cells caused loss of astrocytes within 1 hour, whereas neurons were lost at 4 hours. Time-lapse imaging indicated that delayed neuron loss was due to early destruction of supporting astrocytes. Selective blocking of astrocyte death with anti-NKG2D antibodies reduced neuron loss, as did blocking of CD54 on astrocytes. gammadelta T cells also induced astrocyte cytotoxicity, leading to subsequent neuronal displacement. In astrocytes, NK cells caused caspase-dependent fragmentation of the intermediate filament proteins glial fibrillary acidic protein and vimentin, whereas anti-CD3-activated T cells produced fragmentation to a lesser extent and without measurable cytotoxicity. Glial fibrillary acidic protein fragmentation was also demonstrated in lysates from chronic multiple sclerosis plaques but not from normal control white matter. These data suggest that non-major histocompatibility complex-restricted immune effector cells may contribute to neuron loss in neuroinflammatory disorders indirectly through injury of glia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".