Viral meningitis in real time
Bibliographic record
Abstract
Meningitis is a potentially fatal disorder induced by a long list of human pathogens. We therefore propose that a detailed understanding of this pathogenic process in real time may foster the development of novel interventions to prevent permanent neurological dysfunction / fatalities. Intracerebral inoculation of mice with LCMV Armstrong (Arm) induces fatal meningitis within 6 days that is mediated by cytotoxic lymphocytes (CTL). The precise mechanisms that mediate seizures and fatal injury during virus‐induced meningitis are not known. To gain advanced mechanistic insights into immune cell dynamics and function in the virally infected central nervous system (CNS), we examined disease pathogenesis in real time using intravital two photon microscopy. Our real time studies revealed highly dynamic immune cell activity in the meningeal space of LCMV‐infected mice, which resulted in profound blood barrier breakdown. Our studies also provide direct evidence that CTL divide within the CNS and that innate immune cells (e.g., microglia) respond rapidly to point sources of CNS damage. Finally, direct injection of anti‐MHC I antibody into the subarachnoid space interfered with the activities of virus‐specific CTL. We therefore propose that examination and antagonism of immune cells through a “window on the brain” should rapidly advance our understanding of CNS viral pathogenesis.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".