Acute brain pathology and long-term neurological sequelae in experimental pneumococcal meningitis
Bibliographic record
Abstract
Pneumococcal meningitis is a fatal form of bacterial meningitis caused by brain infection of Streptococcus pneumoniae. Not only does it cause acute mortality, but pneumococcal meningitis also leads to long-term neurological disabilities in up to half of the survivors. To identify the molecular events that participate in the pathogenesis of meningitis-associated central nervous system dysfunction, we infected C57BL/6J mice intracerebroventricularly with S. pneumoniae serotype 3, and subsequently treated the animals with ceftriaxone. The post-meningitic (PM) mice were subjected to IntelliCage-based behavioural and cognitive assessment. Multiple neurobehavioural consequences of pneumococcal meningitis were identified in these mice, namely: (i) diurnal hypoactivity during adaptation; (ii) nocturnal hyperactivity during adaptation; (iii) learning impairment in a complex patrolling task; (iv) executive functioning deficit in a visual discrimination task. Further studies on gene knockout mice showed improved survival, diminished brain inflammatory responses, and improved long-term brain complications in the IFN-γ-/- mice compared to their wild-type (WT) equivalents. While PM mice deficient in IFN-γ-inducing factor IL-18 also showed reduced fatality and attenuated acute brain inflammation, they were less protected against neurological sequelae than the IFN-γ-/- equivalents. Furthermore, PM mice deficient in IFN-γ-inducible effector IDO1 showed no better protection against acute mortality and long-term neurological sequelae following pneumococcal infection compared to the IFN-γ-/- equivalents. Taken together, the results illustrate the importance of IFN-γ-driven mechanistic events in pneumococcus-induced brain inflammation, which subsequently modulates the pathogenesis of long-term neurological sequelae. It is also concluded that the pathogeneses of acute mortality and persistent neurological sequelae only partially overlap.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".