Induction of Distinct Neurologic Disease Manifestations during Relapsing Fever Requires T Lymphocytes
Bibliographic record
Abstract
Relapsing fever borreliosis is a multisystemic infection characterized primarily by bacteremia but can extend to the CNS. The incidence of CNS disease manifestations in humans depends on the infecting relapsing fever Borrelia species. In the murine model of Borrelia hermsii infection we found high incidence of distinct signs of CNS disease that ranged from a flaccid tail to complete paralysis of hind limbs. Infiltration of large number of T cells into the spinal cord of B. hermsii-infected mice and the upregulation of MHC class II and CD80 on infiltrating macrophages and on microglial cells suggested a role for T cell and Ag-presenting cell interactions in this pathogenesis. Indeed, B. hermsii infection did not induce CNS disease manifestations in T cell-deficient mice (TCR-beta x delta(-/-)), although it resulted in bacteremia comparable to wild-type (Wt) level. Moreover, the infiltration of immune cells into the spinal cord of TCR-beta x delta(-/-) mice was reduced and the resident microglial cells were not activated. Histopathological analysis of lumbar sections of the spinal cord confirmed severe inflammation in Wt but not in TCR-beta x delta(-/-) mice. Induction of CNS disease was dependent on the B. hermsii strain as well as on the ability of the host to control bacteremia. Mice that are impaired in controlling B. hermsii, such as CD14(-/-) mice, exhibited more severe CNS disease than Wt mice. This study demonstrates that distinct neurologic disease manifestations develop during relapsing fever and that T cells play a critical role in the induction of neuropathogenesis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".