Species differences in immune‐mediated CNS tissue injury and repair: A (neuro)inflammatory topic
Bibliographic record
Abstract
Cells of the adaptive and innate immune systems in the brain parenchyma and in the meningeal spaces contribute to physiologic functions and disease states in the central nervous system (CNS). Animal studies have demonstrated the involvement of immune constituents, along with major histocompatibility complex (MHC) molecules, in neural development and rare genetic disorders (e.g., colony stimulating factor 1 receptor [CSF1R] deficiency). Genome wide association studies suggest a comparable role of the immune system in humans. Although the CNS can be the target of primary autoimmune disorders, no current experimental model captures all of the features of the most common human disorder placed in this category, multiple sclerosis (MS). Such features include spontaneous onset, environmental contributions, and a recurrent/progressive disease course in a genetically predisposed host. Numerous therapeutic interventions related to antigen and cytokine specific therapies have demonstrated effectiveness in experimental autoimmune encephalomyelitis (EAE), the animal model used to define principles underlying immune-mediated mechanisms in MS. Despite the similarities in the two diseases, most treatments used to ameliorate EAE have failed to translate to the human disease. As directly demonstrated in animal models and implicated by correlative studies in humans, adaptive and innate immune constituents within the systemic compartment and resident in the CNS contribute to the disease course of neurodegenerative and neurobehavioral disorders. The expanding knowledge of the molecular properties of glial cells provides increasing insights into species related variables. These variables affect glial bidirectional interactions with the immune system as well as their own production of "immune molecules" that mediate tissue injury and repair.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".