Synaptoimmunology - roles in health and disease
Bibliographic record
Abstract
Mounting evidence suggests that the nervous and immune systems are intricately linked. Many proteins first identified in the immune system have since been detected at synapses, playing different roles in normal and pathological situations. In addition, novel immunological functions are emerging for proteins typically expressed at synapses. Under normal conditions, release of inflammatory mediators generally represents an adaptive and regulated response of the brain to immune signals. On the other hand, when immune challenge becomes prolonged and/or uncontrolled, the consequent inflammatory response leads to maladaptive synaptic plasticity and brain disorders. In this review, we will first provide a summary of the cell signaling pathways in neurons and immune cells. We will then examine how immunological mechanisms might influence synaptic function, and in particular synaptic plasticity, in the healthy and pathological CNS. A better understanding of neuro-immune system interactions in brain circuitries relevant to neuropsychiatric and neurological disorders should provide specific biomarkers to measure the status of the neuroimmunological response and help design novel neuroimmune-targeted therapeutics.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".