Brain-derived neurotrophic factor (BDNF) has direct anti-inflammatory effects on microglia
Bibliographic record
Abstract
Microglia are the primary immunocompetent cells that protect the brain from environmental stressors, but can also be driven to release pro-inflammatory cytokines and induce a cytotoxic environment. Brain-derived neurotrophic factor (BDNF) is important for the regulation of plasticity, synapse formation, and general neuronal health. Yet, little is known about how BDNF impacts microglial activity. We hypothesized that BDNF would have a direct modulatory effect on primary cortical (Postnatal Day 1-3: P1-3) microglia and (Embryonic Day 16: E16) neuronal cultures in the context of a bacterial endotoxin. To this end, we found that a BDNF treatment following LPS-induced inflammation had a marked anti-inflammatory effect, reversing the release of both IL-6 and TNF-α in cortical primary microglia. This modulatory effect was transferrable to cortical primary neurons, such that LPS-activated microglial media was able produce an inflammatory effect when added to a separate neuronal culture, and again, BDNF priming attenuated this effect. BDNF also reversed the overall cytotoxic impact of LPS exposure in microglia. We speculate that BDNF can directly play a role in regulating microglia state and hence, influence microglia-neuron interactions.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".