Spinal Microglial Motility is Independent of Neuronal Activity and Plasticity in Adult Mice
Bibliographic record
Abstract
Microglia are the resident macrophages in the central nervous system. In the spinal cord dorsal horn, microglia stay in resting condition during physiological sensory processing, and are activated under pathological conditions such as peripheral nerve injury. In cases such as this, the nearby resting microglia increase their motility and accumulate at the site of injury. However, direct evidence to support that nerve activity can enhance the motility of microglia has not yet to be reported. In this study we investigated whether the activation of spinal microglia under in vivo nerve injury may be mimicked by neuronal activity in the spinal cord slice preparation. We found that local application of spinal excitatory neurotransmitters, such as glutamate and substance P did not cause any change in the motility of microglial cells in the spinal cord dorsal horn. The motility of microglial cells is unlikely modulated by other transmitters, neuromodulators and chemokines, because similar applications such as GABA, serotonin, noradrenaline, carbachol, fractalkine or interleukin did not produce any obvious effect. Furthermore, low or high frequency stimulation of spinal dorsal root fibers at noxious intensities failed to cause any enhanced extension or retraction of the microglia processes. By contrast, focal application of ATP triggered rapid and robust activation of microglial cells in the spinal dorsal horn. Our results provide the first evidence that the activation of microglia in the spinal cord after nerve injury is unlikely due solely to neuronal activity, non-neuronal factors are likely responsible for the activation of nerve injury-related microglial cells in the spinal dorsal horn.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.006 | 0.002 |
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".