CSF1R-mediated myeloid cell depletion shifts the ratio of motor cortical excitatory to inhibitory neurons in a multiple system atrophy model
Bibliographic record
Abstract
Motor cortical circuit functions depend on the coordinated fine-tuning of two functionally diverse neuronal populations: glutamatergic pyramidal neurons providing synaptic excitation and GABAergic interneurons adjusting the response of pyramidal neurons through synaptic inhibition. Microglia are brain resident macrophages which dynamically refine cortical circuits by monitoring perineuronal extracellular matrix and remodelling synapses. Previously, we showed that colony-stimulating factor 1 receptor (CSF1R)-mediated myeloid cell depletion extended the lifespan, but impaired motor functions of MBP29 mice, a mouse model for multiple system atrophy. In order to better understand the mechanisms underlying these motor deficits we characterized the microglial involvement in the cortical balance of GABAergic interneurons and glutamatergic pyramidal neurons in 4-months-old MBP29 mice following CSF1R inhibition for 12 weeks. Lack of myeloid cells resulted in a decreased number of COUP TF1 interacting protein 2-positive (CTIP2+) layer V pyramidal neurons, however in a proportional increase of calretinin-positive GABAergic interneurons in MBP29 mice. While myeloid cell depletion did not alter the expression of important presynaptic and postsynaptic proteins, the loss of cortical perineuronal net area was attenuated by CSF1R inhibition in MBP29 mice. These cortical changes may restrict synaptic plasticity and potentially modify parvalbumin-positive perisomatic input. Collectively, this study suggests, that the lack of myeloid cells shifts the neuronal balance toward an increased inhibitory connectivity in the motor cortex of MBP29 mice thereby potentially deteriorating motor functions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".