Survival motor neuron protein deficiency alters microglia reactivity
Bibliographic record
Abstract
Survival motor neuron (SMN) protein deficiency results in loss of alpha motor neurons and subsequent muscle atrophy in patients with spinal muscular atrophy (SMA). Reactive microglia have been reported in SMA mice and depleting microglia rescues the number of proprioceptive synapses, suggesting a role in SMA pathology. Here, we explore the contribution of lymphocytes on microglia reactivity in SMA mice and investigate how SMN deficiency alters the reactive profile of human induced pluripotent stem cell (iPSC)-derived microglia. We show that microglia adopt a reactive morphology in spinal cords of SMA mice. Ablating lymphocytes did not alter the reactive morphology of SMA microglia and did not improve the survival or motor function of SMA mice, indicating limited impact of peripheral immune cells on the SMA phenotype. We found iPSC-derived SMA microglia adopted an amoeboid morphology and displayed a reactive transcriptome profile, increased cell migration, and enhanced phagocytic activity. Importantly, cell morphology and electrophysiological properties of motor neurons were altered when they were incubated with conditioned media from SMA microglia. Together, these data reveal that SMN-deficient microglia adopt a reactive profile and exhibit an exaggerated inflammatory response with potential impact on SMA neuropathology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".