Knockout of Dectin-1 does not modify disease onset or progression in a MATR3 S85C knock-in mouse model of ALS
Bibliographic record
Abstract
Abstract Microglia have been increasingly implicated in neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). Dectin-1, encoded by the Clec7a gene, is highly upregulated in a specific microglial response state called disease-associated microglia (DAM) in various neurodegenerative conditions. However, the role of Dectin-1 in ALS is undetermined. Here, we show that Clec7a mRNA upregulation occurs in central nervous system (CNS) regions that exhibit neurodegeneration in a MATR3 S85C knock-in mouse model ( Matr3 S85C/S85C ) of ALS. Furthermore, a significant increase in the number of Dectin-1 + microglia coincides with the onset of motor deficits, and this number increases with disease severity. We demonstrate that the knockout of Dectin-1 does not affect survival, motor function, neurodegeneration, or microglial responses in Matr3 S85C/S85C mice. These findings suggest that Dectin-1 does not play a role in modifying ALS onset or progression but could potentially serve as a valuable biomarker for ALS severity. Subject areas Physiology; Molecular biology; Neuroscience; Immunology Highlights Clec7a upregulation is confined to central nervous system regions that exhibit overt neurodegeneration in a MATR3 S85C knock-in mouse model of ALS The appearance of Dectin-1 + microglia coincides with the onset of motor deficits, and its number increases with disease progression Knockout of Dectin-1 does not modify survival, motor deficits, neurodegeneration, or microglial responses in MATR3 S85C knock-in mice
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".