SPARC Regulates Microgliosis and Functional Recovery following Cortical Ischemia
Bibliographic record
Abstract
Secreted protein acidic rich in cysteine (SPARC) is a matricellular protein that modulates the activity of growth factors, cytokines, and extracellular matrix to play multiple roles in tissue development and repair, such as cellular adhesion, migration, and proliferation. Throughout the CNS, SPARC is highly localized in mature ramified microglia, but its role in microglia--in development or during response to disease or injury--is not understood. In the postnatal brain, immature amoeboid myeloid precursors only induce SPARC expression after they cease proliferation and migration, and transform into mature, ramified resting microglia. SPARC null/CX3CR1-GFP reporter mice reveal that SPARC regulates the distribution and branching of mature microglia, with significant differences between cortical gray and white matter in both controls and SPARC nulls. Following ischemic and excitotoxic lesion, reactive, hypertrophic microglia rapidly downregulate and release SPARC at the lesion, concomitant with reactive, hypertrophic perilesion astrocytes upregulating SPARC. After photothrombotic stroke in the forelimb sensorimotor cortex, SPARC nulls demonstrate enhanced microgliosis in and around the lesion site, which accompanies significantly enhanced functional recovery by 32 d after lesion. Microglia from SPARC nulls also intrinsically proliferate at a greater rate in vitro--an enhanced effect that can be rescued by the addition of exogenous SPARC. SPARC is thus a novel regulator of microglial proliferation and structure, and, in addition to regulating glioma progression, may play an important role in differently regulating the gray and white matter microglial responses to CNS lesion--and modulating behavioral recovery--after injury.
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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 | 0.001 |
| 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".