Deficient Surveillance and Phagocytic Activity of Myeloid Cells Within Demyelinated Lesions in Aging Mice Visualized by<i>Ex Vivo</i>Live Multiphoton Imaging
Bibliographic record
Abstract
Aging impairs regenerative processes including remyelination, the synthesis of a new myelin sheath. Microglia and other infiltrating myeloid cells such as macrophages are essential for remyelination through mechanisms that include the clearance of inhibitory molecules within the lesion. Prior studies have shown that the quantity of myeloid cells and the clearance of inhibitory myelin debris are deficient in aging, contributing to the decline in remyelination efficiency with senescence. It is unknown, however, whether the impaired clearance of debris is simply the result of the reduced number of phagocytes or if the dynamic activity of myeloid cells within the demyelinating plaque also declines with aging and this question is relevant to the proper design of therapeutics to mobilize myeloid cells for repair. Herein, we describe a high-resolution multiphotonex vivolive imaging protocol that visualizes individual myelinated/demyelinated axons and lipid-containing myeloid cells to investigate the demyelinated lesion of aging female mice. We found that aging lesions have fewer myeloid cells and that these have reduced phagocytosis of myelin. Although the myeloid cells are actively migratory within the lesion of young mice and have protrusions that seem to survey the environment, this motility and surveillance is significantly reduced in aging mice. Our results emphasize the necessity of not only increasing the number of phagocytes, but also enhancing their activity once they are within demyelinated lesions. The high-resolution live imaging of demyelinated lesions can serve as a platform with which to discover pharmacological agents that rejuvenate intralesional remodeling that promotes the repair of plaques. SIGNIFICANCE STATEMENTThe repair of myelin after injury depends on myeloid cells that clear debris and release growth factors. As organisms age, remyelination becomes less efficient correspondent with fewer myeloid cells that populate the lesions. It is unknown whether the dynamic activity of cells within lesions is also altered with age. Herein, using high-resolution multiphotonex vivolive imaging with several novel features, we report that myeloid cells within demyelinated lesions of aging mice have reduced motility, surveillance, and phagocytic activity, suggesting an intralesional impairment that may contribute to the age-related decline in remyelination efficiency. Medications to stimulate deficient aging myeloid cells should not only increase their representation, but also enter into lesions to stimulate their activity.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".