Differential Detection and Distribution of Microglial and Hematogenous Macrophage Populations in the Injured Spinal Cord of<i>lys</i>-EGFP-<i>ki</i>Transgenic Mice
Bibliographic record
Abstract
The acute inflammatory response that follows spinal cord injury (SCI) contributes to secondary injury that results in the expansion of the lesion and further loss of neurologic function. A cascade of receptor-mediated signaling events after SCI leads to activation of innate immune responses including the migration of microglia and active recruitment of circulating leukocytes. Because conventional techniques do not always distinguish macrophages derived from CNS-resident microglia from blood-derived monocytes, the role that each macrophage type performs cannot be assessed unambiguously in these processes. We demonstrate that, in the normal and spinal cord-injured lys-EGFP-ki transgenic mouse, enhanced green fluorescent protein (EGFP) is expressed only in mature hematopoietic granulomyelomonocytic cells and not in microglia. This allowed us to assess the temporal and spatial relationships between microglia-derived and hematogenous macrophages as well as neutrophils during a period of 6 weeks after clip compression SCI. Within the lesion, EGFP-positive monocyte-derived macrophages were found at the epicenter surrounded by EGFP-negative-activated microglia and microglia-derived macrophages. Neutrophils were not present when EGFP-positive monocyte-derived macrophages were depleted, indicating that neutrophil persistence in the lesion depended on the presence of these monocytes. Thus, these 2 distinct macrophage populations can be independently identified and tracked, thereby allowing their roles in acute and chronic stages of SCI-associated inflammation to be defined.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".