Microglia in cerebral ischemia: molecular actions and interactionsThis paper is one of a selection of papers published in this Special Issue, entitled Young Investigator's Forum.
Bibliographic record
Abstract
The precise role of microglia in stroke and cerebral ischemia has been the subject of debate for a number of years. Microglia are capable of synthesizing numerous soluble and membrane-bound biomolecules, some known to be neuroprotective, some neurotoxic, whereas others have less definitive bioactivities. The molecular mechanisms through which microglia activate these molecules have thus become an important area of ischemia research. Here we provide a survey review that summarizes the key actions of microglial factors in cerebral ischemia including complement proteins, chemokines, pro-inflammatory cytokines, neurotrophic factors, hormones, and proteinases, as well several important messenger molecules that play a part in how these factors respond to extracellular signals during ischemic injuries. We also provide some new perspectives on how microglial intracellular signaling may contribute to the seemingly contradictory roles of several microglial effector molecules.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".