Bibliographic record
Abstract
Unlike most organs, tissue regeneration and repair are not very efficient in the CNS, which explains the severity of neurodegenerative diseases. Many have hoped that stem cells would provide an effective mean to solve this problem. Unfortunately, evidence supporting this approach remains controversial. In this review, we discuss the capacity of stem cells to generate the cells that reside in the brain. Neural stem cells are able to generate new neurons, astrocytes and oligodendrocytes, but not microglia. The latter are instead replenished by self-replication and monocyte recruitment across the blood-brain barrier. The fact that blood-derived monocytes can enter the brain and differentiate into microglial cells has many implications for neurodegenerative diseases. They are more efficient antigen-presenting cells and produce proinflammatory molecules that can be both detrimental to the brain and beneficial to recovery and repair after insults. It is therefore very important to better understand the role of these newly differentiated microglia before devising therapeutic strategies to either inhibit or improve their recruitment at diseased and injured sites.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".