Microglia Heterogeneity in Alzheimer’s Disease: Insights From Single-Cell Technologies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Microglia are resident immune cells in the central nervous system and play critical roles in brain immunity, development, and homeostasis. The pathology of Alzheimer's disease (AD) triggers activation of microglia. Microglia express many AD risk genes, suggesting that their response to AD pathology can affect disease progression. Microglia have long been considered a homogenous cell population. The diversity of microglia has gained great interest in recent years due to the emergence of novel single-cell technologies, such as single-cell/nucleus RNA sequencing and single-cell mass cytometry by time-of-flight. This review summarizes the current knowledge about the diversity/heterogeneity of microglia and distinct microglia states in the brain of both AD mouse models and patients, as revealed by single-cell technologies. It also discusses the future developments for application of single-cell technologies and the integration of these technologies with functional studies to further dissect microglia biology in AD. Defining the functional correlates of distinct microglia states will shed new light on the pathological roles of microglia and might uncover new relevant therapeutic targets for AD.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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 it