Increased circulating TREM2+ microglial extracellular vesicles in aged APP/PS1 Alzheimer's disease rats
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
<title>Abstract</title> TREM2 is a microglial marker important in Alzheimer’s disease (AD) risk and pathogenesis, but current methods to detect microglial TREM2 expression <italic>in vivo</italic> are limited. Circulating extracellular vesicles (EVs) show promise as potential biomarkers for AD, and microglial EVs (MEVs) may offer valuable insight into brain TREM2 activity. Here, we investigated plasma-derived TREM2<sup>+</sup> MEVs as a potential biomarker of brain microglial TREM2 activity and cognition in a rat model of aging and AD. TMEM119<sup>+</sup>/TREM2<sup>+</sup> EVs were fluorescently labelled and assessed using nanoscale flow cytometry directly in plasma collected from wildtype and APP/PS1 rats aged to 3-, 9-, and 15-months-old. Molecular and histological assays were used to assess microglial markers in rat brain tissue, and a radial arm water maze task was employed to evaluate spatial working and reference memory. We demonstrated that TMEM119<sup>+</sup>/TREM2<sup>+</sup> EVs can be detected in the systemic circulation and were increased in 15-month APP/PS1 rats. Further, the amount of TMEM119<sup>+</sup>/TREM2<sup>+</sup> EVs associated with the severity of cognitive impairment in aged rats, while TREM2 brain expression varied by anatomical region, age, transgene, and assay. Collectively, this study provides the first assessment of TMEM119<sup>+</sup>/TREM2<sup>+</sup> EVs as a biomarker of brain microglial expression and cognition in a rat model of aging and 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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