Bone Marrow-Derived Macrophages from AβPP/PS1 Mice are Sensitized to the Effects of Inflammatory Stimuli.
Bibliographic record
Abstract
Macrophages are key cells in tissue defense in the periphery and, under certain circumstances, infiltrate the central nervous system, where they may play a similar role in the brain, perhaps supporting the function of microglia. Macrophages have been shown to adopt different activation states in response to various stimuli. Specifically, when exposed to inflammatory stimuli such as interferon (IFN)γ, the cells adopt the M1 phenotype, whereas when exposed to anti-inflammatory cytokines such as interleukin (IL)-4 or IL-13, the M2 phenotype is adopted. While M1 macrophages are associated with tissue defense and destruction of invading pathogens, M2 macrophages are involved in tissue repair and in terminating inflammation. It is well known that an inflammatory microenvironment exists in the brain of aged animals and also in the brain of mice that overexpress amyloid-β protein precursor (AβPP) and presenilin 1 (PS1; AβPP/PS1 mice), a commonly-used model of Alzheimer's disease (AD). Recent studies have revealed that immune cells, including macrophages, infiltrate the brain in both circumstances raising the possibility that these cells adopt the M1 activation state and contribute to the already-existing neuroinflammation. We set out to examine the responses of bone marrow-derived macrophages prepared from wildtype and AβPP/PS1 mice and demonstrate that cells from AβPP/PS1 mice, even after several days in culture, respond more profoundly to IFNγ than those from wildtype mice. We suggest that this propensity to respond to M1-polarizing stimuli, together with the described changes in the brain of AβPP/PS1 mice, contribute to the development of chronic neuroinflammation
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".