Amyloid-β-driven Alzheimer’s disease reshapes the colonic immune system in mice
Bibliographic record
Abstract
The "gut-brain axis" is an emerging target in Alzheimer's disease (AD), although its immunological features remain poorly understood. Using single-cell RNA sequencing, coupled to extensive spectral-tuning flow cytometry validation of the colon immune compartment in the 5XFAD amyloid-β mouse model, we found several AD-associated changes including in B/plasma cell activity. Notably, levels of CXCR4 + antibody-secreting cells are reduced in 5XFAD colons. This change corresponds with accumulating CXCR4 + B cells and gut-specific IgA + cells in the brain and dura mater, respectively. Consistently, a chemokine ligand for CXCR4, CXCL12, is expressed at higher levels in the 5XFAD brain and in in silico -analyzed human AD brain studies, supporting altered neuroimmune trafficking. An inulin prebiotic fiber diet could expand gut IgA + cells, rescue peripheral T reg levels, reduce dysbiosis, improve serum microbial metabolite levels, and attenuate overall AD-associated frailty. Our study reveals key aspects of the gut-brain axis and highlights potential targets against 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.
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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".