Macrophages drive inguinal fat pad and lymph node remodelling in response to peripheral inflammation
Bibliographic record
Abstract
Abstract Adaptive immune responses are intensely energy-dependent and rely on a local source of fuel-producing molecules which have been proposed to be derived from fat pads in which mammalian lymph nodes are embedded. However, the trigger for their release has not been identified. Here we demonstrate that cutaneous inflammation is directly correlated with rapid atrophy of perinodal fat pads and increase in embedded lymph node size. We further demonstrate that the fat pad atrophy is associated with influx of a CCR2-independent, lipid metabolising, macrophage population. Macrophage depletion ameliorates fat pad atrophy, and lymph node expansion, downstream of inflamed sites. Our data therefore identify peripheral inflammation as an antigen-independent trigger of downstream fat pad and lymph node remodelling and contributes to the release of essential nutrients to drive the energetic requirements of the adaptive immune response. Significance statement To our knowledge, this striking correlation between peripheral inflammation and reciprocal fat pad and lymph node remodelling has not been reported previously. Our report of this correlation and our mechanistic insight, have clear implications for our understanding of the inflammation-driven rapid release of sources of energy from fat pads to drive the immune response. Our data also potentially shed light on additional aspects of the functionality of pro-inflammatory vaccine adjuvants. We believe that our findings are fully novel and will be of interest to immunologists, infectious disease specialists and researchers interested in adipose tissue derived energetics.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".