Fibroblastic Reticular Cells Control Conduit Matrix Deposition during Lymph Node Expansion
Bibliographic record
Abstract
Lymph nodes (LNs) act as filters, constantly sampling peripheral cues. This is facilitated by the conduit network, a tubular structure of aligned extracellular matrix (ECM) fibrils ensheathed by fibroblastic reticular cells (FRCs). LNs undergo 3-5-fold expansion during each adaptive immune response but these ECM-rich structures are not permanently damaged. Whether conduit integrity and filtering function is affected during LN expansion is unknown. Here we show that conduits are disrupted during acute LN expansion but FRC-FRC contacts remain connected. We reveal that polarised FRCs deposit ECM basolaterally utilising LL5-β, and that ECM production is regulated at transcriptional and secretory levels by the C-type lectin CLEC-2, expressed by dendritic cells. Inflamed LNs maintain conduit size-exclusion, but flow becomes leaky, allowing soluble molecules increased access to antigen-presenting cells. We show how dynamic communication between peripheral tissues and LNs changes during immune responses, and describe a mechanism enabling LNs to prevent inflammation-induced fibrosis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".