Lymph Node Subcapsular Sinus Macrophages as the Frontline of Lymphatic Immune Defense
Bibliographic record
Abstract
Lymphatic vessels collect and transport lymph and pathogens to the draining lymph node (LN) to generate proper immune protection. A layer of macrophages that strategically line the LN subcapsular sinus (SCS) is directly exposed to the afferent lymph and are denoted as SCS macrophages. These macrophages are the frontline of immune defense that interact with lymph-borne antigens. The importance of these macrophages in limiting the spread of pathogens has been demonstrated in both viral and bacterial infection. In anti-microbial responses, these macrophages can directly or indirectly activate other LN innate immune cells to fight against pathogens, as well as activate T cells or B cells for adaptive immunity. As the first layer of immune cells embracing the tumor-derived antigens, SCS macrophages also actively participate in cancer immune regulation. Recent studies have shown that the LNs' SCS macrophage layer is interrupted in disease models. Despite their importance in fighting the spread of pathogens and in activating anti-tumor immunity, the mechanism and the immunological functional consequences for their disruption are not well-understood. Understanding the mechanism of these macrophages will enhance their capability for therapeutic targeting.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".