A role for lymphatic endothelium in the sequestration of recirculating γ δ T cells in TNF-α-stimulated lymph nodes
Bibliographic record
Abstract
TNF-alpha is one of the most potent immunoregulatory molecules in vivo. In addition to important regulatory effects, it is also a potent inducer of extravascular lymphocyte infiltration. To examine the dynamic changes that are induced in local lymphocyte migration through regional lymph nodes following TNF-alpha injection, we used a protocol of direct lymphatic cannulation to quantitatively and qualitatively examine the traffic of lymphocytes through regional lymph nodes. We observed that local TNF-alpha injection reduced the output of lymphocytes from lymph nodes up to 90% within 6-10 h following stimulation. TNF-alpha also altered the specificity of migration of lymphocyte traffic through subcutaneous lymph nodes. In addition to the decreased output, phenotypic analysis demonstrated decreases in the concentration of gamma delta T cells by up to 30% following TNF-alpha injection. Histological examination showed that the gamma delta T cells were found in close association with VCAM-1-expressing cells in TNF-stimulated lymph nodes, at least some of which appeared to be lymphatic endothelium. These data indicate that TNF-alpha is capable of altering the number and specificity of lymphocytes recirculating through stimulated lymph nodes by selectively altering the entry of lymphocytes into the efferent lymphatics of inflamed lymph nodes in vivo.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".