Age-related enlargement of lymphoid tissue and altered leukocyte composition in serglycin-deficient mice
Bibliographic record
Abstract
Serglycin (SG) is a proteoglycan that is located predominantly in the secretory granules of hematopoietic cells. Previous studies have established a crucial role for SG in promoting the storage of various secretory granule compounds that are of importance in the immune defense system. Here, we show that mice lacking SG spontaneously develop enlargement of multiple lymphoid organs, including the spleen, Peyer's patches (PP), and bronchus-associated lymphoid tissue. In the spleen, the lack of SG resulted in a significant decrease in the proportion of CD4(+) cells as well as an increase of the CD45RC(+) leukocyte population, indicating an expansion of naïve lymphocytes. In the PP, the lack of SG resulted in a general increase in cellularity, without significant alterations in the proportion of individual leukocyte populations. The enlargement of lymphoid tissues was not accompanied by increased serum levels of inflammatory cytokines. The number of mast cells in the peritoneum was not affected by the lack of SG, as judged by surface staining for CD117 (c-kit). However, the intensity of c-kit staining was reduced significantly in SG null animals. Moreover, the number of peritoneal macrophages, defined by morphological criteria and by CD11b staining, was decreased markedly in older, SG-deficient animals. Finally, experiments in which airway inflammation was induced by bacterial LPS revealed a more pronounced inflammatory response in old, SG-deficient as compared with wild-type mice. Taken together, our data show that SG deficiency causes multiple, age-related effects on the lymphoid system.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".