Loss of CD34 Leads To Exacerbated Autoimmune Arthritis through Increased Vascular Permeability
Bibliographic record
Abstract
CD34 is a cell surface sialomucin expressed by hematopoietic precursors, eosinophils, mast cells, and vascular endothelia and is suggested to play an integral role in mucosal inflammatory responses. Although Cd34(-/-) mice have normal hematopoietic cell subsets in peripheral tissues at steady state, they exhibit a cell recruitment defect when challenged, offering a unique opportunity to distinguish between local inflammatory cell proliferation and peripheral recruitment in disease. Autoimmune arthritis is an inflammatory disease dependent on hematopoietic infiltration, and in this study, we have examined the role of CD34 in disease development and progression. Using an autoimmune serum transfer model, arthritis was induced in C57BL/6 wild-type and Cd34(-/-) mice. Surprisingly, we found that Cd34(-/-) mice were more susceptible to arthritis than wild-type mice. We examined mast cell-transplanted, eosinophil-deficient, and bone marrow-chimeric mice to determine the role of CD34 expression on disease progression. These experiments excluded CD34-deficient mast cells, eosinophils, or hematopoietic cells as the cause of the exacerbated disease. Further study demonstrated that Cd34(-/-) mice exhibit increased vascular leakage at onset of disease and in response to TNF, which correlated with a subsequent increase in disease severity. We conclude that loss of CD34 expression leads to increased vascular permeability in the joints at onset of disease, leading to exacerbated arthritic disease in Cd34(-/-) mice.
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 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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".