The thrombomodulin lectin-like domain does not change host responses to tuberculosis
Bibliographic record
Abstract
Tuberculosis (TB), caused by Mycobacterium (M.) tuberculosis, is a devastating infectious disease causing many deaths world-wide. Thrombomodulin (TM) is a multidomain glycoprotein expressed on all vascular endothelial cells. We here studied the role of the lectin-like domain of TM, responsible for a variety of anti-inflammatory properties of TM, during TB. We compared the extent of TM-expression in human lung tissue of TB and control patients. The, the role of the lectin-like domain of TM was investigated by comparing mice lacking this domain (TMLeD/LeD mice) with wild-type (WT) mice during experimental lung TB induced by infection with M. tuberculosis via the airways. Lungs were harvested for analyses at two, six and 29 weeks after infection. Lung TM-expression was downregulated in TB patients, which was not related to changes in the amount of endothelium in infected lungs. TMLeD/LeD mice showed unaltered mycobacterial loads in lungs, liver and spleen during experimental TB. Additionally, lung histopathology and cytokine concentrations were largely similar in TMLeD/LeD and WT mice, while total leukocyte counts were increased in lungs of TMLeD/LeD mice after 29 weeks of infection. Mortality did not occur in either group. The lectin-like domain of TM does not play an important role in the host response to M. tuberculosis infection in mice.
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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 | 0.001 |
| 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".