The lectin-like domain of thrombomodulin ameliorates diabetic glomerulopathy via complement inhibition
Bibliographic record
Abstract
Coagulation and complement regulators belong to two interactive systems constituting emerging mechanisms of diabetic nephropathy. Thrombomodulin (TM) regulates both coagulation and complement activation, in part through discrete domains. TM's lectin like domain dampens complement activation, while its EGF-like domains independently enhance activation of the anti-coagulant and cytoprotective serine protease protein C (PC). A protective effect of activated PC in diabetic nephropathy is established. We hypothesised that TM controls diabetic nephropathy independent of PC through its lectin-like domain by regulating complement. Diabetic nephropathy was analysed in mice lacking TM's lectin-like domain (TMLeD/LeD) and controls (TMwt/wt). Albuminuria (290 μg/mg vs. 166 μg/mg, p=0.03) and other indices of experimental diabetic nephropathy were aggravated in diabetic TMLeD/LeD mice. Complement deposition (C3 and C5b-9) was markedly increased in glomeruli of diabetic TMLeD/LeD mice. Complement inhibition with enoxaparin ameliorated diabetic nephropathy in TMLeD/LeD mice (e.g. albuminuria 85 μg/mg vs. 290 μg/mg, p<0.001). In vitro TM's lectin-like domain cell-autonomously prevented glucose-induced complement activation on endothelial cells and - notably - on podocytes. Podocyte injury, which was enhanced in diabetic TMLeD/LeD mice, was reduced following complement inhibition with enoxaparin. The current study identifies a novel mechanism regulating complement activation in diabetic nephropathy. TM's lectin-like domain constrains glucose-induced complement activation on endothelial cells and podocytes and ameliorates albuminuria and glomerular damage in 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".