Transcriptome Analysis Identified <i>SPP1+</i> Monocytes as a Key in Extracellular Matrix Formation in Thrombi
Bibliographic record
Abstract
Abstract Thrombi follow various natural courses. They are known to become harder over time and may persist long-term; some of them can also undergo early spontaneous dissolution and disappearance. Hindering thrombus stability may contribute to the treatment of thrombosis and the prevention of embolisms. However, the detailed mechanisms underlying thrombus maturation remain unknown. Using RNA sequencing, we revealed the transcriptional landscape of thrombi retrieved from the cerebral vessels and identified SPP1 as a hub gene related to extracellular matrix formation. Immunohistochemistry confirmed the expression of osteopontin in monocytes/macrophages in the thrombi, particularly in older thrombi. Single-cell RNA sequencing of thrombi from the pulmonary artery revealed increased communication between SPP1 -high monocytes/macrophages and fibroblasts. These data suggest that SPP1 -high monocytes/macrophages play a crucial role in extracellular matrix formation in thrombi and provide a basis for new antithrombotic therapies targeting thrombus maturation. Teaser SPP1+ monocytes play a key role in thrombus maturation, which can be a potential target for novel antithrombotic therapies.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".