Immune cells surveil aberrantly sialylated <i>O</i>-glycans on megakaryocytes to regulate platelet count
Bibliographic record
Abstract
Immune thrombocytopenia (ITP) is a platelet disorder. Pediatric and adult ITP have been associated with sialic acid alterations, but the pathophysiology of ITP remains elusive, and ITP is often a diagnosis of exclusion. Our analysis of pediatric ITP plasma samples showed increased anti-Thomsen-Friedenreich antigen (TF antigen) antibody representation, suggesting increased exposure of the typically sialylated and cryptic TF antigen in these patients. The O-glycan sialyltransferase St3gal1 adds sialic acid specifically on the TF antigen. To understand if TF antigen exposure associates with thrombocytopenia, we generated a mouse model with targeted deletion of St3gal1 in megakaryocytes (MK) (St3gal1MK-/-). TF antigen exposure was restricted to MKs and resulted in thrombocytopenia. Deletion of Jak3 in St3gal1MK-/- mice normalized platelet counts implicating involvement of immune cells. Interferon-producing Siglec H-positive bone marrow (BM) immune cells engaged with O-glycan sialic acid moieties to regulate type I interferon secretion and platelet release (thrombopoiesis), as evidenced by partially normalized platelet count following inhibition of interferon and Siglec H receptors. Single-cell RNA-sequencing determined that TF antigen exposure by MKs primed St3gal1MK-/- BM immune cells to release type I interferon. Single-cell RNA-sequencing further revealed a new population of immune cells with a plasmacytoid dendritic cell-like signature and concomitant upregulation of the immunoglobulin rearrangement gene transcripts Igkc and Ighm, suggesting additional immune regulatory mechanisms. Thus, aberrant TF antigen moieties, often found in pathological conditions, regulate immune cells and thrombopoiesis in the BM, leading to reduced platelet count.
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 | 0.000 | 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 | 0.000 | 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 | 0.001 |
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 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".