OC 66.1 Comparative Analysis of Coagulopathy in Baboon Models of Toxigenic Versus Non-Toxigenic Bacillus Anthracis Sepsis
Bibliographic record
Abstract
with heavy chains expressing conserved HCDR3 amino acid motifs, indicating shared pathways of anti-PF4 production (PMID:35661872).Given the likely role of these antibodies in mediating VITT, we sought to generate recombinant antibodies (recAbs) from these serum anti-PF4 clonotypes utilising a reverse engineering approach and study their immunological and functional properties.Aims: Engineer and characterize anti-PF4 recAbs derived from serum Ab sequences and investigate their effects on platelet and endothelial cell (EC) function.Methods: Ig heavy-and light-chain genes were constructed from anti-PF4 Ig variable (IgV) and constant (IgC) region amino acid sequences and expressed as full length clonotypic IgGs in CHO cells.Immunoreactivity was confirmed by Biolayer interferometry (BLI) and ELISA.The effect of anti-PF4 recAbs on platelet activation was studied by PF4-induced platelet activation assay (PIPAA).Human lung microvascular EC stimulation was assessed by Pselectin, ICAM-1, and VE-cadherin expression following 24-hour incubation with anti-PF4 recAbs and VITT sera.Results: Five BLI-and ELISA-immunoreactive anti-PF4 recAbs were reverse engineered from two VITT patient sera and their translated IgV and IgC amino acid sequences authenticated by MS.Epitope specificity as assessed by human PF4 alanine mutants revealed R22 as a key PF4-binding residue, consistent with an earlier study (PMID:34233346).All anti-PF4 recAbs elicited a positive reaction in PIPAA.Furthermore, there was an upregulation of P-selectin on ECs by recAbs and 5%(v/v) VITT sera. Conclusion(s):We report the first successful "reverse engineering" of platelet-activating, stereotypic anti-PF4 recAbs whose sequences are based on authentic serum clonotypes.The anti-PF4-induced up-regulation of EC P-selectin may contribute to thrombotic events and requires further study.These authentic human anti-PF4 recAbs will be important research tools for unravelling VITT pathogenesis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.005 | 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".