A novel small molecule phagocytosis inhibitor, <scp>KB</scp>‐208, ameliorates <scp>ITP</scp> in mouse models with similar efficacy as <scp>IVIG</scp>
Bibliographic record
Abstract
BACKGROUND: The characteristic feature of immune cytopenias involves the process of extravascular phagocytosis, wherein macrophages in the spleen and/or liver engage in the destruction of blood cells that have been opsonized by auto- or alloantibodies. Therefore, new treatments that prevent phagocytosis will be advantageous, especially for short-term usage along with alternative options. STUDY DESIGN AND METHODS: KB-208, a small molecule drug, previously shown to be efficacious for the in vitro inhibition of phagocytosis was synthesized. A passive antibody mouse model of immune thrombocytopenia (ITP) was used. Three different mouse strains (BALB/c, C57BL/6, CD1) were used to determine the efficacy of KB-208 compared with IVIG to ameliorate the ITP. Toxicity was investigated after 60-day chronic administration of KB-208 by a biochemistry panel, gross necroscopy and histopathology. RESULTS: KB-208 showed similar efficacy to ameliorate the thrombocytopenia compared with IVIG in all three mouse strains. This small molecule drug was effective at 1 mg/kg in ameliorating ITP, in comparison with IVIG at 1000-2500 mg/kg. KB-208 did not affect other blood parameters or elevate serum biochemistry markers of toxicity nor were any abnormal histopathological findings found. CONCLUSION: KB-208 is similar to IVIG for the amelioration of ITP in multiple mouse strains. Chronic administration of KB-208 for 60 days did not demonstrate in vivo toxicity. These findings indicate that KB-208 is efficacious, without significant in vivo toxicities in mice, and is a potential small molecule candidate for further evaluation to be used in the treatment of ITP and possibly all immune cytopenias where phagocytosis is responsible for the pathophysiology.
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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".