Relevance of the Bruton Tyrosine Kinase as a Target for COVID-19 Therapy
Bibliographic record
Abstract
The outbreak of the novel coronavirus disease 2019 (COVID-19) has emerged as one of the biggest global health threats worldwide. As of October 2020, more than 44 million confirmed cases and more than 1,160,000 deaths have been reported globally, and the toll is likely to be much higher before the pandemic is over. There are currently little therapeutic options available and new potential targets are intensively investigated. Recently, Bruton tyrosine kinase (BTK) has emerged as an interesting candidate. Elevated levels of BTK activity have been reported in blood monocytes from patients with severe COVID-19, compared with those from healthy volunteers. Importantly, various studies confirmed empirically that administration of BTK inhibitors (acalabrutinib and ibrutinib) decreased the duration of mechanical ventilation and mortality rate for hospitalized patients with severe COVID-19. Herein, we review the current information regarding the role of BTK in severe acute respiratory syndrome coronavirus 2 infections and the suitability of its inhibitors as drugs to treat COVID-19. The use of BTK inhibitors in the management of COVID-19 shows promise in reducing the severity of the immune response to the infection and thus mortality. However, BTK inhibition may be contributing in other ways to inhibit the effects of the virus and this will need to be carefully studied.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".