Editorial: Repurposing β-blockers for non-cardiovascular diseases
Bibliographic record
Abstract
Editorial on the Research Topic Repurposing β-blockers for non-cardiovascular diseases β-Blockers are a class of drugs that have been approved by the FDA for the treatment of cardiovascular diseases.However, Some β-blockers have been found to be effective in treating other disorders beyond the cardiovascular system, such as CNS conditions, diabetes, cancer, and organ toxicities (Alaskar et al., 2023;Beaman et al., 2023;Chen et al., 2023;Shahid et al., 2023).Furthermore, β-blockers are proposed to act as immunomodulators due to the role of β-adrenergic receptors in immunity (Fjaestad et al., 2022).Regarding the protection against organ toxicity, non-selective β-blockers, such as carvedilol and propranolol, have been found to protect against renal toxicity (Rodrigues et al., 2010;Rezayat et al., 2017).The effects of β-blockers on diseases outside of the cardiovascular system may not necessarily be related to their β-blocking activity.This issue compiles preclinical and clinical studies, along with a review article, on the use of βblockers for non-cardiovascular diseases.These studies provide evidence for repurposing these FDA-approved drugs for other diseases and identifying new mechanisms for their use beyond β-adrenergic receptor blockade.According to Massalee and Coa, β-blockers could be a possible treatment for cancer by blocking β-adrenergic receptor signaling, which is associated with tumor growth and immune system suppression.β-Blockers may also work well in combination with chemotherapy by enhancing anti-proliferative, antimitotic, and antimitochondrial properties, leading to better control of tumors and improved therapy outcomes.β-Blockers could also improve cancer immunotherapy by blocking immunosuppressive signaling and boosting the functionality of immune cells such as CD8 + T cells.Nonselective β-blockers, which inhibit both β1-and β2-adrenergic receptors, may be more effective in decreasing tumor proliferation and improving overall survival compared to selective β-blockers.More preclinical and clinical studies are needed to confirm the synergistic potential of combining β-blockers with conventional cancer therapies and/or immunotherapies.There are still challenges in understanding the mechanisms underlying the non-cardiovascular effects of β-blockers and how to use these drugs to improve clinical outcomes in non-cardiovascular diseases.Yang et al. aimed to evaluate the potential association between β-blockers and reduced mortality in patients with sepsis.The study involved analyzing data from two large ICU databases comprising 61,751 sepsis patients, out of which 43.8% received β-blockers.The data set included both selective and non-selective β-blockers administered by intravenous
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.023 | 0.022 |
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".