Barbara Casadei receives award for outstanding research into atrial fibrillation
Bibliographic record
Abstract
All correspondence relating to this article should be sent to [email protected] Barbara Casadei, MD, DPhil, FMedSci, Professor at the British Heart Foundation (BHF) Centre of Research Excellence at the University of Oxford, UK, has been awarded the Lucian Award for outstanding research in the field of circulatory diseases in recognition of her pioneering work into atrial fibrillation (AF). She has been a BHF Professor at Oxford since 2012 and served as President of the European Society of Cardiology from 2018 to 2020 (Figure 1). Barbara Casadei, winner of the 2022 Lucian Award. Prof. Casadei and her team have a long-term focus on understanding the underlying mechanisms of AF and identifying potential targets for treatment which has led to cataloguing key processes behind the genesis and maintenance of this common arrhythmia, including the part played by nitric oxide (NO), reactive oxygen species, and inflammation. Her work has also put potential AF treatments to the test in clinical studies that may ultimately lead to better treatment and prevention of AF. These include investigations of the characteristics of blood flow in the left atrium by magnetic resonance imaging and their relationship with brain infarcts and the use of genetically informed biological pathways to understand the aetiological heterogeneity of AF and to refine prediction of AF-related complications, in collaboration with Prof. Jemma Hopewell in Oxford. The group’s investigations into the effects of myocardial NO production in AF-induced electrical remodelling goes back over 20 years following a 2002 study which described a reduction in NO availability in the atrial endocardium of animal models with pacing-induced AF. This prompted questions and further investigation. Prof. Casadei says: ‘When we started looking at atrial tissue samples from patients with AF, we confirmed that there was a dramatic reduction in NO production due to the near disappearance of the neuronal NO synthase (nNOS) from the fibrillating atrial myocardium in humans and animal models. We then asked ourselves what the mechanisms might be underpinning such a dramatic reduction and looked at what may affect the stability of the nNOS protein.’ To answer this question, the team drew inspiration from studies in patients and animal models of Duchenne muscular dystrophy. Prof. Casadei says: ‘From work on Duchenne Muscular Dystrophy, we knew that lack of dystrophin displaces nNOS from the cell membrane and, in the skeletal muscle, leads to its near disappearance. We found that AF was associated with a reduction in dystrophin in the atrial myocardium, and then found that there was an upregulation of a microRNA that was already known in Duchenne’s to inhibit the translation of the dystrophin messenger RNA. Furthermore, upregulation of that particular microRNA was also accelerating the decay of nNOS mRNA. The dramatic reduction in atrial nNOS that followed, altered the function of several myocardial ion channels which contribute to the atrial electrical remodelling that begets AF.’ Prof. Svetlana Reilly, MD, DPhil, who was one of the Prof. Casadei’s graduate students and is now a BHF Senior Research Fellow, is taking this work forward into investigations of the mechanisms responsible for atrial structural remodelling and fibrosis in the presence of AF. Understanding the mechanisms behind atrial fibrosis, Prof. Casadei says, may open up new avenues for preventing AF, greatly increasing the efficacy of ablation and possibly even reducing the risk of cardioembolic stroke. ‘The mechanisms that regulate the fibrotic process in the human atrium can uncover, as Prof. Reilly demonstrated, novel therapeutic targets that could be relevant to a host of conditions, from HFpEP to pulmonary hypertension, for which we only have partially effective treatment.’ Prof. Casadei acknowledges that translating science discovery into clinical practice is a long and challenging process that requires a breadth of techniques and models and sustained funding from many sources. ‘Failure to take a basic discovery into the clinic is much more common than success’ she says, ‘but rigorously conducted research always makes an important contribution to our knowledge, whether it proves or disproves our original hypothesis’. The Lucian Award is an annual accolade for research in circulatory disease, established by a bequest to McGill University, Canada, in 1965 in memory of brothers Louis and Artur Lucian. Prof. Casadei was the sole recipient of the 2022 award; however, she emphasizes the recognition of her team’s work rather than personal accolades. ‘It’s always a great honour to be given awards and I was very happy to receive the Lucian Award on this occasion. However, this is not just an award for me, it’s also a recognition for the work that my graduate students, clinical fellows and collaborators have undertaken with passion and determination, and of everything we have been able to achieve together as a “team of explorers”.’ All authors declare no conflict of interest for this contribution.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.100 | 0.066 |
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".