Bibliographic record
Abstract
The 2023 annual meeting of the European Council for Cardiovascular Research (ECCR) was a successful virtual on-line meeting. More than 100 participants, including trainees, early career researchers and established investigators from several European countries, UK, USA, and Canada participated and enjoyed two days of outstanding research presentations. The meeting covered different topics of cardiovascular and cardiometabolic research from basic to clinical science.The lectures' programme included the cutting-edge research in the cardiovascular pathophysiology and cardiometabolic diseases. Eminent international scientists presented and discussed different topics including the role of aging in neurovascular interface of the heart, the role of reactive oxygen species, inflammation and immune system in hypertension and hypertension related neurovascular dysfunction and cognitive impairment. Great interest and discussion were also stimulated by lectures on the mechanisms of autophagy in cardiomyopathies, the role of immune-mediated denervation of the pineal gland in the sleep disturbance associated to cardiac diseases, and the role of microtubule network on arterial contractility. New aspects of renin-angiotensin system modulation were also presented with a particular focus on the biological role of angiotensin-(1-5) in the vascular (patho)-physiology and the role of angiotensin suppression in cardiorenal protection. Great interest was also stimulated by the lectures on the mechanisms and therapeutic solutions in obesity for cardiovascular protection, the role of magnesium in health and disease as well as by translational research on the cardiorenal protective effects of combining SGLT2 Inhibition, endothelin receptor antagonism and RAS blockade in a model of diabetes. The audience, and particularly the young researchers, also appreciated the provocative keynote lecture by Michael Ryan on cardiovascular research and publishing in the era of AI.ECCR always encourages interaction among young scientists in the cardio-metabolic field and promotes networking among them and dedicates great effort to promote education and mentorship. Forty-four abstracts were selected, and the meeting has been an opportunity for young researchers to present themselves and their research to an international audience by giving either an oral or a poster presentation.In relation to both training and mentoring, ECCR has a strong connection to the Innovative Training Network MINDSHIFT and organized a session where early-stage researchers included in this program presented and discussed their data.Overall, the 26th meeting was a great success, all enjoyed the meeting, and look forward to meeting next year in the 27th meeting in October 2024.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".