February 2016 at a Glance. Focus Issue on Cardiac Regeneration, Medical Treatment and Cardiac Devices
Bibliographic record
Abstract
Five articles deal with cardiac regeneration. An overview presents the Committee for Advanced Therapies of the European Medicines Agency viewpoint on cell-based therapies for cardiac repair.1 Different therapies and endpoints to be used in experimental models and for patients with acute myocardial infarction and heart failure (HF) are thoroughly discussed.1 A second review discusses an alternative approach, compared with the traditional ones, based on cell delivery, in situ reprogramming of endogenous cardiac fibroblasts into functional cardiomyocytes.2 This has been achieved in experimental models using critical transcription factors, microRNA mimics, and small molecules able to cause fibroblast reprogramming to cells with cardiomyocyte-like morphology, gene expression, and spontaneous contraction. These new cells are able to improve cardiac function in post-infarction models. The results and future perspectives are nicely reviewed in this issue of the journal.2 Finally, the design of a randomized controlled trial of cardiopoietic regenerative therapy in patients with HF (CHART-1) is presented.3 Patients are randomized to a sham procedure or the injection of cardiopoietic stem cells. These cells are obtained through the expansion and conditioning of non-regenerative patient-derived stem cells towards the cardiac lineage using a cardiogenic conditioning medium administered through a new retention-enhanced intramyocardial injection catheter.4 The primary efficacy endpoint is a hierarchical composite one including mortality, worsening HF, quality of life, 6 minute walk test and left ventricular volumes and function at 9 months.3 With regard to medical treatment, an analysis from the Efficacy of Vasopressin Antagonism in Heart Failure Outcome Study With Tolvaptan trial (EVEREST) shows an attenuation of the osmolality changes induce by tolvaptan administration with their disappearance at week 56, consistently with its lack of effects on outcomes. The Authors hypothesize that counter-regulatory up-regulation of vasopressin may have attenuated tolvaptan-induced osmolality changes as well as its effects on symptoms and diuretic needs.5 A meta-analysis of 11 randomized controlled trials of implantable telemonitoring devices in patients with HF shows a 44% reduction in the total number of visits and planned visits with a slight increase in unplanned visits and no difference in hospitalization and mortality rates. Costs of treatment were reduced because of the reduction in planned visits.6 New studies continue to add data to the large database regarding predictive factors of the response to cardiac resynchronization therapy.7, 8 In this issue of the journal, Stolfo et al. show that an early improvement in right ventricular dysfunction, in those patients in whom it is impaired at baseline, can be a further independent predictor of a favorable outcome after cardiac resynchronization therapy in HF patients.9 Enjoy this issue more focused on translational medicine and devices.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.345 | 0.256 |
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".