Cancer therapy-related cardiac dysfunction: is endothelial dysfunction at the heart of the matter?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Significant improvements in cancer survival have brought to light unintended long-term adverse cardiovascular effects associated with cancer treatment. Although capable of manifesting a broad range of cardiovascular complications, cancer therapy-related cardiac dysfunction (CTRCD) remains particularly common among the mainstay anthracycline-based and human epidermal growth factor receptor-targeted therapies. Unfortunately, the early asymptomatic stages of CTRCD are difficult to detect by cardiac imaging alone, and the initiating mechanisms remain incompletely understood. More recently, circulating inflammatory markers, cardiac biomarkers, microRNAs, and extracellular vesicles (EVs) have been considered as early markers of cardiovascular injury. Concomitantly, the role of the endothelium in regulating cardiac function in the context of CTRCD is starting to be understood. In this review, we highlight the impact of breast cancer therapies on the cardiovascular system with a focus on the endothelium, and examine the status of circulating biomarkers, including inflammatory markers, cardiac biomarkers, microRNAs, and endothelial cell-derived EVs. Investigation of these emerging biomarkers may uncover mechanisms of injury, detect early stages of cardiovascular damage, and elucidate novel therapeutic approaches.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it