Human papilloma virus and atherosclerotic cardiovascular disease
Bibliographic record
Abstract
Human Papilloma virus (HPV) is a non-enveloped DNA virus that infects cervical epithelial cells and is a known cause of cervical cancer in women. Less known are the findings of recent epidemiological studies that associate HPV with a higher risk of atherosclerotic cardiovascular morbidity and mortality. There are at least two possible ways in which HPV infection can contribute to this process and its complications. First, HPV could directly invade atherosclerotic plaques, thereby causing plaque progression and/or instability. Although the prevailing opinion is that HPV is an infection limited to epithelial cells, some authors have reported the detection of HPV DNA and protein in atheromatous coronary arteries as well as in endothelial cells, smooth muscle cells, plasma cells and foamy macrophages located in these plaques. The transport mechanism to infect distant sites is still being elucidated but a possibility is that extra-cellular vesicles, which contain HPV DNA released from infected cells, transport the viral elements in blood to other sites. Second, HPV infection could trigger a systemic inflammatory response (including inflammasome activation) that accentuates atherosclerosis and promotes plaque instability.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".