Electro-magnetic radiation of terahertz range, NO molecular specter frequencies, and coagulation hemostasis in patients with various angina forms
Bibliographic record
Abstract
Aim. To study hypocoagulation effectiveness and mechanisms of electro-magnetic radiation, terahertz range, NO molecular specter frequencies (EMR THF-NO), in patients with various angina forms. Material and methods. The authors examined 80 patients with unstable angina, Class IIA and IIB (E. Braunwald classification), or effort angina, Functional Class II-IV (Canadian Cardiovascular Society). Twenty patients received standard medication therapy plus EMR THF-NO. Noteworthy, EMR THF-NO effects in unstable angina (UA) were studied in the absence of heparin therapy. The effects on main hemostatic parameters were studied: activated partial thromboplastin time (APTT), activated recalcification time (ART), prothrombin time, euglobulin fibrinolysis, fibrinogen (F) levels, antithrombin-III (At-III) activity, complex parameter of protein C system disturbances, Va factor resistance to activated C-protein. Results. EMR THF-NO demonstrated hypocoagulation effect in patients with stable angina (SA) and UA. In SA, hypocoagulation mechanism is explained by procoagulation potential reduction, by affecting the first (APTT and ART increase) and the third (F level decrease) coagulation phases. In US, it’s explained by increase in anticoagulant potential, due to At-III and modulation of initially disturbed fibrinolysis. Conclusion. EMR THF-NO should be included into complex therapy of angina patients, for greater hypocoagulation effect. EMR THF-NO could be used as an alternative method in patients with hypercoagulation and contraindications to special pharmaceutical hypocoagulation, or intolerance to these medications.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".