Evaluation of the proper level of specific absorption rate of human blood for 532 nm laser in blood low-level laser therapy
Bibliographic record
Abstract
Abstract Low-level laser has been used for a variety of clinical applications as a practical non-medicinal treatment, due to its ability to modulate blood rheology and improve biostimulation. This article research aim was to evaluate the proper level of specific absorption rate (SAR) of human blood during low-level laser treatment. Measurements were conducted on human blood in vitro , at different laser powers (wavelength 532 nm at powers of 50, 60, 70 and 80 mW) and exposure duration. Dielectric parameters were observed as a function of frequency from 40 Hz–30 MHz by utilizing an Agilent 4294A impedance analyzer at average room temperature of 25 °C. The SAR increased steadily with increasing frequency until it attained saturation peak, and thereafter exhibited a decrease trend. The SAR values range from 0.173–1.417 W kg −1 for blood irradiated using laser power of 50 mW and range from 0.178–0.754 W kg −1 for 60 mW. These values of SAR within 5–10 min of radiation present better stimulation results. Using laser powers of 70 and 80 mW for irradiations, the SAR values within the range from 0.003–0.791 W kg −1 and 0.130–0.491 W kg −1 , respectively, were computed. The SAR values here portend high risk associated to blood than its stimulation mechanism because the blood already attained a plateau and became saturated. This causes imbalance within the blood molecules resulting in a decrease in SAR as the frequency increases. This is due to a phase lag that develops between the electric field and induced dipole alignment creating a significant drop in the SAR of blood. The rate of inhibition increases rather than stimulation since the thermal radiation becomes exceedingly high resulting in crenation and hemolyzation of the blood. Therefore, we recommend using a laser at an output of power 50 mW for 5–10 min to reach the maximum capacity of SAR for more absorption and optimal stimulation.
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".