The effects of electromagnetic fields on B16‐BL6 cells are dependent on their spatial and temporal character
Bibliographic record
Abstract
Exposure to low intensity, low frequency electromagnetic fields (EMF) has effects on several biological systems. Spatiotemporal characteristics of these EMFs are critical. The effect of several complex EMF patterns on the proliferation of B16-BL6 mouse melanoma cells was tested. Exposure to one of these patterns, the Thomas-EMF, inhibited cell proliferation and promoted calcium uptake. The Thomas-EMF is coded from a digital-to-analog file comprised of 849 points, which provides power to solenoids and can be set to alter timing, intensity, and duration of variable EMF. Setting the point duration to 3 ms generated a time-varying EMF pattern which began at 25 Hz and slowed to 6 Hz over a 2.5 s repeat. Exposing B16-BL6 cells to Thomas-EMF set to 3 ms for 1 h/day inhibited cell proliferation by 40% after 5 days, while setting the point duration to 1, 2, 4, or 5 ms had no effect on cell proliferation. Similarly, exposing cells to Thomas-EMF set to 3 ms promoted a three-fold increase in calcium uptake after 1 h, while the other timings had no effect. Exposure to Thomas-EMF for as short as 15 min/day slowed cell proliferation, but exposure for 1 h/day was optimal. This corresponded to the effect on calcium uptake where uptake was detected after 15 min exposure and was maximal by 1 h of treatment. Studies show that the specific spatiotemporal character of EMF is critical in mediating their biological activities. Bioelectromagnetics. 38:165-174, 2017. © 2016 Wiley Periodicals, Inc.
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 | 0.000 |
| 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".