Magnetic Field Configurations Corresponding to Electric Field Patterns That Evoke Long-Term Potentiation Shift Power Spectra of Light Emissions from Microtubules from Non-Neural Cells
Bibliographic record
Abstract
Photon counts were measured every 15 ms for 75 s from microtubule-enriched preparations (and nuclei) from mouse melanoma cells during baseline and after 2 min exposures to 1 μT magnetic fields. The magnetic fields were generated from a circular array of solenoids and presented with accelerating or decelerating rotation velocities. The range of photon radiant flux density was in the order of 10-12 W·m-2. Microtubules preparations that had been exposed for only 2 min to a magnetic field configuration corresponding to the electric field pattern that induced long-term potentiation in neural tissue when applied as electric current displayed peaks of spectral power densities within 7 - 8 Hz, 9.5 Hz, 14 - 15 Hz, and 22 Hz bands. The major peak (9.4 Hz) bandwidth was approximately 0.1 Hz. While microtubule preparations exposed for 2 min to a 7 Hz sine-wave or in the absence of a field emitted an overall similar level of spectral power density, the peaks in power density were not present. Treatment with the LTP patterned fields, compared to the baseline or sine-wave fields primarily altered the frequency band in which the amplitude of the photon field was expressed. These results suggest that the photon emissions from microtubule preparations have the capacity to respond to specifically-patterned or geometric shapes of magnetic fields by altering spectral configurations rather than the absolute numbers of photons.
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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".