Devils Advocate: Why I do not believe any of you!
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- Опубліковано 12 тра 2024
- Mr. James Carroll, founder and CEO of THOR Photomedicine and a Fellow of the Royal Society of Medicine presented at the MGH Brain PBM Clinic Rounds (05.03.24) on the urgent need to report uniform parameters in tPBM research in order to advance the field further.
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What an amazing presentation! i have had exactly the same gripes with the studies i've read, and have seen the same issues with under performing devices, most numbers are bogus! Very well presented, accurate and professional, Thank you Mr Carroll!
One more confounding element to studies with very low light levels -- the spectra of ambient room light and exposure to natural sunlight, essentially as noise (really "DC offset") added to the low power levels used in those studies.
As a retired biophysics PhD I am appalled at the state of PBM research. Do journals, and speaker showed several highly respected ones in his list, no longer have quality peer review processes? I expect devices for sale on Amazon to sometimes be shoddy, but had hoped the science was better. Does no one do an action spectrum? Shouldn't an intensity VS action curve be done every time ? If one got a device with say 850 light, what is the range of wavelengths actually being delivered? If cytochrome oxidase is involved, how can light in the 1000nm range be active?
Salute for your input. Triple state technologies
You would not trust the spectrum provided by the manufacturers data sheet?
for sure this is an impeccable channel, I have never watched a video that was not wonderful. So thank you and I wish you blessed.
Because of the unknown (at present) mechanism involved in systemic (remote) effects (increased blood flow, free mitochondria in the blood as carriers, stem cells, etc.), it would still be useful to have the response surface shape for remote effects. More funding is needed for important work like this!
If there are truly multiple parallel effects involved (ATP, NO, ROS's, cellular hormesis, bloodflow, stem cells, mitochondria carrying effects systemically, and so on), then over the space of parameter variation, there is likely varying levels of optimal vs. sub-optimal (vs negative) responses from each of the physiological system components that may be responding in parallel. This may be one reason why it's not so simple to pin down an optimal setting of parameters. (I'm now contradicting an earlier post here, ha, about how simple the response surface may be). This reminds me of the early days in speech recognition (70's & 80's), where any number of completely different types of algorithms could achieve roughly the same level of performance -- each algorithm having particular strengths and weaknesses, in light of an extremely difficult problem. PBM could very well be in the same phase of development of the science and engineering at this point in time.
During my mispent youth, I did spend way too much time involved in curve fitting and interpolation. So far it seems we really don't have a sufficient number of datapoints in any study I've seen, in order to truly characterize the shape of this curve -- even for just one cell type, or application. It shouldn't be that hard to do this, in vitro, for an important set of cell types. Once a higher resolution curve is obtained (for a given target organ cell type), it's relatively easy (given that this curve is probably fairly smooth, with a single peak), to iteratively figure out where the peak response would be by "sampling" this curve in a given application, in order to home in on the peak in the power vs. time surface. I should have mentioned this is obviously a 3D plot, with a response surface over the two dimensions of power / cm^2 and time of application.
With respect to devices which are clusters of LED's, as the ensemble of LED's will have variation over emitted power, wavelength, and beam properties, (over time, as the LED's pn junctions rise in temperature over time, and the typical plastic lenses cannot also be identical), I would also propose a measure of overall variation in power output, and possibly wavelength within a defined ROI representing the primary portion of the area of the device's output, at the target distance. This would combine the effect of the overlapping beam pattern of the cluster of LED's, with the individual variation of each LED in terms of these parameters. If you look at datasheets for LED's from reputable semiconductor companies, it's common to see parameter variation spec'd in the neighborhood of +/- 5% to +/- 10%, depending on the parameter, and also the "bin" that the individual LED falls into (they can be sorted based on testing by the manufacturer). So a relatively simple spec of peak-to-peak (or better yet, rms, or mad) variation over the defined ROI at the target tissue distance, for both power and wavelength, would give a pretty good picture of how uniform the photon flux from the device was. With diffusion within tissues, this may turn out to be academic, except for applications like wound healing, which may be much more sensitive to incident power levels on delicate cells during the healing process, for example. One other thing specs like this would do would be to indicate the quality of the device, in terms of the uniformity of the parameters over the set of LED's used in each device. This would help both scientists and end users assess the quality of devices relative to the set of devices under consideration.
Has anybody looked at what happen to cellular membrane potentials while being irradiating?
There was some work from Prof Pancho Benzanilla University of Chicago and Prof Paul Stoddart from Swinburn University of technology with PBM, patch clamp and Neurons in vitro.
After being so verbose in my last comment, I would like to ask: How likely is some of the effects of PBM due to the activation of either local stem cells or stems cells in the blood being activated?
Bottom line is pbm is helpful regardless of all the scientific numbers and that's what matters 😊