Red and near-infrared light treatment can change the intensity of biophoton emissions in cell culture

Red and near-infrared light treatment can change the intensity of biophoton emissions in cell culture | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Red and near-infrared light treatment can change the intensity of biophoton emissions in cell culture Jaimie Hoh Kam, Romain Clément, Tigrane Cantat-Moltrecht, Malvina Billères, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6809450/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract We explored the patterns of biophoton - ultra-weak light made by cells - emissions in Neuro-2a cells and astrocytes in culture. Biophotons were detected using a photomultiplier as a single photon counter. We measured intensity of emissions when healthy (and at rest), stressed with toxins (sodium troclosene or rotenone) and/or treated with red and near infrared light (R-NIr). We measured ATP (adenosine triphosphate) and ROS (reactive oxygen species) levels also. Our results showed that emissions from Neuro-2a cells and astrocytes were similar when both healthy and stressed. Both cell types emitted biophotons at low intensities when healthy (~ 12photons/sec), but this changed markedly under stress. The extent of change was however, dependant on the stressor involved; sodium troclosene increased emissions, while rotenone had a far more limited impact. Finally, we showed that R-NIr did not influence emissions when heathy, but did so when stressed, particularly with sodium troclosene. These emission patterns under different conditions did not relate uniformly to the changes in ATP and ROS levels. In summary, we found that biophoton emissions did not readily define cell type, but could - under some circumstances - be reflective of cell health. Further, that R-NIr could influence these emissions, particularly under stress. Biological sciences/Biological techniques Biological sciences/Cell biology Biological sciences/Neuroscience astrocytes Neuro-2a photomultipliers photobiomodulation ultra-weak photon emission Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 INTRODUCTION The idea that living cells can generate light and use it to communicate with each other has been discussed for over a century. With the development of better technology over the years, this endogenous light has been shown to be very weak, being in the range of 2-200 photons/sec/cm 2 . It is not detectable with the naked eye, but only with ultra-sensitive low-light detection systems. For this reason, it has been referred to as ultra-weak photon emissions; in more recent times, the term "biophotons" has been used [1–11]. The two main cell organelles considered to be involved in the biophoton functional system are mitochondria and microtubules. Mitochondria, that produce the vital adenosine triphosphate (ATP) energy for cell function, as well as maintaining normal levels of reactive oxygen species (ROS), are thought to be the main generators of biophotons. Microtubules are suspected to work a little further downstream, being involved in the capture and transmission of biophotons along the cell processes [ 4 , 5 , 10 , 12 , 13 ]. Many authors have argued that biophoton emissions are not merely a by-product, a collateral, of mitochondrial activity, but rather, that they subserve a distinct biological function [1–11]. First, of all the metabolic mitochondrial reactions, the ones involving ROS appear to be the main source of biophotons. Under normal physiological conditions, ROS have important roles in maintaining a delicate balance of cell homeostasis, while under pathological conditions, ROS levels can be elevated and become toxic, leading to much cell dysfunction and death. Because the process of ROS generation is so precise, it has been suggested that the biophoton emissions serve as key indicators of oxidative metabolism. Second, biophoton emissions include a broad range of wavelengths, from ultraviolet (λ=~200nm) to infrared (λ=~950nm) and their intensity can vary considerably. Both these latter features can change dramatically with different states of cell activity and/or health. Third, biophoton emissions, for each emitted wavelength, are considered to be coherent and highly-structured, a feature that is viewed as a cooperation of many parts subserving a specific function. Fourth, the mitochondria have receptors that absorb light across a range of wavelengths (see above), including flavinic and pyridinic rings, lipids, aromatic amino acids, cytochrome c oxidase and interfacial water. These receptors are present even among cells located very deep in the body, in regions where no external light can reach. Indeed, when external light, in the form of red and near infrared light (R-NIr) - known also as photobiomodulation - has been applied to cells located deep in the body, there has been a distinct functional response from cells, changing their functional activity and improving their cell survival rate when suffering stress. Hence, it is likely that these receptors are there for a purpose, that is, to use light to influence various cellular mechanisms. Indeed, it has been suggested that a main mechanism of action of R-NIr is that it taps into the biophoton system and uses it to facilitate changes in cell function and survival [ 6 , 10 ]. Taken all together, these factors indicate that there is a distinct biological significance for the biophotons [1–11]. As to what precisely this distinct biological function associated with biophotons is, it remains far from clear. Several have been proposed however, including; (1) that biophotons are used for cell communication, that one cell may inform other cells of their state of health or activity [1–11], and; (2) that biophotons play a part in cell repair and regeneration, that a stressed cell may release biophotons to repair itself and/or be repaired by biophotons from nearby healthy cells [ 6 , 7 , 10 ]. Most previous studies examining patterns of biophoton emissions have focussed on various types of plant cells [1,2,14,15] and bacteria [ 16 , 17 ], together with cancer cells [ 8 , 18 – 22 ]. There have also been some studies that have considered biophoton activity in neural cells, both peripheral [14,23] and central [14,24–31], but most of these have either been in brain slices or on whole preparations, none from cell lines in culture. The major aims of this study were three-fold. First, to determine whether different types of neural cells - neurones and astrocytes - displayed a signature biophoton intensity emission pattern. Second, if the intensity of biophoton emissions could be reflective of the state of neural cell health. Third, to explore whether external application of R-NIr influenced the intensity of biophoton emissions from these cells. For each of these three issues, we examined the intensity of emissions of cells when healthy (and at rest) and when stressed with toxins. In addition, we measured the ATP and ROS levels (measures of mitochondrial health) under various conditions and related these levels to any changes in biophoton emissions. Our results will hopefully provide insights into whether biophoton emissions can be a key indicator of cell type and health, together with the mechanism of action behind R-NIr treatment. RESULTS In the section that follows, we will consider if biophoton emissions: (1) defined neural cell type (2) reflected state of cell health (3) were influenced by external R-NIr treatment and (4) mirrored changes in ATP and ROS levels. (1) Biophoton emissions and neural cell type Our first aim was to determine whether the patterns of biophoton emission intensities defined neural cell type - Neuro-2a cells and astrocytes - at both rest and when stressed. Figure 1 shows graphs of the number of biophotons detected from healthy cells (at rest, baseline) (Fig. 1 A) and when stressed with either sodium troclosene (Fig. 1 C) or rotenone (Fig. 1 E), relative to the medium only. Individual traces of activity for both cell types are shown also, at either rest (Fig. 1 B), sodium troclosene-treated (Fig. 1 D) or rotenone-treated (Fig. 1 F). When comparing the detected emissions from Neuro-2a cells and astrocytes, no major differences were evident, either at rest (p = 0.18) or after being stressed with sodium troclosene (p = 0.06) or with rotenone (p = 0.15). In fact, they were largely indistinguishable. This feature is particularly clear from the traces of each cell type under the different conditions (Fig. 1 B,D,F); traces from both cells overlapped considerably. In essence, there appeared to be no signature pattern of biophoton emission that defined either cell type. (2) Biophoton emissions and state of cell health We then explored whether biophoton emissions reflected the state of health of neural cells. For this, we again examined the patterns of biophoton emissions in healthy cells (at rest) and from stressed cells after application of sodium troclosene and rotenone (Fig. 2 ). In healthy Neuro-2a cells and astrocytes, biophoton emission recordings were very low, averaging 11.7 counts/sec, with a range of 6–17 counts/sec for Neuro-2a cells and 12.4 counts/sec, with a range of 6–18 counts/sec for astrocytes. These values, although being very low, were higher than those relative to the medium only (p < 0.0001; Fig. 2 A,B); they formed our baseline recordings. After application of sodium troclosene, biophoton emissions increased considerably, relative to healthy cells (p < 0.0001), in Neuro-2a cells (Fig. 2 A) and astrocytes (Fig. 2 B). After application of rotenone, a very different pattern of biophoton emissions was evident. For Neuro-2a cells, rotenone induced a slight reduction in biophoton emissions relative to healthy cells (p < 0.05; Fig. 2 A), while for astrocytes, there was no major change in biophoton emissions compared to healthy cells (p = 0.56; Fig. 2 B). Hence, the detected biophoton emissions from both Neuro-2a cells and astrocytes could define - to some extent - their state of health; when healthy, their detected emissions were similar, both being very low, but when stressed, their responses differed somewhat, either increasing, decreasing or staying the same, dependent on the stressor involved. (3) The impact of R-NIr treatment on biophoton emissions Next, we examined the impact of R-NIr (λ = 660 nm and 850 nm) on the intensity of biophoton emissions of healthy and stressed Neuro-2a cells and astrocytes. We examined the effect of two doses of R-NIr, a lower (R-NIr; 78.5 mW/cm² and a total fluence of 9.4 J/cm²) and higher (R-NIr + ; 137.4 mW/cm² and a total fluence of 16.5 J/cm²) one. In healthy cells, there was no major change in the patterns of biophoton emissions detected for both Neuro-2a cells (Fig. 3 A; p = 0.42 for R-NIr and p = 0.90 for R-NIr+) or astrocytes (Fig. 4 B; p = 0.91 for R-NIr and p = 0.30 for R-NIr + ) compared to baseline after application of either a lower or higher dose of R-NIr. It should be noted that this result indicated that R-NIr did not generate any delayed illuminance, at least for the 5 minutes after the exposure and during the recording of biophoton activity [ 8 ]. We then undertook a separate series of experiments where we measured the intensity of biophoton emissions when R-NIr was applied after either of the two stressors (Fig. 4 ). For the sodium troclosene, post-application of either dose of R-NIr increased the detected biophoton emissions in Neuro-2a cells, particularly after R-NIr + (Fig. 4 A; p = 0.15 (R-NIr), p < 0.005 (R-NIr + )). By contrast, astrocytes showed a decreased biophoton activity after post-application of either dose of R-NIr, again particularly after R-NIr + (Fig. 4 B; p = 0.13 (R-NIr), p < 0.05 (R-NIr + )). For rotenone, the changes in patterns of detected biophoton emissions post-application of both R-NIr doses were far less dramatic - in Neuro-2a cells (Fig. 4 C) and astrocytes (Fig. 5 D) - compared to that seen with sodium troclosene. R-NIr after rotenone treatment induced only very small increases in the Neuro-2a cells with both doses (Fig. 4 C; p < 0.05), and no changes in the astrocytes (Fig. 4 D; p = 0.78 (R-NIr), p = 0.99 (R-NIr + )). Following on from that series of experiments, we explored the patterns of biophoton emissions when R-NIr was applied before either of the stressors (Fig. 5 ). For the sodium troclosene, pre-application of either dose of R-NIr increased the detected biophoton emissions considerably in Neuro-2a cells (Fig. 5 A; p < 0.001 (R-NIr), p < 0.05 (R-NIr + )), well over and above the activity evident with sodium troclosene stress alone (Fig. 5 A). By contrast, astrocytes showed only minimal changes in detected biophoton activity after pre-application of either dose of R-NIr compared to sodium troclosene alone (Fig. 6 B; p = 0.13 (R-NIr), p = 0.02 (R-NIr + )). For rotenone, the patterns of biophoton emissions after pre-application of both R-NIr doses were very different - in the Neuro-2a cells (Fig. 5 C) and astrocytes (Fig. 5 D) - to that evident with sodium troclosene. Here, with rotenone, there was minimal change in activity before R-NIr treatment (Neuro-2a: p = 0.71 (R-NIr); astrocytes: p = 0.87 (R-NIr), p = 0.99 (R-NIr + )), although a small increase was seen for the R-NIr + in the Neuro-2a cells (Fig. 5 C; p < 0.05). Thus, externally applied R-NIr appeared to have little effect on the intensity of detected biophoton emissions from both Neuro-2a cells and astrocytes when healthy. By contrast, R-NIr did have an impact on the detected emissions from Neuro-2a cells, and to a lesser extent, from astrocytes, when stressed from at least one of the two stressors. (4) Changes in ATP and ROS levels (4) Changes in ATP and ROS levels Finally, in order to relate our findings on biophotons emissions in healthy Neuro-2a cells and astrocytes at rest and after treatment - stress and/or R-NIr - to the overall state of mitochondrial health, we measured ATP and ROS levels in both cell types under the same conditions (Fig. 6 , 7 ). We chose to focus on one dose of R-NIr (R-NIr + , because there was no major difference between the two doses and this dose generally produced a greater response) and the changes when R-NIr was applied after the stress (again, there were limited differences between the before and after application, Fig. 4 , 5 ) For ATP levels, there was little change in Neuro-2a cells (p = 0.9; Fig. 6 A) and a slight increase in astrocytes (p < 0.05; Fig. 6 B) after R-NIr treatment when the cells were healthy. When Neuro-2a cells were stressed, with either sodium troclosene (Fig. 6 C) or rotenone (Fig. 6 E), there were clear increases in ATP (p < 0.0001); these levels were reduced dramatically after R-NIr treatment in rotenone (p < 0.0001), and to a much lesser extent, in sodium troclosene (p = 0.5) stressed cells. When astrocytes were stressed, there was little change in ATP levels after application of sodium troclosene (p = 0.44; Fig. 6 D) or rotenone (p 0.4; Fig. 6 F); with R-NIr treatment, there were minimal changes in ATP levels after sodium troclosene (p = 0.4) and a decrease after rotenone (p < 0.001). For ROS levels, there was little change in both Neuro-2a cells (p = 0.14; Fig. 7 A) and astrocytes (p = 0.68; Fig. 7 B) after R-NIr treatment when healthy. When Neuro-2a cells were stressed, with either sodium troclosene (p < 0.05; Fig. 7 C) or rotenone (p < 0.001; Fig. 7 E), there were clear increases in ROS levels, and these were reduced after R-NIr treatment in the sodium troclosene (p < 0.0001) and rotenone (p < 0.0001) affected cells. When astrocytes were stressed, there was a small decrease in ROS levels after application of sodium troclosene (p < 0.05; Fig. 7 D) but not with rotenone (p = 0.63; Fig. 7 F); with R-NIr treatment, there were minimal changes in ROS levels after either sodium troclosene (p = 0.98) or rotenone application (p = 0.96). DISCUSSION We had three major findings. First, that neural cells - Neuro-2a (neurone-like) and astrocytes - when either healthy or stressed, had no distinctive cell-specific pattern of biophoton emissions. Second, that the emissions from both cell types could define - to some extent - their state of health; when healthy, their intensity of emissions were similar, both being very low, but when stressed, their responses differed somewhat, either increasing, decreasing or staying the same, dependent on the stressor involved. Third, that while externally applied R-NIr had no influence on the intensity of biophoton emissions from both Neuro-2a cells and astrocytes when healthy, it could have an influence on emissions in Neuro-2a cells, and to a lesser extent, in astrocytes, when placed under stressful conditions. These major findings will be the focus of the Discussion below. First, some limitations of our study will be considered. Limitations Our study had two main limitations. First, we examined the impact of stress and R-NIr on biophoton emissions of cells in culture. Ideally, one would have used an in vivo set-up to examine these cellular issues but, unfortunately, such technology is not available currently. There are methods to examine endogenous light output in the whole organism in vivo, but these would not reveal the level of detail that we have documented here; further, most of the output from the current in vivo methods is from the skin and not the brain, our area of interest [32-34]. Nevertheless, cell culture experiments are often a first step in testing new ideas and paradigms and set the template for further study in vivo. Second, we used Neuro-2a cells that, strictly speaking, are not neurones. They are fast-growing and robust neuroblastoma cells. However, many previous studies have used such cells as a window into neuronal function, in both health and disease [ 35 ]. For our purposes here, these "neurone-like" cells - with their fast-growing and robust nature - formed an ideal cell line to measure the intensity of biophoton emissions. The intensity of biophoton emissions did not define neural cell type One of the key issues associated with research into the biophoton phenomenon is whether the emissions can define cell type. This may be a way, for instance, by which cells communicate their particular lineage. Further, in terms of development of a therapeutic device, a signature biophoton emission could make different cell types readily identifiable. Previous studies on this specific issue have been rather limited, however. Perhaps the best known examples come from studies examining differences between cancer and normal cells [ 8 , 18 – 22 ]. For example, cancer cells have been reported to have higher emissions over the lower wavelengths (eg ultraviolet) compared to normal cells [21,22]. In this study, we explored whether the intensity of biophoton emissions could define neural cell type, namely Neuro-2a cells and astrocytes. We found that their intensity of emissions was very similar, with neither showing any distinctive, cell-specific pattern. Thus, this measure may not necessarily be a good indicator of neural cell type. But, there may be other ways. For instance, as with cancer cells, there may be different patterns of intensities across the range of wavelengths, from ultraviolet to R-NIr, and these may change with time [18,18,21]. Taken together, although neurones and astrocytes may have the same detected intensity of biophoton emissions, there may be different combinations of wavelengths involved and these may help better define their different identity. Future studies could explore this issue further. Does the intensity of biophoton emissions reflect cell health? Previous studies have shown that the intensity of biophoton emissions can provide some indication as to the state of cell health. There have been reports of clear changes in the intensity of biophoton emissions after application of a variety of different types of stimulants and/or conditions. For example, an increase in emissions is induced after application of glutamate to mouse brain slices [29,30], toxins such as silver nanoparticles to adult mouse stem cells [ 36 ], electrical stimulation of the rat sciatic nerve [ 23 ] and temperature change (ie heat) to azuki beans [25], while a decrease in emissions becomes evident after application of anaesthetic (procaine) to spinal cord nerve roots [14]. There have been no previous studies exploring the patterns of biophoton emissions in neural cell lines, Neuro-2a cells and astrocytes, under healthy and/or stressed conditions, however. Our results showed that the intensity of biophoton emissions - to some extent - could be reflective of cell health. We found that healthy Neuro-2a cells and astrocytes had very low levels of detected biophoton emissions at rest (~ 12photons/sec), probably indicative of their low level of activity in this state and/or of their overall homeostasis. And this generally changed under stress. The extent of the change was however, dependant on the stressor involved; sodium troclosene increased emissions in both cell types, while rotenone had a much more limited impact, with a very small decrease in Neuro-2a cells and no change in astrocytes. This difference between the two stressors cannot be explained readily by the patterns of ATP and ROS produced by the cells; both stressors increased ROS and, rather surprisingly, ATP levels as well. The latter may be reflective of an immediate response reaction to the toxicity induced by the stressor; with a greater time-period, one would assume that these high ATP levels would drop off considerably with increasingly more mitochondrial and cell damage. The stressor-induced changes in ROS levels are of particular interest here, because these levels have been linked closely to the biophoton emissions (see Introduction). While there was a clear relationship between the increase in ROS levels and biophoton emissions after sodium troclosene, there was no such relationship after rotenone treatment, with the biophoton emissions not matching the increase in ROS levels (see Fig. 1 , 4 ). Hence, there may be other factors generating these differences in biophoton emission responses - other than changes in ROS levels - from, at the very least, one of the stressors. Of course the pattern may change over time, but in these initial stages of the stress, the changes in biophoton intensity emissions do not appear to match uniformly - across different stressors - the changes in ROS levels. In summary, our findings indicated that the intensity of biophoton emissions from Neuro-2a cells and astrocytes could be reflective of cell health when healthy, but not necessarily when stressed, with the intensity being dependant on the type of stressor involved. Further, that such changes, in both cell types, did not relate readily to changes in ROS levels in the cells, suggesting that there may well be other factors to consider in the generation of biophoton emissions. Red and near infrared light treatment influences the intensity of biophoton emissions Perhaps our most novel and striking set of findings related to the effect of R-NIr on biophoton emissions from both cell types. There has been one previous study examining the impact of white light, spanning a range of wavelengths (λ = 410-1200nm), showing an increase in the emissions in germinating green bean seeds [14], but no study has examined specifically the effect of R-NIr on emissions from any type of cell (λ = 660nm and 850nm). A major reason why we focused on R-NIr was to explore whether it can influence the emission intensity; if so, it would support the idea that R-NIr can facilitate many of its beneficial cellular effects by using the biophoton network system [6,7,10,37]. For example, if a cell is damaged then it, or nearby cells, may release R-NIr in an effort to help repair the damage and improve its survival. Externally-applied R-NIr may tap into this system - albeit at higher doses - and help the repair process even more; it could potentially form a key mechanism of action behind many of the benefits of R-NIr treatment [ 6 , 7 , 10 ]. Taking all our results on R-NIr and biophoton emission intensity together, some general comments can be made (see Fig. 8 ): (1) that R-NIr had a greater impact on emissions in stressed cells than those that are healthy and at rest. This is, on the whole, consistent with many previous reports indicating that R-NIr is more effective on cells suffering pathology than those that are healthy and functioning normally [ 38 , 39 ]. The R-NIr-induced patterns of biophoton emissions we report here reflect this trend. (2) there were clear differences in the emission responses with R-NIr from Neuro-2a cells and astrocytes, with the latter being far less dramatic. For Neuro-2a cells, rather than decrease the intensity of emissions in stress, R-NIr increased the intensity. If one assumes that intensity of emissions is related to level of stress suffered by a cell, and that R-NIr should decrease this stress, then this finding is counter-intuitive. We suggest however, that this intensity increase includes a range of different wavelengths, all functioning in different ways. For example, under stress, the cells could release biophotons in the UV range, as a signal of distress, as well as some biophotons in the R-NIr range, as to help the repair process; the external application of R-NIr could evoke a further wave R-NIr release and aid the repair [6,7,10,18,19,21]. Determining the spectral distribution of biophoton emission was beyond the scope of the present study, but we are in the planning stage of examining this issue in the future. For the astrocytes, the minimal changes in emissions after R-NIr treatment with stress suggests that these cells are less responsive to the external light and may not need an extra dose to help any repair process, either for themselves or nearby neurones. Astrocytes have been shown to be directly responsive to R-NIr in cell culture [40], but this response - judging by their biophoton emissions - may not be as intense as it is for neurones or neurone-like cells (ie Neuro-2a cells). (3) the higher and lower R-NIr doses we used generally produced the same biophoton emission response, whether it was an increase, decrease or no change. There was a tendency however, for the higher dose to generate a slightly greater change in intensity than the lower one. For our study here, we aimed only to determine some preliminary insights into dosage and hence used only two doses. A more comprehensive analysis of dose awaits, to determine the precise parameters of the biphasic response of R-NIr treatment, where the so-called "sweet-spot" dose lies and where the null-effect dose ranges are found [ 38 ]. (4) globally, there were very similar patterns of emissions evident from both cell types whether the R-NIr was applied after or before the stressor. This would indicate - assuming a beneficial role for R-NIr application and the biophoton system - that a pre-treatment of R-NIr could be just as effective as a post-treatment; indeed, this has been reported for this method in various animal models of Parkinson's disease [ 41 , 42 ]. (5) the R-NIr-induced changes in emissions did not match closely the changes in ATP and ROS levels in both cell types. While R-NIr treatment either increased, decreased or had no impact on the intensity of biophoton emissions, depending on the stressor, it almost uniformly decreased the ATP and ROS levels under the corresponding conditions. It appeared that R-NIr worked to restore the balance after a massive and immediate increase in ATP and ROS levels following the toxic shock induced by the stressor; in most cases, particularly in Neuro-2a cells, R-NIr reduced levels to near baseline. Either way, the intensity of biophoton emissions after R-NIr treatment did not relate readily to changes in ATP, and perhaps more importantly, ROS levels, suggesting that others factors may be at play (see above). CONCLUSIONS We have shown that the intensity of biophoton emissions from Neuro-2a cells and astrocytes were similar when both healthy and stressed, with neither showing any distinctive, cell-specific pattern. Thus, this measure may not necessarily be a good indicator of neural cell type. We also found that the intensity of biophoton emissions - to some extent - could be reflective of cell health when healthy, but not necessarily when stressed, with the intensity being dependant on the type of stressor applied; sodium troclosene increased emissions, while rotenone had a more limited impact. Further, that such changes, in both cell types, did not relate to changes in ROS levels in the cells, suggesting that there may well be other factors involved in generating the emissions. Finally, we showed that R-NIr did not influence emissions when heathy, but did so when stressed, particularly in Neuro-2a cells and with at least one of the stressors used. The next step in the exploration would be to define the wavelengths associated with the biophotons from both healthy and stressed neural cells and whether R-NIr influences the pattern of these wavelengths. MATERIALS & METHODS Cells Mouse "neurone-like" (ie Neuro-2a CCL-131) cells and astrocytes (C8-D1A) were obtained from American Type Culture Collection (LGC Standards France). Neuro-2a cells are a fast-growing mouse neuroblastoma cell line that have been used to explore extensively aspects of neurone function and dysfunction (Tremblay et al 2010). They were cultured in Dulbecco’s Modified Eagle’s medium containing glutamine and 10% foetal bovine serum and kept at 37 o C, 5% CO 2 and 85% relative humidity. Cells were plated in 60mm petri dishes at a density of 1 million cells 24 hours prior to biophoton recording and cells were kept in complete darkness. In fact, we made absolutely sure that the cells were not exposed to any light for up to 24 hours before experimentation, limiting any so-called delayed luminescence [ 8 ]. Biophoton experimental set-up and detection system Biophotons emitted by the Neuro-2a cells and astrocytes in a culture dish were measured at room temperature using a photomultiplier tube H16722P-40 (Hamamatsu Photonics, Japan) in a purpose-built dark chamber (Fig. 9 ). The photomultiplier had a GaAsP photocathode with a spectral sensitivity in the 300nm-740nm range. The photomultiplier was cooled with an internal thermo-electric module, in order to reduce dark counts and improve its signal-to-noise ratio, and equipped with a heatsink and fan A7423 that effectively radiated the heat away. The photomultiplier was powered by a C8137-02 power supply unit (Hamamatsu Photonics, Japan) that also handled temperature regulation. The output of the PMT was connected to a C9744 photon counting unit (Hamamatsu Photonics, Japan), supplied with + 5V/-5V, that generated pulses from the current output of the photomultiplier. A C8855-01 counting unit counts these pulses and was connected to the recording computer. Measurements from healthy and stressed cells We made measurements from healthy (at rest) and stressed Neuro-2a cells and astrocytes in culture. For the measurements from healthy cells, biophoton emissions were recorded and the values compared relative to the medium only (containing no cells) for 3 minutes; these recordings from the cells formed our baseline readings. For the measurements from stressed cells, after recording baseline readings, we applied the stressors by pipetting them gently on the wall of the petri dish and into medium of the cells. We used two agents to stress the Neuro-2a cells and astrocytes, sodium troclosene and rotenone. We used these two because they have different mechanisms of action. Sodium troclosene (0.25mM) is a strong oxidising agent that slowly releases chlorine in low concentration into the medium at a relatively constant rate and hence changes the pH of the medium to acidic [ 43 ]. Rotenone (9nM) is an inhibitor of complex I in the mitochondrial electron transport chain and has been shown to increase the production of ROS, lower the production of ATP and decrease the mitochondrial membrane potential [44]. After application of stressor, we recorded emissions for the next 5 minutes and these readings were compared relative to the baseline. Measurements with external red and near infra red light (R-NIr) treatment For the effect of external light (R-NIr) treatment, intensity of biophoton emissions were recorded first from healthy cells at rest (baseline) and then again with cells exposed to R-NIr either after or before application of a stressor. We exposed the cell cultures to R-NIr continuously for 2 minutes. For this, the Neuro-2a cells and astrocytes were treated with light emitting diode (LED) light at 660nm and 850nm at either; (1) a lower intensity R-NIr exposure at an irradiance of 29.8mW/cm² at 660nm and 48.7mW/cm² at 850 nm, with the lamp placed 20cm above the petri dish, giving a total irradiance of 78.5mW/cm² and a total fluence of 9.4J/cm² or; (2) a higher intensity R-NIr exposure (RNIr + ) at an irradiance of 51.2mW/cm² at 660 nm and 86.2mW/cm² at 850 nm, with the lamp placed at 10cm above the petri dish, giving a total irradiance of 137.4 mW/cm² and a total fluence of 16.5J/cm². The biophoton activity was then recorded for 5 minutes thereafter. The readings of biophoton activity with R-NIr treatment were compared relative to the baseline. Biophoton emissions were also recorded using a sham treatment, that is, where the cells were placed under the R-NIr device (see below) but the device was not switched on. There was no difference in the number of photons emitted between the baseline and the sham-treated cells (data not shown). Other measures In order to make direct comparisons with any observed changes in biophoton emissions, we made some measures of ATP and ROS levels under the same experimental conditions as those were we measured biophoton activity, ie, at rest, under stress and after exposure to external R-NIr. In order to normalise our analysis of ATP and ROS, total protein content was measured. For this, measurement was performed using a commercially available kit, BCA Protein Assay by Thermo Scientific. Bovine serum albumin was used as a standard, and the amount of protein was measured following the manufacturer’s instructions. ATP Assay ATP production was quantified using the ATP Determination kit (Fisher Scientific). Cells were harvested and homogenised in 100µL of 6M guanidine-HCl in extraction buffer (100mM Tris and 4mM EDTA, pH 7.8) to inhibit ATPases, followed by freezing in dry ice. The homogenate was then heat- treated at 95 o C for 5 minutes and then centrifuged for 15 mins at maximum speed (13 500 RPM). The supernatant was collected and ATP was measured according to the manufacturer’s instructions. ROS Assay To assess oxidative stress, ROS levels were measured using dichloro-dihydrofluorescein diacetate. Cells were harvested and homogenised in 200µL of ice-cold 0.4M Tris-HCl buffer (pH 7.4) (Merck) followed by a 10 minutes centrifugation at 2000g at 4 o C. 50µl of each supernatant was added to a 96 microplate well containing 7.5µl of 5µM dichloro-dihydrofluorescein diacetate (Merck) and total volume was adjusted to 100µL with homogenising buffer. After 1 hour incubation at room temperature, the conversion of dichloro-dihydrofluorescein diacetate to dichloro-dihydrofluorescein was measured at 485nm excitation and 520nm emission. Statistics Data were analysed with GraphPad Prism v.10 (San Diego, USA) and statistical analyses were undertaken using a one-way ANOVA, using Tukey or Bonferroni’s multiple comparison test. Data presented are mean SEM. The significance was asserted as *p < 0.05, **p < 0.01, ***p < 0.001, **** p < 0.0001. Declarations Competing Interest : none Funding: Fonds Clinatec and Fondation COVEA France Author Contribution All authors contributed to the writing and analysis of the manuscript. JHK undertook all the experiments and biophoton measurements with the help of RC, while JHK, TCM and MB were involved in the setting-up of the detection system. Acknowledgement We thank Nils TANNEAU for his help with the biophoton system set up. 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Zapata, F., Pastor-Ruiz, V., Ortega-Ojeda, F., Montalvo, G. & García-Ruiz, C. Increment of spontaneous human biophoton emission caused by anger emotional states. Proof of concept. Microchemical Journal 169 , 106558 (2021). Casey, H., DiBerardino, I., Bonzanni, M., Rouleau, N. & Murugan, N. J. Exploring ultraweak photon emissions as optical markers of brain activity. iScience 28 , 112019 (2025). Tremblay, R. G. et al. Differentiation of mouse Neuro 2A cells into dopamine neurons. J Neurosci Methods 186 , 60–67 (2010). Salari, V., Valian, H., Bassereh, H., Bókkon, I. & Barkhordari, A. Ultraweak photon emission in the brain. J. Integr. Neurosci. 14 , 419–429 (2015). Liebert, A. D., Bicknell, B. T. & Adams, R. D. Protein conformational modulation by photons: A mechanism for laser treatment effects. Medical Hypotheses 82 , 275–281 (2014). Hamblin, M. R. Do Biophotons Play Any Role in Transcranial Photobiomodulation of the Brain? 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Swarnkar, S., Singh, S., Mathur, R., Patro, I. K. & Nath, C. A study to correlate rotenone induced biochemical changes and cerebral damage in brain areas with neuromuscular coordination in rats. Toxicology 272 , 17–22 (2010). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 14 Jul, 2025 Reviews received at journal 13 Jul, 2025 Reviews received at journal 09 Jul, 2025 Reviews received at journal 07 Jul, 2025 Reviewers agreed at journal 29 Jun, 2025 Reviewers agreed at journal 27 Jun, 2025 Reviewers agreed at journal 26 Jun, 2025 Reviewers invited by journal 26 Jun, 2025 Editor assigned by journal 26 Jun, 2025 Editor invited by journal 18 Jun, 2025 Submission checks completed at journal 17 Jun, 2025 First submitted to journal 17 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6809450","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":477909905,"identity":"e5a99d85-04d0-44a2-a840-c4a60400b8b3","order_by":0,"name":"Jaimie Hoh Kam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBACxgbGBoYEBiCSYD4A5EvIkKKFLQGkhYdo24BaeAxADMJamNsPt254UMGQxy/d8/nVjRoLHgb2w0c34HVYT2LbjYQzDMWSc85us845BnQYT1raDfx+AWpJbGNI3HAjd5txDhtQiwSPGX4t/Q+BWv6BtOQ8M875R4yWGSBbGsBamB/nthGlBWhLwjGJxJkz0syYc/skeNgI+cWwP/3ZzR81Non9EsmPP+d8q5PjZz98DL+WBjAlASLYICQ+5SAgj8Rm/kBI9SgYBaNgFIxMAAD3u0y65t8K9AAAAABJRU5ErkJggg==","orcid":"","institution":"Université Grenoble Alpes, Fonds Clinatec","correspondingAuthor":true,"prefix":"","firstName":"Jaimie","middleName":"Hoh","lastName":"Kam","suffix":""},{"id":477909906,"identity":"c1ad9b2f-e2cd-46d0-8b54-ee39b2d23ddc","order_by":1,"name":"Romain Clément","email":"","orcid":"","institution":"Université Grenoble Alpes, Fonds Clinatec","correspondingAuthor":false,"prefix":"","firstName":"Romain","middleName":"","lastName":"Clément","suffix":""},{"id":477909907,"identity":"a329ff3e-9444-4da4-8b7d-933ece601333","order_by":2,"name":"Tigrane Cantat-Moltrecht","email":"","orcid":"","institution":"Université Grenoble Alpes, Fonds Clinatec","correspondingAuthor":false,"prefix":"","firstName":"Tigrane","middleName":"","lastName":"Cantat-Moltrecht","suffix":""},{"id":477909908,"identity":"74d19636-2e16-4ec5-9ef2-743f72420174","order_by":3,"name":"Malvina Billères","email":"","orcid":"","institution":"Université Grenoble Alpes, Fonds Clinatec","correspondingAuthor":false,"prefix":"","firstName":"Malvina","middleName":"","lastName":"Billères","suffix":""},{"id":477909909,"identity":"2189e25c-3635-4df8-a42e-742aa2436870","order_by":4,"name":"John Mitrofanis","email":"","orcid":"","institution":"Université Grenoble Alpes, Fonds Clinatec","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Mitrofanis","suffix":""}],"badges":[],"createdAt":"2025-06-03 09:23:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6809450/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6809450/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-22344-0","type":"published","date":"2025-11-04T15:57:06+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":85691175,"identity":"0ce257a4-4c6d-417d-b105-58c128cf20bd","added_by":"auto","created_at":"2025-06-30 16:54:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":656045,"visible":true,"origin":"","legend":"\u003cp\u003eGraphs and traces of biophoton emissions defining cell type. (A) Graph showing the photon counts per second for healthy Neuro-2a cells (light green) and astrocytes (light purple) at rest compared to medium only (dotted line). (C,E) Graphs showing the photon counts per second for stressed Neuro-2a cells (dark green) and astrocytes (dark purple) with either sodium troclosene (C) or rotenone (E) compared to baseline (dotted line; healthy cells). (B,D,F) Schematic diagram of individual biophoton emission read-outs for healthy Neuro-2a cells and astrocytes at rest (B) and stressed Neuro-2a cells and astrocytes with sodium troclosene (D) or rotenone (F). For the graphs and traces, healthy environments have a white background and stressed ones a blue background. For the traces, the biophoton emissions for Neuro-2a cells are displayed as green lines and astrocytes as purple lines. Error bars in graphs indicate SEM. No major differences were found between the two cell types. See text for full statistics details.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/4999bce07871a18086c66e20.png"},{"id":85691543,"identity":"2a71e521-993e-4581-b833-b3f323f04203","added_by":"auto","created_at":"2025-06-30 17:02:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":99941,"visible":true,"origin":"","legend":"\u003cp\u003eGraphs indicating biophoton emissions as indictor of cell health in Neuro-2a cells (A; green columns) and astrocytes (B; purple). Healthy cells are shown in lightest-shaded columns, stressed cells with sodium troclosene (ST) in darkest-shaded columns and stressed cells with rotenone in mid-shaded columns. Medium only represented as dotted lines. Error bars in graphs indicate SEM. The statistical significant differences are indicated at p\u0026lt;0.05 (*) and p\u0026lt;0.0001 (****) between healthy and stressed conditions and between healthy and medium only (asterisks above healthy columns); non-significant differences are not shown (for the sake of clarity in the graphs). See text for full statistics details.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/fbb61d1c013865b4a29b151f.png"},{"id":85691174,"identity":"25057f57-9dd9-4179-a083-95241d72cca6","added_by":"auto","created_at":"2025-06-30 16:54:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":85340,"visible":true,"origin":"","legend":"\u003cp\u003eGraphs of biophoton emission read-outs after R-NIr treatment in healthy cells at rest (A,B). Neuro-2a cell emission graph has a green background (A), while astrocyte emission graph has a purple background (B). For each graph, biophoton baseline activity is represented as dotted line, lower intensity R-NIr in light red, higher intensity R-NIr (R-NIr+) in dark red. Error bars indicate SEM. No major differences were found between the R-NIr treatments and baseline. See text for full statistics details.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/4bcb802a571a04d674886f2a.png"},{"id":85691544,"identity":"29b828ec-0c0d-499e-a861-5f5a3c1edeb5","added_by":"auto","created_at":"2025-06-30 17:02:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":277133,"visible":true,"origin":"","legend":"\u003cp\u003eGraphs of biophoton emission read-outs after R-NIr was applied either after each stressor (sodium troclosene A,B; rotenone C,D). Neuro-2a cell emission graphs have a green background (A,C), while astrocyte emission graphs have a purple background (B,D). For each graph, biophoton baseline activity is represented as dotted line, both stresses are blue columns, lower intensity R-NIr in light red, higher intensity R-NIr (R-NIr+) in dark red; blue-shadowed columns indicate cultures that were exposed to stressor and R-NIr, either lower (light red column) or higher (dark red column) intensity. Error bars indicate SEM. The asterisks indicate statistical significant differences at p\u0026lt;0.05 (*) and p\u0026lt;0.01 (**) and are shown only for differences between baseline and stressor and stressor and R-NIr applications; non-significant differences are not shown (for the sake of clarity in the graphs). See text for full statistics details.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/0c0eea96d85efa4be3c827fe.png"},{"id":85691179,"identity":"bb432fa1-4d5f-4cd8-b1af-54bff37276fa","added_by":"auto","created_at":"2025-06-30 16:54:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":302786,"visible":true,"origin":"","legend":"\u003cp\u003eGraphs of biophoton emission read-outs before R-NIr was applied before each stressor (sodium troclosene A,B; rotenone C,D). Neuro-2a cell emission graphs have a green background (A,C), while astrocyte emission graphs have a purple background (B,D). For each graph, biophoton baseline activity is represented as dotted line, both stresses are blue columns, lower intensity R-NIr in light red, higher intensity R-NIr (R-NIr+) in dark red; blue-shadowed columns indicate cultures that were exposed to stressor and R-NIr, either lower (light red column) or higher (dark red column) intensity. Error bars indicate SEM. The asterisks indicate statistical significant differences at p\u0026lt;0.05 (*) and p\u0026lt;0.001 (***) and are shown only for differences between baseline and stressor and stressor and R-NIr applications; non-significant differences are not shown (for the sake of clarity in the graphs). See text for full statistics details.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/63848dd98edba9f9e34c5094.png"},{"id":85691178,"identity":"90457d0d-1347-4cd8-ba02-7e1afea35503","added_by":"auto","created_at":"2025-06-30 16:54:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":254700,"visible":true,"origin":"","legend":"\u003cp\u003eGraphs of ATP levels after R-NIr treatment, either in healthy cells at rest (A,B), treated with sodium troclosene (C,D) or with (rotenone (E,F); R-NIr (high intensity; ie, R-NIr+) was applied after each stressor. Neuro-2a cell graphs have a green background (A,C,E), while astrocyte graphs have a purple background (B,D). For each graph, the columns of baseline activity in healthy cells is in black, both stresses are in blue, higher intensity R-NIr in dark red with blue-stripes (indicative of cultures that were exposed to both stressor and R-NIr+). Error bars indicate SEM. The asterisks indicate statistical significant differences at p\u0026lt;0.05 (*) and p\u0026lt;0.0001 (****) and are shown only for differences between baseline and stressor and stressor and R-NIr applications; non-significant differences are not shown (for the sake of clarity in the graphs). See text for full statistics details.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/51a1ea67374018112b2f23c9.png"},{"id":85692156,"identity":"c14cafb8-0754-442e-a59d-4081484727ba","added_by":"auto","created_at":"2025-06-30 17:10:41","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":233522,"visible":true,"origin":"","legend":"\u003cp\u003eGraphs of ROS levels after R-NIr treatment, either in healthy cells at rest (A,B), treated with sodium troclosene (C,D) or with (rotenone (E,F); R-NIr (high intensity; ie, R-NIr+) was applied after each stressor. Neuro-2a cell graphs have a green background (A,C,E), while astrocyte graphs have a purple background (B,D). For each graph, the columns of baseline activity in healthy cells is in black, both stresses are in blue, higher intensity R-NIr in dark red with blue-stripes (indicative of cultures that were exposed to both stressor and R-NIr+). Error bars indicate SEM. The asterisks indicate statistical significant differences at p\u0026lt;0.05 (*), p\u0026lt;0.01 (**) and p\u0026lt;0.0001 (****) and are shown only for differences between baseline and stressor and stressor and R-NIr applications; non-significant differences are not shown (for the sake of clarity in the graphs). See text for full statistics details.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/dd38a4bca374d89abbec9d61.png"},{"id":85693106,"identity":"8be04d90-ff84-41d7-b381-4eb6b548a87a","added_by":"auto","created_at":"2025-06-30 17:26:41","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1185591,"visible":true,"origin":"","legend":"\u003cp\u003eSummary schematic diagram of the patterns of intensity of biophoton emissions from (A) healthy cells and (B) stressed cells and the relationship with ATP and ROS levels, together with the impact of R-NIr treatment. Note that the patterns of biophoton emissions did no relate readily to the patterns of ATP and ROS levels. The stressed cells refer to either ones that were rotenone- or sodium troclosene-treated.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/6a00a24e1e3e251805d5eeba.png"},{"id":85692155,"identity":"41c5b095-3cae-4b78-ae3b-4c919e142f32","added_by":"auto","created_at":"2025-06-30 17:10:40","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":132731,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of the basic biophoton detection set-up. Within the dark chamber, the biophoton emissions from cell cultures were captured and processed by a photomultiplier and the photons counted with a counting unit. The counts were analysed by a computer and the biophoton number and patterns were displayed on screen. The photomultiplier was orientated horizontally (and not vertically) for the sake of clarity of schematic.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/94a710630d7b7c743fd796ad.png"},{"id":95564030,"identity":"2994c405-f047-4773-b4d6-b210cb102f09","added_by":"auto","created_at":"2025-11-10 16:06:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3678522,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6809450/v1/4af41bb5-cd33-47a8-a335-3aac27c4d422.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Red and near-infrared light treatment can change the intensity of biophoton emissions in cell culture","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe idea that living cells can generate light and use it to communicate with each other has been discussed for over a century. With the development of better technology over the years, this endogenous light has been shown to be very weak, being in the range of 2-200 photons/sec/cm\u003csup\u003e2\u003c/sup\u003e. It is not detectable with the naked eye, but only with ultra-sensitive low-light detection systems. For this reason, it has been referred to as ultra-weak photon emissions; in more recent times, the term \"biophotons\" has been used [1\u0026ndash;11].\u003c/p\u003e \u003cp\u003eThe two main cell organelles considered to be involved in the biophoton functional system are mitochondria and microtubules. Mitochondria, that produce the vital adenosine triphosphate (ATP) energy for cell function, as well as maintaining normal levels of reactive oxygen species (ROS), are thought to be the main generators of biophotons. Microtubules are suspected to work a little further downstream, being involved in the capture and transmission of biophotons along the cell processes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMany authors have argued that biophoton emissions are not merely a by-product, a collateral, of mitochondrial activity, but rather, that they subserve a distinct biological function [1\u0026ndash;11]. First, of all the metabolic mitochondrial reactions, the ones involving ROS appear to be the main source of biophotons. Under normal physiological conditions, ROS have important roles in maintaining a delicate balance of cell homeostasis, while under pathological conditions, ROS levels can be elevated and become toxic, leading to much cell dysfunction and death. Because the process of ROS generation is so precise, it has been suggested that the biophoton emissions serve as key indicators of oxidative metabolism. Second, biophoton emissions include a broad range of wavelengths, from ultraviolet (λ=~200nm) to infrared (λ=~950nm) and their intensity can vary considerably. Both these latter features can change dramatically with different states of cell activity and/or health. Third, biophoton emissions, for each emitted wavelength, are considered to be coherent and highly-structured, a feature that is viewed as a cooperation of many parts subserving a specific function. Fourth, the mitochondria have receptors that absorb light across a range of wavelengths (see above), including flavinic and pyridinic rings, lipids, aromatic amino acids, cytochrome c oxidase and interfacial water. These receptors are present even among cells located very deep in the body, in regions where no external light can reach. Indeed, when external light, in the form of red and near infrared light (R-NIr) - known also as photobiomodulation - has been applied to cells located deep in the body, there has been a distinct functional response from cells, changing their functional activity and improving their cell survival rate when suffering stress. Hence, it is likely that these receptors are there for a purpose, that is, to use light to influence various cellular mechanisms. Indeed, it has been suggested that a main mechanism of action of R-NIr is that it taps into the biophoton system and uses it to facilitate changes in cell function and survival [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Taken all together, these factors indicate that there is a distinct biological significance for the biophotons [1\u0026ndash;11].\u003c/p\u003e \u003cp\u003eAs to what precisely this distinct biological function associated with biophotons is, it remains far from clear. Several have been proposed however, including; (1) that biophotons are used for cell communication, that one cell may inform other cells of their state of health or activity [1\u0026ndash;11], and; (2) that biophotons play a part in cell repair and regeneration, that a stressed cell may release biophotons to repair itself and/or be repaired by biophotons from nearby healthy cells [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMost previous studies examining patterns of biophoton emissions have focussed on various types of plant cells [1,2,14,15] and bacteria [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], together with cancer cells [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19 CR20 CR21\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. There have also been some studies that have considered biophoton activity in neural cells, both peripheral [14,23] and central [14,24\u0026ndash;31], but most of these have either been in brain slices or on whole preparations, none from cell lines in culture.\u003c/p\u003e \u003cp\u003eThe major aims of this study were three-fold. First, to determine whether different types of neural cells - neurones and astrocytes - displayed a signature biophoton intensity emission pattern. Second, if the intensity of biophoton emissions could be reflective of the state of neural cell health. Third, to explore whether external application of R-NIr influenced the intensity of biophoton emissions from these cells. For each of these three issues, we examined the intensity of emissions of cells when healthy (and at rest) and when stressed with toxins. In addition, we measured the ATP and ROS levels (measures of mitochondrial health) under various conditions and related these levels to any changes in biophoton emissions. Our results will hopefully provide insights into whether biophoton emissions can be a key indicator of cell type and health, together with the mechanism of action behind R-NIr treatment.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn the section that follows, we will consider if biophoton emissions: (1) defined neural cell type (2) reflected state of cell health (3) were influenced by external R-NIr treatment and (4) mirrored changes in ATP and ROS levels.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e(1) Biophoton emissions and neural cell type\u003c/h2\u003e \u003cp\u003eOur first aim was to determine whether the patterns of biophoton emission intensities defined neural cell type - Neuro-2a cells and astrocytes - at both rest and when stressed. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows graphs of the number of biophotons detected from healthy cells (at rest, baseline) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) and when stressed with either sodium troclosene (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) or rotenone (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), relative to the medium only. Individual traces of activity for both cell types are shown also, at either rest (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), sodium troclosene-treated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) or rotenone-treated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). When comparing the detected emissions from Neuro-2a cells and astrocytes, no major differences were evident, either at rest (p\u0026thinsp;=\u0026thinsp;0.18) or after being stressed with sodium troclosene (p\u0026thinsp;=\u0026thinsp;0.06) or with rotenone (p\u0026thinsp;=\u0026thinsp;0.15). In fact, they were largely indistinguishable. This feature is particularly clear from the traces of each cell type under the different conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB,D,F); traces from both cells overlapped considerably. In essence, there appeared to be no signature pattern of biophoton emission that defined either cell type.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e(2) Biophoton emissions and state of cell health\u003c/h3\u003e\n\u003cp\u003eWe then explored whether biophoton emissions reflected the state of health of neural cells. For this, we again examined the patterns of biophoton emissions in healthy cells (at rest) and from stressed cells after application of sodium troclosene and rotenone (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn healthy Neuro-2a cells and astrocytes, biophoton emission recordings were very low, averaging 11.7 counts/sec, with a range of 6\u0026ndash;17 counts/sec for Neuro-2a cells and 12.4 counts/sec, with a range of 6\u0026ndash;18 counts/sec for astrocytes. These values, although being very low, were higher than those relative to the medium only (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA,B); they formed our baseline recordings.\u003c/p\u003e \u003cp\u003eAfter application of sodium troclosene, biophoton emissions increased considerably, relative to healthy cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), in Neuro-2a cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) and astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). After application of rotenone, a very different pattern of biophoton emissions was evident. For Neuro-2a cells, rotenone induced a slight reduction in biophoton emissions relative to healthy cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), while for astrocytes, there was no major change in biophoton emissions compared to healthy cells (p\u0026thinsp;=\u0026thinsp;0.56; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eHence, the detected biophoton emissions from both Neuro-2a cells and astrocytes could define - to some extent - their state of health; when healthy, their detected emissions were similar, both being very low, but when stressed, their responses differed somewhat, either increasing, decreasing or staying the same, dependent on the stressor involved.\u003c/p\u003e\n\u003ch3\u003e(3) The impact of R-NIr treatment on biophoton emissions\u003c/h3\u003e\n\u003cp\u003eNext, we examined the impact of R-NIr (λ\u0026thinsp;=\u0026thinsp;660 nm and 850 nm) on the intensity of biophoton emissions of healthy and stressed Neuro-2a cells and astrocytes. We examined the effect of two doses of R-NIr, a lower (R-NIr; 78.5 mW/cm\u0026sup2; and a total fluence of 9.4 J/cm\u0026sup2;) and higher (R-NIr\u003csup\u003e+\u003c/sup\u003e; 137.4 mW/cm\u0026sup2; and a total fluence of 16.5 J/cm\u0026sup2;) one.\u003c/p\u003e \u003cp\u003eIn healthy cells, there was no major change in the patterns of biophoton emissions detected for both Neuro-2a cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA; p\u0026thinsp;=\u0026thinsp;0.42 for R-NIr and p\u0026thinsp;=\u0026thinsp;0.90 for R-NIr+) or astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; p\u0026thinsp;=\u0026thinsp;0.91 for R-NIr and p\u0026thinsp;=\u0026thinsp;0.30 for R-NIr\u003csup\u003e+\u003c/sup\u003e) compared to baseline after application of either a lower or higher dose of R-NIr. It should be noted that this result indicated that R-NIr did not generate any delayed illuminance, at least for the 5 minutes after the exposure and during the recording of biophoton activity [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe then undertook a separate series of experiments where we measured the intensity of biophoton emissions when R-NIr was applied after either of the two stressors (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For the sodium troclosene, post-application of either dose of R-NIr increased the detected biophoton emissions in Neuro-2a cells, particularly after R-NIr\u003csup\u003e+\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA; p\u0026thinsp;=\u0026thinsp;0.15 (R-NIr), p\u0026thinsp;\u0026lt;\u0026thinsp;0.005 (R-NIr\u003csup\u003e+\u003c/sup\u003e)). By contrast, astrocytes showed a decreased biophoton activity after post-application of either dose of R-NIr, again particularly after R-NIr\u003csup\u003e+\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB; p\u0026thinsp;=\u0026thinsp;0.13 (R-NIr), p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (R-NIr\u003csup\u003e+\u003c/sup\u003e)). For rotenone, the changes in patterns of detected biophoton emissions post-application of both R-NIr doses were far less dramatic - in Neuro-2a cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) and astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) - compared to that seen with sodium troclosene. R-NIr after rotenone treatment induced only very small increases in the Neuro-2a cells with both doses (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and no changes in the astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD; p\u0026thinsp;=\u0026thinsp;0.78 (R-NIr), p\u0026thinsp;=\u0026thinsp;0.99 (R-NIr\u003csup\u003e+\u003c/sup\u003e)).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFollowing on from that series of experiments, we explored the patterns of biophoton emissions when R-NIr was applied before either of the stressors (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). For the sodium troclosene, pre-application of either dose of R-NIr increased the detected biophoton emissions considerably in Neuro-2a cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (R-NIr), p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (R-NIr\u003csup\u003e+\u003c/sup\u003e)), well over and above the activity evident with sodium troclosene stress alone (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). By contrast, astrocytes showed only minimal changes in detected biophoton activity after pre-application of either dose of R-NIr compared to sodium troclosene alone (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB; p\u0026thinsp;=\u0026thinsp;0.13 (R-NIr), p\u0026thinsp;=\u0026thinsp;0.02 (R-NIr\u003csup\u003e+\u003c/sup\u003e)). For rotenone, the patterns of biophoton emissions after pre-application of both R-NIr doses were very different - in the Neuro-2a cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC) and astrocytes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) - to that evident with sodium troclosene. Here, with rotenone, there was minimal change in activity before R-NIr treatment (Neuro-2a: p\u0026thinsp;=\u0026thinsp;0.71 (R-NIr); astrocytes: p\u0026thinsp;=\u0026thinsp;0.87 (R-NIr), p\u0026thinsp;=\u0026thinsp;0.99 (R-NIr\u003csup\u003e+\u003c/sup\u003e)), although a small increase was seen for the R-NIr\u003csup\u003e+\u003c/sup\u003e in the Neuro-2a cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThus, externally applied R-NIr appeared to have little effect on the intensity of detected biophoton emissions from both Neuro-2a cells and astrocytes when healthy. By contrast, R-NIr did have an impact on the detected emissions from Neuro-2a cells, and to a lesser extent, from astrocytes, when stressed from at least one of the two stressors.\u003c/p\u003e\n\u003ch3\u003e(4) Changes in ATP and ROS levels\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003e(4) Changes in ATP and ROS levels\u003c/div\u003e \u003cp\u003eFinally, in order to relate our findings on biophotons emissions in healthy Neuro-2a cells and astrocytes at rest and after treatment - stress and/or R-NIr - to the overall state of mitochondrial health, we measured ATP and ROS levels in both cell types under the same conditions (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e,\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). We chose to focus on one dose of R-NIr (R-NIr\u003csup\u003e+\u003c/sup\u003e, because there was no major difference between the two doses and this dose generally produced a greater response) and the changes when R-NIr was applied after the stress (again, there were limited differences between the before and after application, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e,\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor ATP levels, there was little change in Neuro-2a cells (p\u0026thinsp;=\u0026thinsp;0.9; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA) and a slight increase in astrocytes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB) after R-NIr treatment when the cells were healthy. When Neuro-2a cells were stressed, with either sodium troclosene (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC) or rotenone (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE), there were clear increases in ATP (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001); these levels were reduced dramatically after R-NIr treatment in rotenone (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and to a much lesser extent, in sodium troclosene (p\u0026thinsp;=\u0026thinsp;0.5) stressed cells. When astrocytes were stressed, there was little change in ATP levels after application of sodium troclosene (p\u0026thinsp;=\u0026thinsp;0.44; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD) or rotenone (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u0026thinsp;\u0026gt;\u0026thinsp;0.4; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF); with R-NIr treatment, there were minimal changes in ATP levels after sodium troclosene (p\u0026thinsp;=\u0026thinsp;0.4) and a decrease after rotenone (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eFor ROS levels, there was little change in both Neuro-2a cells (p\u0026thinsp;=\u0026thinsp;0.14; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA) and astrocytes (p\u0026thinsp;=\u0026thinsp;0.68; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB) after R-NIr treatment when healthy. When Neuro-2a cells were stressed, with either sodium troclosene (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC) or rotenone (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE), there were clear increases in ROS levels, and these were reduced after R-NIr treatment in the sodium troclosene (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and rotenone (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) affected cells. When astrocytes were stressed, there was a small decrease in ROS levels after application of sodium troclosene (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD) but not with rotenone (p\u0026thinsp;=\u0026thinsp;0.63; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF); with R-NIr treatment, there were minimal changes in ROS levels after either sodium troclosene (p\u0026thinsp;=\u0026thinsp;0.98) or rotenone application (p\u0026thinsp;=\u0026thinsp;0.96).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWe had three major findings. First, that neural cells - Neuro-2a (neurone-like) and astrocytes - when either healthy or stressed, had no distinctive cell-specific pattern of biophoton emissions. Second, that the emissions from both cell types could define - to some extent - their state of health; when healthy, their intensity of emissions were similar, both being very low, but when stressed, their responses differed somewhat, either increasing, decreasing or staying the same, dependent on the stressor involved. Third, that while externally applied R-NIr had no influence on the intensity of biophoton emissions from both Neuro-2a cells and astrocytes when healthy, it could have an influence on emissions in Neuro-2a cells, and to a lesser extent, in astrocytes, when placed under stressful conditions. These major findings will be the focus of the Discussion below. First, some limitations of our study will be considered.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eOur study had two main limitations. First, we examined the impact of stress and R-NIr on biophoton emissions of cells in culture. Ideally, one would have used an in vivo set-up to examine these cellular issues but, unfortunately, such technology is not available currently. There are methods to examine endogenous light output in the whole organism in vivo, but these would not reveal the level of detail that we have documented here; further, most of the output from the current in vivo methods is from the skin and not the brain, our area of interest [32-34]. Nevertheless, cell culture experiments are often a first step in testing new ideas and paradigms and set the template for further study in vivo. Second, we used Neuro-2a cells that, strictly speaking, are not neurones. They are fast-growing and robust neuroblastoma cells. However, many previous studies have used such cells as a window into neuronal function, in both health and disease [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. For our purposes here, these \"neurone-like\" cells - with their fast-growing and robust nature - formed an ideal cell line to measure the intensity of biophoton emissions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe intensity of biophoton emissions did not define neural cell type\u003c/h3\u003e\n\u003cp\u003eOne of the key issues associated with research into the biophoton phenomenon is whether the emissions can define cell type. This may be a way, for instance, by which cells communicate their particular lineage. Further, in terms of development of a therapeutic device, a signature biophoton emission could make different cell types readily identifiable. Previous studies on this specific issue have been rather limited, however. Perhaps the best known examples come from studies examining differences between cancer and normal cells [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19 CR20 CR21\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. For example, cancer cells have been reported to have higher emissions over the lower wavelengths (eg ultraviolet) compared to normal cells [21,22].\u003c/p\u003e \u003cp\u003eIn this study, we explored whether the intensity of biophoton emissions could define neural cell type, namely Neuro-2a cells and astrocytes. We found that their intensity of emissions was very similar, with neither showing any distinctive, cell-specific pattern. Thus, this measure may not necessarily be a good indicator of neural cell type. But, there may be other ways. For instance, as with cancer cells, there may be different patterns of intensities across the range of wavelengths, from ultraviolet to R-NIr, and these may change with time [18,18,21]. Taken together, although neurones and astrocytes may have the same detected intensity of biophoton emissions, there may be different combinations of wavelengths involved and these may help better define their different identity. Future studies could explore this issue further.\u003c/p\u003e\n\u003ch3\u003eDoes the intensity of biophoton emissions reflect cell health?\u003c/h3\u003e\n\u003cp\u003ePrevious studies have shown that the intensity of biophoton emissions can provide some indication as to the state of cell health. There have been reports of clear changes in the intensity of biophoton emissions after application of a variety of different types of stimulants and/or conditions. For example, an increase in emissions is induced after application of glutamate to mouse brain slices [29,30], toxins such as silver nanoparticles to adult mouse stem cells [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], electrical stimulation of the rat sciatic nerve [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and temperature change (ie heat) to azuki beans [25], while a decrease in emissions becomes evident after application of anaesthetic (procaine) to spinal cord nerve roots [14]. There have been no previous studies exploring the patterns of biophoton emissions in neural cell lines, Neuro-2a cells and astrocytes, under healthy and/or stressed conditions, however.\u003c/p\u003e \u003cp\u003eOur results showed that the intensity of biophoton emissions - to some extent - could be reflective of cell health. We found that healthy Neuro-2a cells and astrocytes had very low levels of detected biophoton emissions at rest (~\u0026thinsp;12photons/sec), probably indicative of their low level of activity in this state and/or of their overall homeostasis. And this generally changed under stress. The extent of the change was however, dependant on the stressor involved; sodium troclosene increased emissions in both cell types, while rotenone had a much more limited impact, with a very small decrease in Neuro-2a cells and no change in astrocytes. This difference between the two stressors cannot be explained readily by the patterns of ATP and ROS produced by the cells; both stressors increased ROS and, rather surprisingly, ATP levels as well. The latter may be reflective of an immediate response reaction to the toxicity induced by the stressor; with a greater time-period, one would assume that these high ATP levels would drop off considerably with increasingly more mitochondrial and cell damage. The stressor-induced changes in ROS levels are of particular interest here, because these levels have been linked closely to the biophoton emissions (see Introduction). While there was a clear relationship between the increase in ROS levels and biophoton emissions after sodium troclosene, there was no such relationship after rotenone treatment, with the biophoton emissions not matching the increase in ROS levels (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e,\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Hence, there may be other factors generating these differences in biophoton emission responses - other than changes in ROS levels - from, at the very least, one of the stressors. Of course the pattern may change over time, but in these initial stages of the stress, the changes in biophoton intensity emissions do not appear to match uniformly - across different stressors - the changes in ROS levels.\u003c/p\u003e \u003cp\u003eIn summary, our findings indicated that the intensity of biophoton emissions from Neuro-2a cells and astrocytes could be reflective of cell health when healthy, but not necessarily when stressed, with the intensity being dependant on the type of stressor involved. Further, that such changes, in both cell types, did not relate readily to changes in ROS levels in the cells, suggesting that there may well be other factors to consider in the generation of biophoton emissions.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRed and near infrared light treatment influences the intensity of biophoton emissions\u003c/h2\u003e \u003cp\u003ePerhaps our most novel and striking set of findings related to the effect of R-NIr on biophoton emissions from both cell types. There has been one previous study examining the impact of white light, spanning a range of wavelengths (λ\u0026thinsp;=\u0026thinsp;410-1200nm), showing an increase in the emissions in germinating green bean seeds [14], but no study has examined specifically the effect of R-NIr on emissions from any type of cell (λ\u0026thinsp;=\u0026thinsp;660nm and 850nm). A major reason why we focused on R-NIr was to explore whether it can influence the emission intensity; if so, it would support the idea that R-NIr can facilitate many of its beneficial cellular effects by using the biophoton network system [6,7,10,37]. For example, if a cell is damaged then it, or nearby cells, may release R-NIr in an effort to help repair the damage and improve its survival. Externally-applied R-NIr may tap into this system - albeit at higher doses - and help the repair process even more; it could potentially form a key mechanism of action behind many of the benefits of R-NIr treatment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTaking all our results on R-NIr and biophoton emission intensity together, some general comments can be made (see Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e):\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e(1) that R-NIr had a greater impact on emissions in stressed cells than those that are healthy and at rest. This is, on the whole, consistent with many previous reports indicating that R-NIr is more effective on cells suffering pathology than those that are healthy and functioning normally [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The R-NIr-induced patterns of biophoton emissions we report here reflect this trend.\u003c/p\u003e \u003cp\u003e(2) there were clear differences in the emission responses with R-NIr from Neuro-2a cells and astrocytes, with the latter being far less dramatic. For Neuro-2a cells, rather than decrease the intensity of emissions in stress, R-NIr increased the intensity. If one assumes that intensity of emissions is related to level of stress suffered by a cell, and that R-NIr should decrease this stress, then this finding is counter-intuitive. We suggest however, that this intensity increase includes a range of different wavelengths, all functioning in different ways. For example, under stress, the cells could release biophotons in the UV range, as a signal of distress, as well as some biophotons in the R-NIr range, as to help the repair process; the external application of R-NIr could evoke a further wave R-NIr release and aid the repair [6,7,10,18,19,21]. Determining the spectral distribution of biophoton emission was beyond the scope of the present study, but we are in the planning stage of examining this issue in the future. For the astrocytes, the minimal changes in emissions after R-NIr treatment with stress suggests that these cells are less responsive to the external light and may not need an extra dose to help any repair process, either for themselves or nearby neurones. Astrocytes have been shown to be directly responsive to R-NIr in cell culture [40], but this response - judging by their biophoton emissions - may not be as intense as it is for neurones or neurone-like cells (ie Neuro-2a cells).\u003c/p\u003e \u003cp\u003e(3) the higher and lower R-NIr doses we used generally produced the same biophoton emission response, whether it was an increase, decrease or no change. There was a tendency however, for the higher dose to generate a slightly greater change in intensity than the lower one. For our study here, we aimed only to determine some preliminary insights into dosage and hence used only two doses. A more comprehensive analysis of dose awaits, to determine the precise parameters of the biphasic response of R-NIr treatment, where the so-called \"sweet-spot\" dose lies and where the null-effect dose ranges are found [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e(4) globally, there were very similar patterns of emissions evident from both cell types whether the R-NIr was applied after or before the stressor. This would indicate - assuming a beneficial role for R-NIr application and the biophoton system - that a pre-treatment of R-NIr could be just as effective as a post-treatment; indeed, this has been reported for this method in various animal models of Parkinson's disease [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e(5) the R-NIr-induced changes in emissions did not match closely the changes in ATP and ROS levels in both cell types. While R-NIr treatment either increased, decreased or had no impact on the intensity of biophoton emissions, depending on the stressor, it almost uniformly decreased the ATP and ROS levels under the corresponding conditions. It appeared that R-NIr worked to restore the balance after a massive and immediate increase in ATP and ROS levels following the toxic shock induced by the stressor; in most cases, particularly in Neuro-2a cells, R-NIr reduced levels to near baseline. Either way, the intensity of biophoton emissions after R-NIr treatment did not relate readily to changes in ATP, and perhaps more importantly, ROS levels, suggesting that others factors may be at play (see above).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eWe have shown that the intensity of biophoton emissions from Neuro-2a cells and astrocytes were similar when both healthy and stressed, with neither showing any distinctive, cell-specific pattern. Thus, this measure may not necessarily be a good indicator of neural cell type. We also found that the intensity of biophoton emissions - to some extent - could be reflective of cell health when healthy, but not necessarily when stressed, with the intensity being dependant on the type of stressor applied; sodium troclosene increased emissions, while rotenone had a more limited impact. Further, that such changes, in both cell types, did not relate to changes in ROS levels in the cells, suggesting that there may well be other factors involved in generating the emissions. Finally, we showed that R-NIr did not influence emissions when heathy, but did so when stressed, particularly in Neuro-2a cells and with at least one of the stressors used. The next step in the exploration would be to define the wavelengths associated with the biophotons from both healthy and stressed neural cells and whether R-NIr influences the pattern of these wavelengths.\u003c/p\u003e "},{"header":"MATERIALS \u0026 METHODS","content":"\u003ch2\u003eCells\u003c/h2\u003e\u003cp\u003eMouse \"neurone-like\" (ie Neuro-2a CCL-131) cells and astrocytes (C8-D1A) were obtained from American Type Culture Collection (LGC Standards France). Neuro-2a cells are a fast-growing mouse neuroblastoma cell line that have been used to explore extensively aspects of neurone function and dysfunction (Tremblay et al 2010). They were cultured in Dulbecco’s Modified Eagle’s medium containing glutamine and 10% foetal bovine serum and kept at 37\u003csup\u003eo\u003c/sup\u003eC, 5% CO\u003csub\u003e2\u003c/sub\u003e and 85% relative humidity. Cells were plated in 60mm petri dishes at a density of 1\u0026nbsp;million cells 24 hours prior to biophoton recording and cells were kept in complete darkness. In fact, we made absolutely sure that the cells were not exposed to any light for up to 24 hours before experimentation, limiting any so-called delayed luminescence [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003ch2\u003eBiophoton experimental set-up and detection system\u003c/h2\u003e\u003cp\u003eBiophotons emitted by the Neuro-2a cells and astrocytes in a culture dish were measured at room temperature using a photomultiplier tube H16722P-40 (Hamamatsu Photonics, Japan) in a purpose-built dark chamber (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). The photomultiplier had a GaAsP photocathode with a spectral sensitivity in the 300nm-740nm range. The photomultiplier was cooled with an internal thermo-electric module, in order to reduce dark counts and improve its signal-to-noise ratio, and equipped with a heatsink and fan A7423 that effectively radiated the heat away. The photomultiplier was powered by a C8137-02 power supply unit (Hamamatsu Photonics, Japan) that also handled temperature regulation. The output of the PMT was connected to a C9744 photon counting unit (Hamamatsu Photonics, Japan), supplied with + 5V/-5V, that generated pulses from the current output of the photomultiplier. A C8855-01 counting unit counts these pulses and was connected to the recording computer.\u003c/p\u003e\u003ch2\u003eMeasurements from healthy and stressed cells\u003c/h2\u003e\u003cp\u003eWe made measurements from healthy (at rest) and stressed Neuro-2a cells and astrocytes in culture. For the measurements from healthy cells, biophoton emissions were recorded and the values compared relative to the medium only (containing no cells) for 3 minutes; these recordings from the cells formed our baseline readings.\u003c/p\u003e\u003cp\u003eFor the measurements from stressed cells, after recording baseline readings, we applied the stressors by pipetting them gently on the wall of the petri dish and into medium of the cells. We used two agents to stress the Neuro-2a cells and astrocytes, sodium troclosene and rotenone. We used these two because they have different mechanisms of action. Sodium troclosene (0.25mM) is a strong oxidising agent that slowly releases chlorine in low concentration into the medium at a relatively constant rate and hence changes the pH of the medium to acidic [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Rotenone (9nM) is an inhibitor of complex I in the mitochondrial electron transport chain and has been shown to increase the production of ROS, lower the production of ATP and decrease the mitochondrial membrane potential [44]. After application of stressor, we recorded emissions for the next 5 minutes and these readings were compared relative to the baseline.\u003c/p\u003e\u003ch2\u003eMeasurements with external red and near infra red light (R-NIr) treatment\u003c/h2\u003e\u003cp\u003eFor the effect of external light (R-NIr) treatment, intensity of biophoton emissions were recorded first from healthy cells at rest (baseline) and then again with cells exposed to R-NIr either after or before application of a stressor.\u003c/p\u003e\u003cp\u003eWe exposed the cell cultures to R-NIr continuously for 2 minutes. For this, the Neuro-2a cells and astrocytes were treated with light emitting diode (LED) light at 660nm and 850nm at either; (1) a lower intensity R-NIr exposure at an irradiance of 29.8mW/cm² at 660nm and 48.7mW/cm² at 850 nm, with the lamp placed 20cm above the petri dish, giving a total irradiance of 78.5mW/cm² and a total fluence of 9.4J/cm² or; (2) a higher intensity R-NIr exposure (RNIr\u003csup\u003e+\u003c/sup\u003e) at an irradiance of 51.2mW/cm² at 660 nm and 86.2mW/cm² at 850 nm, with the lamp placed at 10cm above the petri dish, giving a total irradiance of 137.4 mW/cm² and a total fluence of 16.5J/cm². The biophoton activity was then recorded for 5 minutes thereafter. The readings of biophoton activity with R-NIr treatment were compared relative to the baseline. Biophoton emissions were also recorded using a sham treatment, that is, where the cells were placed under the R-NIr device (see below) but the device was not switched on. There was no difference in the number of photons emitted between the baseline and the sham-treated cells (data not shown).\u003c/p\u003e\u003ch2\u003eOther measures\u003c/h2\u003e\u003cp\u003eIn order to make direct comparisons with any observed changes in biophoton emissions, we made some measures of ATP and ROS levels under the same experimental conditions as those were we measured biophoton activity, ie, at rest, under stress and after exposure to external R-NIr. In order to normalise our analysis of ATP and ROS, total protein content was measured. For this, measurement was performed using a commercially available kit, BCA Protein Assay by Thermo Scientific. Bovine serum albumin was used as a standard, and the amount of protein was measured following the manufacturer’s instructions.\u003c/p\u003e\u003cp\u003eATP Assay\u003c/p\u003e\u003cp\u003eATP production was quantified using the ATP Determination kit (Fisher Scientific). Cells were harvested and homogenised in 100µL of 6M guanidine-HCl in extraction buffer (100mM Tris and 4mM EDTA, pH 7.8) to inhibit ATPases, followed by freezing in dry ice. The homogenate was then heat- treated at 95\u003csup\u003eo\u003c/sup\u003eC for 5 minutes and then centrifuged for 15 mins at maximum speed (13 500 RPM). The supernatant was collected and ATP was measured according to the manufacturer’s instructions.\u003c/p\u003e\u003cp\u003eROS Assay\u003c/p\u003e\u003cp\u003eTo assess oxidative stress, ROS levels were measured using dichloro-dihydrofluorescein diacetate. Cells were harvested and homogenised in 200µL of ice-cold 0.4M Tris-HCl buffer (pH 7.4) (Merck) followed by a 10 minutes centrifugation at 2000g at 4\u003csup\u003eo\u003c/sup\u003eC. 50µl of each supernatant was added to a 96 microplate well containing 7.5µl of 5µM dichloro-dihydrofluorescein diacetate (Merck) and total volume was adjusted to 100µL with homogenising buffer. After 1 hour incubation at room temperature, the conversion of dichloro-dihydrofluorescein diacetate to dichloro-dihydrofluorescein was measured at 485nm excitation and 520nm emission.\u003c/p\u003e\u003ch2\u003eStatistics\u003c/h2\u003e\u003cp\u003eData were analysed with GraphPad Prism v.10 (San Diego, USA) and statistical analyses were undertaken using a one-way ANOVA, using Tukey or Bonferroni’s multiple comparison test. Data presented are mean SEM. The significance was asserted as *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, **** p \u0026lt; 0.0001.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eCompeting Interest\u003c/strong\u003e:\u003c/h2\u003e\n\u003cp\u003enone\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eFonds Clinatec and Fondation COVEA France\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors contributed to the writing and analysis of the manuscript. JHK undertook all the experiments and biophoton measurements with the help of RC, while JHK, TCM and MB were involved in the setting-up of the detection system.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe thank Nils TANNEAU for his help with the biophoton system set up.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePopp, F. A. et al. Biophoton emission. Cell Biophysics \u003cstrong\u003e6\u003c/strong\u003e, 33\u0026ndash;52 (1984).\u003c/li\u003e\n\u003cli\u003ePopp, F. A., Chang, J. J., Herzog, A., Yan, Z. \u0026amp; Yan, Y. Evidence of non-classical (squeezed) light in biological systems. 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Toxicology \u003cstrong\u003e272\u003c/strong\u003e, 17\u0026ndash;22 (2010).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"astrocytes, Neuro-2a, photomultipliers, photobiomodulation, ultra-weak photon emission","lastPublishedDoi":"10.21203/rs.3.rs-6809450/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6809450/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe explored the patterns of biophoton - ultra-weak light made by cells - emissions in Neuro-2a cells and astrocytes in culture. Biophotons were detected using a photomultiplier as a single photon counter. We measured intensity of emissions when healthy (and at rest), stressed with toxins (sodium troclosene or rotenone) and/or treated with red and near infrared light (R-NIr). We measured ATP (adenosine triphosphate) and ROS (reactive oxygen species) levels also. Our results showed that emissions from Neuro-2a cells and astrocytes were similar when both healthy and stressed. Both cell types emitted biophotons at low intensities when healthy (~\u0026thinsp;12photons/sec), but this changed markedly under stress. The extent of change was however, dependant on the stressor involved; sodium troclosene increased emissions, while rotenone had a far more limited impact. Finally, we showed that R-NIr did not influence emissions when heathy, but did so when stressed, particularly with sodium troclosene. These emission patterns under different conditions did not relate uniformly to the changes in ATP and ROS levels. In summary, we found that biophoton emissions did not readily define cell type, but could - under some circumstances - be reflective of cell health. Further, that R-NIr could influence these emissions, particularly under stress.\u003c/p\u003e","manuscriptTitle":"Red and near-infrared light treatment can change the intensity of biophoton emissions in cell culture","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-30 16:54:36","doi":"10.21203/rs.3.rs-6809450/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-14T07:32:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-13T13:06:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-09T12:44:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-07T12:08:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"293211225910879565477010846536155738920","date":"2025-06-29T08:54:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53311173719057246037278948066088252809","date":"2025-06-27T07:06:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255165464024150085232150105110883552631","date":"2025-06-26T16:01:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-26T13:15:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-26T12:14:46+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-18T11:01:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-17T07:10:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-06-17T07:06:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"02a7724d-1093-4480-a3f6-9d12240202b9","owner":[],"postedDate":"June 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":50742426,"name":"Biological sciences/Biological techniques"},{"id":50742427,"name":"Biological sciences/Cell biology"},{"id":50742428,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2025-11-10T16:01:42+00:00","versionOfRecord":{"articleIdentity":"rs-6809450","link":"https://doi.org/10.1038/s41598-025-22344-0","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-04 15:57:06","publishedOnDateReadable":"November 4th, 2025"},"versionCreatedAt":"2025-06-30 16:54:36","video":"","vorDoi":"10.1038/s41598-025-22344-0","vorDoiUrl":"https://doi.org/10.1038/s41598-025-22344-0","workflowStages":[]},"version":"v1","identity":"rs-6809450","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6809450","identity":"rs-6809450","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}