On 2016 May 15, Felix Scholkmann commented:

We read with interest the article by Rizzo et al. [1] about the alleged ability for diagnosing “cardiovascular disease through mitochondria respiration as depicted through biophotonic emission”. As researchers in the field of ultra-weak photon emission (UPE) from biological systems (e.g. [2-12]) (also termed “biophotonic emission”) we were surprised to notice that some important statements made in the publication of Rizzo et al. are not correct or unsubstantiated, unfortunately. In the following we will point out these issues in detail.

(1) The “ClearView System” is neither able to detect UPE, nor is the measurement principle related to UPE.

The authors claim that the measurement device used, i.e., the ClearView System, “can detect cardiovascular disease through the measurement of mitochondria dysfunction through biophoton emission.” Concerning the measurement principle of the ClearView System the authors wrote that the “system measures electromagnetic energy at a smaller scale through amplification of biophotons.” Furthermore, it is stated that through “measuring mitochondrial respiration via biophoton detection, the ClearView system has the ability to quantify electrophysiological biophoton activity.”

Unfortunately, the statements are technically not correct. As described in section “1.3 ClearView System” of the paper, and also on the companies’ website (http://epicdiagnostics.com/clearview), the ClearView System is a corona discharge photography (CDP) device (for a detailed description of the technique see [13, 14]), i.e., a device performing contact print photographs of the coronal discharge (of the finger tip) by a high-frequency and high voltage pulse exposure (sinusoidal, 1 KHz, according to the patent for the device [15]). A CCD camera under a transparent electrode is capturing then this discharge pattern. The obtained image is due to the electrical discharge causing air-ionization and subsequently electromagnetic radiation in the optical spectrum when the excited electrons of molecules in the air return to the energetic ground state. This measured light by the device is neither “biophoton emission” nor is it due to an “amplification of biophotons”. The detection of UPE is only possible using high-sensitive photodetectors (i.e., photomultipliers or specific CCD cameras [16-19]). The optical radiation detected using CDP is a stimulated emission, whereas the UPE is a spontaneous emission. Furthermore, the authors state that the “ClearView System is a non-invasive, electrophysiological measurement tool”. And the sentence “[u]nlike other bio-impedance devices, … the ClearView System is ...” is misleading since it links the ClearView system to “bio-impedance devices”. However, this is erroneous and introduces further confusion.

(2) The assignment of the measured corona discharge patters to mitochondria respiration is unsubstantiated.

The authors state that the used measurement device (ClearView) is able of “measuring mitochondrial respiration” indirectly, and “can detect cardiovascular disease through the measurement of mitochondria dysfunction”. Even if we assume that the device would be able to measure UPE (which we showed is not justified), the detected UPE from the skin (i.e., finger tips) is a result of many different biochemical reactions that are not necessarily linked to mitochondrial function/respiration only. A detailed description of the UPE sources in biological systems can be found in the recent reviews [20, 21].

(3) Further questionable statements.

According to the authors, the “ClearView system taps into the global electromagnetic holographic communication system via the fingertips.” Neither give the authors an explanation what they mean with the term “global electromagnetic holographic communication system” nor do they refer to scientific literature that supports their statement.

Also the authors state that it “has been scientifically proven that every cell in the body emits more than 100,000 light impulses or photons per second.” This statement is inconsistent with the earlier statement that “biophoton emission is described to be less than 1000 photons per second per cm”. Additionally that statement contains incorrect units (it should be “per cm²”).In addition the authors state that the “biophotons”, they are allegedly measuring, “have been found to be the steering mechanism behind all biochemical reactions.” Whereas there are indeed theories linking UPE to physiological functions (i.e., delivering activation energy for biochemical reactions and coordinating them) these concepts are based on theoretical work (e.g., [22]) and there exist no scientific consensus regarding this issue at present.

(4) Flaws in the studies experimental design and statistical analysis.

Although the results presented by the authors are interesting, according to our view they should be regarded with caution because of the following reasons:

(a) A case-control study must ensure that the characteristics of the investigated populations (cases and controls) are similar, i.e. the populations should be age-matched and the number of subjects should be approximately the same [23]. Both conditions seem to be not fulfilled in the study of Rizzo et al. According to the authors the “age of cardiovascular subjects was 64.22 (95%CI: 62.44, 65.99) and the mean age of controls was 44.14 (95% CI: 40.73, 47.55).” That the age is a confounder was even found by the authors using the statistical analysis (i.e., OR for cardiovascular disease without considering age: 4.03 (2.71, 6.00), OR with age as a confounder: OR: 3.44 (2.13-5.55)). Additionally, the sample sizes were different (n = 195 vs. n = 64).

(b) The authors state the studies aim was to “indicate the presence or absence of cardiovascular disease”. For such an assessment the calculation of the odds ratios are not sufficient since they give only information about the prevalence, whereas the sensitivity and specificity are important factors to determine if a biomarker is useful for diagnostic purposes [24]. Such an analysis is classically performed by calculating the receiver operating characteristic (ROC) curves and quantifying them. Unfortunately, this kind of analysis is not reported by the authors in the manuscript. However, in the patent application (from which the results of the study were taken), ROC curves were given [25].

(c) Another important factor in showing the usefulness of the proposed novel diagnostic approach is to show the reproducibility of the measurement. The authors report that “a second measurement session was done 3-5 minutes after the first one was completed” in order to “assess the reproducibility and variability of the measurements”. However, we cannot find the results of this assessment in the published paper.

Felix Scholkmann^1, ^2, Michal Cifra³

¹ Biomedical Optics Research Laboratory, Division of Neonatology, University Hospital Zurich, 8091 Zurich, Switzerland

² Research Office of Complex Physical and Biological Systems (ROCoS), 8038 Zurich, Switzerland

³ Institute of Photonics and Electronics, The Czech Academy of Sciences, 18200 Prague, Czech Republic

On 2016 May 15, Felix Scholkmann commented:

References

[1] Rizzo, N.R., N.C. Hank, and J. Zhang, Detecting Presence of Cardiovascular Disease through Mitochondria Respiration as Depicted through Biophotonic Emission. Redox Biologx, 2016. 8: p. 11-17

[2] Cifra, M. and P. Pospisil, Ultra-weak photon emission from biological samples: definition, mechanisms, properties, detection and applications. J Photochem Photobiol B, 2014. 139: p. 2-10.

[3] Kucera, O. and M. Cifra, Cell-to-cell signaling through light: just a ghost of chance? Cell Commun Signal, 2013. 11: p. 87.

[4] Scholkmann, F., D. Fels, and M. Cifra, Non-chemical and non-contact cell-to-cell communication: a short review. Am J Transl Res, 2013. 5(6): p. 586-93.

[5] Rahnama, M., et al., Emission of mitochondrial biophotons and their effect on electrical activity of membrane via microtubules. J Integr Neurosci, 2011. 10(1): p. 65-88.

[6] Cifra, M., J.Z. Fields, and A. Farhadi, Electromagnetic cellular interactions. Prog Biophys Mol Biol, 2011. 105(3): p. 223-46.

[7] Kucera, O., M. Cifra, and J. Pokorny, Technical aspects of measurement of cellular electromagnetic activity. Eur Biophys J, 2010. 39(10): p. 1465-70.

[8] Scholkmann, F., et al., The effect of venous and arterial occlusion of the arm on changes in tissue hemodynamics, oxygenation, and ultra-weak photon emission. Adv Exp Med Biol, 2013. 765: p. 257-64.

[9] Fels, D., M. Cifra, and F. Scholkmann, eds. Fields of the cell. 2015, Research Signpost: Trivandrum.

[10] Scholkmann, F., et al., Using multifractal analysis of ultra-weak photon emission from germinating wheat seedlings to differentiate between two grades of intoxication with potassium dichromate. Journal of Physics: Conference Series, 2011. 329: p. 012020.

[11] Cifra, M., et al., Spontaneous ultra-weak photon emission from human hands is time dependent. Radioengineering, 2007. 16(2): p. 15-19.

[12] Cifra, M., et al., Biophotons, coherence and photocount statistics: A critical review. Journal of Luminescence, 2015. 164: p. 38–51.

[13] Boyers, D.G. and W.A. Tiller, Corona discharge photography. Journal of Applied Physics, 1973. 44(3102).

[14] Kwark, C. and C.W. Lee, Experimental study of a real-time corona discharge imaging system as a future biomedical imaging device. Med Biol Eng Comput, 1994. 32(3): p. 283-8.

[15] Rizzo, N.R., Localized physiologic status from luminosity around fingertip or toe, I. Epic Research And Diagnostics, Editor. 2013.

[16] Van Wijk, R., M. Kobayashi, and E.P. Van Wijk, Anatomic characterization of human ultra-weak photon emission with a moveable photomultiplier and CCD imaging. J Photochem Photobiol B, 2006. 83(1): p. 69-76.

[17] Kobayashi, M., et al., Two-dimensional photon counting imaging and spatiotemporal characterization of ultraweak photon emission from a rat's brain in vivo. J Neurosci Methods, 1999. 93(2): p. 163-8.

[18] Kobayashi, M., Highly sensitive imaging for ultra-weak photon emission from living organisms. J Photochem Photobiol B, 2014. 139: p. 34-8.

[19] Yang, M., et al., Spectral discrimination between healthy people and cold patients using spontaneous photon emission. Biomed Opt Express, 2015. 6(4): p. 1331-9.

[20] Prasad, A., Pospisil, P., The photon source within the cell, in Field of the cell, D. Fels, M. Cifra, and F. Scholkmann, Editors. 2015, Research Signpost: Trivandrum. p. 113-129.

[21] Pospisil, P., A. Prasad, and M. Rac, Role of reactive oxygen species in ultra-weak photon emission in biological systems. J Photochem Photobiol B, 2014. 139: p. 11-23.

[22] Popp, F.A. and J.J. Chang, The Physical Background and the Informational Character of Biophoton Emission, in Biophotons, J.-J. Chang, J. Fisch, and F.-A. Popp, Editors. 1998, Springer Netherlands. p. 239-250.

[23] Bland, M., An Introduction to Medical Statistics. 4th ed. 2015: Oxford University Press.

[24] Grund, B. and C. Sabin, Analysis of biomarker data: logs, odds ratios, and receiver operating characteristic curves. Curr Opin HIV AIDS, 2010. 5(6): p. 473-9.

[25] Rizzo, N.R., Isolated physiological state of brightness by fingertip or toe, I. Epic Research And Diagnostics, Editor. 2014.

On 2016 May 15, Felix Scholkmann commented:

References

[1] Rizzo, N.R., N.C. Hank, and J. Zhang, Detecting Presence of Cardiovascular Disease through Mitochondria Respiration as Depicted through Biophotonic Emission. Redox Biologx, 2016. 8: p. 11-17

[2] Cifra, M. and P. Pospisil, Ultra-weak photon emission from biological samples: definition, mechanisms, properties, detection and applications. J Photochem Photobiol B, 2014. 139: p. 2-10.

[3] Kucera, O. and M. Cifra, Cell-to-cell signaling through light: just a ghost of chance? Cell Commun Signal, 2013. 11: p. 87.

[4] Scholkmann, F., D. Fels, and M. Cifra, Non-chemical and non-contact cell-to-cell communication: a short review. Am J Transl Res, 2013. 5(6): p. 586-93.

[5] Rahnama, M., et al., Emission of mitochondrial biophotons and their effect on electrical activity of membrane via microtubules. J Integr Neurosci, 2011. 10(1): p. 65-88.

[6] Cifra, M., J.Z. Fields, and A. Farhadi, Electromagnetic cellular interactions. Prog Biophys Mol Biol, 2011. 105(3): p. 223-46.

[7] Kucera, O., M. Cifra, and J. Pokorny, Technical aspects of measurement of cellular electromagnetic activity. Eur Biophys J, 2010. 39(10): p. 1465-70.

[8] Scholkmann, F., et al., The effect of venous and arterial occlusion of the arm on changes in tissue hemodynamics, oxygenation, and ultra-weak photon emission. Adv Exp Med Biol, 2013. 765: p. 257-64.

[9] Fels, D., M. Cifra, and F. Scholkmann, eds. Fields of the cell. 2015, Research Signpost: Trivandrum.

[10] Scholkmann, F., et al., Using multifractal analysis of ultra-weak photon emission from germinating wheat seedlings to differentiate between two grades of intoxication with potassium dichromate. Journal of Physics: Conference Series, 2011. 329: p. 012020.

[11] Cifra, M., et al., Spontaneous ultra-weak photon emission from human hands is time dependent. Radioengineering, 2007. 16(2): p. 15-19.

[12] Cifra, M., et al., Biophotons, coherence and photocount statistics: A critical review. Journal of Luminescence, 2015. 164: p. 38–51.

[13] Boyers, D.G. and W.A. Tiller, Corona discharge photography. Journal of Applied Physics, 1973. 44(3102).

[14] Kwark, C. and C.W. Lee, Experimental study of a real-time corona discharge imaging system as a future biomedical imaging device. Med Biol Eng Comput, 1994. 32(3): p. 283-8.

[15] Rizzo, N.R., Localized physiologic status from luminosity around fingertip or toe, I. Epic Research And Diagnostics, Editor. 2013.

[16] Van Wijk, R., M. Kobayashi, and E.P. Van Wijk, Anatomic characterization of human ultra-weak photon emission with a moveable photomultiplier and CCD imaging. J Photochem Photobiol B, 2006. 83(1): p. 69-76.

[17] Kobayashi, M., et al., Two-dimensional photon counting imaging and spatiotemporal characterization of ultraweak photon emission from a rat's brain in vivo. J Neurosci Methods, 1999. 93(2): p. 163-8.

[18] Kobayashi, M., Highly sensitive imaging for ultra-weak photon emission from living organisms. J Photochem Photobiol B, 2014. 139: p. 34-8.

[19] Yang, M., et al., Spectral discrimination between healthy people and cold patients using spontaneous photon emission. Biomed Opt Express, 2015. 6(4): p. 1331-9.

[20] Prasad, A., Pospisil, P., The photon source within the cell, in Field of the cell, D. Fels, M. Cifra, and F. Scholkmann, Editors. 2015, Research Signpost: Trivandrum. p. 113-129.

[21] Pospisil, P., A. Prasad, and M. Rac, Role of reactive oxygen species in ultra-weak photon emission in biological systems. J Photochem Photobiol B, 2014. 139: p. 11-23.

[22] Popp, F.A. and J.J. Chang, The Physical Background and the Informational Character of Biophoton Emission, in Biophotons, J.-J. Chang, J. Fisch, and F.-A. Popp, Editors. 1998, Springer Netherlands. p. 239-250.

[23] Bland, M., An Introduction to Medical Statistics. 4th ed. 2015: Oxford University Press.

[24] Grund, B. and C. Sabin, Analysis of biomarker data: logs, odds ratios, and receiver operating characteristic curves. Curr Opin HIV AIDS, 2010. 5(6): p. 473-9.

[25] Rizzo, N.R., Isolated physiological state of brightness by fingertip or toe, I. Epic Research And Diagnostics, Editor. 2014.

On 2016 May 15, Felix Scholkmann commented:

We read with interest the article by Rizzo et al. [1] about the alleged ability for diagnosing “cardiovascular disease through mitochondria respiration as depicted through biophotonic emission”. As researchers in the field of ultra-weak photon emission (UPE) from biological systems (e.g. [2-12]) (also termed “biophotonic emission”) we were surprised to notice that some important statements made in the publication of Rizzo et al. are not correct or unsubstantiated, unfortunately. In the following we will point out these issues in detail.

(1) The “ClearView System” is neither able to detect UPE, nor is the measurement principle related to UPE.

The authors claim that the measurement device used, i.e., the ClearView System, “can detect cardiovascular disease through the measurement of mitochondria dysfunction through biophoton emission.” Concerning the measurement principle of the ClearView System the authors wrote that the “system measures electromagnetic energy at a smaller scale through amplification of biophotons.” Furthermore, it is stated that through “measuring mitochondrial respiration via biophoton detection, the ClearView system has the ability to quantify electrophysiological biophoton activity.”

Unfortunately, the statements are technically not correct. As described in section “1.3 ClearView System” of the paper, and also on the companies’ website (http://epicdiagnostics.com/clearview), the ClearView System is a corona discharge photography (CDP) device (for a detailed description of the technique see [13, 14]), i.e., a device performing contact print photographs of the coronal discharge (of the finger tip) by a high-frequency and high voltage pulse exposure (sinusoidal, 1 KHz, according to the patent for the device [15]). A CCD camera under a transparent electrode is capturing then this discharge pattern. The obtained image is due to the electrical discharge causing air-ionization and subsequently electromagnetic radiation in the optical spectrum when the excited electrons of molecules in the air return to the energetic ground state. This measured light by the device is neither “biophoton emission” nor is it due to an “amplification of biophotons”. The detection of UPE is only possible using high-sensitive photodetectors (i.e., photomultipliers or specific CCD cameras [16-19]). The optical radiation detected using CDP is a stimulated emission, whereas the UPE is a spontaneous emission. Furthermore, the authors state that the “ClearView System is a non-invasive, electrophysiological measurement tool”. And the sentence “[u]nlike other bio-impedance devices, … the ClearView System is ...” is misleading since it links the ClearView system to “bio-impedance devices”. However, this is erroneous and introduces further confusion.

(2) The assignment of the measured corona discharge patters to mitochondria respiration is unsubstantiated.

The authors state that the used measurement device (ClearView) is able of “measuring mitochondrial respiration” indirectly, and “can detect cardiovascular disease through the measurement of mitochondria dysfunction”. Even if we assume that the device would be able to measure UPE (which we showed is not justified), the detected UPE from the skin (i.e., finger tips) is a result of many different biochemical reactions that are not necessarily linked to mitochondrial function/respiration only. A detailed description of the UPE sources in biological systems can be found in the recent reviews [20, 21].

(3) Further questionable statements.

According to the authors, the “ClearView system taps into the global electromagnetic holographic communication system via the fingertips.” Neither give the authors an explanation what they mean with the term “global electromagnetic holographic communication system” nor do they refer to scientific literature that supports their statement.

Also the authors state that it “has been scientifically proven that every cell in the body emits more than 100,000 light impulses or photons per second.” This statement is inconsistent with the earlier statement that “biophoton emission is described to be less than 1000 photons per second per cm”. Additionally that statement contains incorrect units (it should be “per cm²”).In addition the authors state that the “biophotons”, they are allegedly measuring, “have been found to be the steering mechanism behind all biochemical reactions.” Whereas there are indeed theories linking UPE to physiological functions (i.e., delivering activation energy for biochemical reactions and coordinating them) these concepts are based on theoretical work (e.g., [22]) and there exist no scientific consensus regarding this issue at present.

(4) Flaws in the studies experimental design and statistical analysis.

Although the results presented by the authors are interesting, according to our view they should be regarded with caution because of the following reasons:

(a) A case-control study must ensure that the characteristics of the investigated populations (cases and controls) are similar, i.e. the populations should be age-matched and the number of subjects should be approximately the same [23]. Both conditions seem to be not fulfilled in the study of Rizzo et al. According to the authors the “age of cardiovascular subjects was 64.22 (95%CI: 62.44, 65.99) and the mean age of controls was 44.14 (95% CI: 40.73, 47.55).” That the age is a confounder was even found by the authors using the statistical analysis (i.e., OR for cardiovascular disease without considering age: 4.03 (2.71, 6.00), OR with age as a confounder: OR: 3.44 (2.13-5.55)). Additionally, the sample sizes were different (n = 195 vs. n = 64).

(b) The authors state the studies aim was to “indicate the presence or absence of cardiovascular disease”. For such an assessment the calculation of the odds ratios are not sufficient since they give only information about the prevalence, whereas the sensitivity and specificity are important factors to determine if a biomarker is useful for diagnostic purposes [24]. Such an analysis is classically performed by calculating the receiver operating characteristic (ROC) curves and quantifying them. Unfortunately, this kind of analysis is not reported by the authors in the manuscript. However, in the patent application (from which the results of the study were taken), ROC curves were given [25].

(c) Another important factor in showing the usefulness of the proposed novel diagnostic approach is to show the reproducibility of the measurement. The authors report that “a second measurement session was done 3-5 minutes after the first one was completed” in order to “assess the reproducibility and variability of the measurements”. However, we cannot find the results of this assessment in the published paper.

Felix Scholkmann^1, ^2, Michal Cifra³

¹ Biomedical Optics Research Laboratory, Division of Neonatology, University Hospital Zurich, 8091 Zurich, Switzerland

² Research Office of Complex Physical and Biological Systems (ROCoS), 8038 Zurich, Switzerland

³ Institute of Photonics and Electronics, The Czech Academy of Sciences, 18200 Prague, Czech Republic