[1] M. Morán, D. Moreno-Lastres, L. Marín-Buera, J. Arenas, M. A. Martín, C. Ugalde. Mitochondrial respiratory chain dysfunction: Implications in neurodegeneration. Free Radic. Biol. Med., 53, 595-609(2012).
[2] I. Georgakoudi, K. P. Quinn. Optical imaging using endogenous contrast to assess metabolic state. Annu. Rev. Biomed. Eng., 14, 351-367(2012).
[3] K. Alhallak, L. G. Rebello, T. J. Muldoon, K. P. Quinn, N. Rajaram. Optical redox ratio identifies metastatic potential-dependent changes in breast cancer cell metabolism. Biomed. Opt. Exp., 7, 4364-4374(2016).
[4] J. S. Baker, M. C. McCormick, R. A. Robergs. Interaction among skeletal muscle metabolic energy systems during intense exercise. J. Nutr. Metab., 2010, 905612(2010).
[5] J. Zheng. Energy metabolism of cancer: Glycolysis versus oxidative phosphorylation (Review). Oncol. Lett., 4, 1151-1157(2012).
[6] B. Egan, J. R. Zierath. Exercise metabolism and the molecular regulation of skeletal muscle adaptation. Cell Metab., 17, 162-184(2013).
[7] R. J. DeBerardinis, C. B. Thompson. Cellular metabolism and disease: What do metabolic outliers teach us?. CellPress, 148, 1132-1144(2012).
[8] M. T. Lewis, J. D. Kasper, J. N. Bazil, J. C. Frisbee, R. W. Wiseman. Quantification of mitochondrial oxidative phosphorylation in metabolic disease: Application to type 2 diabetes. Int. J. Mol. Sci., 20, 5271(2019).
[9] E. P. Widmaier, S. Vander Luciano. Human Physiology: The Mechanisms of Body Function(2004).
[10] L. D. Osellame, T. S. Blacker, M. R. Duchen. Cellular and molecular mechanisms of mitochondrial function. Best. Pract. Res. Clin. Endocrinol., 26, 711-723(2012).
[11] E. A. Shoubridge. Supersizing the mitochondrial respiratory chain. Cell Metab., 15, 271-272(2012).
[12] E. Lapuente-Brun, R. Moreno-Loshuertos, R. Acín-Pérez, A. Latorre-Pellicer, C. Colás, E. Balsa, E. Perales-Clemente, P. M. Quirós, E. Calvo, M. A. Rodríguez-Hernández, P. Navas, R. Cruz, A.́ Carracedo, C. López-Otín, A. Pérez-Martos, P. Fernández-Silva, E. Fernández-Vizarra, J. A. Enríquez. “Supercomplex assembly determines electron flux in the mitochondrial electron transport chain,”. Science, 340, 1567-1570(2013).
[13] R. M. Stroud. Balancing ATP in the cell. Nat. Struct. Biol., 3, 567-569(1996).
[14] J. Berg, Y. P. Hung, G. Yellen. A genetically encoded fluorescent reporter of ATP:ADP ratio. Nat. Methods, 6, 161-166(2009).
[15] B. S. Khakh, G. Burnstock. The double life of ATP. Sci. Am., 301, 84-90(2009).
[16] H. Imamura, K. P. Huynh Nhat, H. Togawa, K. Saito, R. Iino, Y. Kato-Yamada, T. Nagai, H. Noji. Visualization of ATP levels inside single living cells with fluorescence resonance energy transfer-based genetically encoded indicators. Proc. Natl. Acad. USA, 106, 15651-15656(2009).
[17] O. I. Kolenc, K. P. Quinn. Evaluating cell metabolism through autofluorescence imaging of NAD(P)H and FAD. Antioxid. Redox Signal., 30, 875-889(2019).
[18] B. Chance, B. Schoener, R. Oshino, F. Itshak, Y. Nakase. Oxidation reduction ratio studies of mitochondria in freeze-trapped samples. NADH and flavoprotein fluorescence signals. J. Biol. Chem., 254, 4764-4771(1979).
[19] C. H. Barlow, B. Chance. Ischemic areas in perfused rat hearts: measured by NADH fluorescence photography. Science, 193, 909-910(1976).
[20] B. Chance, V. Legallais, J. Sorge, N. Graham. A versatile time-sharing multichannel spectrophotometer, reflectometer, and fluorometer. Anal. Biochem., 66, 498-514(1975).
[21] B. Chance, S. Nioka, J. Kent, K. McCully, M. Fountain, R. Greenfeld, G. Holtom. Time-resolved spectroscopy of hemoglobin and myoglobin in resting and ischemic muscle. Anal. Biochem., 174, 698-707(1988).
[22] A. Villringer, B. Chance. Non-invasive optical spectroscopy and imaging of human brain function. Trends Neurosci., 20, 435-442(1997).
[23] K. P. Quinn, G. V. Sridharan, R. S. Hayden, D. L. Kaplan, K. Lee, I. Georgakoudi. Quantitative metabolic imaging using endogenous fluorescence to detect stem cell differentiation. Sci. Rep., 3, 3432(2013).
[24] H. B. S. Griffiths, C. Williams, S. J. King, S. J. Allison. Nicotinamide adenine dinucleotide (NAD+): Essential redox metabolite, co-substrate and an anti-cancer and anti-ageing therapeutic target. Biochem. Soc. Trans., 48, 733-744(2020).
[25] B. R. Masters, P. T. C. So, E. Gratton. Optical biopsy of in vivo human skin multiphoton excitation microscopy. Lasers Med. Sci., 13, 196-203(1998).
[26] J. D. Jones, H. E. Ramser, A. E. Woessner, A. Veves, K. P. Quinn. Quantifying Age-related changes in skin wound metabolism using in vivo multiphoton microscopy. Adv. Wound Care, 9, 90-102(2020).
[27] M. Lukina, A. Orlova, M. Shirmanova, D. Shirokov, A. Pavlikov, A. Neubauer, H. Studier, W. Becker, E. Zagaynova, T. Yoshihara, S. Tobita, V. Shcheslavskiy. Interrogation of metabolic and oxygen states of tumors with fiber-based luminescence lifetime spectroscopy. Opt. Lett., 42, 731-734(2017).
[28] P. M. Schaefer, S. Kalinina, A. Rueck, C. A. F. von Arnim, B. von Einem. NADH autofluorescence: A marker on its way to boost bioenergetic research. Cytometry A, 95, 34-46(2019).
[29] J. Deal, S. Mayes, C. Browning, S. Hill, P. Rider, C. Boudreaux, T. C. Rich, S. J. Leavesley. Identifying molecular contributors to autofluorescence of neoplastic and normal colon sections using excitation-scanning hyperspectral imaging. J. Biomed. Opt., 24, 1-11(2018).
[30] H. Westerblad, J. D. Bruton, A. Katz. Skeletal muscle: Energy metabolism, fiber types, fatigue. Exp. Cell Res., 316, 3093-3099(2010).
[31] M. Müller, M. Mentel, J. J. van Hellemond, K. Henze, C. Woehle, S. B. Gould, R.-Y. Yu, M. van der Giezen, A. G. M. Tielens, W. F. Martin. Biochemistry and evolution of anaerobic energy metabolism in eukaryotes. Microbiol. Mol. Biol. Rev., 76, 444-495(2012).
[32] M. Ahmad, A. Wolberg, C. I. Kahwaji. Biochemistry, Electron Transport Chain(2022).
[33] J. T. Kim, B. M. Kasukonis, L. A. Brown, T. A. Washington, J. C. Wolchok. Recovery from volumetric muscle loss injury: A comparison Between young and aged rats. Exp. Gerontol., 83, 37-46(2016).
[34] B. Kasukonis, J. Kim, L. Brown, J. Jones, S. Ahmadi, T. Washington, J. Wolchok. Codelivery of Infusion Decellularized skeletal muscle with minced muscle autographs improved recovery from volumetric muscle loss injury in a rat model. Tissue Eng. A, 22, 1151-1163(2016).
[35] X. Wu, B. T. Corona, X. Chen, T. J. Walters. A standardized rat model of volumetric muscle loss injury for the development of tissue engineering therapies. Biores. Open Access, 1, 280-290(2012).
[36] T. A. Washington, R. A. Perry, J. T. Kim, W. S. Haynie, N. P. Greene, J. C. Wolchok. The effect of autologous repair and voluntary wheel running on torque recovery in a rat model of volumetric muscle loss. Exp. Physiol., 106, 994-1004(2021).
[37] V. V. Ghukasyan, F.-J. Kao. Monitoring cellular metabolism with fluorescence lifetime of reduced nicotinamide adenine dinucleotide. J. Phys. Chem. C, 113, 11532-11540(2009).
[38] T. S. Blacker, R. J. Marsh, M. R. Duchen, A. J. Bain. Activa-ted barrier crossing dynamics in the non-radiative decay of NADH and NADPH. Chem. Phys., 422, 184-194(2013).
[39] G. Cui, S. B. Jun, X. Jin, G. Luo, M. D. Pham, D. M. Lovinger, S. S. Vogel, R. M. Costa. Deep brain optical measurements of cell type—specific neural activity in behaving mice. Nat. Protoc., 9, 1213-1228(2014).
[40] G. Cui, S. B. Jun, X. Jin, G. Luo, M. D. Pham, S. S. Vogel, D. M. Lovinger, R. M. Costa. Concurrent activation of striatal direct and indirect pathways during action initiation. Nature, 494, 238-242(2013).
[41] D. Duboc, M. Muffat-Joly, G. Renault, M. Degeorges, M. Toussaint, J. J. Pocidalo. In situ NADH laser fluorimetry of rat fast- and slow-twitch muscles during tetanus. J. Appl. Physiol., 64, 2692-2695(1988).
[42] Y. Chen, Q. Yu, C.-B. Xu. A convenient method for quantifying collagen fibers in atherosclerotic lesions by ImageJ software. Int. J. Clin. Exp. Med., 10, 14904-14910(2017).
[43] S. Wichaiyo, S. Lax, S. J. Montague, Z. Li, B. Grygielska, J. A. Pike, E. J. Haining, A. Brill, S. P. Watson, J. Rayes. Platelet glycoprotein VI and C-type lectin-like receptor 2 deficiency accelerates wound healing by impairing vascular integrity in mice. Platelet Biol. Disord., 104, 1648-1660(2019).
[44] A. Rudkouskaya, J. T. Smith, X. Intes, M. Barroso. Quantification of Trastuzumab-HER2 engagement in vitro and in vivo. Molecules, 25, 5976(2020).
[45] D. Llères, S. Swift, A. I. Lamond. Detecting protein-protein interactions in vivo with FRET using multiphoton fluorescence lifetime imaging microscopy (FLIM). Curr. Protocols Cytom., 42, 12.10.1-12.10.10(2007).
[46] H. E. Schepers, J. H. G. M. van Beek, J. B. Bassingthwaighte. Four methods to estimate the fractal dimension from self-affine signals. IEEE Eng. Med. Biol. Mag., 11, 57-64(1992).
[47] D. W. Repperger, K. A. Farris, C. C. Barton, S. F. Tebbens. Time series data analysis using fractional calculus concepts and fractal analysis. IEEE Int. Conf. Systems, Man and Cybernetics, 3311-3315(2009).
[48] T. Higuchi. Approach to an irregular time series on the basis of the fractal theory. Physica D: Nonlinear Phenomena, 31, 277-283(1998).
[49] T. S. Blacker, M. R. Duchen. Investigating mitochondrial redox state using NADH and NADPH autofluorescence. Free Radic. Biol. Med., 100, 53-65(2016).
[50] M. C. Skala, K. M. Riching, A. Gendron-Fitzpatrick, J. Eickhoff, K. W. Eliceiri, J. G. White, N. Ramanujam. In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proc. Natl. Acad. Sci., 104, 19494-19499(2007).
[51] K. E. Conley, W. F. Kemper, G. J. Crowther. Limits to sustainable muscle performance: Interaction between glycolysis and oxidative phosphorylation. J. Exp. Biol., 204, 3189-3194(2001).
[52] M. Sekine, T. Tamura, M. Akay, T. Fujimoto, T. Togawa, Y. Fukui. Discrimination of walking patterns using wavelet-based fractal analysis. IEEE Trans. Neural Syst. Rehabil. Eng., 10, 188-196(2002).
[53] S. A. Eming, T. A. Wynn, P. Martin. Inflammation and metabolism in tissue repair and regeneration. Science, 356, 1026-1030(2017).
[54] G. Soto-Heredero, M. M. Gómez de las Heras, E. Gabandé-Rodríguez, J. Oller, M. Mittelbrunn. Glycolysis — a key player in the inflammatory response. FEBS J., 287, 3350-3369(2020).
[55] C. Smith, M. J. Kruger, R. M. Smith, K. H. Myburgh. The inflammatory response to skeletal muscle injury. Sports Med., 38, 947-969(2008).
[56] K. Ohlendieck. Proteomics of skeletal muscle glycolysis. Biochim. Biophys. Acta (BBA) — Proteins Proteomics, 1804, 2089-2101(2010).
[57] A. Torrelo, I. Colmenero, L. Requena, A. S. Paller, Y. Ramot, C.-C. R. Lee, A. Vera, A. Zlotogorski, R. Goldbach-Mansky, H. Kutzner. The histological and immunohistochemical features of the skin lesions in CANDLE syndrome. Am. J. Dermatopathol., 37, 517-522(2015).
[58] A. Viola, F. Munari, R. Sanchez-Rodriguez, T. Scolaro, A. Castegna. Metabolic signature of macrophage responses. Front. Immunol., 10, 1462(2019).
[59] Y.-F. Chen, C.-W. Lee, H.-H. Wu, W.-T. Lin, O. K. Lee. Immunometabolism of macrophages regulates skeletal muscle regeneration. Front. Cell Dev. Biol., 10, 948819(2022).
[60] A. L. Goldberger, L. A. N. Amaral, J. M. Hausdorff, P. C. Ivanov, C.-K. Peng, H. E. Stanley. Fractal dynamics in physiology: Alterations with disease and aging. Proc. Natl. Acad. Sci., 99, 2466-2472(2002).
[61] S. Spasic, A. Kalauzi, G. Grbic, L. Martac, M. Culic. Fractal analysis of rat brain activity after injury. Med. Biol. Eng. Comput., 43, 345-348(2005).
[62] C. Lenz, A. Rebel, K. van Ackern, W. Kuschinsky, K. Waschke. Local cerebral blood flow, local cerebral glucose utilization, and flow-metabolism coupling during sevoflurane versus isoflurance anesthesia in rats. Anesthesiology, 89, 1480-1488(1998).
[63] M. Maciejewski, H Qui, I. Rujan, M. Mobli, J. Hoch. Nonuniform sampling and spectral aliasing. J. Magn. Reson., 199, 1090-7807(2009).
[64] S. Luo, P. Johnston. A review of electrocardiogram filtering. J. Electrocardiol., 43, 486-496(2010).
[65] M. Seeck, L. Koessler, T. Bast, F. Leijten, C. Michel, C. Baumgartner, B. He, S. Beniczky. The standardized EEG electrode array of the IFCN. Clin. Neurophysiol., 128, 2070-2077(2017).
[66] G. Yang, S. Yu, H. Dong, G. Slabaugh, P. Dragotti, X. Ye, F. Liu, S. Arridge, J. Keegan, Y. Guo, D. Firmin. DAGAN: Deep de-aliasing generative adversarial networks for fast compressed sensing MRI reconstruction. IEEE Trans. Med. Imaging, 37, 1310-1321(2018).
[67] I. Gorbunova, M. Sasin, J. Rubayo-Soneira, A. Smolin, O. Vasyutinskii. Two-photon excited fluorescence dynamics in NADH in water-mathanol solutions: The role of conformation states. J. Phys. Chem., 124, 10682-10697(2020).
[68] A. Belashov, A. Zhikhoreva, A. Salova, T. Belyaeva, I. Litvinov, E. Kornilova, I. Semenova, O. Vasyutinskii. Analysis of Radachlorin localization in living cells by fluorescence lifetime imaging microscopy. J. Photochem. Photobiol., B Biol., 243, 112699(2023).