Visible Blue Light Therapy: Molecular Mechanisms and Therapeutic Opportunities.

BACKGROUND: Visible light is absorbed by photoacceptors in pigmented and non-pigmented mammalian cells, activating signaling cascades and downstream mechanisms that lead to the modulation of cellular processes. Most studies have investigated the molecular mechanisms and therapeutic applications of UV and the red to near infrared regions of the visible spectrum. Considerably less effort has been dedicated to the blue, UV-free part of the spectrum. OBJECTIVE: In this review, we discuss the current advances in the understanding of the molecular photoacceptors, signaling mechanisms, and corresponding therapeutic opportunities of blue light photoreception in non-visual mammalian cells in the context of inflammatory skin conditions. METHODS: The literature was scanned for peer-reviewed articles focusing on the molecular mechanisms, cellular effects, and therapeutic applications of blue light. RESULTS: At a molecular level, blue light is absorbed by flavins, porphyrins, nitrosated proteins, and opsins; inducing the generation of ROS, nitric oxide release, and the activation of G protein coupled signaling. Limited and contrasting results have been reported on the cellular effects of blue light induced signaling. Some investigations describe a regulation of proliferation and differentiation or a modulation of inflammatory parameters; others show growth inhibition and apoptosis. Regardless of the elusive underlying mechanism, clinical studies show that blue light is beneficial in the treatment of inflammatory skin conditions. CONCLUSION: To strengthen the use of blue light for therapeutic purposes, further in depth studies are clearly needed with regard to its underlying molecular and cellular mechanisms, and their translation into clinical applications.

Altered Energetics of Exercise Explain Risk of Rhabdomyolysis in Very Long-Chain Acyl-CoA Dehydrogenase Deficiency.

Rhabdomyolysis is common in very long-chain acyl-CoA dehydrogenase deficiency (VLCADD) and other metabolic myopathies, but its pathogenic basis is poorly understood. Here, we show that prolonged bicycling exercise against a standardized moderate workload in VLCADD patients is associated with threefold bigger changes in phosphocreatine (PCr) and inorganic phosphate (Pi) concentrations in quadriceps muscle and twofold lower changes in plasma acetyl-carnitine levels than in healthy subjects. This result is consistent with the hypothesis that muscle ATP homeostasis during exercise is compromised in VLCADD. However, the measured rates of PCr and Pi recovery post-exercise showed that the mitochondrial capacity for ATP synthesis in VLCADD muscle was normal. Mathematical modeling of oxidative ATP metabolism in muscle composed of three different fiber types indicated that the observed altered energy balance during submaximal exercise in VLCADD patients may be explained by a slow-to-fast shift in quadriceps fiber-type composition corresponding to 30% of the slow-twitch fiber-type pool in healthy quadriceps muscle. This study demonstrates for the first time that quadriceps energy balance during exercise in VLCADD patients is altered but not because of failing mitochondrial function. Our findings provide new clues to understanding the risk of rhabdomyolysis following exercise in human VLCADD.

Combined in vivo and in silico investigations of activation of glycolysis in contracting skeletal muscle.

The hypothesis was tested that the variation of in vivo glycolytic flux with contraction frequency in skeletal muscle can be qualitatively and quantitatively explained by calcium-calmodulin activation of phosphofructokinase (PFK-1). Ischemic rat tibialis anterior muscle was electrically stimulated at frequencies between 0 and 80 Hz to covary the ATP turnover rate and calcium concentration in the tissue. Estimates of in vivo glycolytic rates and cellular free energetic states were derived from dynamic changes in intramuscular pH and phosphocreatine content, respectively, determined by phosphorus magnetic resonance spectroscopy ((31)P-MRS). Computational modeling was applied to relate these empirical observations to understanding of the biochemistry of muscle glycolysis. Hereto, the kinetic model of PFK activity in a previously reported mathematical model of the glycolytic pathway (Vinnakota KC, Rusk J, Palmer L, Shankland E, Kushmerick MJ. J Physiol 588: 1961-1983, 2010) was adapted to contain a calcium-calmodulin binding sensitivity. The two main results were introduction of regulation of PFK-1 activity by binding of a calcium-calmodulin complex in combination with activation by increased concentrations of AMP and ADP was essential to qualitatively and quantitatively explain the experimental observations. Secondly, the model predicted that shutdown of glycolytic ATP production flux in muscle postexercise may lag behind deactivation of PFK-1 (timescales: 5-10 s vs. 100-200 ms, respectively) as a result of accumulation of glycolytic intermediates downstream of PFK during contractions.

Computational modeling of mitochondrial energy transduction.

Mitochondria are the power plant of the heart, burning fat and sugars to supply the muscle with the adenosine triphosphate (ATP) free energy that drives contraction and relaxation during each heart beat. This function was first captured in a mathematical model in 1967. Today, interest in such a model has been rekindled by ongoing in silico integrative physiology efforts such as the Cardiac Physiome project. Here, the status of the field of computational modeling of mitochondrial ATP synthetic function is reviewed.

The use of a reference tissue arterial input function with low-temporal-resolution DCE-MRI data.

Pharmacokinetic modeling is a promising quantitative analysis technique for cancer diagnosis. However, diagnostic dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast is commonly performed with low temporal resolution. This limits its clinical utility. We investigated for a range of temporal resolutions whether pharmacokinetic parameter estimation is impacted by the use of data-derived arterial input functions (AIFs), obtained via analysis of dynamic data from a reference tissue, as opposed to the use of a standard AIF, often obtained from the literature. We hypothesized that the first method allows the use of data at lower temporal resolutions than the second method. Test data were obtained by downsampling high-temporal-resolution rodent data via a k-space-based strategy. To fit the basic Tofts model, either the data-derived or the standard AIF was used. The resulting estimates of K(trans) and v(e) were compared with the standard estimates obtained by using the original data. The deviations in K(trans) and v(e), introduced when lowering temporal resolution, were more modest using data-derived AIFs compared with using a standard AIF. Specifically, lowering the resolution from 5 to 60 s, the respective changes in K(trans) were 2% (non-significant) and 18% (significant). Extracting the AIF from a reference tissue enables accurate pharmacokinetic parameter estimation for low-temporal-resolution data.

System identification theory in pharmacokinetic modeling of dynamic contrast-enhanced MRI: influence of contrast injection.

Optimization of experimental settings of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), like the contrast administration protocol, is of great importance for reliable quantification of the microcirculatory properties, such as the volume transfer-constant K(trans). Using system identification theory and computer simulations, the confounding effects of volume, rate and multiplicity of a contrast injection on the reliability of K(trans) estimation was assessed. A new tracer-distribution model (TDM), based on in vivo data from rectal cancer patients, served to describe the relationship between the contrast agent injection and the blood time-course. A pharmacokinetic model (PKM) was used to describe the relation between the blood and tumor tissue time-courses. By means of TDM and PKM in series, the tissue-transfer function of the PKM was analyzed. As both the TDM and PKM represented low-frequency-pass filters, the energy-density at low frequencies of the blood and tissue time-courses was larger than at high frequencies. The simulations, based on measurements in humans, predict that the K(trans) is most reliable with a high injection volume administered in a single injection, where high rates only modestly improve K(trans).

Computational model of excitable cell indicates ATP free energy dynamics in response to calcium oscillations are undampened by cytosolic ATP buffers.

Mitochondria in excitable cells are recurrently exposed to pulsatile calcium gradients that activate cell function. Rapid calcium uptake by the mitochondria has previously been shown to cause uncoupling of oxidative phosphorylation. To test (i) if periodic nerve firing may cause oscillation of the cytosolic thermodynamic potential of ATP hydrolysis and (ii) if cytosolic adenylate (AK) and creatine kinase (CK) ATP buffering reactions dampen such oscillations, a lumped kinetic model of an excitable cell capturing major aspects of the physiology has been developed. Activation of ATP metabolism by low-frequency calcium pulses caused large oscillation of the cytosolic, but not mitochondrial ATP/ADP, ratio. This outcome was independent of net ATP synthesis or hydrolysis during mitochondrial calcium uptake. The AK/CK ATP buffering reactions dampened the amplitude and rate of cytosolic ATP/ADP changes on a timescale of seconds, but not milliseconds. These model predictions suggest that alternative sources of capacitance in neurons and striated muscles should be considered to protect ATP-free energy-driven cell functions.

Identifiability analysis of the standard pharmacokinetic models in DCE MR imaging of tumours.

The usage of dynamic contrast-enhanced MRI (DCE-MRI) as a clinical tool is still widely assessed. Application of the standard pharmacokinetic models to obtain physiologically relevant parameter values using DCE-MRI in tumours is not trivial, when the temporal resolution is low. Mathematical analysis and analysis by simulation of the identifiability for the generalized and extended Kety models was executed. Parameter estimation was executed using synthetic data sets and maximum likelihood estimation (MLE). The influence of temporal resolution was examined. The generalized and extended Kety model showed a large bias in the parameter estimates (10-120%) for sampling times >4 s, although the estimated variance was relatively low (<1%). This was in accordance with the generated contour plots of the hyperplane of the MLE cost-function. The influence of measurement noise on the input and output turned out to be less significant than the temporal resolution.