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Background: The human heart rhythm can be quantified by analyzing the heart rate variability (HRV). A major influencing factor of the HRV is the circadian rhythm. The ocular light and the hormone melatonin play decisive roles in the circadian rhythm.The beat rate variability (BRV) is considered to be the in vitro equivalent of the HRV. Previous studies have demonstrated the influence of melatonin on cardiomyocytes. Also, the influence of light on cardiomyocytes has been described before. Nevertheless, the effect of light on the BRV of cardiomyocytes has not yet been examined. Material and methods: The BRV of spontaneously beating cardiomyocytes was measured with microelectrode arrays over a time period of 30 min. The experiments were either performed with light exposure (with and without an infrared filter) or in complete darkness. Results: The BRV was higher and the beating frequency was lower when the cardiomyocytes were exposed to the full spectrum of light, compared to the measurements in darkness as well as to the measurements with an infrared filter. In contrast, the differences of BRV between the measurements in darkness and the measurements with an infrared filter were not as distinct. Conclusions: This is the first study demonstrating the influence of light on the beating rhythm of heart tissue in vitro. The results indicate that especially the infrared spectrum of light alters the BRV. These findings could be of interest for clinical applications such as the field of optical pacing as well as in neonatal patient care.

ObjectiveLiver cancer is one of the most commonly diagnosed cancer, and energy-based tumor ablation is a widely accepted treatment. Automatic and robust segmentation of liver tumors and ablation zones would facilitate the evaluation of treatment success. The purpose of this study was to develop and evaluate an automatic deep learning based method for (1) segmentation of liver and liver tumors in both arterial and portal venous phase for pre-treatment CT, and (2) segmentation of liver and ablation zones in both arterial and portal venous phase for after ablation treatment.Materials and Methods252 CT images from 63 patients undergoing liver tumor ablation at a large University Hospital were retrospectively included; each patient had pre-treatment and post-treatment multi-phase CT images. 3D voxel-wise manual segmentation of the liver, tumors and ablation region by the radiologist provided reference standard. Deep learning models for liver and lesion segmentation were initially trained on the public Liver Tumor Segmentation Challenge (LiTS) dataset to obtain base models. Then, transfer learning was applied to adapt the base models on the clinical training-set, to obtain tumor and ablation segmentation models both for arterial and portal venous phase images. For modeling, 2D residual-attention Unet (RA-Unet) was employed for liver segmentation and a multi-scale patch-based 3D RA-Unet for tumor and ablation segmentation.ResultsOn the independent test-set, the proposed method achieved a dice similarity coefficient (DSC) of 0.96 and 0.95 for liver segmentation on arterial and portal venous phase, respectively. For liver tumors, the model on arterial phase achieved detection sensitivity of 71%, DSC of 0.64, and on portal venous phase sensitivity of 82%, DSC of 0.73. For liver tumors >0.5cm3 performance improved to sensitivity 79%, DSC 0.65 on arterial phase and, sensitivity 86%, DSC 0.72 on portal venous phase. For ablation zone, the model on arterial phase achieved detection sensitivity of 90%, DSC of 0.83, and on portal venous phase sensitivity of 90%, DSC of 0.89.ConclusionThe proposed deep learning approach can provide automated segmentation of liver tumors and ablation zones on multi-phase (arterial and portal venous) and multi-time-point (before and after treatment) CT enabling quantitative evaluation of treatment success.

Background In healthy individuals, a major factor influencing the heart rate variability (HRV) is the circadian rhythm. The role of melatonin as an essential component of the circadian rhythm in the adult human organism and the beneficial effects of a treatment with melatonin during the fetal period is well described. Toxic effects of melatonin are discussed less frequently. Since pharmacological studies cannot be carried out on pregnant women, the establishment of an equivalent in vitro model is important. We therefore tested whether melatonin can influence the beat rate variability (BRV) of spontaneously beating cardiomyocytes derived from murine embryonic stem cells (mESCs) and whether melatonin exhibits toxic effects in this in vitro model. Methods Microelectrode Arrays recorded extracellular field potentials of spontaneously beating cardiomyocytes. Melatonin was applied in a concentration range from 10−11 M to 10–5 M. The analysis of the BRV focused on time domain methods. Results In line with clinical observations, melatonin decreased the beating frequency and increased the BRV. The effect of melatonin up to a concentration of 10−6 M was reversible, whereas the application of higher concentrations induced an irreversible effect. Conclusion The study underlines the potential of this in vitro model to help explore the development of circadian rhythms and their modulation by melatonin in the embryonic phase. The results imply that melatonin influences the heart rhythm as early as during the embryonic heart development. Furthermore, the results indicate a potentially toxic effect of melatonin that has not been described in detail before.

Das Lungenkarzinom ist eine der haufigsten Krebserkrankungen des Menschen. Die komplexen und haufig multimodalen Therapiekonzepte dieses Krankheitsbildes setzen eine exakte Klassifikation jedes Tumors anhand von Tumorgrose (T), Lymphknotenstatus (N) und Fernmetastasen (M) voraus. Die TNM-Klassifikation fur Lungentumoren ist von der International Association for the Study of Lung Cancer (IASLC) kurzlich in der 8. Auflage veroffentlicht worden. Lung cancer is one of the most common cancers in humans. The complex and often multimodal therapy concepts of this disease require a precise classification of each tumour on the basis of tumour size (T), lymph node status (N) and distant metastases (M). The 8th edition of the TNM classification for lung cancer, that was recently published by the International Association for the Study of Lung Cancer (IASLC), is presented with regard to the radiological staging.

Embryonic stem cell (ESC) derived tissue is a promising tool to be used in different clinical, preclinical and also scientific settings, for example as in vivo biological pacemaker, preclinical drug safety screening tool or ultimately as part of a cell replacement therapy. However, before ESC derived tissue can be used routinely for these purposes in humans, further studies are needed. In this context, the aims of the present study were to examine the effect of antiarrhythmic drugs on human ESC (hESC) und human induced pluripotent stem cell (hiPSC) derived cardiomyocytes by analyzing the beat rate variability (BRV), which can be considered as the in vitro equivalent of the heart rate variability (HRV) in vivo. Short-term recordings of extracellular field potentials of spontaneously beating cardiomyocytes derived from hESCs and hiPSCs were made using Microelectrode Arrays (MEA). The effect of Flecainide, Ivabradine and Metoprolol was tested. The offline analysis of the BRV was mainly focused on time domain methods. Additionally a non-linear analysis method was used. The evaluation of the Poincaré-Plots of the measurements without pharmacological intervention revealed that the vast majority of the scatter plots have a similar, ellipsoid shape. Flecainide and Ivabradine influenced BRV parameters significantly, whereas Metoprolol did not alter the BRV markedly. We detected remarkable similarities between the BRV of hESC and hiPSC derived cardiomyocytes in vitro and the HRV in vivo. The effect of antiarrhythmic drugs on spontaneously beating cardiomyocytes derived from hESC and hiPSC was generally consistent with clinical experiences and also with our previous study based on murine ESC derived cardiomyocytes. In conclusion, our study points out the great potential of hESC and hiPSC derived tissue to be used routinely for many different applications in medicine and science.

Objectives To investigate whether virtual monoenergetic images (VMI) and iodine maps derived from spectral detector computed tomography (SDCT) improve early assessment of technique efficacy in patients who underwent microwave ablation (MWA) for hepatocellular carcinoma (HCC) in liver cirrhosis. Methods This retrospective study comprised 39 patients with 49 HCC lesions treated with MWA. Biphasic SDCT was performed 7.7±4.0 days after ablation. Conventional images (CI), VMI and IM were reconstructed. Signal- and contrast-to-noise ratio (SNR, CNR) in the ablation zone (AZ), hyperemic rim (HR) and liver parenchyma were calculated using regions-of-interest analysis and compared between CI and VMI between 40–100 keV. Iodine concentration and perfusion ratio of HR and residual tumor (RT) were measured. Two readers evaluated subjective contrast of AZ and HR, technique efficacy (complete vs. incomplete ablation) and diagnostic confidence at determining technique efficacy. Results Attenuation of liver parenchyma, HR and RT, SNR of liver parenchyma and HR, CNR of AZ and HR were significantly higher in low-keV VMI compared to CI (all p50keV improved subjective AZ-to-liver contrast, HR-to-liver contrast, visualization of AZ margin and vessels adjacent to AZ compared to CI (all p50keV compared to CI (0.92 vs. 0.89), while diagnostic confidence was significantly higher in VMI50keV (p Conclusions Spectral detector computed tomography derived low-keV virtual monoenergetic images and iodine maps provide superior early assessment of technique efficacy of MWA in HCC compared to CI.

Background/Aims: Heart rate variability (HRV) refers to the fluctuation of the time interval between consecutive heartbeats in humans. It has recently been discovered that cardiomyocytes derived from human embryonic and induced pluripotent stem cells show beat rate variability (BRV) that is similar to the HRV in humans. In the present study, clinical aspects of HRV were transferred to an in vitro model. The aims of the study were to explore the BRV in murine embryonic stem cell (mESC)-derived cardiomyocytes and to demonstrate the influence of antiarrhythmic drugs on BRV as has been shown in clinical trials previously. Methods: The Microelectrode Array (MEA) technique was used to perform short-term recordings of extracellular field potentials (FPs) of spontaneously beating cardiomyocytes derived from mESCs (D3 cell line, αPig-44). Offline analysis was focused on time domain and nonlinear methods. Results: The Poincaré-Plot analysis of measurements without pharmacological intervention revealed that three different shapes of scatter plots occurred most frequently. Comparable shapes have been described in clinical studies before. The antiarrhythmic drugs Ivabradine, Verapamil and Sotalol augmented BRV, whereas Flecainide decreased BRV parameters at low concentrations (SDSD 79.0 ± 8.7% of control at 10-9 M, p < 0.05) and increased variability measures at higher concentrations (SDNN 258.8 ± 42.7% of control at 10-5 M, p < 0.05). Amiodarone and Metoprolol did not alter BRV significantly. Conclusions: Spontaneously beating cardiomyocytes derived from mESCs showed BRV that appears to be similar to the HRV known from humans. Antiarrhythmic drugs affected BRV parameters similar to clinical observations. Therefore, our study demonstrates that this in vitro model can contribute to a better understanding of electrophysiological properties of mESC-derived cardiomyocytes and might serve as a valuable tool for drug safety screening.