Evaluation of the Storage Stability and Quality Properties of Fresh Noodles Mixed with Plasma-Activated Water

Enhancing the quality retention of fresh noodles remains challenging. In this study, we investigated the effect of dough mixing with plasma-activated water (PAW) of different activation times on the storage stability and quality characteristics of fresh noodles. It was found that the total plate count in the fresh noodles prepared by PAW (PAWN) showed no obvious inhibition during storage at 25 °C, but could be significantly reduced at 4 °C as compared with the control. The decrease in L* value and pH of the PAWN was significantly retarded during storage, indicating an enhanced storage stability. The stability time of dough mixed with PAW could be significantly improved. PAW treatment decreased the viscosity properties and setback value of starch, while enhancing the interaction of water and non-water components in fresh noodles. In addition, dynamic polymerization and depolymerization of proteins were detected in Size-Exclusion High-Performance Liquid Chromatography (SE-HPLC) profiles of PAWN. The hardness and adhesiveness of the cooked noodles decreased, while the springiness significantly increased. These results implied the potential of PAW in improving the storage stability and quality of fresh noodles.

Electromyographic Determination of Jump Landing Sequence and Pre-activation Times During One-foot Landing

Introduction: Monopodal jumping is a common gesture in daily life and sports. In the Landing Phase (LF), potential energy is absorbed from the tridimensional stability of the Lower Limb (LH). This stability depends on neuromuscular strategies that include factors such as Muscle Preactivation Times (MAT) and the Sequence of Participation (SP) of the muscle groups. The alteration of TPA has been pointed out as a factor of possible injury. The aim of this study was to determine the preactivation times and participation sequence of the gluteus medius, adductor magnus, rectus femoris, vastus medialis quadriceps, biceps femoris longus, semimembranosus and soleus muscles during the monopodal jump landing in university students. At the same time, we sought to determine the existence or not of significant differences between men and women. Materials and methods: Twenty-six young adults, 16 women and 10 men, participated. An inertial sensor and 7 surface electrodes were used to collect electromyographic data in the gluteus medius, rectus femoris and vastus medialis quadriceps, semimembranosus, biceps femoris long head, soleus and adductor magnus muscles. Results: The general activation sequence was Vastus medialis -Biceps femoris longus - Adductor magnus - Gluteus medius - Rectus femoris -Semimembranosus and soleus. The data obtained reflects the activation prior to ground contact of all the muscles studied. There were differences between genders. Women presented a previous activation in all muscles with the exception of the gluteus medius. The muscles with the greatest variability were the adductor magnus in men and the rectus femoris in women. Conclusion: The significant differences found between men and women show that there are trends that can be the beginning to better understand the risk factors for injury generation. The TPA data presented a great variability which could reflect the existence of different activation patterns and not a unique behavior of the MMII musculature.

Numerical methods for the detection of phase defect structures in excitable media

Electrical waves that rotate in the heart organize dangerous cardiac arrhythmias. Finding the region around which such rotation occurs is one of the most important practical questions for arrhythmia management. For many years, the main method for finding such regions was so-called phase mapping, in which a continuous phase was assigned to points in the heart based on their excitation status and defining the rotation region as a point of phase singularity. Recent analysis, however, showed that in many rotation regimes there exist phase discontinuities and the region of rotation must be defined not as a point of phase singularity, but as a phase defect line. In this paper we use this novel methodology and perform comparative study of three different phase definitions applied to in-silico data and to experimental data obtained from optical voltage mapping experiments on monolayers of human atrial myocytes. We introduce new phase defect detection algorithms and compare them with those that appeared in literature already. We find that the phase definition is more important than the algorithm to identify sudden spatial phase variations. Sharp phase defect lines can be obtained from a phase derived from local activation times observed during one cycle of arrhythmia. Alternatively, similar quality can be obtained from a reparameterization of the classical phase obtained from observation of a single timeframe of transmembrane potential. We found that the phase defect line length was 35.9(62)mm in the Fenton-Karma model and 4.01(55)mm in cardiac human atrial myocyte monolayers. As local activation times are obtained during standard clinical cardiac mapping, the methods are also suitable to be applied to clinical datasets. All studied methods are publicly available and can be downloaded from an institutional web-server.

Synthesis and Characterization of Activated Carbon Fibers Derived from Linear Low-Density Polyethylene Fibers Stabilized at a Low Temperature

In this study, activated carbon fibers (ACFs) were prepared using a new method from polyethylene (PE) fibers. The stabilizing (or crosslinking) process of PE, an essential step, was achieved through a hybrid treatment using electron-beam/sulfuric acid at 110 °C that was more effective than the traditional method of using sulfuric acid at 180 °C for polyolefin. The stabilized precursor was then carbonized at 700 °C and activated at 900 °C with different activation times. The structural characteristics and morphologies of these ACFs were observed using an X-ray diffractometer and a field-emission scanning electron microscope, respectively. In addition, the N2/77K adsorption isotherm was used to discern textural properties. The total pore volume and specific surface area of these ACFs were found to be increased with a longer activation time, reaching final values of 0.99 cm3/g and 1750 m2/g, respectively. These ACFs also exhibited a high mesopore volume ratio (39%) according to crosslinking and crystallite formation conditions.

The Use of Electrocardiographic Imaging in Localising the Origin of Arrhythmias During Catheter Ablation of Ventricular Tachycardia

Non-invasive electrocardiographic imaging (ECGI) is a novel clinical tool for mapping ventricular arrhythmia. Using multiple body surface electrodes to collect unipolar electrograms and conventional medical imaging of the heart, an epicardial shell can be created to display calculated electrograms. This calculation is achieved by solving the inverse problem and allows activation times to be calculated from a single beat. The technology was initially pioneered in the US using an experimental torso-shaped tank. Accuracy from studies in humans has varied. Early data was promising, with more recent work suggesting only moderate accuracy when reproducing cardiac activation. Despite these limitations, the system has been successfully used in pioneering work with non-invasive cardiac radioablation to treat ventricular arrhythmia. This suggests that the resolution may be sufficient for treatment of large target areas. Although untested in a well conducted clinical study it is likely that it would not be accurate enough to guide more discreet radiofrequency ablation.

Extrapolation of Ventricular Activation Times From Sparse Electroanatomical Data Using Graph Convolutional Neural Networks

Electroanatomic mapping is the gold standard for the assessment of ventricular tachycardia. Acquiring high resolution electroanatomic maps is technically challenging and may require interpolation methods to obtain dense measurements. These methods, however, cannot recover activation times in the entire biventricular domain. This work investigates the use of graph convolutional neural networks to estimate biventricular activation times from sparse measurements. Our method is trained on more than 15,000 synthetic examples of realistic ventricular depolarization patterns generated by a computational electrophysiology model. Using geometries sampled from a statistical shape model of biventricular anatomy, diverse wave dynamics are induced by randomly sampling scar and border zone distributions, locations of initial activation, and tissue conduction velocities. Once trained, the method accurately reconstructs biventricular activation times in left-out synthetic simulations with a mean absolute error of 3.9 ms ± 4.2 ms at a sampling density of one measurement sample per cm2. The total activation time is matched with a mean error of 1.4 ms ± 1.4 ms. A significant decrease in errors is observed in all heart zones with an increased number of samples. Without re-training, the network is further evaluated on two datasets: (1) an in-house dataset comprising four ischemic porcine hearts with dense endocardial activation maps; (2) the CRT-EPIGGY19 challenge data comprising endo- and epicardial measurements of 5 infarcted and 6 non-infarcted swines. In both setups the neural network recovers biventricular activation times with a mean absolute error of less than 10 ms even when providing only a subset of endocardial measurements as input. Furthermore, we present a simple approach to suggest new measurement locations in real-time based on the estimated uncertainty of the graph network predictions. The model-guided selection of measurement locations allows to reduce by 40% the number of measurements required in a random sampling strategy, while achieving the same prediction error. In all the tested scenarios, the proposed approach estimates biventricular activation times with comparable or better performance than a personalized computational model and significant runtime advantages.

Atrial slow conduction develops and dynamically expands during premature stimulation in an animal model of persistent atrial fibrillation

Slow conduction areas and conduction block in the atria are considered pro-arrhythmic conditions. Studies examining the size and distribution of slow conduction regions in the context of persistent atrial fibrillation (AF) may help to develop improved therapeutic strategies for patients with AF. In this work, we studied the differences of size and number in slow conduction areas between control and persistent AF goats and the influence of propagation direction on the development of these pathological conduction areas. Epicardial atrial electrical activations from the left atrial roof were optically mapped with physiological pacing cycle lengths and for the shortest captured cycle lengths. The recordings were converted to local activation times and conduction velocity measures. Regions with slow conduction velocity (less than 0 . 2 m s) were identified. The size of the connected regions and the number of non-connected regions were counted for propagation from different orthogonal directions. We found that regions of slow conduction significantly increases in our 15 persistent AF goat recordings in response to premature stimulation (24.4±4.3% increase to 36.6±4.4%, p < 0.001). This increase is driven by an increase of size from (3.70±0.89[mm2] to 6.36±0.91[mm2], p = 0.014) for already existing regions and not by generation of new slow conduction regions (11.6±1.8 vs. 13±1.9, p = 0.242). In 12 control goat recordings, no increase from baseline pacing to premature pacing was found. Similarly, size of the slow conduction areas and the count did not change significantly in control animals.

A mixed-reality holographic viewing platform enabling interaction with 3D electroanatomical maps using the HoloLens

Introduction Three dimensional (3D) electroanatomical maps (EAMs) created during electrophysiology procedures are traditionally displayed on 2D monitors connected to mapping systems. This has limitations, such as the lack of interaction with EAMs, the need for another user to control them, and the size of EAM displayed, which is limited by the resolution of these monitors. To overcome these, we created a novel technology to display EAMs on a mixed reality (MR) platform. Methods We used the Microsoft® HoloLens to create this MR platform. Studies from patients who had already undergone catheter ablation for atrial fibrillation, where EAMs of the left atria had been generated using different mapping systems (CARTO®, Rhythmia™ and EnSite Precision™) were utilised. These EAMs consisting of 3D coordinates and annotations (e.g. voltage & activation times) were exported from the mapping system. EAMs were then compiled and transferred to the HoloLens using custom-developed functions on Unity©, Microsoft® C# and VisualStudio. Subsequently, feedback was obtained from 3 independent electrophysiologists on this technology. Results We successfully exported the EAMs generated on CARTO®, Rhythmia™ and EnSite Precision™ mapping systems as holograms on to the HoloLens (Figure). Positive feedback included themes such as 1) the ability to use hand gestures and voice commands to interact with EAMs independent of another user unlike traditional cardiac mapping systems 2) offering an interactive 3D holographic experience whilst preserving the operators' physical interaction in the cardiac catheter lab 3) the capacity to better appreciate 3D geometry of EAMs in comparison to 2D monitors. The challenge of wearing a headset during long procedures was perceived as a disadvantage. Conclusion This technology, which can be used with any mapping system, is currently optimised for offline display. Our software will be made available as an opensource teaching and simulation tool. Users will be able to explore EAMs for research, planning complex cases and immersive learning. The future directions will include extending this toolkit for real-time cardiac mapping with catheter localisation, and could potentially be translated to other cardiac imaging modalities. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Cardiovascular diseases charitable fund (CDCF) at Guy's and St Thomas' NHS Foundation Trust. Process of creating Holograms of EAMs Voltage map of left atrium as a Hologram

Reduction of Conduction Velocity in Patients with Atrial Fibrillation

It is unknown to what extent atrial fibrillation (AF) episodes affect intra-atrial conduction velocity (CV) and whether regional differences in local CV heterogeneities exist during sinus rhythm. This case-control study aims to compare CV assessed throughout both atria between patients with and without AF. Patients (n = 34) underwent intra-operative epicardial mapping of the right atrium (RA), Bachmann’s bundle (BB), left atrium (LA) and pulmonary vein area (PVA). CV vectors were constructed to calculate median CV in addition to total activation times (TAT) and unipolar voltages. Biatrial median CV did not differ between patients with and without AF (90 ± 8 cm/s vs. 92 ± 6 cm/s, p = 0.56); only BB showed a CV reduction in the AF group (79 ± 12 cm/s vs. 88 ± 11 cm/s, p = 0.02). In patients without AF, there was no predilection site for the lowest CV (P5) (RA: 12%; BB: 29%; LA: 29%; PVA: 29%). In patients with AF, lowest CV was most often measured at BB (53%) and ranged between 15 to 22 cm/s (median: 20 cm/s). Lowest CVs were also measured at the LA (18%) and PVA (29%), but not at the RA. AF was associated with a prolonged TAT (p = 0.03) and decreased voltages (P5) at BB (p = 0.02). BB was a predilection site for slowing of conduction in patients with AF. Prolonged TAT and decreased voltages were also found at this site. The next step will be to determine the relevance of a reduced CV at BB in relation to AF development and maintenance.