Q negatively regulates wheat salt tolerance through directly repressing the expression of TaSOS1 and reactive oxygen species scavenging genes.

The Q transcription factor plays important roles in improving multiple wheat domestication traits such as spike architecture, threshability and rachis fragility. However, whether and how it regulates abiotic stress adaptation remain unclear. We found that the transcriptional expression of Q can be induced by NaCl and abscisic acid treatments. Using the q mutants generated by CRISPR/Cas9 and Q overexpression transgenic lines, we showed that the domesticated Q gene causes a penalty in wheat salt tolerance. Then, we demonstrated that Q directly represses the transcription of TaSOS1-3B and reactive oxygen species (ROS) scavenging genes to regulate Na+ and ROS homeostasis in wheat. Furthermore, we showed that wheat salt tolerance protein TaWD40 interacts with Q to competitively interfere with the interaction between Q and the transcriptional co-repressor TaTPL. Taken together, our findings reveal that Q directly represses the expression of TaSOS1 and some ROS scavenging genes, thus causing a harmful effect on wheat salt tolerance.

A wild rice CSSL population facilitated identification of salt tolerance genes and rice germplasm innovation.

Salt stress is one of the major factors that limits rice production. Therefore, identification of salt-tolerant alleles from wild rice is important for rice breeding. In this study, we constructed a set of chromosome segment substitution lines (CSSLs) using wild rice as the donor parent and cultivated rice Nipponbare (Nip) as the recurrent parent. Salt tolerance germinability (STG) was evaluated, and its association with genotypes was determined using this CSSL population. We identified 17 QTLs related to STG. By integrating the transcriptome and genome data, four candidate genes were identified, including the previously reported AGO2 and WRKY53. Compared with Nip, wild rice AGO2 has a structure variation in its promoter region and the expression levels were upregulated under salt treatments; wild rice WRKY53 also has natural variation in its promoter region, and the expression levels were downregulated under salt treatments. Wild rice AGO2 and WRKY53 alleles have combined effects for improving salt tolerance at the germination stage. One CSSL line, CSSL118 that harbors these two alleles was selected. Compared with the background parent Nip, CSSL118 showed comprehensive salt tolerance and higher yield, with improved transcript levels of reactive oxygen species scavenging genes. Our results provided promising genes and germplasm resources for future rice salt tolerance breeding.

Relationship Analysis Between Pericoronary Fat Attenuation Index and Parameters of Single Plaque.

OBJECTIVE: The aim of the study is to investigate the relationship between plaque parameters and pericoronary fat attenuation index (FAI). METHODS: A retrospective collection was performed on 227 patients with coronary heart disease who underwent coronary computed tomography angiography examinations in our hospital from May 2021 to April 2023, with a total of 254 right coronary or left anterior descending coronary arteries exhibiting solitary plaques within the FAI measurement area. Based on whether the proximal coronary FAI value was ≥ -70.0 HU, patients and coronary arteries were divided into FAI-positive group (67 cases, 73 coronary arteries) and FAI-negative group (160 cases, 181 coronary arteries). Quantitative parameters of coronary solitary plaques were collected, including stenosis severity, plaque length, plaque volume, plaque composition ratios, minimal luminal area, and calcification score, as well as qualitative parameters such as plaque types and high-risk plaques. Differences in plaque parameters between the FAI-positive and FAI-negative groups were compared. RESULTS: The proportion of positive remodeling in the FAI-positive group (73 coronary arteries) was higher than that in the FAI-negative group (181 coronary arteries) with statistical significance (89.0% vs 78.5%, P = 0.049). Multivariate analysis revealed that positive remodeling was a risk factor for abnormal FAI values in solitary plaques (odds ratio, 2.271, P = 0.049). CONCLUSIONS: The FAI-positive group had a higher proportion of positive remodeling, and positive remodeling was an independent risk factor for positive FAI values.

Prediction of Vascular Access Stenosis by Lightweight Convolutional Neural Network Using Blood Flow Sound Signals.

This research examines the application of non-invasive acoustic analysis for detecting obstructions in vascular access (fistulas) used by kidney dialysis patients. Obstructions in these fistulas can interrupt essential dialysis treatment. In this study, we utilized a condenser microphone to capture the blood flow sounds before and after angioplasty surgery, analyzing 3819 sound samples from 119 dialysis patients. These sound signals were transformed into spectrogram images to classify obstructed and unobstructed vascular accesses, that is fistula conditions before and after the angioplasty procedure. A novel lightweight two-dimension convolutional neural network (CNN) was developed and benchmarked against pretrained CNN models such as ResNet50 and VGG16. The proposed model achieved a prediction accuracy of 100%, surpassing the ResNet50 and VGG16 models, which recorded 99% and 95% accuracy, respectively. Additionally, the study highlighted the significantly smaller memory size of the proposed model (2.37 MB) compared to ResNet50 (91.3 MB) and VGG16 (57.9 MB), suggesting its suitability for edge computing environments. This study underscores the efficacy of diverse deep-learning approaches in the obstructed detection of dialysis fistulas, presenting a scalable solution that combines high accuracy with reduced computational demands.

Estimation of Gait Parameters for Adults with Surface Electromyogram Based on Machine Learning Models.

Gait analysis has been studied over the last few decades as the best way to objectively assess the technical outcome of a procedure designed to improve gait. The treating physician can understand the type of gait problem, gain insight into the etiology, and find the best treatment with gait analysis. The gait parameters are the kinematics, including the temporal and spatial parameters, and lack the activity information of skeletal muscles. Thus, the gait analysis measures not only the three-dimensional temporal and spatial graphs of kinematics but also the surface electromyograms (sEMGs) of the lower limbs. Now, the shoe-worn GaitUp Physilog® wearable inertial sensors can easily measure the gait parameters when subjects are walking on the general ground. However, it cannot measure muscle activity. The aim of this study is to measure the gait parameters using the sEMGs of the lower limbs. A self-made wireless device was used to measure the sEMGs from the vastus lateralis and gastrocnemius muscles of the left and right feet. Twenty young female subjects with a skeletal muscle index (SMI) below 5.7 kg/m2 were recruited for this study and examined by the InBody 270 instrument. Four parameters of sEMG were used to estimate 23 gait parameters. They were measured using the GaitUp Physilog® wearable inertial sensors with three machine learning models, including random forest (RF), decision tree (DT), and XGBoost. The results show that 14 gait parameters could be well-estimated, and their correlation coefficients are above 0.800. This study signifies a step towards a more comprehensive analysis of gait with only sEMGs.

Tumor immune contexture predicts recurrence after prostatectomy and efficacy of androgen deprivation and immunotherapy in prostate cancer.

BACKGROUND: Prostate cancer is one of the most common cancers in men with notable interpatient heterogeneity. Implications of the immune microenvironment in predicting the biochemical recurrence-free survival (BCRFS) after radical prostatectomy and the efficacy of systemic therapies in prostate cancer remain ambiguous. METHODS: The tumor immune contexture score (TICS) involving eight immune contexture-related signatures was developed using seven cohorts of 1120 patients treated with radical prostatectomy (training: GSE46602, GSE54460, GSE70769, and GSE94767; validation: GSE70768, DKFZ2018, and TCGA). The association between the TICS and treatment efficacy was investigated in GSE111177 (androgen deprivation therapy [ADT]) and EGAS00001004050 (ipilimumab). RESULTS: A high TICS was associated with prolonged BCRFS after radical prostatectomy in the training (HR = 0.32, 95% CI 0.24-0.45, P < 0.001) and the validation cohorts (HR = 0.45, 95% CI 0.32-0.62, P < 0.001). The TICS showed stable prognostic power independent of tumor stage, surgical margin, pre-treatment prostatic specific antigen (PSA), and Gleason score (multivariable HR = 0.50, 95% CI 0.39-0.63, P < 0.001). Adding the TICS into the prognostic model constructed using clinicopathological features significantly improved its 1/2/3/4/5-year area under curve (P < 0.05). A low TICS was associated with high homologous recombination deficiency scores, abnormally activated pathways concerning DNA replication, cell cycle, steroid hormone biosynthesis, and drug metabolism, and fewer tumor-infiltrating immune cells (P < 0.05). The patients with a high TICS had favorable BCRFS with ADT (HR = 0.25, 95% CI 0.06-0.99, P = 0.034) or ipilimumab monotherapy (HR = 0.23, 95% CI 0.06-0.81, P = 0.012). CONCLUSIONS: Our study delineates the associations of tumor immune contexture with molecular features, recurrence after radical prostatectomy, and the efficacy of ADT and immunotherapy. The TICS may improve the existing risk stratification systems and serve as a patient-selection tool for ADT and immunotherapy in prostate cancer.

Gut-derived bacterial LPS attenuates incubation of methamphetamine craving via modulating microglia.

BACKGROUND: The microbiota-gut-brain axis plays a critical role in the pathophysiology of neuropsychiatric disorders, and the compositions of gut microbiota are altered by addictive drugs. However, the role of gut microbiota in the incubation of methamphetamine (METH) craving remains poorly understood. METHODS: 16S rRNA gene sequencing was performed to assess the richness and diversity of gut microbiota in METH self-administration model. Hematoxylin and eosin staining was performed to evaluate the integrity of intestinal barrier. Immunofluorescence and three-dimensional reconstruction were performed to assess the morphologic changes of microglia. Serum levels of lipopolysaccharide (LPS) were determined using the rat enzyme-linked immunosorbent assay kits. Quantitative real-time PCR was performed to assess transcript levels of dopamine receptor, glutamate ionotropic AMPA receptor 3 and brain-derived neurotrophic factor. RESULTS: METH self-administration induced gut microbiota dysbiosis, intestinal barrier damage and microglia activation in the nucleus accumbens core (NAcc), which was partially recovered after prolonged withdrawal. Microbiota depletion via antibiotic treatment increased LPS levels and induced a marked change in the microglial morphology in the NAcc, as indicated by the decreases in the lengths and numbers of microglial branches. Depleting the gut microbiota also prevented the incubation of METH craving and increased the population of Klebsiella oxytoca. Furthermore, Klebsiella oxytoca treatment or exogenous administration of the gram-negative bacterial cell wall component LPS increased serum and central LPS levels, induced microglial morphological changes and reduced the dopamine receptor transcription in the NAcc. Both treatments and NAcc microinjections of gut-derived bacterial LPS significantly decreased METH craving after prolonged withdrawal. CONCLUSIONS: These data suggest that LPS from gut gram-negative bacteria may enter circulating blood, activate microglia in the brain and consequently decrease METH craving after withdrawal, which may have important implications for novel strategies to prevent METH addiction and relapse.

Neurocan regulates vulnerability to stress and the anti-depressant effect of ketamine in adolescent rats.

Depression is more prevalent among adolescents than adults, but the underlying mechanisms remain largely unknown. Using a subthreshold chronic stress model, here we show that developmentally regulated expressions of the perineuronal nets (PNNs), and one of the components, Neurocan in the prelimbic cortex (PrL) are important for the vulnerability to stress and depressive-like behaviors in both adolescent and adult rats. Reduction of PNNs or Neurocan with pharmacological or viral methods to mimic the expression of PNNs in the PrL during adolescence compromised resilience to stress in adult rats, while virally mediated overexpression of Neurocan reversed vulnerability to stress in adolescent rats. Ketamine, a recent-approved drug for treatment-resistant depression rescued impaired function of Parvalbumin-positive neurons function, increased expression of PNNs in the PrL, and reversed depressive-like behaviors in adolescent rats. Furthermore, we show that Neurocan mediates the anti-depressant effect of ketamine, virally mediated reduction of Neurocan in the PrL abolished the anti-depressant effect of ketamine in adolescent rats. Our findings show an important role of Neurocan in depression in adolescence, and suggest a novel mechanism for the anti-depressant effect of ketamine.

Rh(III)-catalyzed [4 + 1] cyclization of aryl substituted pyrazoles with cyclopropanols via C-H activation.

A rhodium-catalyzed formal [4 + 1]-cyclization reaction of aryl substituted pyrazoles with cyclopropanols via C-H bond activation/cyclization processes to selectively construct a series of carbonyl functionalized pyrazolo[5,1-a]isoindoles is described. The reaction features good functional group compatibility and a broad substrate scope with respect to both cyclization components with up to 84% yields. Mechanistic studies indicated that the C-H cleavage might be the rate-determining step in this transformation.

Using Ballistocardiogram and Impedance Plethysmogram for Minimal Contact Measurement of Blood Pressure Based on a Body Weight-Fat Scale.

Electronic health (eHealth) is a strategy to improve the physical and mental condition of a human, collecting daily physiological data and information from digital apparatuses. Body weight and blood pressure (BP) are the most popular and important physiological data. The goal of this study is to develop a minimal contact BP measurement method based on a commercial body weight-fat scale, capturing biometrics when users stand on it. The pulse transit time (PTT) is extracted from the ballistocardiogram (BCG) and impedance plethysmogram (IPG), measured by four strain gauges and four footpads of a commercial body weight-fat scale. Cuffless BP measurement using the electrocardiogram (ECG) and photoplethysmogram (PPG) serves as the reference method. The BP measured by a commercial BP monitor is considered the ground truth. Twenty subjects participated in this study. By the proposed model, the root-mean-square errors and correlation coefficients (r2s) of estimated systolic blood pressure and diastolic blood pressure are 7.3 ± 2.1 mmHg and 4.5 ± 1.8 mmHg, and 0.570 ± 0.205 and 0.284 ± 0.166, respectively. This accuracy level achieves the C grade of the corresponding IEEE standard. Thus, the proposed method has the potential benefit for eHealth monitoring in daily application.

Muscle Mass Measurement Using Machine Learning Algorithms with Electrical Impedance Myography.

Sarcopenia is a wild chronic disease among elderly people. Although it does not entail a life-threatening risk, it will increase the adverse risk due to the associated unsteady gait, fall, fractures, and functional disability. The import factors in diagnosing sarcopenia are muscle mass and strength. The examination of muscle mass must be carried in the clinic. However, the loss of muscle mass can be improved by rehabilitation that can be performed in non-medical environments. Electronic impedance myography (EIM) can measure some parameters of muscles that have the correlations with muscle mass and strength. The goal of this study is to use machine learning algorithms to estimate the total mass of thigh muscles (MoTM) with the parameters of EIM and body information. We explored the seven major muscles of lower limbs. The feature selection methods, including recursive feature elimination (RFE) and feature combination, were used to select the optimal features based on the ridge regression (RR) and support vector regression (SVR) models. The optimal features were the resistance of rectus femoris normalized by the thigh circumference, phase of tibialis anterior combined with the gender, and body information, height, and weight. There were 96 subjects involved in this study. The performances of estimating the MoTM used the regression coefficient (r2) and root-mean-square error (RMSE), which were 0.800 and 0.929, and 1.432 kg and 0.980 kg for RR and SVR models, respectively. Thus, the proposed method could have the potential to support people examining their muscle mass in non-medical environments.

An Examination System to Detect Deep Vein Thrombosis of a Lower Limb Using Light Reflection Rheography.

Deep vein thrombosis (DVT) of lower limbs can easily arise from prolonged sitting or standing. Elders and pregnant women are most likely to have this disease. When the embolus of DVT comes to pass the lung, it will become a life-threatening disease. Thus, for DVT disease, early detection and the early treatment are needed. The goal of this study was to develop an examination system to be used at non-medical places to detect the DVT of lower limbs with light reflection rheography (LRR). Consisting of a wearable device and a mobile application (APP), the system is operated in a wireless manner to control the actions of sensors and display and store the LRR signals on the APP. Then, the recorded LRR signals are processed to find the parameters of DVT examination. Twenty subjects were recruited to perform experiments. The veins of lower limbs were occluded by pressuring the cuff up to 100 mmHg and 150 mmHg to simulate the slight and serious DVT scenarios, respectively. Six characteristic parameters were defined to classify whether there was positive or negative DVT using the receiver operating characteristic curves, including the slopes of emptying and refilling curves in the LRR signal, and the changes of venous pump volume. Under the slight DVT scenario (0 mmHg vs. 100 mmHg), the first three parameters, m10, m40, and m50, had accuracies of 72%, 69%, and 69%, respectively. Under the serious DVT scenario (0 mmHg vs. 150 mmHg), m10, m40, and m50 achieved accuracies of 73%, 76%, and 73%, respectively. The experimental results show that this proposed examination system may be practical as an auxiliary tool to screen DVT in homecare settings.

Noninvasive Measurement of Time-Varying Arterial Wall Elastance Using a Single-Frequency Vibration Approach.

The arterial wall elastance is an important indicator of arterial stiffness and a kind of manifestation associated with vessel-related disease. The time-varying arterial wall elastances can be measured using a multiple-frequency vibration approach according to the Voigt and Maxwell model. However, such a method needs extensive calculation time and its operating steps are very complex. Thus, the aim of this study is to propose a simple and easy method for assessing the time-varying arterial wall elastances with the single-frequency vibration approach. This method was developed according to the simplified Voigt and Maxwell model. Thus, the arterial wall elastance measured using this method was compared with the elastance measured using the multiple-frequency vibration approach. In the single-frequency vibration approach, a moving probe of a vibrator was induced with a radial displacement of 0.15 mm and a 40 Hz frequency. The tip of the probe directly contacted the wall of a superficial radial artery, resulting in the arterial wall moving 0.15 mm radially. A force sensor attached to the probe was used to detect the reactive force exerted by the radial arterial wall. According to Voigt and Maxwell model, the wall elastance (Esingle) was calculated from the ratio of the measured reactive force to the peak deflection of the displacement. The wall elastances (Emultiple) measured by the multiple-frequency vibration approach were used as the reference to validate the performance of the single-frequency approach. Twenty-eight healthy subjects were recruited in the study. Individual wall elastances of the radial artery were determined with the multiple-frequency and the single-frequency approaches at room temperature (25 °C), after 5 min of cold stress (4 °C), and after 5 min of hot stress (42 °C). We found that the time-varying Esingle curves were very close to the time-varying Emultiple curves. Meanwhile, there was a regression line (Esingle = 0.019 + 0.91 Emultiple, standard error of the estimate (SEE) = 0.0295, p < 0.0001) with a high correlation coefficient (0.995) between Esingle and Emultiple. Furthermore, from the Bland-Altman plot, good precision and agreement between the two approaches were demonstrated. In summary, the proposed approach with a single-frequency vibrator and a force sensor showed its feasibility for measuring time-varying wall elastances.

ECG Noise Cancellation Based on Grey Spectral Noise Estimation.

In recent years, wearable devices have been popularly applied in the health care field. The electrocardiogram (ECG) is the most used signal. However, the ECG is measured under a body-motion condition, which is easily coupled with some noise, like as power line noise (PLn) and electromyogram (EMG). This paper presents a grey spectral noise cancellation (GSNC) scheme for electrocardiogram (ECG) signals where two-stage discrimination is employed with the empirical mode decomposition (EMD), the ensemble empirical mode decomposition (EEMD) and the grey spectral noise estimation (GSNE). In the first stage of the proposed GSNC scheme, the input ECG signal is decomposed by the EMD to obtain a set of intrinsic mode functions (IMFs). Then, the noise energies of IMFs are estimated by the GSNE. When an IMF is considered as noisy one, it is forwarded to the second stage for further check. In the second stage, the suspicious IMFs are reconstructed and decomposed by the EEMD. Then the IMFs are discriminated with a threshold. If the IMF is considered as noisy, it is discarded in the reconstruction process of the ECG signal. The proposed GSNC scheme is justified by forty-three ECG signal datasets from the MIT-BIH cardiac arrhythmia database where the PLn and EMG noise are under consideration. The results indicate that the proposed GSNC scheme outperforms the traditional EMD and EEMD based noise cancellation schemes in the given datasets.

An EMG Patch for the Real-Time Monitoring of Muscle-Fatigue Conditions During Exercise.

In recent years, wearable monitoring devices have been very popular in the health care field and are being used to avoid sport injuries during exercise. They are usually worn on the wrist, the same as sport watches, or on the chest, like an electrocardiogram patch. Common functions of these wearable devices are that they use real time to display the state of health of the body, and they are all small sized. The electromyogram (EMG) signal is usually used to show muscle activity. Thus, the EMG signal could be used to determine the muscle-fatigue conditions. In this study, the goal is to develop an EMG patch which could be worn on the lower leg, the gastrocnemius muscle, to detect real-time muscle fatigue while exercising. A micro controller unit (MCU) in the EMG patch is part of an ARM Cortex-M4 processor, which is used to measure the median frequency (MF) of an EMG signal in real time. When the muscle starts showing tiredness, the median frequency will shift to a low frequency. In order to delete the noise of the isotonic EMG signal, the EMG patch has to run the empirical mode decomposition algorithm. A two-electrode circuit was designed to measure the EMG signal. The maximum power consumption of the EMG patch was about 39.5 mAh. In order to verify that the real-time MF values measured by the EMG patch were close to the off-line MF values measured by the computer system, we used the root-mean-square value to estimate the difference in the real-time MF values and the off-line MF values. There were 20 participants that rode an exercise bicycle at different speeds. Their EMG signals were recorded with an EMG patch and a physiological measurement system at the same time. Every participant rode the exercise bicycle twice. The averaged root-mean-square values were 2.86 ± 0.86 Hz and 2.56 ± 0.47 Hz for the first and second time, respectively. Moreover, we also developed an application program implemented on a smart phone to display the participants' muscle-fatigue conditions and information while exercising. Therefore, the EMG patch designed in this study could monitor the muscle-fatigue conditions to avoid sport injuries while exercising.

Effects of hyperglycemia on bone metabolism and bone matrix in goldfish scales.

Increased risk of fracture associated with type 2 diabetes has been a topic of recent concern. Fracture risk is related to a decrease in bone strength, which can be affected by bone metabolism and the quality of the bone. To investigate the cause of the increased fracture rate in patients with diabetes through analyses of bone metabolism and bone matrix protein properties, we used goldfish scales as a bone model for hyperglycemia. Using the scales of seven alloxan-treated and seven vehicle-treated control goldfish, we assessed bone metabolism by analyzing the activity of marker enzymes and mRNA expression of marker genes, and we measured the change in molecular weight of scale matrix proteins with SDS-PAGE. After only a 2-week exposure to hyperglycemia, the molecular weight of α- and ß-fractions of bone matrix collagen proteins changed incrementally in the regenerating scales of hyperglycemic goldfish compared with those of euglycemic goldfish. In addition, the relative ratio of the γ-fraction significantly increased, and a δ-fraction appeared after adding glyceraldehyde-a candidate for the formation of advanced glycation end products in diabetes-to isolated type 1 collagen in vitro. The enzymatic activity and mRNA expression of osteoblast and osteoclast markers were not significantly different between hyperglycemic and euglycemic goldfish scales. These results indicate that hyperglycemia is likely to affect bone quality through glycation of matrix collagen from an early stage of hyperglycemia. Therefore, non-enzymatic glycation of collagen fibers in bone matrix may lead to the deterioration of bone quality from the onset of diabetes.

Transmural, interventricular, apicobasal and anteroposterior action potential duration gradients are all essential to the genesis of the concordant and realistic T wave: A whole-heart model study.

BACKGROUND: It has been reported that ventricular repolarization dispersion resulting from transmural, apicobasal and interventricular action potential duration (APD) gradients makes the T wave concordant with the QRS complex. METHOD AND RESULTS: A whole-heart model integrating transmural, apicobasal, interventricular and anteroposterior APD gradients was used, and the corresponding electrocardiograms were simulated to study the influence of these APD gradients on the T-wave amplitudes. The simulation results showed that changing a single APD gradient (e.g., interventricular APD gradient alone) only made substantial changes to the T-wave amplitudes in a limited number of leads and was not able to generate T waves with amplitudes comparable with clinical findings in all leads. A combination of transmural, apicobasal and interventricular APD gradients could simulate T waves with amplitudes similar to clinical values in the limb leads only. Adding the anteroposterior APD gradient into the model greatly improved the consistency between the simulated T-wave amplitudes and the clinical values. CONCLUSION: The simulation results support that the transmural, apicobasal, interventricular and the anteroposterior APD gradient are all essential to the genesis of the clinical T wave.

Evaluation of structural and thermophysical effects on the measurement accuracy of deep body thermometers based on dual-heat-flux method.

To help pave a path toward the practical use of continuous unconstrained noninvasive deep body temperature measurement, this study aims to evaluate the structural and thermophysical effects on measurement accuracy for the dual-heat-flux method (DHFM). By considering the thermometer's height, radius, conductivity, density and specific heat as variables affecting the accuracy of DHFM measurement, we investigated the relationship between those variables and accuracy using 3-D models based on finite element method. The results of our simulation study show that accuracy is proportional to the radius but inversely proportional to the thickness of the thermometer when the radius is less than 30.0mm, and is also inversely proportional to the heat conductivity of the heat insulator inside the thermometer. The insights from this study would help to build a guideline for design, fabrication and optimization of DHFM-based thermometers, as well as their practical use.

Parallelization of Three Dimensional Cardiac Simulation on GPU.

BACKGROUND: The simulation of electrophysiological cardiac models plays an important role in facilitating the investigation of cardiac behavior under various conditions. However, these simulations often require a lot of computational resources. METHODS: To address this challenge, this study introduced a method for speeding up three-dimensional cardiac simulations using GPU parallelization. A series of optimizations was introduced, encompassing various aspects such as data storage, algorithmic enhancements, and data transfer. RESULTS: The experimental results reveal that the optimized GPU parallel simulations achieve an approximate 50-fold acceleration compared with their CPU serial program. CONCLUSION: This investigation substantiates the considerable potential of GPUs in advancing the field of cardiac electrophysiology simulations.

Computer simulation of low-power and long-duration bipolar radiofrequency ablation under various baseline impedances.

Compared to traditional unipolar radiofrequency ablation (RFA), bipolar RFA offers advantages such as more precise heat transfer and higher ablation efficiency. Clinically, myocardial baseline impedance (BI) is one of the important factors affecting the effectiveness of ablation. We aim at finding suitable ablation protocols and coping strategies by analyzing the ablation effects and myocardial impedance changes of bipolar RFA under different BIs. In this research, a three-dimensional local myocardial computer model was constructed for bipolar RFA simulation, and in vitro experimental data were used to validate accuracy. Four fixed low-power levels (20 W, 25 W, 30 W, and 35 W) and six myocardial BIs (91.02 Ω, 99.83 Ω, 111.03 Ω, 119.77 Ω, 130.03 Ω, and 135.45 Ω) were set as initial conditions, with an ablation duration of 120-s. In the context of low-power and long-duration (LPLD) ablation, the maximum TID (TIDM) decreased by 21-32 Ω, depending on the BI. In cases where steam pop did not occur, TIDM increased with the increase in power. For the same power, there was no significant difference in TIDM for the range of BIs. In cases where steam pop occurred, for every 1 Ω increase in BI, TIDM increased by 0.34-0.41 Ω. The simulation results also showed that using a higher power resulted in a smaller decrease in TIDM. This study provided appropriate ablation times and impedance decrease ranges for bipolar LPLD RFA. The combination of 25 W for 120-s offered optimal performance when considering effectiveness and safety simultaneously.