Search

• Focus on the information loss problem in tracking technologies for surgical navigation systems. • Survey the existing solutions to information loss in tracking surgical instruments. • Information fusion technology to improve accuracy, precision, and stability. • Future research trends on information fusion during surgical navigation. Surgical navigation technology provides minimally invasive surgery (MIS) with the relative pose relationships amongst medical images, surgical instruments, and lesions. On the other hand, traditional operation procedures depend heavily on direct surgical field exposure. Consequently, introducing surgical navigation can enable surgeons to operate more accurately and efficiently. A tracking system is a core enabling technology of a surgical navigation system. In this paper, after reviewing the tracking technologies, we compare and analyze their pros and cons, and find that information loss is a common challenge. The information loss problem is an inherent drawback in mono-modality surgical navigation systems. It is characterized by physical constraints, attenuation, breakdown of signal, and accuracy instability of the tracking algorithms. This review focuses on the information loss problem in tracking technologies for surgical navigation systems. Furthermore, we survey the existing solutions that aim at tackling the information loss problem, especially in the information fusion of surgical tracking technologies, and we also summarize their key improvements and limitations. Particular attention has been given to the modalities, approaches, objectives, and surgical application scenarios, which can improve the accuracy, precision, and stability of surgical navigation systems. Finally, future research trends directed at improving the information loss problem are discussed, i.e., tight integration of sensing technology, augmented reality for visualization in surgical tracking, stable high-speed 5G networks for telesurgery, strong intelligence and affordable service. [ABSTRACT FROM AUTHOR]

We used near-field and regional GNSS (Global Navigation Satellite System) data to quantify the deformation and locking ratio of the Xiaojiang fault (XJF) in southeastern Tibet. The inversion based on the dislocation model shows that the slip rate of the XJF is 9–11 mm/a; the locking depths of the northern, central, and southern segments are 25.5 km, 12 km, and 22.5 km, respectively. The inversion with DEFNODE program shows that the locking of the northern segment is the strongest above a depth of 20 km, while the locking between 20 km and 26 km is intermediate, and the weakest locking is found below 26 km. In the central segment, the depths of the interface are 6 km and 12 km. Additionally, a locked asperity that has the potential of generating an Mw 7.2 earthquake along the northern segment is delineated. The asperity and the shallow locking zone are basically consistent with the rupture area of the 1733 M 7.8 Dongchuan earthquake and the 1833 M 8 Songming earthquake, respectively. Both the activity of the historical strong earthquakes and the seismicity of the microearthquakes recorded over recent years seem to suggest that a potential earthquake is imminent. [ABSTRACT FROM AUTHOR]

Arterial stiffness, as measured by pulse wave velocity, for the early non-invasive screening of cardiovascular disease is becoming ever more widely used and is an independent prognostic indicator for a variety of pathologies including arteriosclerosis. Carotid-femoral pulse wave velocity (cfPWV) is regarded as the gold standard for aortic stiffness. Existing algorithms for cfPWV estimation have been shown to have good repeatability and accuracy, however, further assessment is needed, especially when signal quality is compromised. We propose a method for calculating cfPWV based on a simplified tube-load model, which allows for the propagation and reflection of the pulse wave. In-vivo cfPWV measurements from 57 subjects and numerical cfPWV data based on a one-dimensional model were used to assess the method and its performance was compared to three other existing approaches (waveform matching, intersecting tangent, and cross-correlation). The cfPWV calculated using the simplified tube-load model had better repeatability than the other methods (Intra-group Correlation Coefficient, ICC = 0.985). The model was also more accurate than other methods (deviation, 0.13 ms−1) and was more robust when dealing with noisy signals. We conclude that the determination of cfPWV based on the proposed model can accurately and robustly evaluate arterial stiffness. [ABSTRACT FROM AUTHOR]

Background: NCCN guidelines recommend a dose of 100 μg/kg or a fixed dose of 6 mg pegylated recombinant human granulocyte colony‐stimulating factor (PEG rhG‐CSF) for chemotherapy‐induced neutropenia. However, a single dose of 60 μg/kg or 100 μg/kg produced a similar neutrophil response among patients with chemotherapy‐induced neutropenia (CIN). Thus, this prospective randomized study was designed to investigate the efficacy of 3 mg PEG rhG‐CSF in preventing acute lower respiratory tract infection (ALRTI) after chemotherapy. Methods: Patients with stage IIIB/IVA lung cancer who underwent chemotherapy were randomly divided into a (i) control group, and (ii) treatment group subject to 3 mg PEG rhG‐CSF after chemotherapy. Patients in the control group were administered rhG‐CSF (5 μg/kg) when decreased absolute neutrophil count (ANC) reached grade 3 of adverse events. The primary outcome was incidence of ALRTI, and the secondary outcomes included ANC, febrile neutropenia (FN), incidence of delayed chemotherapy, infection‐related medical expenses and adverse reactions. Results: Compared with the control group, there was a significant decrease in the incidence of ALRTI (9.6% vs. 24.6%, p < 0.01), FN (1.7% vs. 7.3%, p < 0.001) and neutropenia (8.3% vs. 23.3%, p < 0.01) in the PEG‐rhG‐CSF group. The incidence of ALRTI was significantly correlated with the grade of CTCAE on ANC. The main adverse reactions of PEG‐rhG‐CSF were pain and fatigue, among which three cases showed pain of ≥ grade 3. The cost of infection‐associated medical expenditure in the treatment group was greatly reduced compared with the control group (p < 0.001). Conclusions: ALRTI could well be prevented after prophylactic application of PEG‐rhG‐CSF (3 mg), and was related to the reduced neutropenia. [ABSTRACT FROM AUTHOR]

Accurate segmentation of the right ventricle (RV) from cardiac magnetic resonance imaging (MRI) images is an essential step in estimating clinical indices such as stroke volume and ejection fraction. Recently, image segmentation methods based on fully convolutional neural networks (FCN) have drawn much attention and shown promising results. In this paper, a new fully automatic RV segmentation method combining the FC-DenseNet and the level set method (FCDL) is proposed. The FC-DenseNet is efficiently trained end-to-end, using RV images and ground truth masks to make a per-pixel semantic inference. As a result, probability images are produced, followed by the level set method responsible for smoothing and converging contours to improve accuracy. It is noted that the iteration times of the level set method is only 4 times, which is due to the semantic segmentation of the FC-DenseNet for RV. Finally, multi-object detection algorithm is applied to locate the RV. Experimental results (including 45 cases, 15 cases for training, 30 cases for testing) show that the FCDL method outperforms the U-net + level set (UL) and the level set methods that use the same dataset and the cardiac functional parameters are computed robustly by the FCDL method. The results validate the FCDL method as an efficient and satisfactory approach to RV segmentation. [ABSTRACT FROM AUTHOR]

• First-line combination of icotinib with chemotherapy in randomized controlled trial. • Recruited advanced lung adenocarcinoma patients with sensitive EGFR mutations. • PFS was significantly longer in the combination group than the icotinib only group. • ORR and DCR for the combination group were higher than the icotinib only group. • The observed adverse events of combination therapy were tolerable and manageable. To explore the efficacy and safety of icotinib with chemotherapy as first-line therapy for advanced lung adenocarcinoma in patients with sensitive epidermal growth factor receptor (EGFR) mutations. This prospective, randomized, controlled trial was conducted in 10 general hospitals in Shandong Province, China. Previously untreated patients with advanced lung adenocarcinoma and sensitive EGFR mutations were recruited between January 16, 2014 and December 31, 2016 and randomly allocated to the combination group (icotinib plus pemetrexed and carboplatin) or the icotinib only group. The patients were followed up until May 23, 2018. The primary endpoint was progression-free survival (PFS). The efficacy analysis (intention-to-treat analysis) include 179 patients (n = 90 in the combination group and n = 89 in the icotinib only group). PFS was significantly longer in the combination group than in the icotinib only group (16.0 months vs. 10.0 months, hazard ratio [HR] = 0.59, 95% confidence interval [CI] 0.42–0.84, P = 0.003). The objective response rate and the disease control rate for the combination group were significantly higher than those for the icotinib only group (77.8% vs. 64.0%, χ2 = 4.094, P = 0.043; 91.1% vs. 79.8%, χ2 = 4.632, P = 0.031). However, overall survival did not differ between the two groups (36.0 months vs. 34.0 months, HR = 0.81, 95%CI 0.54–1.22, P = 0.309). The incidence rates of leukopenia and liver function damage of grades 3–4 were higher in the combination group than in the icotinib only group (12.2% vs. 0%, χ2 = 11.086, P = 0.001; 12.2% vs. 3.5%, χ2 = 4.488, P = 0.034). However, adverse events were resolved in most patients. Use of the combination of icotinib and chemotherapy as first-line therapy significantly improved the PFS of advanced lung adenocarcinoma patients with sensitive EGFR mutations. Although the combination therapy increased the incidence of leukopenia and liver function damage, the observed adverse events were tolerable and manageable. [ABSTRACT FROM AUTHOR]

Background: Malignant pleural effusion is a common complication of non‐small cell lung cancer (NSCLC); however, treatment options remain limited. This study evaluated the safety and efficacy of sequential intrapleural therapy with lobaplatin and erythromycin for NSCLC‐mediated malignant pleural effusion. Methods: Fifty‐six patients with NSCLC complicated with malignant pleural effusion were recruited for a prospective single‐arm study from December 2014 to 2016; one patient dropped out. In addition to conventional systemic chemotherapy, lobaplatin and erythromycin were intrapleurally injected into subjects. Short and long‐term responses were analyzed. The concentration of ultrafilterable platinum in the pleural effusion and plasma were detected at different time points. Incidences of severe adverse reactions were observed. Results: In the 55 evaluable patients, the effective rate of pleural effusion was 81.8% after six weeks of treatment. Six and twelve months after treatment, the effective rates were 60% and 21.8%, respectively, and the one‐year survival rate was 83.6%. The concentrations of lobaplatin in pleural effusion and plasma two hours after injecting 50 mg lobaplatin into the thoracic cavity were 13.763 ± 1.523 μg/mL and 1.120 ± 0.164 μg/mL, and 17 hours later were 1.961 ± 0.351 μg/mL and 0.578 ± 0.095 μg/mL, respectively. The rate of severe adverse reactions of the first cycle of systemic chemotherapy combined with lobaplatin and erythromycin did not significantly differ from the rate in the second cycle. Conclusion: Intrapleural combination therapy with lobaplatin and erythromycin is a safe and efficient treatment for patients with NSCLC‐mediated malignant pleural effusion. [ABSTRACT FROM AUTHOR]

Accurate segmentation of cardiac anatomy is a prerequisite for the diagnosis of cardiovascular disease. However, due to differences in imaging modalities and imaging devices, known as domain shift, the segmentation performance of deep learning models lacks reliability. In this paper, we propose a two-stage progressive unsupervised domain adaptation network (TSP-UDANet) to reduce domain shift when segmenting cardiac images from various sources. We alleviate the domain shift between the feature distribution of the source and target domains by introducing an intermediate domain as a bridge. The TSP-UDANet consists of three sub-networks: a style transfer sub-network, a segmentation sub-network, and a self-training sub-network. We conduct cooperative alignment of different domains at image level, feature level, and output level. Specifically, we transform the appearance of images across domains and enhance domain invariance by adversarial learning in multiple aspects to achieve unsupervised segmentation of the target modality. We validate the TSP-UDANet on the MMWHS (unpaired MRI and CT images), MS-CMRSeg (cross-modality MRI images), and M&Ms (cross-vendor MRI images) datasets. The experimental results demonstrate excellent segmentation performance and generalizability for unlabeled target modality images. [ABSTRACT FROM AUTHOR]

Based on the fundamental conception of hysteretic systems random vibration, this paper presents a simplified model to analyze the hysteretic nonlinear dynamic response of concrete covering consolidation grouting. The proposed model aims at capturing the hysteretic characteristics of the concrete covering nonlinear behavior and revealing the importance of grouting pressure dynamic load affecting the concrete covering uplift behavior. To this end, the proposed approach considers the concrete covering as Bernoulli-Euler beam, and then incorporating the Bouc-Wen model, simulates the soil force on the concrete covering, the one that beneath the concrete covering can be considered as hysteresis spring and dashpot in parallel. According to the actual grouting parameters, amplitude-frequency response characteristics of concrete covering are discussed under different external load. A comparison of model calculation results and real-field experiments are used to evaluate the effectiveness of the presented method, the results show that the predictions of the model correspond with the measured values. [ABSTRACT FROM AUTHOR]

The effects of polyethylene glycol (PEG) of different molecular (1000, 2000), glycerol, ethylene glycol on the catalytic activity of tryptophan synthase were studied. The results indicated that the addition of PEG 2000 increased the enzymatic activity of tryptophan synthase. The enzymatic activity of tryptophan synthase was enhanced 25.2% by 10 g L PEG 2000. Reaction conditions were optimized by using 10 g L PEG 2000 at pH 9 and 40 °C. L-Serine conversion rate reach 89.9% under the optimal conditions. The kinetic parameters indicated the specificity of TSase to substrate was improved. Graphical Abstract: The mechanism of reaction catalyzed by tryptophan synthase [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

In order to assess the compliance of ingested wireless device (IWD) with related international safety guidelines, the studies on the biological effects and the signal intensity of an IWD in two realistic human body models using the finite-difference time-domain (FDTD) method are reported in this paper. Simulation studies are carried out in 21 scenarios where the IWD is placed at seven positions with three orientations, for each of the two human models. Specific absorption rate (SAR), temperature rise, near fields and far fields are analyzed in the 21 scenarios at four selected operation frequencies of 430 and 800 MHz, and 1.2 and 2.4 GHz, respectively. Our study indicates that the radiation intensity outside of the human body decreases with the increase of operation frequency. Furthermore, the radiation characteristics of the IWD are orientation and position dependent. The polarization of electric field outside of the human body is similar to that of the Radio Frequency (RF) source. As far as the compliance of safety is concerned, among all the simulated scenarios the maxima of the averaged-1g and averaged-10g SARs can reach 3.71 W/kg and 1.37 W/kg at the input power of 25 mW, respectively. [ABSTRACT FROM AUTHOR]

Abstract: The automatic recognition of pulse images is the key in the research of computerized pulse diagnosis. In order to automatically differentiate the pulse patterns by using small samples in pulse diagnosis, a fuzzy neural network for classifying pulse images based on the knowledge of experts in traditional Chinese pulse diagnosis was designed. The designed classifier can make hard decision and soft decision for identifying 16 patterns of pulse images at the accuracy of 90.25%, which is better than the results that are achieved by back propagation neural network. [Copyright &y& Elsevier]

Field survey, hydroponic culture, and pot experiments were carried out to examine and characterize cadmium (Cd) and zinc (Zn) uptake and accumulation by Sedum jinianum, a plant species native to China. Shoot Cd and Zn concentrations in S. jinianum growing on a lead/Zn mine area reached 103-478 and 4165-8349 mg kg-1 (DM), respectively. The shoot Cd concentration increased with the increasing Cd supply, peaking at 5083 mg kg-1 (DM) when grown in nutrient at a concentration of 100 µmol L-1 for 32 d, and decreased as the solution concentration increased from 200 to 400 µmol L-1. The shoot-to-root ratio of plant Cd concentrations was > 1 when grown in solution Cd concentrations = 200 µmol L-1. Foliar, stem, and root Zn concentrations increased linearly with the increasing Zn level from 1 to 9600 µmol L-1. The Zn concentrations in various plant parts decreased in the order roots > stem > leaves, with maximum concentrations of 19.3, 33.8, and 46.1 g kg-1 (DM), respectively, when plants were grown at 9600 µmol Zn L-1 for 32 d. Shoot Cd concentrations reached 16.4 and 79.8 mg kg-1 (DM) when plants were grown in the pots of soil with Cd levels of 2.4mg kg-1 and 9.2 mg kg-1, respectively. At soil Zn levels of 619 and 4082 mg kg-1, shoot Zn concentrations reached 1560 and 15,558 mg kg-1 (DM), respectively. The results indicate that S. jinianum is a Cd hyperaccumulator with a high capacity to accumulate Zn in the shoots. [ABSTRACT FROM AUTHOR]

Three strong earthquakes with magnitudes of Mw 8.4, Mw 7.9 and Mw 7.0 occurred in the sea west of Sumatra Island on September 12 and 13, 2007. We relocated the epicenters and focal depths of the three events by means of the reversal-time imaging technique using broadband digital seismic data from worldwide stations ranging from 30° to 90°, imaged the spatiotemporal variation of the energy radiation sources by means of the nonplane wave array technique using the broadband digital seismic data from a generalized array made up of 33 stations of the Capital Region Digital Seismograph Network (CRDSN), and obtained the rupture duration times, extents and rupture velocities. Also, we discussed the correlations between the locations of the energy radiation sources of the three events. [ABSTRACT FROM AUTHOR]

Pulse diagnosis is a convenient, inexpensive, painless, and non-invasive diagnosis method. Quantifying pulse diagnosis is to acquire and record pulse waveforms by a set of sensor firstly, and then analyze these pulse waveforms. However, respiration and artifact motion during pulse waveform acquisition can introduce baseline wander. It is necessary, therefore, to remove the pulse waveform's baseline wander in order to perform accurate pulse waveform analysis. This paper presents a wavelet-based cascaded adaptive filter (CAF) to remove the baseline wander of pulse waveform. To evaluate the level of baseline wander, we introduce a criterion: energy ratio (ER) of pulse waveform to its baseline wander. If the ER is more than a given threshold, the baseline wander can be removed only by cubic spline estimation; otherwise it must be filtered by, in sequence, discrete Meyer wavelet filter and the cubic spline estimation. Compared with traditional methods such as cubic spline estimation, morphology filter and Linear-phase finite impulse response (FIR) least-squares-error digital filter, the experimental results on 50 simulated and 500 real pulse signals demonstrate the power of CAF filter both in removing baseline wander and in preserving the diagnostic information of pulse waveforms. This CAF filter also can be used to remove the baseline wander of other physiological signals, such as ECG and so on. [Copyright &y& Elsevier]

Falls among the elderly are a common and serious health risk that can lead to physical injuries and other complications. To promptly detect and respond to fall events, radar-based fall detection systems have gained widespread attention. In this paper, a deep learning model is proposed based on the frequency spectrum of radar signals, called the convolutional bidirectional long short-term memory (CB-LSTM) model. The introduction of the CB-LSTM model enables the fall detection system to capture both temporal sequential and spatial features simultaneously, thereby enhancing the accuracy and reliability of the detection. Extensive comparison experiments demonstrate that our model achieves an accuracy of 98.83% in detecting falls, surpassing other relevant methods currently available. In summary, this study provides effective technical support using the frequency spectrum and deep learning methods to monitor falls among the elderly through the design and experimental validation of a radar-based fall detection system, which has great potential for improving quality of life for the elderly and providing timely rescue measures. [ABSTRACT FROM AUTHOR]

BACKGROUND: Coronary artery segmentation is a prerequisite in computer-aided diagnosis of Coronary Artery Disease (CAD). However, segmentation of coronary arteries in Coronary Computed Tomography Angiography (CCTA) images faces several challenges. The current segmentation approaches are unable to effectively address these challenges and existing problems such as the need for manual interaction or low segmentation accuracy. OBJECTIVE: A Multi-scale Feature Learning and Rectification (MFLR) network is proposed to tackle the challenges and achieve automatic and accurate segmentation of coronary arteries. METHODS: The MFLR network introduces a multi-scale feature extraction module in the encoder to effectively capture contextual information under different receptive fields. In the decoder, a feature correction and fusion module is proposed, which employs high-level features containing multi-scale information to correct and guide low-level features, achieving fusion between the two-level features to further improve segmentation performance. RESULTS: The MFLR network achieved the best performance on the dice similarity coefficient, Jaccard index, Recall, F1-score, and 95% Hausdorff distance, for both in-house and public datasets. CONCLUSION: Experimental results demonstrate the superiority and good generalization ability of the MFLR approach. This study contributes to the accurate diagnosis and treatment of CAD, and it also informs other segmentation applications in medicine. [ABSTRACT FROM AUTHOR]

Abstract: An economical method for production of S-phenyl-l-cysteine from keratin acid hydrolysis wastewater (KHW) containing l-serine was developed by recombinant tryptophan synthase. This study provides us with an alternative KHW utilization strategy to synthesize S-phenyl-l-cysteine. Tryptophan synthase could efficiently convert l-serine contained in KHW to S-phenyl-l-cysteine at pH 9.0, 40°C and Trion X-100 of 0.02%. In a scale up study, l-serine conversion rate reach 97.1% with a final S-phenyl-l-cysteine concentration of 38.6gl−1. [Copyright &y& Elsevier]

• Biosynthesis of L-theanine was investigated by ultrasound. • The yield of L-theanine is 2.61 times higher than that obtained without ultrasound. • This is an effective strategy for improvement of L-theanine bioconversion. A mutant library of the key amino acid residue site E387 in γ-glutamyltranspeptidase was constructed to screen the mutant enzymes with significantly improved thermal stability (E387Q). The reaction temperature of the mutant enzyme (E387Q) was 10 ℃ higher than that of the parent enzyme. Ultrasound-assisted synthesis of L-theanine by γ-glutamyltranspeptidase was investigated. The effects of ultrasonic power, reaction pH and substrate concentration on the enzymatic synthesis of L-theanine were studied by the response surface method. The results showed that the optimal process conditions are ultrasonic power of 100 W, reaction pH of 9, substrate L-glutamine concentration of 120 mmol/L, reaction temperature of 45 ℃, and L-theanine yield of 89.1%. The yield of L-theanine is 2.61 times higher than that obtained without ultrasound. Ultrasound can significantly promote the synthesis of L-theanine by γ-glutamyltranspeptidase. [ABSTRACT FROM AUTHOR]

• Graphene nanoplatelets were prepared by a mechanochemistry method. • Stretchable polyurethane-urea nanocomposites were developed as sensing materials. • A sensor revealed a strain sensitivity of 17.57. • A sensor was designed to simultaneously acquire temperature and strain signals. • The healing efficiency for sensitivity of up to 70.46 %. Flexible wearable electronic devices offer promising potential for monitoring physiological signals. However, creating a single sensor that integrates high tensile strength, sensitivity, self-healing capabilities and a wide working range presents a significant and multifaceted challenge. This study reports a novel nanocomposite consisting of polyurethane-urea elastomer (PUU) and graphene nanoplatelets (E-GNPs) that are mechanochemically modified with diethyltoluene diamine ethacure 100. A low electrical percolation threshold was observed at 4.17 vol% E-GNPs. The sensor based on the PUU nanocomposite at 7 vol% of E-GNPs has revealed a gauge factor up to 17.57 and a wide working range of 361.76 % with high tensile strength of 19.73 MPa. It can withstand 20,000 cycles at 50 % strain. The sensor exhibits negative temperature dependence at 20–100 °C, with a resolution of 0.01/°C at 36–40 °C. Treatments with solvents and heat enable a healing efficiency for sensitivity of up to 70.46 %. The healable sensor enables real-time monitoring of temperature and strain signals, making it ideal for wearable devices in human health and sports monitoring. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: The curved planar reformation (CPR) technique is one of the most commonly used methods in clinical practice to locate coronary arteries in medical images. Purpose: The artery centerline is the cornerstone for the generation of the CPR image. Here, we describe the development of a new fully automatic artery centerline tracker with the aim of increasing the efficiency and accuracy of the process. Methods: We propose a COronary artery Centerline Tracker (COACT) framework which consists of an ostium point finder (OPFinder) model, an intersection point detector (IPDetector) model and a set of centerline tracking strategies. The output of OPFinder is the ostium points. The function of the IPDetector is to predict the intersections of a sample sphere and the centerlines. The centerline tracking process starts from two ostium points detected by the OPFinder, and combines the results of the IPDetector with a series of strategies to gradually reconstruct the coronary artery centerline tree. Results: Two coronary CT angiography (CCTA) datasets were used to validate the models. Dataset1 contains 160 cases (32 for test and 128 for training) and dataset2 contains 70 cases (20 for test and 50 for training). The results show that the average distance between the ostium points predicted by the OPFinder and the manually annotated ostium points was 0.88 mm, which is similar to the differences between the results obtained by two observers (0.85 mm). For the IPDetector, the average overlap of the predicted and ground truth intersection points was 97.82% and this is also close to the inter‐observer agreement of 98.50%. For the entire coronary centerline tree, the overlap between the results obtained by COACT and the gold standard was 94.33%, which is slightly lower than the inter‐observer agreement, 98.39%. Conclusions: We have developed a fully automatic centerline tracking method for CCTA scans and achieved a satisfactory result. The proposed algorithms are also incorporated in the medical image analysis platform TIMESlice (https://slice‐doc.netlify.app) for further studies. [ABSTRACT FROM AUTHOR]

The Tanlu Fault Zone in eastern China stretches more than 2,400 km and is a significant, active, feature in the tectonics of East Asia. Here, we show the results of local earthquake travel‐time tomographical approach based on a comprehensive and systematic set of seismic data collected from 2008 to 2018 along the Central South Segment of the Tanlu Fault Zone. According to the model, the uppermost 0–10 km of the crust shows a close relationship between seismic velocity and the lithological properties of surface geological units. The middle crust at 10–20 km depths exhibits a strong connection between its high‐low velocity transitions and sites of augmented seismic activity. The top mantle at 34 km depths has lower velocities in the western region in comparison to the east, implying that the seismic Moho is deeper in the western area. These characteristics may reflect spatial variations in the destruction of the North China Craton. [ABSTRACT FROM AUTHOR]

Purpose: Epicardial fat is the adipose tissue between the serosal pericardial wall layer and the visceral layer. It is distributed mainly around the atrioventricular groove, atrial septum, ventricular septum and coronary arteries. Studies have shown that the density, thickness, volume and other characteristics of epicardial adipose tissue (EAT) are independently correlated with a variety of cardiovascular diseases. Given this association, the accurate determination of EAT volume is an essential aim of future research. Therefore, the purpose of this study was to establish a framework for fully automatic EAT segmentation and quantification in coronary computed tomography angiography (CCTA) scans. Methods: A set of 103 scans are randomly selected from our medical center. An automatic pipeline has been developed to segment and quantify the volume of EAT. First, a multi‐slice deep neural network is used to simultaneously segment the pericardium in multiple adjacent slices. Then a deformable model is employed to reduce false positive and negative regions in the segmented binary pericardial images. Finally, the pericardium mask is used to define the region of interest (ROI) and the threshold method is utilized to extract the pixels ranging from −175 Hounsfield units (HU) to −15 HU for the segmentation of EAT. Results: The Dice indices of the pericardial segmentation using the proposed method with respect to the manual delineation results of two radiology experts were 97.1% ± 0.7% and 96.9% ± 0.6%, respectively. The inter‐observer variability was also assessed, resulting in a Dice index of 97.0% ± 0.7%. For the EAT segmentation results, the Dice indices between the proposed method and the two radiology experts were 93.4% ± 1.5% and 93.3% ± 1.3%, respectively, and the same measurement between the experts themselves was 93.6% ± 1.9%. The Pearson's correlation coefficients between the EAT volumes computed from the results of the proposed method and the manual delineation by the two experts were 1.00 and 0.99 and the same coefficients between the experts was 0.99. Conclusions: This work describes the development of a fully automatic EAT segmentation and quantification method from CCTA scans and the results compare favorably with the assessments of two independent experts. The proposed method is also packaged with a graphical user interface which can be found at https://github.com/MountainAndMorning/EATSeg. [ABSTRACT FROM AUTHOR]

Background: S-Phenyl-L-cysteine is regarded as having potential applicability as an antiretroviral/protease inhibitor for human immunodeficiency virus (HIV). In the present study, optically active S-phenyl-L-cysteine was prepared in a highly efficient manner from inexpensive bromobenzene using tryptophan synthase through a chemoenzymatic method. Results: The chemoenzymatic method used a four-step reaction sequence. The process started with the reaction of magnesium and bromobenzene, followed by a Grignard reaction, and then hydrolysis and enzymatic synthesis using tryptophan synthase. Through this approach, S-phenyl-L-cysteine was chemoenzymatically synthesized using tryptophan synthase from thiophenol and L-serine as the starting material. Conclusions: High-purity, optically active S-phenyl-L-cysteine was efficiently and inexpensively obtained in a total yield of 81.3% (> 99.9% purity). [ABSTRACT FROM AUTHOR]

The physiological processes and mechanisms of an arterial system are complex and subtle. Physics-based models have been proven to be a very useful tool to simulate actual physiological behavior of the arteries. The current physics-based models include high-dimensional models (2D and 3D models) and low-dimensional models (0D, 1D and tube-load models). High-dimensional models can describe the local hemodynamic information of arteries in detail. With regard to an exact model of the whole arterial system, a high-dimensional model is computationally impracticable since the complex geometry, viscosity or elastic properties and complex vectorial output need to be provided. For low-dimensional models, the structure, centerline and viscosity or elastic properties only need to be provided. Therefore, low-dimensional modeling with lower computational costs might be a more applicable approach to represent hemodynamic properties of the entire arterial system and these three types of low-dimensional models have been extensively used in the study of cardiovascular dynamics. In recent decades, application of physics-based models to estimate central aortic pressure has attracted increasing interest. However, to our best knowledge, there has been few review paper about reconstruction of central aortic pressure using these physics-based models. In this paper, three types of low-dimensional physical models (0D, 1D and tube-load models) of systemic arteries are reviewed, the application of three types of models on estimation of central aortic pressure is taken as an example to discuss their advantages and disadvantages, and the proper choice of models for specific researches and applications are advised. [ABSTRACT FROM AUTHOR]

Background: Pulmonary embolism is a kind of cardiovascular disease that threatens human life and health. Since pulmonary embolism exists in the pulmonary artery, improving the segmentation accuracy of pulmonary artery is the key to the diagnosis of pulmonary embolism. Traditional medical image segmentation methods have limited effectiveness in pulmonary artery segmentation. In recent years, deep learning methods have been gradually adopted to solve complex problems in the field of medical image segmentation. Purpose: Due to the irregular shape of the pulmonary artery and the adjacent‐complex tissues, the accuracy of the existing pulmonary artery segmentation methods based on deep learning needs to be improved. Therefore, the purpose of this paper is to develop a segmentation network, which can obtain higher segmentation accuracy and further improve the diagnosis effect. Methods: In this study, the pulmonary artery segmentation performance from the network model and loss function is improved, proposing a pulmonary artery segmentation network (PA‐Net) to segment the pulmonary artery region from 2D CT images. Reverse Attention and edge attention are used to enhance the expression ability of the boundary. In addition, to better use feature information, the channel attention module is introduced in the decoder to highlight the important channel features and suppress the unimportant channels. Due to blurred boundaries, pixels near the boundaries of the pulmonary artery may be difficult to segment. Therefore, a new contour loss function based on the active contour model is proposed in this study to segment the target region by assigning dynamic weights to false positive and false negative regions and accurately predict the boundary structure. Results: The experimental results show that the segmentation accuracy of this proposed method is significantly improved in comparison with state‐of‐the‐art segmentation methods, and the Dice coefficient is 0.938 ± 0.035, which is also confirmed from the 3D reconstruction results. Conclusions: Our proposed method can accurately segment pulmonary artery structure. This new development will provide the possibility for further rapid diagnosis of pulmonary artery diseases such as pulmonary embolism. Code is available at https://github.com/Yuanyan19/PA‐Net. [ABSTRACT FROM AUTHOR]

Background: Exercise is accepted as an important contribution to the rehabilitation of patients with cardiovascular disease (CVD). This study aims to better understand the possible causes for lack of consensus and reviews the effects of three exercise modalities (aerobic, resistance and combined exercise) on central hemodynamics, arterial stiffness and cardiac function for better rehabilitation strategies in CVD. Methods: The electronic data sources, Cochrane Library, MEDLINE, Web of Science, EBSCO (CINAHL), and ScienceDirect from inception to July 2017 were searched for randomized controlled trials (RCTs) investigating the effect of exercise modalities in adult patients with CVD. The effect size was estimated as mean differences (MD) with 95% confidence intervals (CI). Subgroup analysis and meta-regression were used to study potential moderating factors. Results: Thirty-eight articles describing RCTs with a total of 2089 patients with CVD were included. The pooling revealed that aerobic exercise [MD(95%CI) = -5.87 (-8.85, -2.88), P = 0.0001] and resistance exercise [MD(95%CI) = -7.62 (-10.69, -4.54), P<0.00001] significantly decreased aortic systolic pressure (ASP). Resistance exercise significantly decreased aortic diastolic pressure [MD(95%CI) = -4(-5.63, -2.37), P<0.00001]. Aerobic exercise significantly decreased augmentation index (AIx) based on 24-week exercise duration and patients aged 50–60 years. Meanwhile, aerobic exercise significantly improved carotid-femoral pulse wave velocity (cf-PWV) [MD(95%CI) = -0.42 (-0.83, -0.01), P = 0.04], cardiac output (CO) [MD(95% CI) = 0.36(0.08, 0.64), P = 0.01] and left ventricular ejection fraction (LVEF) [MD(95%CI) = 3.02 (2.11, 3.93), P<0.00001]. Combined exercise significantly improved cf-PWV [MD(95%CI) = -1.15 (-1.95, -0.36), P = 0.004] and CO [MD(95% CI) = 0.9 (0.39, 1.41), P = 0.0006]. Conclusions: Aerobic and resistance exercise significantly decreased ASP, and long-term aerobic exercise reduced AIx. Meanwhile, aerobic and combined exercise significantly improved central arterial stiffness and cardiac function in patients with CVD. These findings suggest that a well-planned regime could optimize the beneficial effects of exercise and can provide some evidence-based guidance for those involved in cardiovascular rehabilitation of patients with CVD. [ABSTRACT FROM AUTHOR]

Objective: To investigate the possibility of false-negative occurrence of non-specific benign pathological results on CT-guided transthoracic lung core-needle biopsy and identify risk factors for false-negative results. Methods: The clinical, imaging, and surgical data of 403 lung biopsy patients were retrospectively analyzed. Patients were divided into true-negative and false-negative (FN) groups according to the final diagnosis. Univariate analysis was used to compare the variables in two groups for statistical differences, and multivariate analysis was used to clarify the risk factors associated with FN results. Results: Of the 403 lesions, 332 were finally confirmed as benign and 71 to be malignant, with a FN rate of 17.6%. Older patient age (P = 0.01), burr sign (P = 0.00), and pleural traction sign (P = 0.02) were independent risk factors for FN results. The area under the receiver operating characteristic (ROC) curve's area under curve (AUC) was 0.73. Conclusion: CT-guided transthoracic lung core-needle biopsy has a high diagnostic accuracy and low rate of FN results. Older patient age, the burr sign, and the pleural traction sign are independent risk factors for FN results that should be monitored prior to surgery to reduce the risk of FN results. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID‐19) epidemic has devastating effects on personal health around the world. It is significant to achieve accurate segmentation of pulmonary infection regions, which is an early indicator of disease. To solve this problem, a deep learning model, namely, the content‐aware pre‐activated residual UNet (CAPA‐ResUNet), was proposed for segmenting COVID‐19 lesions from CT slices. In this network, the pre‐activated residual block was used for down‐sampling to solve the problems of complex foreground and large fluctuations of distribution in datasets during training and to avoid gradient disappearance. The area loss function based on the false segmentation regions was proposed to solve the problem of fuzzy boundary of the lesion area. This model was evaluated by the public dataset (COVID‐19 Lung CT Lesion Segmentation Challenge—2020) and compared its performance with those of classical models. Our method gains an advantage over other models in multiple metrics. Such as the Dice coefficient, specificity (Spe), and intersection over union (IoU), our CAPA‐ResUNet obtained 0.775 points, 0.972 points, and 0.646 points, respectively. The Dice coefficient of our model was 2.51% higher than Content‐aware residual UNet (CARes‐UNet). The code is available at https://github.com/malu108/LungInfectionSeg. [ABSTRACT FROM AUTHOR]

Despite their great advancement, current pedestrian detection methods focus on single static images, which fail to employ richer information available from the video sequences. Compared with still images, videos can offer temporal information of objects in the time dimension, thus providing the potential to obtain more robust detection performance. Here, a novel pedestrian detection method based on visible part detection and temporal calibration is proposed. Specifically, a part‐aware module to predict the visible body part of each pedestrian instance, which enables us to obtain precise motion information of partially occluded pedestrians in a video sequence, is first developed. Then, the temporal coherence for each pedestrian instance based on the predicted motion information is constructed. After that, an adaptive temporal calibration method is introduced to effectively calibrate the final detection result. This method on two video pedestrian detection benchmarks, that is, Caltech‐New and MOT17Det, is evaluated. Experimental results show that this method performs favourably against existing pedestrian detection approaches. [ABSTRACT FROM AUTHOR]

Understanding the stress patterns produced by microbubbles (MB) in blood vessels is important in enhancing the efficacy and safety of ultrasound-assisted therapy, diagnosis, and drug delivery. In this study, the wall stress produced by the non-spherical oscillation of MBs within the lumen of micro-vessels was numerically analyzed using a three-dimensional finite element method. We systematically simulated configurations containing an odd number of bubbles from three to nine, equally spaced along the long axis of the vessel, insonated at an acoustic pressure of 200 kPa. We observed that 3 MBs were sufficient to simulate the stress state of an infinite number of bubbles. As the bubble spacing increased, the interaction between them weakened to the point that they could be considered to act independently. In the relationship between stress and acoustic frequency, there were differences between the single and 3 MB cases. The stress induced by 3 MBs was greater than the single bubble case. When the bubbles were near the wall, the shear stress peak was largely independent of vessel radius, but the circumferential stress peak increased with the radius. This study offers further insight into our understanding of the magnitude and distribution of stresses produced by multiple ultrasonically excited MBs inside capillaries. [ABSTRACT FROM AUTHOR]

The analysis of vascular impedance by monitoring blood pressure and volume pulse waves is an effective addition to the techniques for the early diagnosis and treatment of cardiovascular disease, which should be made at the same site simultaneously for maximum accuracy measurements. However, the current challenge is that there is still a lack of devices that satisfy both sensing functions simultaneously. In this study, we intend to develop a combined resistive and photoelectric sensor that can monitor both types of pulse waves in real time at the same location. A graphene/PDMS rubber composite serves as resistance element for monitoring the pressure pulse waves. By varying the graphene contents of the composites, it is found that the optimal graphene weight fraction was 11% giving a sensitivity of 210.6 and a response time of 18 ms. The tensile test shows high stability after 10,000 cycles with a resistance retention of 91.74%. The photoelectric component of the sensor monitors the blood volume pulse waves using the well-established principle of reflection photoplethysmography. The combined resistance-photoelectric sensor has good stability, high sensitivity and is found to be suitable for monitoring the blood pressure and volume waves at the same time at several anatomical sites close to superficial arteries. We conclude that this bimodal sensor is able to provide the data required to estimate peripheral vascular impedance by analyzing the changes in pressure and blood volume of peripheral arteries, thus adding a novel measure for cardiovascular function to a new generation of wearable electronics. [ABSTRACT FROM AUTHOR]

Background: Many cardiovascular diseases are closely related to the composition of epicardial adipose tissue (EAT). Accurate segmentation of EAT can provide a reliable reference for doctors to diagnose the disease. The distribution and composition of EAT often have significant individual differences, and the traditional segmentation methods are not effective. In recent years, deep learning method has been gradually introduced into EAT segmentation task. Purpose: The existing EAT segmentation methods based on deep learning have a large amount of computation and the segmentation accuracy needs to be improved. Therefore, the purpose of this paper is to develop a lightweight EAT segmentation network, which can obtain higher segmentation accuracy with less computation and further alleviate the problem of false‐positive segmentation. Methods: First, the obtained computed tomography was preprocessed. That is, the threshold range of EAT was determined to be −190, −30 HU according to prior knowledge, and the non‐adipose pixels were excluded by threshold segmentation to reduce the difficulty of training. Second, the image obtained after thresholding was input into the lightweight RDU‐Net network to perform the training, validating, and testing process. RDU‐Net uses a residual multi‐scale dilated convolution block in order to extract a wider range of information without changing the current resolution. At the same time, the form of residual connection is adopted to avoid the problem of gradient expansion or gradient explosion caused by too deep network, which also makes the learning easier. In order to optimize the training process, this paper proposes PNDiceLoss, which takes both positive and negative pixels as learning targets, fully considers the class imbalance problem, and appropriately highlights the status of positive pixels. Results: In this paper, 50 CCTA images were randomly selected from the hospital, and the commonly used Dice similarity coefficient (DSC), Jaccard similarity, accuracy (ACC), specificity (SP), precision (PC), and Pearson correlation coefficient are used as evaluation metrics. Bland–Altman analysis results show that the extracted EAT volume is consistent with the actual volume. Compared with the existing methods, the segmentation results show that the proposed method achieves better performance on these metrics, achieving the DSC of 0.9262. The number of false‐positive pixels has been reduced by more than half. Pearson correlation coefficient reached 0.992, and linear regression coefficient reached 0.977 when measuring the volume of EAT obtained. In order to verify the effectiveness of the proposed method, experiments are carried out in the cardiac fat database of VisualLab. On this database, the proposed method also achieved good results, and the DSC value reached 0.927 in the case of only 878 slices. Conclusions: A new method to segment and quantify EAT is proposed. Comprehensive experiments show that compared with some classical segmentation algorithms, the proposed method has the advantages of shorter time‐consuming, less memory required for operations, and higher segmentation accuracy. The code is available at https://github.com/lvanlee/EAT_Seg/tree/main/EAT_seg. [ABSTRACT FROM AUTHOR]

Extended range (10-30 d) heavy rain forecasting is difficult but performs an important function in disaster prevention and mitigation. In this paper, a nonlinear cross prediction error (NCPE) algorithm that combines nonlinear dynamics and statistical methods is proposed. The method is based on phase space reconstruction of chaotic single-variable time series of precipitable water and is tested in 100 global cases of heavy rain. First, nonlinear relative dynamic error for local attractor pairs is calculated at different stages of the heavy rain process, after which the local change characteristics of the attractors are analyzed. Second, the eigen-peak is defined as a prediction indicator based on an error threshold of about 1.5, and is then used to analyze the forecasting validity period. The results reveal that the prediction indicator features regarded as eigenpeaks for heavy rain extreme weather are all reflected consistently, without failure, based on the NCPE model; the prediction validity periods for 1-2 d, 3-9 d and 10-30 d are 4, 22 and 74 cases, respectively, without false alarm or omission. The NCPE model developed allows accurate forecasting of heavy rain over an extended range of 10-30 d and has the potential to be used to explore the mechanisms involved in the development of heavy rain according to a segmentation scale. This novel method provides new insights into extended range forecasting and atmospheric predictability, and also allows the creation of multi-variable chaotic extreme weather prediction models based on high spatiotemporal resolution data. [ABSTRACT FROM AUTHOR]

• RNF99 was significantly decreased in lung of ALI. • FA significantly via regulation of RNF99/TRAF6/NF-κB signal pathway. The aim of this study was to investigated the effects of forsythiaside A (FA) on acute lung injury (ALI). The lung tissue pathological was detected by hematoxylin-eosin staining (HE) staining. Wet weight/dry weight (w/d) of the lung in mice was measured. Cytokine such as interleukin 1β (IL-1β), IL-6 and tumor necrosis factor-α (TNF-α) were also detected. Compared with the vector group, the protein expression levels of TRAF6 and TAK1 the RNF99 group were significantly reduced. Ubiquitinated TRAF6 protein was increased after knockdown of RNF99. Finally, it was found that FA significantly ameliorated ALI via regulation of RNF99/TRAF6/NF-κB signal pathway. In conclusion, RNF99 was an important biomarker in ALI and FA alleviated ALI via RNF99/ TRAF6/NF-κB signal pathway. [ABSTRACT FROM AUTHOR]

• We propose a new algorithm to estimate the aortic BP waveform non-invasively. • Imaging is used to obtain aortic flow and diameter waveforms to derive aortic PWV. • Aortic BP is reconstructed from PWV and peripheral pressure recorded tonometrically. • The algorithm's accuracy is validated from invasive and non-invasive reference values. • This new approach gives central BP and additional clinically valuable information. Aortic blood pressure (ABP) is a more effective prognostic indicator of cardiovascular disease than peripheral blood pressure. A highly accurate algorithm for non-invasively deriving the ABP wave, based on ultrasonic measurement of aortic flow combined with peripheral pulse wave measurements, has been proposed elsewhere. However, it has remained at the proof-of-concept stage because it requires a priori knowledge of the ABP waveform to calculate aortic pulse wave velocity (PWV). The objective of this study is to transform this proof-of-concept algorithm into a clinically feasible technique. We used the Bramwell-Hill equation to non-invasively calculate aortic PWV which was then used to reconstruct the ABP waveform from non-invasively determined aortic blood flow velocity, aortic diameter, and radial pressure. The two aortic variables were acquired by an ultrasound system from 90 subjects, followed by recordings of radial pressure using a SphygmoCor device. The ABPs estimated by the new algorithm were compared with reference values obtained by cardiac catheterization (invasive validation, 8 subjects aged 62.3 ± 12.7 years) and a SphygmoCor device (non-invasive validation, 82 subjects aged 45.0 ± 17.8 years). In the invasive comparison, there was good agreement between the estimated and directly measured pressures: the mean error in systolic blood pressure (SBP) was 1.4 ± 0.8 mmHg; diastolic blood pressure (DBP), 0.9 ± 0.8 mmHg; mean blood pressure (MBP), 1.8 ± 1.2 mmHg and pulse pressure (PP), 1.4 ± 1.1 mmHg. In the non-invasive comparison, the estimated and directly measured pressures also agreed well: the errors being: SBP, 2.0 ± 1.4 mmHg; DBP, 0.8 ± 0.1 mmHg; MBP, 0.1 ± 0.1 mmHg and PP, 2.3 ± 1.6 mmHg. The significance of the differences in mean errors between calculated and reference values for SBP, DBP, MBP and PP were assessed by paired t -tests. The agreement between the reference methods and those obtained by applying the new approach was also expressed by correlation and Bland-Altman plots. The new method proposed here can accurately estimate ABP, allowing this important variable to be obtained non-invasively, using standard, well validated measurement techniques. It thus has the potential to relocate ABP estimation from a research environment to more routine use in the cardiac clinic. A highly accurate algorithm for non-invasively deriving the ABP wave has been proposed elsewhere. However, it has remained at the proof-of-concept stage because it requires a priori knowledge of the ABP waveform to calculate aortic pulse wave velocity (PWV). This study aims to transform this proof-of-concept algorithm into a clinically feasible technique. We used the Bramwell-Hill equation to non-invasively calculate aortic PWV which was then used to reconstruct the ABP waveform. The ABPs estimated by the new algorithm were compared with reference values obtained by cardiac catheterization or a SphygmoCor device. The results showed that there was good agreement between the estimated and directly measured pressures. The new method proposed can accurately estimate ABP, allowing this important variable to be obtained non-invasively, using standard, well validated measurement techniques. It thus has the potential to relocate ABP estimation from a research environment to more routine use in the cardiac clinic. [ABSTRACT FROM AUTHOR]

Ballistocardiography (BCG) is considered a good alternative to HRV analysis with its non-contact and unobtrusive acquisition characteristics. However, consensus about its validity has not yet been established. In this study, 50 healthy subjects (26.2 ± 5.5 years old, 22 females, 28 males) were invited. Comprehensive statistical analysis, including Coefficients of Variation (CV), Lin's Concordance Correlation Coefficient (LCCC), and Bland-Altman analysis (BA ratio), were utilized to analyze the consistency of BCG and ECG signals in HRV analysis. If the methods gave different answers, the worst case was taken as the result. Measures of consistency such as Mean, SDNN, LF gave good agreement (the absolute value of CV difference < 2%, LCCC > 0.99, BA ratio < 0.1) between J-J (BCG) and R-R intervals (ECG). pNN50 showed moderate agreement (the absolute value of CV difference < 5%, LCCC > 0.95, BA ratio < 0.2), while RMSSD, HF, LF/HF indicated poor agreement (the absolute value of CV difference ≥ 5% or LCCC ≤ 0.95 or BA ratio ≥ 0.2). Additionally, the R-R intervals were compared with P-P intervals extracted from the pulse wave (PW). Except for pNN50, which exhibited poor agreement in this comparison, the performances of the HRV indices estimated from the PW and the BCG signals were similar. [ABSTRACT FROM AUTHOR]

Cell fusion is an essential event in many biological processes and has gained increasing attention in the field of biotechnology. In this study, we demonstrate an effective and convenient strategy for cell capture, pairing, and fusion based on oscillating bubbles within an acoustofluidic device. Multirectangular structures of the same size were fabricated at the sidewall of polydimethylsiloxane to generate monodisperse microbubbles. These microbubbles oscillated with a similar amplitude under single-frequency acoustic excitation. Cells were simultaneously captured and paired on the surface of the oscillating bubbles within 40 ms, and the efficiency reached approximately 90%. Homotypic or heterotypic cell membrane fusion was achieved within 15 and 20 min, respectively. More importantly, the homotypic fused cells enabled migration and proliferation at 24 h, indicating that the important biological functions were not altered. [ABSTRACT FROM AUTHOR]

A moment magnitude (M w) 5.0 earthquake hit Qiaojia, Yunnan, China on 18 May 2020. Its hypocentre is only approximately 20 km away from the Baihetan reservoir, the second largest hydropower station in China. The Baihetan Reservoir is located at the junction of multiple fault zones on the eastern boundary of the Sichuan-Yunnan rhombic block, an area with high background seismic activity. The Baihetan Reservoir was planned to be impounded in April 2021 and the M w 5.0 earthquake occurred during its water-retaining. Thus, it is critical to investigate the seismogenesis of the Qiaojia M w 5.0 main shock and evaluate the risk of inducing earthquakes near the Baihetan Reservoir after impoundment. In this study, we built a complete and accurate earthquake catalogue to analyse seismicity in the reservoir area before and after the M w 5.0 Qiaojia earthquake. We adopted a machine learning-based seismic phase picker, PhaseNet, to automatically detect seismic picks from continuous raw seismic data. Seismic phase picks were associated and located using sequential earthquake association and location methods, including REAL, VELEST and hypoDD. We eventually obtained high-precision locations of 1640 earthquakes by the hypoDD. The distribution of earthquake locations indicates that a concealed fault nearly vertical to the surface accommodated the M w 5.0 Qiaojia main shock. The majority of its aftershocks is located within a narrow depth range of 8–13 km, indicating that the stresses in the hypocentral area were concentrated near the hypocentre of the M w 5.0 earthquake. Along with focal mechanism solutions, we suggested that the M w 5.0 Qiaojia earthquake is more likely a tectonic earthquake. However, we cannot exclude the possibility that earthquakes could be induced after the impoundment of Baihetan Reservoir, because the identified concealed fault is located in the middle of many large fault zones and only 20 km away from the Baihetan Reservoir. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions The aim of the study was to assess the efficacy and side‐effects of intrapleural treatment in non‐small cell lung cancer (NSCLC) patients with malignant pleural effusions (MPEs).The medical records of NSCLC patients with MPEs diagnosed in four Chinese hospitals from October 2014 to December 2019 were searched. The Kaplan–Meier method is used to calculate median overall survival (MOS) and subgroup analyses are done.A total of 285 patients were evaluated; 81.1% of patients received intrapleural treatment, and no patients received talc pleurodesis. MOS of the whole cohort was 21 months. Patients were divided into three groups: erythromycin group (EG; intrapleural treatment with drugs and erythromycin); intrathoracic treatment group (ITG; intrapleural treatment with drugs); control group (CG; no drug treatment in the pleural cavity). The MOS of patients in the EG, ITG and CG was 20, 22, and 19 months, respectively. Among patients who received only chemotherapy as systemic therapy, the MOS of intrathoracic administration group (IAG; i.e., EG and ITG) was longer than that of CG (12 vs. 6 months; p = 0.034), and the MOS of patients with a ratio of carcinoembryonic antigen in pleural effusion (PE‐CEA): CEA in blood (B‐CEA) ≤1 is worse than that of patients with a ratio >1 (4 vs. 12 months, p = 0.021) and that of CG (4 vs. 6 months, p = 0.442).Intrapleural treatment can prolong the survival of NSCLC patients with MPE who do not receive targeted treatment or who only receive chemotherapy. The PE‐CEA: B‐CEA ratio can be used to predict the efficacy if intrapleural treatment is indicated. [ABSTRACT FROM AUTHOR]

Carotid-femoral pulse transit time (cfPTT) is a widely accepted measure of central arterial stiffness. The cfPTT is commonly calculated from two synchronized pressure waves. However, measurement of synchronized pressure waves is technically challenging. In this paper, a method of decomposing the radial pressure wave is proposed for estimating cfPTT. From the radial pressure wave alone, the pressure wave can be decomposed into forward and backward waves by fitting a double triangular flow wave. The first zero point of the second derivative of the radial pressure wave and the peak of the dicrotic segment of radial pressure wave are used as the peaks of the fitted double triangular flow wave. The correlation coefficient between the measured wave and the estimated forward and backward waves based on the decomposition of the radial pressure wave was 0.98 and 0.75, respectively. Then from the backward wave, cfPTT can be estimated. Because it has been verified that the time lag estimation based on of backward wave has strong correlation with the measured cfPTT. The corresponding regression function between the time lag estimation of backward wave and measured cfPTT is y = 0.96x + 5.50 (r = 0.77; p < 0.001). The estimated cfPTT using radial pressure wave decomposition based on the proposed double triangular flow wave is more accurate and convenient than the decomposition of the aortic pressure wave based on the triangular flow wave. The significance of this study is that arterial stiffness can be directly estimated from a noninvasively measured radial pressure wave. [ABSTRACT FROM AUTHOR]

Objective. Aortic stiffness is associated with risk of cardiovascular events. Carotid-femoral pulse wave velocity (cfPWV) is the current noninvasive gold standard for assessing aortic stiffness. However, the cfPWV measurement is challenging, requiring simultaneous signals at the carotid and femoral sites. Approach. In this study, the aortic PWV is estimated using a single radial pressure waveform and compared with cfPWV. 111 subjects’ aortic PWVs are estimated from the decomposition of the derived central aortic pressure waveform based on three types of reconstructed flow waveform: the peak of triangular flow waveform based on 30% ejection time (Q 30%tri), the peak of triangular flow waveform based on inflection point (Q tri), and averaged flow waveform (Q avg). The central aortic pressure waveform is derived from a radial pressure waveform via a validated transfer function. Main results. The Q avg is used for estimating aortic PWV without the determination of the peak point of the triangular flow waveforms. The estimated aortic PWV shows good agreement with cfPWV. The mean difference ± SD is 0.29 ± 1.50 m sâˆ'1 (r 2 = 0.29, p < 0.001) for the Q 30%tri; 0.27 ± 1.40 m sâˆ'1 (r 2 = 0.38, p  < 0.001) for the Q tri; 0.23 ± 1.39 m sâˆ'1 (r 2 = 0.40, p  < 0.001) for the Q avg. The correlation between estimated aortic PWV based on Q 30%tri and measured cfPWV is weak. The results of Q tri and Q avg show no obvious difference. Significance. The proposed method can be used as a less complex way than conventional measurement of cfPWV to further assess arterial stiffness and predict cardiovascular risks or events. [ABSTRACT FROM AUTHOR]

Presents a study on the relationship between the radiation in the varying wavelengths and the microphysics of cirrus clouds. Details on the remote sensing of cirrus clouds; Application of single and multiple scattering techniques in the study; Methodology; Results and discussion; Conclusion.

Electromyography (EMG) plays a vital role in detecting medical abnormalities and analyzing the biomechanics of human or animal movements. However, long-term EMG signal monitoring will increase the bandwidth requirements and transmission system burden. Compressed sensing (CS) is attractive for resource-limited EMG signal monitoring. However, traditional CS reconstruction algorithms require prior knowledge of the signal, and the reconstruction process is inefficient. To solve this problem, this paper proposed a reconstruction algorithm based on deep learning, which combines the Temporal Convolutional Network (TCN) and the fully connected layer to learn the mapping relationship between the compressed measurement value and the original signal, and it has been verified in the Ninapro database. The results show that, for the same subject, compared with the traditional reconstruction algorithms orthogonal matching pursuit (OMP), basis pursuit (BP), and Modified Compressive Sampling Matching Pursuit (MCo), the reconstruction quality and efficiency of the proposed method is significantly improved under various compression ratios (CR). • Solve the problem of poor compressed sensing reconstruction effect of EMG. • Propose a novel EMG compressed sensing reconstruction method TCNN. • TCNN improves the reconstruction quality and efficiency of EMG. • Obtain the most suitable compressed ratio for EMG recovery. [ABSTRACT FROM AUTHOR]

The hypothalamus plays an important role in the control of aging. Transcranial ultrasound stimulation (TUS) has been reported as a noninvasive method of neuromodulation. However, the effect of TUS of the hypothalamus on aging remains unclear. Therefore, the aim of this study is to verify whether TUS of the hypothalamus could affect the behaviors of aging mice and the expression level of apoptosis factors and inflammatory cytokines. TUS was delivered to the hypothalamus of mice (${n} = {44}$) for 14 days (15 min/day) at a fundamental frequency of 1 MHz, pulse repetition frequency of 1 kHz (US1) or 10 Hz (US2), duty cycle of 10%, and acoustic pressure of 0.13 MPa. The effect of TUS on aging was evaluated by the behavioral tests or Western blotting in different stages. The behavioral results showed that mice in the US2 group improved their movement and learning. In addition, there was a significant improvement in the grip strength after TUS in the second behavioral tests (Sham: 0.0351 ± 0.0020 N/g; US1: 0.0340 ± 0.0023 N/g; US2: 0.0425 ± 0.0029 N/g, ${p} = {0.034}$). Furthermore, the level of inflammation (TNF- $\alpha $ : Sham: 0.69 ± 0.084; US1: 0.39 ± 0.054; US2: 0.49 ± 0.1, ${p} = {0.021}$) and apoptosis (Bax: Sham: 0.47 ± 0.049; US1: 0.42 ± 0.054; US2: 0.18 ± 0.055, ${p} = {0.001}$) was significantly reduced after TUS in this stage. We did not see a long-lasting effect of TUS in the third behavioral tests. In addition, we found that TUS is safe according to hematoxylin and eosin (HE) staining. In conclusion, TUS could effectively modulate the hypothalamus, which may provide a new method for controlling aging. [ABSTRACT FROM AUTHOR]

• This is the first study to estimate RM and RI directly from a single radial blood pressure waveform without the measurement or estimation of aortic blood pressure and flow waveform required by the traditional method wave separation analysis (WSA). • This ANN method yields better accuracy than the WSA method. • The proposed method has potential application for RM and RI measurement in ambulatory situation or during exercise. Wave reflection in aorta has been shown to have incremental value for predicting cardiovascular events. However, its estimation by wave separation analysis (WSA) is complex. In this study, a novel method was proposed based on a cascade artificial neural network (ANN) for wave reflection estimation by the frequency features of radial pressure waveform alone. The simulation database of 4000 samples was generated by a 55-segment transmission line model of human arterial tree and was used for evaluating the ANN with 10-fold cross validation for the estimation of reflection magnitude (RM ANN) and reflection index (RI ANN) of wave reflection in aorta. RM and RI also were estimated by the WSA with a triangle waveform of aortic flow (RM WSA and RI WSA) and with a real aortic flow waveform (RM Ref and RI Ref) as reference values. The results showed the correlation coefficient and mean difference between RM ANN and RM Ref (R 2 = 0.92, mean ± standard deviation (SD) = 0.0 ± 0.02) and those between RI ANN and RI Ref (R 2 = 0.91, mean ± SD = 0.0 ± 0.01) were better than those between RM WSA and RM Ref (R 2 = 0.51, mean ± SD = 0.01 ± 0.07) and those between RI WSA and RI Ref (R 2 = 0.50, mean ± SD = 0.0 ± 0.02). As the sample diversity in the simulation database was increased but the total number of samples keeps constant, the advantage of the ANN, though decreased slightly, became more significant than those of WSA (RM ANN VS. RM Ref and RI ANN VS. RI Ref : R 2 = 0.88 and 0.88, mean ± SD = 0.0 ± 0.05 and 0.0 ± 0.05; RM WSA VS. RM Ref and RI WSA VS. RI Ref : R 2 = 0.24 and 0.24, mean ± SD = 0.07 ± 0.24 and 0.02 ± 0.08, respectively). In addition, the ANN can achieve better results than the traditional method WSA even only two hidden neurons are used. ANN is a potential method for the estimation of wave reflection in aorta by a single radial pulse waveform, but further validation of this method in clinic trials is needed. [ABSTRACT FROM AUTHOR]

Non-negative matrix factorization (NMF) can be used in clustering, feature representation or blind source separation. Many NMF methods have been developed including least squares (LS) error, Kullback–Leibler (KL) divergence, Itakura–Saito (IS) divergence, Bregman-divergence, α -divergence, β -divergence, γ -divergence, convex, constrained, graph-regularized NMFs. The main contribution of this paper is to develop a framework to generalize the existing NMF methods and also provide new NMF methods. This paper constructs a general optimization model and develops a generic updating rule with a simple structure using a surrogate function, which possesses similar properties as the standard NMF methods. The experimental results, obtained using several standard databases, demonstrate the power of the work in which some new methods provide performance superior to that of the other existing methods. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to investigate the feasibility of using a combination of apatinib in the treatment of non‐small cell lung cancer. Apatinib is a tyrosine kinase inhibitor which selectivelyacts on vascular endothelial growth factor receptor 2 (VEGFR‐2) and has shown good efficacy in a variety of malignancies, but the drug resistance is fast in single drug therapy. Methods: The inhibitory effect of apatinib and other drugs on lung cancer cells was determined by CCK‐8 test in vitro, and the IC50 value was determined. To establish a nude mouse xenograft model, observe the inhibitory effect of apatinib combined with other drugs on lung cancer xenografts in nude mice; immunohistochemical staining of tumor microvessel density and Ki67 expression in transplanted tumor tissues; Western blot analysis of related signaling pathways expression; immunohistochemistry was used to detect tumor microvessel density in other organs and to observe its safety. Results: In this study, we found apatinib combined with pemetrexed, the first and third generation of epidermal growth factor receptor tyrosine kinase inhibitor, could synergistically inhibit the proliferation of non‐small cell lung cancer cell (NSCLC) lines, reduce the microvessel density and Ki67 protein levels of three non‐small cell lung cancer xenografts, and enhance anti‐tumor activity by synergistically inhibiting the MAPK‐ERK and PI3K‐AKT‐mTOR signaling pathway. Furthermore, there were no pathological abnormalities in the heart, brain, liver and kidney of each group. Conclusions: The efficacy of apatinib combination is better than that of monotherapy, and there is no significant difference in toxicity of important organs, which suggests the feasibility of a combination of apatinib in the treatment of non‐small cell lung cancer. [ABSTRACT FROM AUTHOR]

This work developed a facile approach to fabricate highly sensitive and flexible polyurethane/graphene platelets composite film for wearable strain sensor. The composite film was fabricated via layer-by-layer laminating method which is simple and cost-effective; it exhibited outstanding electrical conductivity of 1430 ± 50 S/cm and high sensitivity to strain (the gauge factor is up to 150). In the sensor application test, the flexible strain sensor achieves real-time monitoring accurately for five bio-signals such as pulse movement, finger movement, and cheek movement giving a great potential as wearable-sensing device. In addition, the developed strain sensor shows response to pressure and temperature in a certain region. A multifaceted comparison between reported flexible strain sensors and our strain sensor was made highlighting the advantages of the current work in terms of (1) high sensitivity (gauge factor) and flexibility, (2) facile approach of fabrication, and (3) accurate monitoring for body motions. [ABSTRACT FROM AUTHOR]

Abstract Despite that microfluidic paper-based analytical devices (μPADs) provide effective analytical platforms for point-of-care diagnosis in resource-limited areas, it remains challenging to achieve simple and low-cost fabrication of μPADs. A novel method for fabrication of μPADs is developed in this study using a folded polydimethylsiloxane (PDMS)-coated paper mask with a specific pattern to form a sandwich structure with inserted chromatographic paper. PDMS penetrates the target paper from the front and the back sides, and then is cured in the target paper to form legible channels. This method for prototyping μPADs has many favorable merits including simple operation without the need of trained personnel, fast fabrication and low cost. We further investigated colorimetric detection of melamine in the μPADs, and it showed a remarkable measurement with a detection limit of 0.1 ppm in aqueous solutions and liquid milk discriminated by the naked eye, which meets the detection limit required by USA and China. The fabricating strategy developed in this study is very promising and attractive for the development of simple μPADs for point-of-care applications, including diagnostic testing, food safety control and environmental monitoring. Graphical abstract Image 1 Highlights • A novel, efficient, low-cost and practical strategy for fabrication of μPADs was developed. • A folded printing paper coated with uncured PDMS was used to fabricate the μPADs. • The current μPADs have been successfully applied to melamine detection in liquid milk. • A home-made smartphone App was used to quantitatively analyze the concentration of melamine in liquid milk. [ABSTRACT FROM AUTHOR]