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Radiation‐induced heart disease (RIHD) is a heterogeneous, delayed, and potentially fatal adverse reaction to radiation that can damage all structures of the heart, including the pericardium, myocardium, coronary arteries, valves, and conduction system, leading to a series of diseases. Acute and chronic disease processes play a role in the development of RIHD, the onset times of which range from months to decades. However, the clinical manifestations of RIHD are usually insidious, overlap with several other diseases, and lack specificity. Cardiovascular imaging is essential for early diagnosis, follow‐up, and outcome assessment in patients with RIHD. This review first describes the pathogenesis and clinical manifestations of RIHD before providing an overview of the practical approaches and research advances in multimodal cardiovascular imaging in patients with RIHD, including echocardiography, cardiac magnetic resonance (CMR) and nuclear medicine, and cardiac computed tomography (CT). Then, the value of new cardiac imaging assessments for the early diagnosis of RIHD is described, particularly with relation to speckle‐tracking echocardiography, extracellular volume fraction assessment as a quantitative CMR technique, CMR myocardial strain assessment, positron emission tomography‐CT myocardial perfusion imaging, CT‐ECV, and CT strain assessment, amongst others. In addition, the advantages and disadvantages of each screening technique are compared with the aim of better guiding the follow‐up and diagnosis of subclinical RIHD and preventing cardiovascular events. Radiation‐induced heart disease (RIHD) is a heterogeneous, delayed, and potentially fatal adverse reaction to radiation that can cause damage to all structures of the heart. Cardiovascular imaging is essential for the early diagnosis, follow‐up, and prognostic assessment of RIHD. This article provides an overview of the practical approaches and research advances in multimodal cardiovascular imaging in patients with RIHD, including echocardiography, cardiac magnetic resonance and nuclear medicine, and cardiac computed tomography, and explores the roles of new cardiac technologies in the early and accurate diagnosis of RIHD.

Purpose: Bridges play a crucial role in ensuring regional connectivity and traffic safety. However, their vulnerability to environmental factors and material degradation can lead to varying degrees of damage. The bridge structural health monitoring system (SHMS) has emerged as an efficient and intelligent alternative to traditional detection methods to tackle these challenges. Methods: This paper presents an improved approach for reconstructing the response of measuring points based on proper orthogonal decomposition. First, the novel sensor layout scheme based on orthogonal decomposition is introduced to reconstruct stress responses at measuring points. Subsequently, the proposed response reconstruction theory is developed by decomposing stress responses from known points into random time functions and modes. These components are then combined with verification point modes and random time functions using the interpolation method, enabling the determination of stress responses at verification points. Lastly, the proposed response reconstruction theory is validated through numerical simulations and laboratory experiments. Results: The results demonstrate that the proposed method achieves an error rate of less than 5% when comparing the maximum stress response identified by the proposed method to the actual value. Moreover, it has minimal impact on vehicle weight, speed, and complex load factors. Conclusion: Therefore, the response reconstruction method and sensor layout scheme proposed in this study provide an accurate and efficient solution for bridge SHMS.

A torque enhancement scheme using axial assisted magnets (AAMs) for surface-mounted permanent magnet synchronous machines (SPMSMs) is proposed in this paper. It divides the total permanent magnets into two parts viz. main magnets mounted on the rotor surface, and axial assisted magnets at the end of the rotor, with the restriction of the same volume of magnets. According to the theoretical derivation and the finite element (FE) analyses, the proposed design can effectively enhance the output torque and air gap flux density after the optimization of size parameters of main and axial assisted magnets, while the machine outer size, armature current, and volume of total magnets are designed to be the same as the conventional structures of SPMSMs. Besides, the output torque of the proposed SPMSM with AAMs is optimized by way of sequential optimization and a prototype machine is fabricated afterward. Compared with the conventional SPMSM, the proposed design can increase the rated torque by 6.9% in experiments while the value of peak-to-peak torque ripple is kept almost the same.

Purpose: This study aims to improve the availability of regenerative braking for urban metro vehicles by introducing a sensorless operational temperature estimation method for the braking resistor (BR) onboard the vehicle, which overcomes the vulnerability of having conventional temperature sensor. Design/methodology/approach: In this study, the energy model based sensorless estimation method is developed. By analyzing the structure and the convection dissipation process of the BR onboard the vehicle, the energy-based operational temperature model of the BR and its cooling domain is established. By adopting Newton's law of cooling and the law of conservation of energy, the energy and temperature dynamic of the BR can be stated. To minimize the use of all kinds of sensors (including both thermal and electrical), a novel regenerative braking power calculation method is proposed, which involves only the voltage of DC traction network and the duty cycle of the chopping circuit; both of them are available for the traction control unit (TCU) of the vehicle. By utilizing a real-time iterative calculation and updating the parameter of the energy model, the operational temperature of the BR can be obtained and monitored in a sensorless manner. Findings: In this study, a sensorless estimation/monitoring method of the operational temperature of BR is proposed. The results show that it is possible to utilize the existing electrical sensors that is mandatory for the traction unit’s operation to estimate the operational temperature of BR, instead of adding dedicated thermal sensors. The results also validate the effectiveness of the proposal is acceptable for the engineering practical. Originality/value: The proposal of this study provides novel concepts for the sensorless operational temperature monitoring of BR onboard rolling stocks. The proposed method only involves quasi-global electrical variable and the internal control signal within the TCU.

Full-length grouted bolts play a crucial role in geotechnical engineering thanks to their excellent stability. However, few studies have been concerned with the degrading performance of grouted rock bolts caused by extensive and continuous heat conduction from surrounding rocks in high-geothermal tunnels buried more than 100 m (temperature from 28 °C to 100 °C). To investigate the damage mechanism, we examined the time-varying behaviors of grouted rock bolts in both constant and variable temperature curing environments and their damage due to the coupling effects of high temperature and humidity through mechanical and micro-feature tests, including uniaxial compression test, pull-out test, computed tomography (CT) scans, X-ray diffraction (XRD) test, thermogravimetric analysis (TGA), etc., and further analyzed the relationship between grout properties and anchorage capability. In order to facilitate a rapid assessment and control of the anchorage performance of anchors in different conditions, results of the interface bond degradation tests were correlated to environment parameters based on the damage model of interfacial bond stress proposed. Accordingly, a thermal hazard classification criterion for anchorage design in high-geothermal tunnels was suggested. Based on the reported results, although high temperature accelerated the early-stage hydration reaction of grouting materials, it affected the distribution and quantity of hydration products by inhibiting hydration degree, thus causing mechanical damage to the anchorage system. There was a significant positive correlation between the strength of the grouting material and the anchoring force. Influenced by the changes in grout properties, three failure patterns of rock bolts typically existed. Applying a hot-wet curing regime results in less reduction in anchorage force compared to the hot-dry curing conditions. The findings of this study would contribute to the design and investigations of grouted rock bolts in high-geothermal tunnels.

Objectives: To evaluate whether venous tumor thrombus (VTT) consistency is a risk factor for the patient’s prognosis with renal cell carcinoma (RCC). Materials and methods: A total of 190 RCC patients with VTT, who were treated at Department of Urology, Chinese PLA General Hospital, were retrospectively analyzed in this study. The baseline clinical characteristics, postoperative outcomes, and pathological findings were analyzed. Tumor thrombus was classified as solid and friable based on their respective characteristics. Survival curves were estimated using the Kaplan–Meier survival curve analysis, and univariable and multivariable cox proportional hazard regression models were used. Results: Among the total 190 patients included in this study, 145 (76.3%) patients had solid VTT, and 45 (23.7%) patients had friable VTT in their renal veins and inferior vena cava (IVC). There were no significant differences in the age, gender, BMI, symptoms, complex diseases, tumor side, tumor size, TNM stage, Mayo stage, tumor grade, sarcomatous differentiation, pelvic invasion, and sinus fat invasion of patients. Solid VTT consistency was more likely to have a capsule as compared to those with friable VTT (P= 0.007). Kaplan–Meier survival curve analysis demonstrated no statistically significant differences in the overall survival (OS) (P= 0.973) and progression-free survival (PFS) (P= 0.667) of patients. Moreover, VTT consistency was not associated with OS (P= 0.706) of PFS (P= 0.504) in multivariate cox regression analysis. Conclusions: RCC VTT consistency was not a prognostic risk factor for predicting the OS and PFS of patients.

Due to the discrepancy of paralleled inverters, the zero-sequence circulating current (ZSCC) is a critical issue in a paralleled inverter fed permanent magnet synchronous machine (PMSM) drive system. The conventional solution to this issue is to adjust the duration of two zero vectors; however, it will not be appropriate under the discontinuous space vector pulsewidth modulation (DSVPWM) control using only one zero vector. For overcoming the above issues, an active vector modification (AVM)-based ZSCC suppression and a two-step sector indexing (TSSI)-based DSVPWM are proposed in this article. It uses both reference voltage and current vectors to jointly determine the drive signals in a two-step manner, which avoids the circulating current jump due to the coexistence of different zero vectors and can also reduce the switching loss by 50% in theory. Meanwhile, the low-frequency ZSCC can be online suppressed by a proposed real-time modification of durations of active vectors, which is finally verified together with the proposed TSSI method on a PMSM fed by two paralleled inverters.

Paralleled inverters are widely employed in permanent magnet synchronous machine (PMSM) drives to increase system capacity and reliability. Due to the discrepancy of paralleled inverters, the differential-mode circulating current (DMCC) is a major concern in paralleled inverters fed PMSM drives. The DMCC would result in current unbalance and efficiency reduction. To address this issue, a low-frequency DMCC suppression considering dead time compensation is proposed in this article, which can be effective in the suppression of both DMCC and zero-sequence circulating current. In detail, the DMCC due to the discrepancy of control settings, such as dead time and switching period, is eliminated by a proposed dead time compensation. Besides, the DMCC owing to the hardware differences, including device voltage drops, device turn-on/off delays, and filter inductances, is suppressed by a proposed regulation of phase conduction time, being free of disturbing the command voltage of drive system. Finally, the effectiveness of the proposed method is experimentally validated under both two-level and three-level space vector modulations.

This article examines a new measure of combining the vector Lyapunov function with ${M}$ -matrix for settling the asymptotic stabilization control of fractional-order memristor-based neural networks system (FOMBNNS) has large delays in various dimensional forms. Some new stability and stabilization criteria are deduced. First, the vector Lyapunov function and ${M}$ -matrix are imported for investigating stabilization control for the above system. Then, we solve the problem for a special type of situation that the activation functions no longer consider Lipschitz parameters via the new method. Finally, four numerical examples from different kinds of situations are simulated for expounding the validity of the novel asymptotic stability and stabilization criteria. Compared with the methods mentioned in the current references, the proposed asymptotic stability and stabilization criteria in this article have strong generality and universality. They can be applied not only to the most common feedback control, accordingly, the feedback control law based on which they are designed but also to all fractional-order parameters from 0 to 1. In addition, the new method has lower conservativeness and fewer constraints. Moreover, the new stability and stabilization criteria can also overcome the difficulty in dealing with the above system owning large delays.

Recognizing early cardiac sarcoidosis (CS) imaging phenotypes can help identify opportunities for effective treatment before irreversible myocardial pathology occurs. We aimed to characterize regional CS myocardial remodeling features correlating with future adverse cardiac events by coupling automated image processing and data analysis on cardiac magnetic resonance (CMR) imaging datasets. A deep convolutional neural network (DCNN) was used to process a CMR database of a 10-year cohort of 117 consecutive biopsy-proven sarcoidosis patients. The maximum relevance − minimum redundancy method was used to select the best subset of all the features—24 (from manual processing) and 232 (from automated processing) left ventricular (LV) structural/functional features. Three machine learning (ML) algorithms, logistic regression (LogR), support vector machine (SVM) and multi-layer neural networks (MLP), were used to build classifiers to categorize endpoints. Over a median follow-up of 41.8 (inter-quartile range 20.4–60.5) months, 35 sarcoidosis patients experienced a total of 43 cardiac events. After manual processing, LV ejection fraction (LVEF), late gadolinium enhancement, abnormal segmental wall motion, LV mass (LVM), LVMI index (LVMI), septal wall thickness, lateral wall thickness, relative wall thickness, and wall thickness of 9 (out of 17) individual LV segments were significantly different between patients with and without endpoints. After automated processing, LVEF, end-diastolic volume, end-systolic volume, LV mass and wall thickness of 92 (out of 216) individual LV segments were significantly different between patients with and without endpoints. To achieve the best predictive performance, ML algorithms selected lateral wall thickness, abnormal segmental wall motion, septal wall thickness, and increased wall thickness of 3 individual segments after manual image processing, and selected end-diastolic volume and 7 individual segments after automated image processing. LogR, SVM and MLP based on automated image processing consistently showed better predictive accuracies than those based on manual image processing. Automated image processing with a DCNN improves data resolution and regional CS myocardial remodeling pattern recognition, suggesting that a framework coupling automated image processing with data analysis can help clinical risk stratification.

IMPORTANCE: Machine learning algorithms enable the automatic classification of cardiovascular diseases based on raw cardiac ultrasound imaging data. However, the utility of machine learning in distinguishing between takotsubo syndrome (TTS) and acute myocardial infarction (AMI) has not been studied. OBJECTIVES: To assess the utility of machine learning systems for automatic discrimination of TTS and AMI. DESIGN, SETTINGS, AND PARTICIPANTS: This cohort study included clinical data and transthoracic echocardiogram results of patients with AMI from the Zurich Acute Coronary Syndrome Registry and patients with TTS obtained from 7 cardiovascular centers in the International Takotsubo Registry. Data from the validation cohort were obtained from April 2011 to February 2017. Data from the training cohort were obtained from March 2017 to May 2019. Data were analyzed from September 2019 to June 2021. EXPOSURE: Transthoracic echocardiograms of 224 patients with TTS and 224 patients with AMI were analyzed. MAIN OUTCOMES AND MEASURES: Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the machine learning system evaluated on an independent data set and 4 practicing cardiologists for comparison. Echocardiography videos of 228 patients were used in the development and training of a deep learning model. The performance of the automated echocardiogram video analysis method was evaluated on an independent data set consisting of 220 patients. Data were matched according to age, sex, and ST-segment elevation/non-ST-segment elevation (1 patient with AMI for each patient with TTS). Predictions were compared with echocardiographic-based interpretations from 4 practicing cardiologists in terms of sensitivity, specificity, and AUC calculated from confidence scores concerning their binary diagnosis. RESULTS: In this cohort study, apical 2-chamber and 4-chamber echocardiographic views of 110 patients with TTS (mean [SD] age, 68.4 [12.1] years; 103 [90.4%] were female) and 110 patients with AMI (mean [SD] age, 69.1 [12.2] years; 103 [90.4%] were female) from an independent data set were evaluated. This approach achieved a mean (SD) AUC of 0.79 (0.01) with an overall accuracy of 74.8 (0.7%). In comparison, cardiologists achieved a mean (SD) AUC of 0.71 (0.03) and accuracy of 64.4 (3.5%) on the same data set. In a subanalysis based on 61 patients with apical TTS and 56 patients with AMI due to occlusion of the left anterior descending coronary artery, the model achieved a mean (SD) AUC score of 0.84 (0.01) and an accuracy of 78.6 (1.6%), outperforming the 4 practicing cardiologists (mean [SD] AUC, 0.72 [0.02]) and accuracy of 66.9 (2.8%). CONCLUSIONS AND RELEVANCE: In this cohort study, a real-time system for fully automated interpretation of echocardiogram videos was established and trained to differentiate TTS from AMI. While this system was more accurate than cardiologists in echocardiography-based disease classification, further studies are warranted for clinical application.

ABSTRACTThis study aimed to investigate the roles of the lysine (K)-specific demethylase 5C (KDM5C)–bone morphogenetic protein-7 (BMP-7) signaling pathway in the pathogenesis of severe preeclampsia (sPE). A total of 180 pregnant patients were enrolled in the study and classified into three groups: an early-onset sPE group (EOsPE) (n = 60), a late-onset sPE group (LOsPE) (n = 60), and a control group (normal pregnancy; n = 60). The messenger RNA (mRNA) and protein expression levels of bone morphogenetic protein receptor II (BMPRII), BMP-7, and KDM5C were detected in placenta samples from the two sPE groups, and their sites were evaluated using immunohistochemistry (IHC). The sPE groups showed an increased KDM5C mRNA expression, and the EOsPE group showed a decreased BMP-7 and BMPRII mRNA expression compared with the LOsPE group. However, contradictory results were discovered in terms of protein expression. Immunostaining of KDM5C, BMP-7, and BMPRII was observed in villous trophoblast and extravillous trophoblast cells. Compared with the control group, the staining intensity of KDM5C in the placental tissue trophoblast cell nucleus and vascular endothelial cells of the sPE groups was weaker, while that of BMP-7 and BMPRII was stronger, and the staining intensity was more subjective in the LOsPE group. Consistent findings were obtained by IHC and Western blot analysis. KDM5C nuclear-cytoplasmic translocation may regulate sPE through BMP-7 and its receptors. The KDM5C–BMP-7 signaling pathway may also lead to less invasion and increased apoptosis of the trophoblast cells, which is involved in the pathogenesis of sPE.

Tridiagonal solver is an important kernel used in a wide range of applications and has been well supported in mainstream numerical libraries. Quite a few parallel algorithms have been developed, but the best-performing algorithm may vary across architectures as well as input sizes. Targeting this algorithm choice challenge, we present a model guided approach to determine the best batched tridiagonal algorithm for various many-core architectures and input sizes efficiently and effectively, managing to achieve the accuracy of algorithm choice over 92% for important architectures. Following the approach, we propose a hybrid CR-PCR-pThomas algorithm to well leverage computation and memory access. The hybrid algorithm outperforms the current state-of-the-art alternatives by up to 32% and 21% on Pascal P100 and Knights Landing respectively. On SW26010 that powers the No.6 supercomputer Sunway TaihuLight, we present an improved cyclic reduction algorithm Dist-CR. The proposed Dist-CR outperforms Thomas algorithm by speedups up to 2.14×.

To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysis of the 12-lead electrocardiogram (ECG) can distinguish patients with LQTS from those with acquired QT prolongation.

The microfluidic chip-based nucleic acid detection method significantly improves the sensitivity since it precisely controls the microfluidic flow in microchannels. Nonetheless, significant challenges still exist in improving the detection efficiency to meet the demand for rapid detection of trace substances. This work provides a novel magnetic herringbone (M-HB) structure in a microfluidic chip, and its advantage in rapid and sensitive detection is verified by taking complementary DNA (cDNA) sequences of human immunodeficiency virus (HIV) detection as an example. The M-HB structure is designed based on controlling the magnetic field distribution in the micrometer scale and is formed by accumulation of magnetic microbeads (MMBs). Hence, M-HB is similar to a nanopore microstructure, which has a higher contact area and probe density. All of the above is conducive to improving sensitivity in microfluidic chips. The M-HB chip is stable and easy to form, which can linearly detect cDNA sequences of HIV quantitatively ranging from 1 to 20 nM with a detection limit of 0.073 nM. Compared to the traditional herringbone structure, this structure is easier to form and release by controlling the magnetic field, which is flexible and helps in further study. Results show that this chip can sensitively detect the cDNA sequences of HIV in blood samples, demonstrating that it is a powerful platform to rapidly and sensitively detect multiple nucleic acid-related viruses of infectious diseases.

Purpose: To investigate and identify first-trimester fasting plasma glucose (FPG) is related to gestational diabetes mellitus (GDM) and other adverse pregnancy outcomes in Shenzhen population. Methods: We used data of 48,444 pregnant women that had been retrospectively collected between 2017 and 2019. Logistic regression analysis was used to evaluated the associations between first-trimester FPG and GDM and adverse pregnancy outcomes, and used to construct a nomogram model for predicting the risk of GDM. The performance of the nomogram was evaluated by using ROC and calibration curves. Decision curve analysis (DCA) was used to determine the clinical usefulness of the first-trimester FPG by quantifying the net benefits at different threshold probabilities. Results: The mean first-trimester FPG was 4.62 ± 0.42 mmol/L. A total of 6998 (14.4%) pregnancies developed GDM.489(1.01%) pregnancies developed polyhydramnios, the prevalence rates of gestational hypertensive disorder (GHD), cesarean section, primary cesarean section, preterm delivery before 37 weeks (PD) and dystocia was 1130 (2.33%), 20,426 (42.16%), 7237 (14.94%), 2386 (4.93%), and 1865 (3.85%), respectively. 4233 (8.74%) of the newborns were LGA, and the number of macrosomia was 2272 (4.69%), LBW was 1701 (3.51%) and 5084 (10.49%) newborns had admission to the ICU, which all showed significances between GDM and non-GDM groups (all P< 0.05). The univariate analysis showed that first-trimester FPG was strongly associated with risks of outcomes including GDM, cesarean section, macrosomia, GHD, primary cesarean section, and LGA (all OR > 1, all P< 0.05), furthermore, the risks of GDM, primary cesarean section, and LGA was increasing with first-trimester FPG as early as it was at 4.19–4.63 mmol/L. The multivariable analysis showed that the risks of GDM (ORs for FPG 4.19–4.63, 4.63–5.11 and 5.11–7.0 mmol/L were 1.137, 1.592, and 4.031, respectively, all P< 0.05) increased as early as first-trimester FPG was at 4.19–4.63 mmol/L, and first-trimester FPG which was also associated with the risks of cesarean section, macrosomia and LGA (OR for FPG 5.11–7.0 mmol/L of cesarean section: 1.128; OR for FPG 5.11–7.0 mmol/L of macrosomia: 1.561; OR for FPG 4.63–5.11 and 5.11–7.0 mmol/L of LGA: 1.149 and 1.426, respectively, all P< 0.05) and with its increasing, the risks of LGA increased. Furthermore, the nomogram had a C-indices 0.771(95% CI: 0.763~0.779) and 0.770(95% CI:0.758~0.781) in training and testing validation respectively, which showed an acceptable consistency between the observed, validation and nomogram-predicted probabilities, the DAC curve analysis indicated that the nomogram had important clinical application value for GDM risk prediction. Conclusions: FPG in the first trimester was an independent risk factor for GDM which can be used as a screening test for identifying pregnancies at risk of GDM and adverse pregnancy outcomes.

A 55-year-old Chinese man without significant medical history presented with progressive chest discomfort and night sweats for the past 2 months. He experienced nonexertional chest tightness and palpitation at night, not associated with dyspnea. These symptoms usually lasted for a few minutes and resolved spontaneously. He also reported night sweats but denied fever, chills, or weight change. He had never smoked and denied recent contact with anyone known to be ill.

Background Myocardial infarction can be a trigger of Takotsubo syndrome. We recently characterized imaging features of acute myocardial infarction-induced Takotsubo syndrome (“Takotsubo effect”). In this study, we investigate diagnostic and prognostic implications of Takotsubo effect in patients with anterior wall ST-segment elevation myocardial infarction.Methods We enrolled 111 consecutive patients who developed anterior wall ST-segment elevation myocardial infarction and received percutaneous coronary intervention, and studied systolic/diastolic function, hemodynamic consequences, adverse cardiac events, as well as 30-day and five-year outcomes in patients with and without Takotsubo effect.Results Patients with Takotsubo effect showed significantly worse average peak systolic longitudinal strain (–9.5 ± 2.6% vs –11.1 ± 3.6%, p= 0.038), left ventricular ejection fraction (38.5 ± 6.8% vs 47.7 ± 8.7%, p= 0.000) and myocardial performance index (0.54 ± 0.17 vs 0.37 ± 0.15, p= 0.000) within 48 h of myocardial infarction. There was no significant difference between the two groups in diastolic ventricular filling pressures, hemodynamic consequences, and 30-day rehospitalization and mortality (Gehan-Breslow-Wilcoxon test: p = 0.157). However, patients with Takotsubo effect developed more major adverse cardiac events (log-rank test: p = 0.019) when tested at the five-year follow-up. Cox regression analysis revealed that age, hypotension, tricuspid annular plane systolic excursion, and Takotsubo effect were independent prediction factors for five-year major adverse cardiac events. The Doppler/tissue Doppler parameter E/e’ correlated with MACE only in patients without Takotsubo effect.Conclusion Takotsubo effect secondary to anterior ST-segment elevation myocardial infarction predicts a worse long-term prognosis.

In clinical practice, objective basis for the choice between laparoscopic partial nephrectomy (LPN) and robot-assisted partial nephrectomy (RAPN) is scarce. To evaluate surgical outcomes, assess the individual benefit from LPN to RAPN, which can guide clinical decision-making.

ABSTRACTPreeclampsia (PE) is a pregnancy-specific syndrome that substantially leads to maternal and fetal mortality. Multiple factors contribute to the disease, but the exact pathogenesis still remains elusive. Here we explored the roles of lncRNA MALAT1 and miR-206 in PE. qRT-PCR was applied to measure mRNA levels of MALAT1 and miR-206 in the placenta of PE patients. Scratch wound healing assay and transwell invasion assay were conducted to test the effects of MALAT1 and miR-206 on migration and invasion of trophoblast cells. In addition, we validated MALAT1/miR-206 and miR-206/IGF-1 interactions with dual luciferase reporter assay. Western bot was used to detect protein expressions of IGF-1, p-PI3K, PI3K, p-Akt and Akt. We found that MALAT1 was decreased but miR-206 was increased in the placenta of patients with PE. Inhibition of MALAT1, knockdown IGF-1, or miR-206 mimics suppressed the trophoblast cells migration and invasion, while overexpression of MALAT1, IGF-1 or miR-206 inhibitors exhibited opposite effects. Further, miR-206 was confirmed as a direct target of MALAT1. Besides, miR-206 inhibited IGF-1 expression by directly binding to the 3’UTR. Mechanistically, our study demonstrated that MALAT1 regulates IGF-1/PI3K/Akt signaling via miR-206. Together, these results suggest that MALAT1 and miR-206 play important roles in PE. MALAT1 regulates miR-206/IGF-1 axis, thereby modulating trophoblast cells migration and invasion through PI3K/Akt signal pathway. These results show light on the underlying mechanisms of PE and provide potential targets for PE therapy.Abbreviations:PE: Preeclampsia; lncRNA: Long-non-coding RNA; MALAT1: Metastasis-associated lung adenocarcinoma transcript 1; IGF-1: Insulin-like growth factor 1; PI3k: Phosphatidylinositol-4, 5-bisphosphate 3-kinase; Akt: Protein kinase B; GAPDH: Glyceraldehyde 3-phosphate dehydrogenase; qRT-PCR: Quantitative Reverse Transcription polymerase chain reaction; shRNA: Short hairpin RNA; siRNA: Small interfering RNA; EMT: Epithelial-mesenchymal transition

Metal-halide perovskite solar cells (PSCs) exhibit outstanding efficiencies when fabricated as mm-sized cells, but the fabrication of high-performing larger-area modules presents a challenge. Emerging evidence suggests the serious recombination reaction caused by the limited carrier lifetime is the bottleneck, because we lack effective strategy to deposit large-area perovskite film with sufficient long carrier lifetime. Herein, we report on a strategy of modulating the formation of perovskite film on larger-area substrates via introducing alkyl dithiol additives. Among the dithiols with different lengths, we find hexane-1,6-dithiol can effectively elongate carrier lifetime of perovskite film from 1.5 to 7.6 μs, which is due to the suppression of the formation of inactive PbI2and hexagonal δHphase, along with the enlarged grain size. As a result, we improved the efficiency of solar cells (0.16 cm2) from 21.8% to 23.5%, as well as 16.9%–18.1% for the mini-modules (10.0 cm2). More importantly, the modified modules retained 92% of their initial efficiencies after 500-h aging under ambient condition without encapsulation (ISOS-D-1). This dithiol additive strategy shows great promise for pursuing high-performance PSCs.

Introduction: Sexual activity is often an important component of life. To date, no studies have examined sexual activity before and after total hip arthroplasty (THA) in male patients with ankylosing spondylitis (AS). The purpose of the current study was to evaluate the effect of THA on sexual activity and to explore the most commonly reported and comfortable coital position for male AS patients with hip involvement.Methods: Data from 31 male AS patients who underwent THA for hip involvement were retrospectively reviewed. Information from the International Index of Erectile Function (IIEF), the Harris Hip Score (HHS) and other clinical parameters was collected and monitored over time. We compared the above-mentioned parameters before surgery and 2 years after surgery and analysed the correlation between changes on the IIEF and changes in clinical parameters.Results: The domain and total scores of the IIEF, except EF, were significantly higher after surgery than were those before surgery (p< 0.05). There was a significant positive correlation between changes on the IIEF and improvement in flexion-extension range of motion (ROM), adduction-abduction ROM and HHS (p< 0.05). Most patients (26/31, 83.9%) resumed sexual activity 5–12 weeks after surgery. The pre- and postoperative distributions of the most commonly reported and comfortable position were not significantly different (p> 0.05).Conclusions: Successful THA may improve sexual activity in male AS patients with hip involvement. Changes in hip ROM show the most significant correlation with improvement in sexual activity. Resumption of sexual activity occurs within 5–12 postoperative weeks.

Although anti-PD-1 immunotherapy is widely used to treat melanoma, its efficacy still has to be improved. In this work, we present a therapeutic method that combines immunotherapy and starvation therapy to achieve better antitumor efficacy. We designed the CMSN-GOx method, in which mesoporous silica nanoparticles (MSN) are loaded with glucose oxidase (GOx) and then encapsulate the surfaces of cancer cell membranes to realize starvation therapy. By functionalizing the MSN’s biomimetic surfaces, we can synthesize nanoparticles that can escape the host immune system and homologous target. These attributes enable the nanoparticles to have improved cancer targeting ability and enrichment in tumor tissues. Our synthetic CMSN-GOx complex can ablate tumors and induce dendritic cell maturity to stimulate an antitumor immune response. We performed an in vivoanalysis of these nanoparticles and determined that our combined therapy CMSN-GOx plus PD-1 exhibits a better antitumor therapeutic effect than therapies using CMSN-GOx or PD-1 alone. Additionally, we used the positron emission tomography imaging to measuring the level of glucose metabolism in tumor tissues, for which we investigate the effect with the cancer therapy in vivo.

The roughness of the joint surface plays a significant role in evaluating the shear strength of rock. The waviness (first-order) and unevenness (second-order) of natural joints have different effects on the characterization of joint surface roughness. To accurately quantify the influence of the two-order asperity on the joint roughness coefficient (JRC) prediction of joint surface profile curve, the optimal sampling interval of the asperity was determined through the change of the Rp{R}_{{\rm{p}}}value of the joint surface profile curve. The separation of the two-order asperity of 48 joint surface profile curves was completed at the optimal sampling interval, and morphological parameters of the asperity such as iave{i}_{{\rm{ave}}}, Rmax{R}_{{\rm{\max }}}, and Rp{R}_{{\rm{p}}}were counted from three aspects: asperity angle of the profile curve, asperity degree, and the trace length. Based on the statistical results of the morphological parameters considering the two-order asperity, the new nonlinear prediction models were proposed. The results showed that the curve slope mutation point SI = 2 mm is the optimal separation distance of the two-order asperity of the joint surface profile curve. The refined separation method that considers the waviness and unevenness of morphological parameters can characterize the detailed morphological features of the joint surface in more dimensions. The support vector regression (SVR) and random forest (RF) models that take into account a two-order asperity separated results have higher accuracy than traditional models. The prediction accuracy has improved by 7–8% in SVR model compared with SVR(SO) and RF(SO). The SVR nonlinear model that considering separation of two-orders of joint surface roughness is more suitable for the prediction of JRC.

Neural stem cells derived from human pluripotent stem cells (hPSC-NSCs) are of great value for modeling diseases, developing drugs, and treating neurological disorders. However, manufacturing high-quantity and -quality hPSC-NSCs, especially for clinical applications, remains a challenge. Here, we report a chemically defined, high-yield, and scalable bioprocess for manufacturing hPSC-NSCs. hPSCs are expanded and differentiated into NSCs in microscale tubes made with alginate hydrogels. The tubes are used to isolate cells from the hydrodynamic stresses in the culture vessel and limit the radial diameter of the cell mass to less than 400 μm to ensure efficient mass transport during the culture. The hydrogel tubes provide uniform, reproducible, and cell-friendly microspaces and microenvironments for cells. With this new technology, we showed that hPSC-NSCs could be produced in 12 days with high viability (∼95%), high purity (>90%), and high yield (∼5 × 108cells/mL of microspace). The volumetric yield is about 250 times more than the current state-of-the-art. Whole transcriptome analysis and quantitative real-time polymerase chain reaction showed that hPSC-NSCs made by this process had a similar gene expression to hPSC-NSCs made by the conventional culture technology. The produced hPSC-NSCs could mature into both neurons and glial cells in vitro and in vivo. The process developed in this paper can be used to produce large numbers of hPSC-NSCs for various biomedical applications in the future.

AbstractIn the future, the virtualized (cloned) smartphone is called the virtual network device, which is hosted in the private and the public cloud environments. This is a major research field in next-generation mobile communication networks. Cloud computing platforms provide efficient and flexible ways to offer services and computation facilities to users. However, reliability in the cloud is an important factor to measure the performance of a virtualized cloud computing platform. The paper proposes a new approach to improve reliability of cloud computing platforms for next communication networks.

Vascular smooth muscle cells (VSMCs) are of great value and are needed in large quantities for tissue engineering, drug screening, disease modeling and cell-based therapies. However, getting high quantity VSMCs remains a challenge. Here, we report a method for the scalable manufacturing of VSMCs from human pluripotent stem cells (hPSCs). hPSCs are expanded and differentiated into VSMCs in a three dimensional (3D) thermoreversible hydrogel. The hydrogel not only acts as a 3D scaffold for cells to grow, but also protects cells from hydrodynamic stresses in the culture vessel and prevents cells from excessive aggregation. Together, the hydrogel creates a cell-friendly microenvironment, leading to high culture efficiency. We show that VSMCs can be generated in 10 days with high viability (>90%), high purity (>80%) and high yield (∼2.0 × 107cells per mL hydrogel) in the hydrogel scaffold. The generated VSMCs have normal functions. Genome-wide gene expression analysis shows VSMCs made in the hydrogel (i.e.3D-VSMCs) have higher expression of genes related to vasculature development and glycolysis compared to VSMCs made in the conventional 2D cultures (i.e.2D-VSMCs), while 2D-VSMCs have higher expression of genes related to cell proliferation. This simple, defined and efficient method is scalable for manufacturing hPSC-VSMCs for various biomedical applications.

Human pluripotent stem cell derived endothelial cells (hPSC-ECs) are of great value for studying and treating vascular diseases. However, manufacturing high quantity and quality hPSC-ECs with current cell culture technologies remains very challenging. Here, we report a novel method that can manufacture hPSC-ECs in scalable and cell-friendly microenvironments to address this challenge. Using this method, hPSCs are expanded and differentiated into ECs in microscale alginate hydrogel tubes. The hydrogel tubes protect cells from the highly variable hydrodynamic conditions and critical hydrodynamic stresses in the culture vessel and limit the cell mass less than the diffusion limits (of human tissue) to ensure efficient mass transport. The hydrogel tubes provide uniform and friendly microenvironments for cells to grow. This novel design leads to extremely high production efficiency. We showed that hPSC-ECs could be produced in 10 days with high viability (>90%), high purity (>80%) and high yield (∼5.0 × 108cells per mL of microspace). The yield is about 250 times that of the current-state-of-the-art. hPSC-ECs made in these hydrogel tubes had similar in vitroand in vivofunctions to hPSC-ECs generated by conventional cell culture methods. This simple, scalable, efficient, defined and cost-effective technology will make hPSC-ECs broadly available and affordable for various biomedical applications.

In this paper, an accurate parameter estimation model of surface permanent magnet synchronous machines (SPMSMs) is established by taking into account voltage-source-inverter (VSI) nonlinearity. A fast dynamic particle swarm optimization (DPSO) algorithm combined with a receptor editing (RE) strategy is proposed to explore the optimal values of parameter estimations. This combination provides an accelerated implementation on graphics processing unit (GPU), and the proposed method is, therefore, referred to as G-DPSORE. In G-DPSO-RE, a dynamic labor division strategy is incorporated into the swarms according to the designed evolutionary factor during the evolution process. Two novel modifications of the movement equation are designed to update the velocity of particles. Moreover, a chaotic-logistic-based immune RE operator is developed to facilitate the global best individual (gBest particle) to explore a potentially better region. Furthermore, a GPU parallel acceleration technique is utilized to speed up parameter estimation procedure. It has been demonstrated that the proposed method is effective for simultaneous estimation of the PMSM parameters and the disturbance voltage (Vdead) due to VSI nonlinearity from experimental data for currents and rotor speed measured with inexpensive equipment. The influence of the VSI nonlinearity on the accuracy of parameter estimation is analyzed.

Background: Recently, identification and functional studies of circular RNAs, a type of non-coding RNAs arising from a ligation of 3’ and 5’ ends of a linear RNA molecule, were conducted in mammalian cells with the development of RNA-seq technology. Method: Since compared with animals, studies on circular RNAs in plants are less thorough, a genome-wide identification of circular RNA candidates in Arabidopsis was conducted with our own developed bioinformatics tool to several existing RNA-seq datasets specifically for non-coding RNAs. Results: A total of 164 circular RNA candidates were identified from RNA-seq data, and 4 circular RNA transcripts, including both exonic and intronic circular RNAs, were experimentally validated. Interestingly, our results show that circular RNA transcripts are enriched in the photosynthesis system for the leaf tissue and correlated to the higher expression levels of their parent genes. Sixteen out of all 40 genes that have circular RNA candidates are related to the photosynthesis system, and out of the total 146 exonic circular RNA candidates, 63 are found in chloroplast.

Lysosomal amino acid accumulation is implicated in several diseases, but its role in insulin resistance, the central mechanism to type 2 diabetes and many metabolic diseases, is unclear. In this study, we show the hepatic expression of lysosomal membrane protein solute carrier family 7 member 14 (SLC7A14) is increased in insulin-resistant mice. The promoting effect of SLC7A14 on insulin resistance is demonstrated by loss- and gain-of-function experiments. SLC7A14 is further demonstrated as a transporter resulting in the accumulation of lysosomal γ-aminobutyric acid (GABA), which induces insulin resistance via inhibiting mTOR complex 2 (mTORC2)’s activity. These results establish a causal link between lysosomal amino acids and insulin resistance and suggest that SLC7A14 inhibition may provide a therapeutic strategy in treating insulin resistance-related and GABA-related diseases and may provide insights into the upstream mechanisms for mTORC2, the master regulator in many important processes.

Introduction:Ebstein’s anomaly (EA) is a rare congenital anomaly of the tricuspid valve associated with heart failure and arrhythmias. Currently available imaging modalities like transthoracic echocardiography, cardiac magnetic resonance imaging (MRI), or computerized tomography (CT) are not viable for screening large asymptomatic populations.Hypothesis:A deep learning algorithm, implemented using a convolutional neural network (CNN) applied to the standard 12-lead ECG can be used as an accurate screening tool for EA in children and adults.Method:We identified 1,154 EA patients and 21,430 age- and sex-matched controls (1:20 ratio) between 1987 - 2020. A CNN was trained, validated and tested using digital 12-lead ECGs in 70%, 10% and 20% of the cohort respectively, divided by random shuffling.Results:The mean age was 26.68±19.23 years (41.8% aged < 18 years, 56.41% female) for the EA cohort and 28.36±18.65 years (37.2% aged <18 years, 55.67% female) for the control cohort. Following training and validation the area under the curve (AUC) for detecting EA in the testing cohort was 0.976 (95% CI 0.962 - 0.989) with prediction accuracy of 0.959. In subgroup analysis, the AUC was comparable in males (0.970, 95% CI 0.946-0.995) and females (0.979, 95% CI 0.964-0.994), those <18 (0.980, 95% CI 0.958-1.000) and ≥18 years old (0.972, 95% CI 0.954-0.989), as well as in those with right bundle branch block (RBBB) (0.969, 95% CI 0.950-0.989) and without RBBB (0.950, 95% CI 0.922-0.978) on ECG.Conclusion:Artificial intelligence enhanced ECG based detection of EA is possible with high diagnostic accuracy. Following further refinement and external validation, this algorithm can facilitate early detection of EA using ECGs, a widely available and inexpensive tool.Figure:Receiver operating characteristic (ROC) curve for the performance of the artificial intelligence CNN in detecting EA in the test cohort stratified by (A) age (< 18 and ≥ 18 years) and sex and (B) presence of RBBB.

Introduction:Over 100 FDA-approved medications, electrolyte perturbations, and many disease states can prolong the QTc beyond its 99thpercentile value resulting in acquired QT prolongation. In contrast, approximately 1 in 2000 people have congenital long QT syndrome (LQTS) hallmarked by pathological QT prolongation secondary to genetic defects in the heart.Hypothesis:An artificial intelligence (AI) deep neural network (DNN) can distinguish patients with LQTS from those with acquired QT prolongation.Methods:The study cohort included all patients with LQTS evaluated in the Windland Smith Rice Genetic Heart Rhythm Clinic and controls from Mayo Clinic’s ECG data vault comprising over 2.5 million patients. For the AI-DNN model, every patient/control with ≥ 1 ECG above age- and sex- specific 99thpercentile values for QTc [> 460 ms for all patients (male/female) < 13 years of age, or > 470 ms for men and > 480 ms for women above this age] was included. An AI-DNN involving a multi-layer convolutional neural network (CNN) was developed to classify patients. LQTS patients were age- and sex- matched to controls at 1:5 ratio.Results:Among the 1,599 patients with genetically confirmed LQTS, 808 had ≥ 1 ECG with QTc above the threshold (2,987 ECGs) compared to 361,069/2.5M controls (14% of Mayo Clinic patients getting an ECG, ‘presumed negative’; 989,313 ECGs). Following age- and sex- matching and splitting, 3,309 (training), 411 (validation) and 887 (testing) control ECGs were used. This model distinguished LQTS from those with acquired QT prolongation with an AUC of 0.896 (accuracy 85%, sensitivity 77%, specificity 88%, PPV 0.58, NPV 0.94). After exclusion of patients with a wide QRS (>150 ms) or pacemaker, the model remained successful in distinguishing the two groups (AUC 0.85, accuracy 78%, sensitivity 78%, specificity 87%, PPV 59%, NPV 94%).Conclusions:For patients with a QTc exceeding its 99thpercentile values, this novel AI-DNN functions as a LQTS mutation detector being able to identify patients with abnormal QT prolongation secondary to a LQTS-causative mutation rather than acquired QT prolongation with a >50% positive predictive value. This algorithm may facilitate screening for this potentially lethal, yet highly treatable, genetic heart disease.

Introduction:Despite bariatric surgery is the most effective and durable treatment for clinically morbid obesity, its association with intraoperative or 30-Day postoperative cardiovascular events after bariatric surgery is unclear.Hypothesis:To examine the association of preoperative body mass index (BMI) with adverse intraoperative or 30-day postoperative cardiovascular events after bariatric surgery.Methods:Our study extracted data from 785 321 patients who underwent bariatric surgery from 2015 to 2019 in the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP), which covers more than 90% of all bariatric surgery programs in the United States and Canada. The exposures were preoperative BMI and highest recorded preoperative BMI. The main outcomes were intraoperative or 30-day postoperative major adverse cardiovascular events (MACE).Results:Of the 785 321 patients (mean [SD] age 44.8 [11.8] years; 79.9% women), 1 541 patients suffered at least one MACE event intraoperative or 30-day postoperative bariatric surgery. Compared with patients with a preoperative BMI of 35.0 to 39.9, the multivariable-adjusted ORs (95% CIs) for intraoperative or 30-day postoperative MACE events for patients with preoperative BMI of 40.0 to 44.9, 45.0 to 49.9, 50.0 to 54.9, and 55.0 and greater were 1.05 (95% CI, 0.91-1.21), 1.19 (95% CI, 1.02-1.38), 1.28 (95% CI, 1.07-1.53), and 1.77 (95% CI, 1.50-2.09), respectively (Pfor trend < 0.001). Moreover, compared with highest recorded preoperative BMI of 35.0 to 39.9, the multivariable-adjusted ORs (95% CIs) for intraoperative or 30-day postoperative MACE events for patients with preoperative BMI of 40.0 to 44.9, 45.0 to 49.9, 50.0 to 54.9, and 55.0 and greater were 1.20 (95% CI, 1.01-1.41), 1.18 (95% CI, 0.99-1.40), 1.32 (95% CI, 1.09-1.59), and 1.76 (95% CI, 1.48-2.10), respectively (Pfor trend < 0.001).Conclusions:In this study, we found that higher preoperative BMI and higher highest recorded BMI were both associated with a higher risk of MACE events intraoperative or 30-day postoperative bariatric surgery. These findings may help improve perioperative cardiovascular optimization and provide evidence for future updates of clinical guidelines regarding bariatric surgery.

Acutely decompensated heart failure (HF), one of the most common reasons for hospitalization, places an intense economic pressure on the health care system and adversely affects outcome of HF patients. Due to lack of reliable clinical tools to assess and monitor hemodynamics, accurate judgment on cardiac preload remains a challenge and complicates current inpatient HF management. In this review, we discuss the emerging role of real-time quantitative Doppler echocardiography (DE) in identifying inappropriate cardiac preload, monitoring volume status during the management, and improving quality of care in patients with acute HF. We illustrate the utilization of DE in common clinical scenarios, propose stepwise algorithms to effectively utilize serial quantitative DE in the bedside care, and discuss obstacles and prospects of quantitative DE utilization in HF management. These efforts will further prompt the development of multi-center prospective studies to define and validate the specific roles of quantitative DE in reducing hospitalization time and improving outcome of HF patients.

Primary hepatic neuroendocrine tumors (PHNET) are extremely rare and difficult to distinguish from primary and metastatic liver cancers since PHNETs blood supply comes from the liver artery. This study aims to investigate CT and MR imaging findings of primary hepatic neuroendocrine tumor (PHNET) and correlation with the 2010 WHO pathological classification. We examined CT and MRI scans from 29 patients who were diagnosed with PHNET and correlated the data with the 2010 WHO classification of neuroendocrine tumors. According to the 2010 WHO classification system, PHNETs are divided into three grades based on histological criteria. Grade 1 tumors are singular, solid nodules with enhancement at the arterial phase on CT and MRI scans. In grade 1 tumors, the dynamic-contrast enhancement curve shows rapid wash-in in the arterial phase. Grade 2 tumors can have a singular or multiple distribution pattern, necrosis, and nodule or marginal ring-like enhancements. Grade 3 tumors have multiple lesions, internal necrosis, and evidence of hemorrhage. Portal venous tumor thrombus was seen in one case. As tumor grades increase, the capsule begins to lose integrity and tumor apparent diffusion coefficient (ADC) values decrease(grade 1: 1.39 ± 0.20× 10−3mm2/s versus grade 2: 1.26 ± 0.23× 10−3mm2/s versus grade 3: 1.14 ± 0.17× 10−3mm2/s). CT and MRI can reflect tumor grade and pathological features of PHNETs, which are helpful in accurately diagnosing PHNETs.