bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of radiofrequency catheter ablation on left atrial structure and function in patients with different types of atrial fibrillation
Authors: Liu Yue , Liu Qian , Yang Ying , Zhang Chenfeng , Yin Hongning , Wu Jinglan , Yao Lixia , Jin Lili , Yang Jing , Feng Liang , Xie Ruiqin 
Published: June 2022

AbstractRadiofrequency catheter ablation (RFCA) is widely used to treat atrial fibrillation (AF), but its effect on left atrial (LA) remodeling in patients with AF is not completely clarified. Few studies have reported the changes in structure and function of the left atrium in patients with different types of AF after RFCA. To analyze the effect of RFCA on the LA structure and function in patients with nonvalvular paroxysmal AF, persistent AF and long-standing persistent AF (LSPAF). RFCA was performed in 180 patients with paroxysmal AF, persistent AF and LSPAF. The changes of LA structure and function in echocardiogram and speckle-tracking echocardiography findings were compared before the procedure, and at 1, 2, 3, 4 weeks, and 2, 3, 6, and 9–12 months after the procedure. There were 60 patients in the paroxysmal AF group, 60 in the persistent AF group and 60 patients in LSPAF group. The pre-procedure LA diameter and volume were smaller in the paroxysmal AF group than persistent AF and LSPAF group. There was no significant change of in the LA structure and function in the paroxysmal AF group within 1 year. In the persistent AF and LSPAF groups, LA structure (anteroposterior diameter, LA volume) significantly decreased, but remained larger than that in paroxysmal AF group. In persistent and LSPAF, function (LA ejection fraction, strain, strain rate) increased significantly within 1 week, then gradually increased. RFCA improved the LA structure and function and resulted in heart reverse remodeling, especially for persistent AF and LSPAF.
MicroRNAs and other small RNAs in Aedes aegypti saliva and salivary glands following chikungunya virus infection
Authors: Fiorillo Carmine , Yen Pei-Shi , Colantoni Alessio , Mariconti Marina , Azevedo Nayara , Lombardo Fabrizio , Failloux Anna-Bella , Arcà Bruno 
Published: June 2022

AbstractMosquito saliva facilitates blood feeding through the anti-haemostatic, anti-inflammatory and immunomodulatory properties of its proteins. However, the potential contribution of non-coding RNAs to host manipulation is still poorly understood. We analysed small RNAs from Aedes aegypti saliva and salivary glands and show here that chikungunya virus-infection triggers both the siRNA and piRNA antiviral pathways with limited effects on miRNA expression profiles. Saliva appears enriched in specific miRNA subsets and its miRNA content is well conserved among mosquitoes and ticks, clearly pointing to a non-random sorting and occurrence. Finally, we provide evidence that miRNAs from Ae. aegypti saliva may target human immune and inflammatory pathways, as indicated by prediction analysis and searching for experimentally validated targets of identical human miRNAs. Overall, we believe these observations convincingly support a scenario where both proteins and miRNAs from mosquito saliva are injected into vertebrates during blood feeding and contribute to the complex vector–host–pathogen interactions.
The integrative analysis of competitive endogenous RNA regulatory networks in osteoporosis
Authors: Li Hao , Wang Changyuan , Jin Yue , Cai Yuanqing , Sun Huijun , Liu Mozhen 
Published: June 2022

AbstractOsteoporosis (OP) is a common bone disease of old age resulting from the imbalance between bone resorption and bone formation. CircRNAs are a class of endogenous non-coding RNAs (ncRNAs) involved in gene regulation and may play important roles in the development of OP. Here, we aimed to discover the OP‑related circRNA–miRNA–mRNA (ceRNA) network and the potential mechanisms. Six microarray datasets were obtained from the GEO database and the OP‑related differentially expressed genes (DEGs), circRNAs (DECs), and miRNAs (DEMs) were screened out from these datasets. Then, combined with the prediction of the relationships between DEGs, DEMs, and DECs, a ceRNA network containing 7 target circRNAs, 5 target miRNAs, and 38 target genes was constructed. Then the RNA-seq verification by using total RNAs isolated from the femurs of normal and ovariectomized Wistar rats indicated that MFAP5, CAMK2A, and RGS4 in the ceRNA network were closely associated with osteoporosis. Function enrichment analysis indicated that the target circRNAs, miRNAs, and genes were involved in the process of MAPK cascade, hormone stimulus, cadherin binding, rRNA methyltransferase, PI3K-Akt signaling pathway, and Vitamin digestion and absorption, etc. Then a circRNA–miRNA–hub gene subnetwork was constructed and the qRT-PCR analysis of human bone tissues from the femoral head was used to confirm that the transcription of hsa_circR_0028877, hsa_circR_0082916, DIRAS2, CAMK2A, and MAPK4 showed a significant correlation with osteogenic genes. Besides, the two axes of hsa_circR_0028877/hsa-miR-1273f/CAMK2A and hsa_circR_0028877/hsa-miR-1273f/DIRAS2 conformed to be closely associated with OP. Additionally, by constructing a drug-target gene network, RKI-1447, FRAX486, Hyaluronic, and Fostamatinib were identified as therapeutic options for OP. Our study revealed the potential links between circRNAs, miRNAs, and mRNAs in OP, suggesting that the ceRNA mechanism might contribute to the occurrence of OP.
AMAISE: a machine learning approach to index-free sequence enrichment
Authors: Krishnamoorthy Meera , Ranjan Piyush , Erb-Downward John R. , Dickson Robert P. , Wiens Jenna 
Published: June 2022

AbstractMetagenomics holds potential to improve clinical diagnostics of infectious diseases, but DNA from clinical specimens is often dominated by host-derived sequences. To address this, researchers employ host-depletion methods. Laboratory-based host-depletion methods, however, are costly in terms of time and effort, while computational host-depletion methods rely on memory-intensive reference index databases and struggle to accurately classify noisy sequence data. To solve these challenges, we propose an index-free tool, AMAISE (A Machine Learning Approach to Index-Free Sequence Enrichment). Applied to the task of separating host from microbial reads, AMAISE achieves over 98% accuracy. Applied prior to metagenomic classification, AMAISE results in a 14–18% decrease in memory usage compared to using metagenomic classification alone. Our results show that a reference-independent machine learning approach to host depletion allows for accurate and efficient sequence detection.
TAS1553, a small molecule subunit interaction inhibitor of ribonucleotide reductase, exhibits antitumor activity by causing DNA replication stress
Authors: Ueno Hiroyuki , Hoshino Takuya , Yano Wakako , Tsukioka Sayaka , Suzuki Takamasa , Hara Shoki , Ogino Yoshio , Chong Khoon Tee , Suzuki Tatsuya , Tsuji Shingo , Itadani Hikaru , Yamamiya Ikuo , Otsu Yoshihiro , Ito Satoshi , Yonekura Toshiya , Terasaka Miki , Tanaka Nozomu , Miyahara Seiji 
Published: June 2022

AbstractRibonucleotide reductase (RNR) is composed of two non-identical subunits, R1 and R2, and plays a crucial role in balancing the cellular dNTP pool, establishing it as an attractive cancer target. Herein, we report the discovery of a highly potent and selective small-molecule inhibitor, TAS1553, targeting protein-protein interaction between R1 and R2. TAS1553 is also expected to demonstrate superior selectivity because it does not directly target free radical or a substrate binding site. TAS1553 has shown antiproliferative activity in human cancer cell lines, dramatically reducing the intracellular dATP pool and causing DNA replication stress. Furthermore, we identified SLFN11 as a biomarker that predicts the cytotoxic effect of TAS1553. Oral administration of TAS1553 demonstrated robust antitumor efficacy against both hematological and solid cancer xenograft tumors and also provided a significant survival benefit in an acute myelogenous leukemia model. Our findings strongly support the evaluation of TAS1553 in clinical trials.
Dual nature of magnetic nanoparticle dispersions enables control over short-range attraction and long-range repulsion interactions
Authors: Al Harraq Ahmed , Hymel Aubry A. , Lin Emily , Truskett Thomas M. , Bharti Bhuvnesh 
Published: June 2022

AbstractCompetition between attractive and repulsive interactions drives the formation of complex phases in colloidal suspensions. A major experimental challenge lies in decoupling independent roles of attractive and repulsive forces in governing the equilibrium morphology and long-range spatial distribution of assemblies. Here, we uncover the ‘dual nature’ of magnetic nanoparticle dispersions, particulate and continuous, enabling control of the short-range attraction and long-range repulsion (SALR) between suspended microparticles. We show that non-magnetic microparticles suspended in an aqueous magnetic nanoparticle dispersion simultaneously experience a short-range depletion attraction due to the particulate nature of the fluid in competition with an in situ tunable long-range magnetic dipolar repulsion attributed to the continuous nature of the fluid. The study presents an experimental platform for achieving in situ control over SALR between colloids leading to the formation of reconfigurable structures of unusual morphologies, which are not obtained using external fields or depletion interactions alone.
Alpha7 nicotinic acetylcholine receptor mediates chronic nicotine inhalation-induced cardiopulmonary dysfunction
Authors: Whitehead Anna K. , Fried Nicholas D. , Li Zhen , Neelamegam Kandasamy , Pearson Charlotte S. , LaPenna Kyle B. , Sharp Thomas E. , Lefer David J. , Lazartigues Eric , Gardner Jason D. , Yue Xinping 
Published: June 2022

Abstract
Cigarette smoking remains the leading modifiable risk factor for cardiopulmonary diseases; however, the effects of nicotine alone on cardiopulmonary function remain largely unknown. Previously, we have shown that chronic nicotine vapor inhalation in mice leads to the development of pulmonary hypertension (PH) with right ventricular (RV) remodeling. The present study aims to further examine the cardiopulmonary effects of nicotine and the role of the α7 nicotinic acetylcholine receptor (α7-nAChR), which is widely expressed in the cardiovascular system. Wild-type (WT) and α7-nAChR knockout (α7-nAChR−/−) mice were exposed to room air (control) or nicotine vapor daily for 12 weeks. Consistent with our previous study, echocardiography and RV catheterization reveal that male WT mice developed increased RV systolic pressure with RV hypertrophy and dilatation following 12-week nicotine vapor exposure; in contrast, these changes were not observed in male α7-nAChR−/− mice. In addition, chronic nicotine inhalation failed to induce PH and RV remodeling in female mice regardless of genotype. The effects of nicotine on the vasculature were further examined in male mice. Our results show that chronic nicotine inhalation led to impaired acetylcholine-mediated vasodilatory response in both thoracic aortas and pulmonary arteries, and these effects were accompanied by altered endothelial nitric oxide synthase phosphorylation (enhanced inhibitory phosphorylation at threonine 495) and reduced plasma nitrite levels in WT but not α7-nAChR−/− mice. Finally, RNA sequencing revealed up-regulation of multiple inflammatory pathways in thoracic aortas from WT but not α7-nAChR−/− mice. We conclude that the α7-nAChR mediates chronic nicotine inhalation-induced PH, RV remodeling and vascular dysfunction.
PruneFaceDet: Pruning lightweight face detection network by sparsity training
Authors: Jiang Nanfei , Xiong Zhexiao , Tian Hui , Zhao Xu , Du Xiaojie , Zhao Chaoyang , Wang Jinqiao 
Published: June 2022

AbstractFace detection is the basic step of many face analysis tasks. In practice, face detectors usually run on mobile devices with limited memory and computing resources. Therefore, it is important to keep face detectors lightweight. To this end, current methods usually focus on directly designing lightweight detectors. Nevertheless, it is not fully explored whether the resource consumption of these lightweight detectors can be further suppressed without too much sacrifice on accuracy. In this study, we propose to apply the network pruning method to the lightweight face detection network, to further reduce its parameters and floating point operations. To identify the channels of less importance, we perform network training with sparsity regularisation on channel scaling factors of each layer. Then, we remove the connections and corresponding weights with near‐zero scaling factors after sparsity training. We apply the proposed pruning pipeline to a state‐of‐the‐art face detection method, EagleEye, and get a shrunken EagleEye model, which has a reduced number of computing operations and parameters. The shrunken model achieves comparable accuracy as the unpruned model. By using the proposed method, the shrunken EagleEye achieves a 56.3% reduction of parameter size with almost no accuracy loss on the WiderFace dataset.
Ultra‐short‐term PV power prediction model based on HP‐OVMD and enhanced emotional neural network
Authors: Wang* Yufei , Yang Qixing , Xue Hua , Mi Yang , Tu Yijun 
Published: June 2022

AbstractAccurate photovoltaic (PV) power prediction plays an increasingly crucial role to maintain the safety and reliability of power grid operation. However, the fluctuation and non‐stationarity of PV power make it a challenging task to optimize the accurate results. This paper presents a novel prediction model which is the combination of Hodrick–Prescott (HP) filter, optimized variational mode decomposition (OVMD), and enhanced emotional neural network (EENN). It overcomes the adverse effects of random changes under highly volatile weather conditions. First, the trend component and fluctuation component of PV power are screened through HP filter as the pre‐step to alleviate the non‐linearity impact of PV power data. Then, OVMD is used to decompose the residual PV power time series into a series of relatively stationary intrinsic modes. Finally, the EENN model optimized by the grey wolf optimization (GWO) is established to predict each subseries, and the prediction results of each subseries are reconstructed to obtain the final predicted results. The numerical results based on actual PV power data show that the prediction accuracy of the proposed model is significantly improved compared with the contrast models, and the proposed model achieves the best accuracy against the OVMD‐GWO‐EENN, VMD‐GWO‐EENN, and GWO‐EENN models.
Statistical evaluation of wind speed forecast models for microgrid distributed control
Authors: Cruz‐Victorio Marcos Eduardo , Kazemtabrizi Behzad , Shahbazi Mahmoud 
Published: June 2022

AbstractWith the increasing needs to decarbonise existing energy systems, there is an effort to integrate small‐scale distributed generation sources, such as wind generators, with the electric demand in circuits known as microgrids. The operation of distributed variable renewable resources is subject to an optimum operating regime, ahead of real‐time, which relies on output forecast. However, many wind speed forecast models are designed for centralised controllers, which are vulnerable to control failures. A suitable wind forecast model for a distributed control system is, therefore, required for optimal and reliable use of renewable generation. This paper presents a comparison of wind speed forecast models suited for distributed control, evaluating them in terms of the statistical significant difference in accuracy and computational resource requirements. This is essential since computational resources are limited in distributed control schemes. The data used in this paper is the historical wind speed of the Auchencorth Moss Atmospheric Observatory from 2016 to the end of 2019. Two forecast model types based on Auto‐regression and Artificial Neural Network (ANN) are compared using the Diebold‐Mariano test. Results show that ANN models with parallel hidden layers have the highest accuracy with statistical significant difference, while remaining suitable for microgrid distributed control.
Toward on-sky adaptive optics control using reinforcement learning
Authors: Nousiainen J. , Rajani C. , Kasper M. , Helin T. , Haffert S. Y. , Vérinaud C. , Males J. R. , Van Gorkom K. , Close L. M. , Long J. D. , Hedglen A. D. , Guyon O. , Schatz L. , Kautz M. , Lumbres J. , Rodack A. , Knight J. M. , Miller K. 
Published: June 2022

Context.The direct imaging of potentially habitable exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based, extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current control laws of XAO systems leave strong residuals.Aims.Current AO control strategies such as static matrix-based wavefront reconstruction and integrator control suffer from a temporal delay error and are sensitive to mis-registration, that is, to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction, and, therefore, reduce the residual flux in the coronagraphic point spread function (PSF).Methods.We extend previous work in reinforcement learning for AO. The improved method, called the Policy Optimization for Adaptive Optics (PO4AO), learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensor (PWFS) for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using Magellan Adaptive Optics eXtreme system (MagAO-X) at the Steward laboratory.Results.PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors of 3–5 within the control region of deformable mirror and PWFS, both in simulation and in the laboratory. The presented method is also quick to train, that is, on timescales of typically 5–10 s, and the inference time is sufficiently small (<ms) to be used in real-time control for XAO with currently available hardware even for extremely large telescopes.
The BEHOMO project: Λ Lemaître-Tolman-Bondi N-body simulations
Authors: Marra V. , Castro T. , Camarena D. , Borgani S. , Ragagnin A. 
Published: June 2022

Context. Our universe may feature large-scale inhomogeneities and anisotropies that cannot be explained by the standard model of cosmology, that is, the homogeneous and isotropic Friedmann-Lemaître-Robertson-Walker metric, on which the Λ cold dark matter model is built, may not accurately describe observations. Currently, there is not a satisfactory understanding of the evolution of the large-scale structure on an inhomogeneous background.
Aims. We have launched the cosmology beyond homogeneity and isotropy (BEHOMO) project to study the inhomogeneous Λ Lemaître-Tolman-Bondi model with the methods of numerical cosmology. Understanding the evolution of the large-scale structure is a necessary step in constraining inhomogeneous models with present and future observables and placing the standard model on more solid ground.
Methods. We perform Newtonian N-body simulations, whose accuracy in describing the background evolution is checked against the general relativistic solution. The large-scale structure of the corresponding Λ cold dark matter simulation is also validated.
Results. We obtain the first set of simulations of the Λ Lemaître-Tolman-Bondi model ever produced. The data products consist of 11 snapshots between redshift 0 and 3.7 for each of the 68 simulations that have been performed, together with halo catalogs and lens planes relative to 21 snapshots, between redshift 0 and 4.2, for a total of approximately 180 TB of data.
Conclusions. We plan to study the growth of perturbations at the linear and nonlinear level, gravitational lensing, and cluster abundances and proprieties.
Neue ESC-Leitlinien zur Herzschrittmacher- und Resynchronisationstherapie – Patientenevaluation und Implantation
Authors: Vogler Julia , Castro Liesa , Tilz Roland Richard 
Published: June 2022

ZusammenfassungDie Herzschrittmachertherapie ist ein wesentlicher Teil der klinischen Elektrophysiologie sowie der allgemeinen Kardiologie. Auch wenn sich im Bereich manch klarer Indikationen über die
Jahre wenig verändert hat, sind seit der Publikation der ESC-Leitlinien zur Schrittmachertherapie im Jahr 2013 neue Erkenntnisse z. B. im Bereich der Schrittmachertherapie bei Synkope, nach
TAVI, der kardialen Resynchronisationstherapie und dem Conduction-System-Pacing hinzugekommen. Eine wesentliche Bedeutung kommt daneben sowohl der präoperativen Evaluation eines Patienten
mit vermuteter oder dokumentierter Bradykardie als auch der eigentlichen Implantation und dem perioperativen Management zu. Im Fokus stehen dabei eine standardisierte Diagnostik zur
Abklärung der Indikation sowie die Vermeidung von Komplikationen während der Implantation.
Silver-Catalyzed, One-Pot, Three-Component Difunctionalization of Quinones: Synthesis of Indole-Functionalized p-Iminoquinone Derivatives
Authors: Dong Yu , Li Zhong-Hui , He Bing , Ye Ji-Xian , Luo Qi-Qi , Zheng Yi , Zhou Rui-Qi , Mei Ting , Chen Xiang-Long , Shi Zhi-Chuan 
Published: June 2022

AbstractA one-pot, three-component difunctionalization of quinones with indoles and arylamines has been developed to synthesize indole functionalized p-iminoquinones derivatives. The approach employed AgOAc as the catalyst in the presence of 3-chlorophenylboronic acid, giving a series of indole functionalized p-iminoquinones derivatives in moderate to good yields. This catalytic approach represents a step-economic and convenient strategy for the difunctionalization of quinones. A plausible reaction pathway has been proposed based on a series of control experiments.
(3+2) Cycloadditions of Vinyl Sulfonyl Fluorides with Ethyl Diazoacetate or Azides: Metal-Free Synthesis of Pyrazole and Triazole Scaffolds via SO2 Elimination
Authors: Kumara Swamy K. C. , Sandeep K. , Sanjeeva Kumar A. , Qureshi Asif Ali 
Published: June 2022

AbstractA (3+2) cycloaddition reaction between substituted vinyl sulfonyl fluorides and ethyl diazoacetate or azides for the rapid construction of pyrazole or triazole cores via Michael addition and SO2 gas elimination is developed. Trimethylsilyl azide or organic azide selectively attacks at the β-carbon of vinyl sulfonyl fluoride rather than at the S(VI) center and generates C-substituted or C,N-disubstituted triazole. In contrast, vinyl sulfonyl fluorides react with ethyl diazoacetate to generate pyrazoles in good to high yields.
Penile Ulcer as the Unusual Initial Presentation of Nasal NK/T Cell Lymphoma
Authors: Kanthaje Apoorva , Amirtham Usha , Babu M. C. Suresh , Maregowda Shivalingaiah , Adiga Pramod , Ramachandra C. 
Published: June 2022

AbstractExtranodal natural killer (NK)/T cell lymphoma is a highly aggressive non-Hodgkin lymphoma that predominantly affects the upper aerodigestive tract. The nasal type accounts for ∼80% of cases of NK/T cell lymphomas. In advanced stages, the disease can disseminate to various sites such as skin, testis, eyes, gastrointestinal tract, and soft tissue. NK/T cell lymphoma presenting as lesion in penis is extremely rare. While reviewing the published literature, we found only three reported cases of NK/T cell lymphoma involving the penis. Among them, none was primary NK/T cell lymphoma of penis. We report a 60-year-old NK/T cell lymphoma patient who presented with destructive penile ulcer as the initial presenting symptom, who subsequently was found to have a nasal mass also with features of NK/T cell lymphoma. He underwent partial penectomy elsewhere and chemotherapy with steroid, methotrexate, ifosfamide, L-asparaginase, and etoposide protocol was given.