bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between peak oxygen uptake, lung function, and bronchiectasis in children with cystic fibrosis in the era of CFTR modulators
Authors: Du Berry Cassidy , Westrupp Nicole , Shanthikumar Shivanthan , Welsh Liam 
Published: January 2021

AbstractBackgroundWith the emergence of cystic fibrosis transmembrane conductance regulator (CFTR) modulators, forced expiratory volume in 1 s (FEV1) may become a less sensitive measure of pulmonary disease progression in children with cystic fibrosis (CF). Increasing evidence shows that peak oxygen uptake (VO2peak) is a strong predictor of prognosis in CF. The primary aim of this study was to describe the associations between peak oxygen uptake, lung function, and bronchiectasis in children with CF in the era of CFTR modulators.MethodsSpirometry and a maximal cardiopulmonary exercise test (CPET) were performed on the same day and compared to markers of disease severity. Markers of disease severity included a number of pulmonary exacerbations resulting in hospital admission within the preceding 12 months, body mass index, Pseudomonas aeruginosa (PsA) infection, and bronchiectasis.ResultsFifty‐two subjects (24 female) with CF participated in the study with a mean (SD) age of 13.8 (2.4) years, range 8–18 years. Forty‐nine participants met satisfactory criteria for a maximal CPET. A significant correlation was found between relative VO2peak %predicted and FEV1%predicted (r = .546, p < .001). A total of 4/49 children demonstrated an impaired aerobic capacity despite normal spirometry. Participants who had experienced one or more pulmonary exacerbations in the previous 12 months had a significantly lower relative VO2peak %predicted (p = .02).ConclusionsIn children with CF who have mild pulmonary disease, there is significant correlation between FEV1 and VO2peak. In all, 8.2% of participants had an abnormal CPET result despite normal spirometry, and preceding pulmonary exacerbations were associated with poorer CPET outcomes. CPET may offer important prognostic information for clinical decision making in this new era of CFTR modulators.
Protein structure search to support the development of protein structure prediction methods
Authors: Ayoub Ronald , Lee Yugyung 
Published: January 2021

AbstractProtein structure prediction is a long‐standing unsolved problem in molecular biology that has seen renewed interest with the recent success of deep learning with AlphaFold at CASP13. While developing and evaluating protein structure prediction methods, researchers may want to identify the most similar known structures to their predicted structures. These predicted structures often have low sequence and structure similarity to known structures. We show how RUPEE, a purely geometric protein structure search, is able to identify the structures most similar to structure predictions, regardless of how they vary from known structures, something existing protein structure searches struggle with. RUPEE accomplishes this through the use of a novel linear encoding of protein structures as a sequence of residue descriptors. Using a fast Needleman‐Wunsch algorithm, RUPEE is able to perform alignments on the sequences of residue descriptors for every available structure. This is followed by a series of increasingly accurate structure alignments from TM‐align alignments initialized with the Needleman‐Wunsch residue descriptor alignments to standard TM‐align alignments of the final results. By using alignment normalization effectively at each stage, RUPEE also can execute containment searches in addition to full‐length searches to identify structural motifs within proteins. We compare the results of RUPEE to the protein structure searches mTM‐align, SSM, CATHEDRAL, and VAST using a benchmark derived from the protein structure predictions submitted to CASP13. RUPEE identifies better alignments on average with respect to TM‐score as well as scores specific to SSM and CATHEDRAL, Q‐score and SSAP‐score, respectively.
Comparison of cardiac rehabilitation (exercise + education), exercise only, and usual care for patients with coronary artery disease: A non‐randomized retrospective analysis
Authors: Hu Yanqun , Li Li , Wang Taihao , Liu Yuanyuan , Zhan Xiaohong , Han Shuyan , Huang Li 
Published: January 2021

AbstractCardiac rehabilitation program is well‐established but the Rehabilitation After Myocardial Infarction Trial (RAMIT) is reported that it does not affect mortality and morbidity of patients after myocardial infarction during follow‐up period. The objectives of the study were to compare functional walking capacity, risk factor control, and morbidities in follow‐up for cardiac rehabilitation (exercise + education), exercise only, and usual care among patients with coronary artery disease. A total of 492 male and female patients (age range: 45–73 years) with coronary artery disease after myocardial infarction or underwent percutaneous coronary intervention or coronary artery bypass grafting surgeries referred to cardiac rehabilitation were included in the study. Patients were participating in a cardiac rehabilitation program (exercise + education, CRP cohort, n = 125), exercise only (USC cohort, n = 182), or usual care (NCR cohort, n = 185). Data regarding incremental shuttle walk test, lipid profile, the Patient Health Questionnaire 9, and morbidities in follow‐up of patients were retrospectively collected and analyzed. After completion of 1 year, cardiac rehabilitation program (p < 0.0001, q = 20.939) and exercise (p < 0.0001, q = 6.059) were successfully increased incremental shuttle walk test. After completion of 1 year, cardiac rehabilitation program reduced low‐density lipoprotein (p = 0.007, q = 3.349) and depressive symptoms (p < 0.0001, q = 5.649). Morbidities were reported fewer in the patients of CRP cohort than those of USC (p = 0.003, q = 3.427) and NCR (p = 0.003, q = 4.822) cohorts after completion of 1 year of program. Cardiac rehabilitation program (exercise +education) improved functional walking capacity, controlled risk factors, and reduced morbidities of patients with coronary artery disease than exercise only and usual care (Level of evidence: III).
Engineering Oxygen‐Irrelevant Radical Nanogenerator for Hypoxia‐Independent Magnetothermodynamic Tumor Nanotherapy
Authors: Shen Yujia , Dong Caihong , Xiang Huijing , Li Cuixian , Zhuang Fan , Chen Yixin , Lu Qing , Chen Yu , Huang Beijian 
Published: January 2021

AbstractTumor hypoxia substantially lowers the treatment efficacy of oxygen‐relevant therapeutic modalities because the production of reactive oxygen species in oxygen‐relevant anticancer modalities is highly dependent on oxygen level in tumor tissues. Here a distinctive magnetothermodynamic anticancer strategy is developed that takes the advantage of oxygen‐irrelevant free radicals produced from magnetothermal decomposable initiators for inducing cancer‐cell apoptosis in vitro and tumor suppression in vivo. Free‐radical nanogenerator is constructed through in situ engineering of a mesoporous silica coating on the surface of superparamagnetic Mn and Co‐doped nanoparticles (MnFe2O4@CoFe2O4, denoted as Mag) toward multifunctionality, where mesoporous structure provides reservoirs for efficient loading of initiators and the Mag core serves as in situ heat source under alternating magnetic field (AMF) actuation. Upon exposure to an exogenous AMF, the magnetic hyperthermia effect of superparamagnetic core lead to the rapid decomposition of the loaded/delivered initiators (AIPH) to produce oxygen‐irrelevant free radicals. Both the magnetothermal effect and generation of toxic free radicals under AMF actuation are synergistically effective in promoting cancer‐cell death and tumor suppression in the hypoxic tumor microenvironment. The prominent therapeutic efficacy of this radical nanogenerator represents an intriguing paradigm of oxygen‐irrelevant nanoplatform for AMF‐initiated synergistic cancer treatment.
Neutrophil Extracellular Traps in Atherosclerosis and Thrombosis
Authors: Hofbauer Thomas M. , Ondracek Anna S. , Lang Irene M. 
Published: January 2021

AbstractDespite effective therapeutic and preventive strategies, atherosclerosis and its complications still represent a substantial health burden. Leukocytes and inflammatory mechanisms are increasingly recognized as drivers of atherosclerosis. Neutrophil granulocytes within the circulation were recently shown to undergo neutrophil extracellular trap (NET) formation, linking innate immunity with acute complications of atherosclerosis. In this chapter, we summarize mechanisms of NET formation, evidence for their involvement in atherosclerosis and thrombosis, and potential therapeutic regimens specifically targeting NET components.
An Effective Intrusion Detection Model Based on Pls-Logistic Regression with Feature Augmentation
Authors: Gu Jie 
Published: January 2021

AbstractComputer network is playing a significantly important role in our society, including commerce, communication, consumption and entertainment. Therefore, network security has become increasingly important. Intrusion detection systems have received considerable attention, which not only can detect known attacks or intrusions, but also can detect unknown attacks. Among the various methods applied to intrusion detection, logistic regression is the most widely used, which can achieve good performances and have good interpretability at the same time. However, intrusion detection systems usually confront with data of large scale and high dimension. How to reduce the dimension and improve the data quality is significant to improve the detection performances. Therefore, in this paper, we propose an effective intrusion detection model based on pls-logistic regression with feature augmentation. More specifically, the feature augmentation technique is implemented on the original features with goal of obtaining high-qualified training data; and then, pls-logistic regression is applied on the newly transformed data to perform dimension reduction and detection model building. The NSL-KDD dataset is used to evaluate the proposed method, and the empirical results show that our proposed method can achieve good performances in terms of accuracy, detection rate and false alarm rate.
Perosonalized Differentially Private Location Collection Method with Adaptive GPS Discretization
Authors: Liu Huichuan , Zeng Yong , Liu Jiale , Liu Zhihong , Ma Jianfeng , Zhu Xiaoyan 
Published: January 2021

AbstractIn recent years, with the development of mobile terminals, geographic location has attracted the attention of many researchers because of its convenience in collection and its ability to reflect user profile. To protect user privacy, researchers have adopted local differential privacy in data collection process. However, most existing methods assume that location has already been discretized, which we found, if not done carefully, may introduces huge noise, lowering collected result utility. Thus in this paper, we design a differentially private location division module that could automatically discretize locations according to access density of each region. However, as the size of discretized regions may be large, if directly applying existing local differential privacy based attribute method, the overall utility of collected results may be completely destroyed. Thus, we further improve the optimized binary local hash method, based on personalized differential privacy, to collect user visit frequency of each discretized region. This solution improve the accuracy of the collected results while satisfying the privacy of the user’s geographic location. Through experiments on synthetic and real data sets, this paper proves that the proposed method achieves higher accuracy than the best known method under the same privacy budget.
Logarithmic correction to the entropy of extremal black holes in $$ \mathcal{N} $$ = 1 Einstein-Maxwell supergravity
Authors: Banerjee Gourav , Karan Sudip , Panda Binata 
Published: January 2021

Abstract
We study one-loop covariant effective action of “non-minimally coupled” $$ \mathcal{N} $$
N
= 1, d = 4 Einstein-Maxwell supergravity theory by heat kernel tool. By fluctuating the fields around the classical background, we study the functional determinant of Laplacian differential operator following Seeley-DeWitt technique of heat kernel expansion in proper time. We then compute the Seeley-DeWitt coefficients obtained through the expansion. A particular Seeley-DeWitt coefficient is used for determining the logarithmic correction to Bekenstein-Hawking entropy of extremal black holes using quantum entropy function formalism. We thus determine the logarithmic correction to the entropy of Kerr-Newman, Kerr and Reissner-Nordström black holes in “non-minimally coupled” $$ \mathcal{N} $$
N
= 1, d = 4 Einstein-Maxwell supergravity theory.
Aquaporin-1 and aquaporin-9 gene variations in sudden infant death syndrome
Authors: Opdal Siri Hauge , Ferrante Linda , Rognum Torleiv Ole , Stray-Pedersen Arne 
Published: January 2021

AbstractSeveral studies have indicated that a vulnerability in the development and regulation of brain function is involved in sudden infant death syndrome (SIDS). The aim of this study was to investigate the genes encoding the brain aquaporins (AQPs) AQP1 and AQP9 in SIDS. The hypothesis was that specific variants of these genes are part of the genetic vulnerability predisposing infants to sudden unexpected death. The study included 168 SIDS cases with a median age of 15.5 (range 2–52) weeks and 372 adolescent/adult deceased controls with a median age of 44 (range 11–91) years. In the AQP1 gene, the rs17159702 CC/CT genotypes were found to be associated with SIDS (p = 0.02). In the AQP9 gene, the combination of a TT genotype of rs8042354, rs2292711 and rs13329178 was more frequent in SIDS cases than in controls (p = 0.03). In the SIDS group, an association was found between genetic variations in the AQP1 gene and maternal smoking and between the 3xTT combination in the AQP9 gene and being found lifeless in a prone position. In conclusion, this study adds further evidence to the involvement of brain aquaporins in SIDS, suggesting that specific variants of AQP genes constitute a genetic predisposition, making the infant vulnerable to sudden death together with external risk factors and probably other genetic factors.
Identifying the paths of climate effects on population dynamics: dynamic and multilevel structural equation model around the annual cycle
Authors: Selonen Vesa , Helle Samuli , Laaksonen Toni , Ahola Markus P. , Lehikoinen Esa , Eeva Tapio 
Published: January 2021

AbstractHow environmental factors influence population dynamics in long-distance migrants is complicated by the spatiotemporal diversity of the environment the individuals experience during the annual cycle. The effects of weather on several different aspects of life history have been well studied, but a better understanding is needed on how weather affects population dynamics through the different associated traits. We utilise 77 years of data from pied flycatcher (Ficedula hypoleuca), to identify the most relevant climate signals associated with population growth rate. The strongest signals on population growth were observed from climate during periods when the birds were not present in the focal location. The population decline was associated with increasing precipitation in the African non-breeding quarters in the autumn (near the arrival of migrants) and with increasing winter temperature along the migration route (before migration). The number of fledglings was associated positively with increasing winter temperature in non-breeding area and negatively with increasing winter temperature in Europe. These possible carry-over effects did not arise via timing of breeding or clutch size but the exact mechanism remains to be revealed in future studies. High population density and low fledgling production were the intrinsic factors reducing the breeding population. We conclude that weather during all seasons has the potential to affect the reproductive success or population growth rate of this species. Our results show how weather can influence the population dynamics of a migratory species through multiple pathways, even at times of the annual cycle when the birds are in a different location than the climate signal.
Relationships between resource availability and elevation vary between metrics creating gradients of nutritional complexity
Authors: Lee Mark A. , Burger Grace , Green Emma R. , Kooij Pepijn W. 
Published: January 2021

AbstractPlant and animal community composition changes at higher elevations on mountains. Plant and animal species richness generally declines with elevation, but the shape of the relationship differs between taxa. There are several proposed mechanisms, including the productivity hypotheses; that declines in available plant biomass confers fewer resources to consumers, thus supporting fewer species. We investigated resource availability as we ascended three aspects of Helvellyn mountain, UK, measuring several plant nutritive metrics, plant species richness and biomass. We observed a linear decline in plant species richness as we ascended the mountain but there was a unimodal relationship between plant biomass and elevation. Generally, the highest biomass values at mid-elevations were associated with the lowest nutritive values, except mineral contents which declined with elevation. Intra-specific and inter-specific increases in nutritive values nearer the top and bottom of the mountain indicated that physiological, phenological and compositional mechanisms may have played a role. The shape of the relationship between resource availability and elevation was different depending on the metric. Many consumers actively select or avoid plants based on their nutritive values and the abundances of consumer taxa vary in their relationships with elevation. Consideration of multiple nutritive metrics and of the nutritional requirements of the consumer may provide a greater understanding of changes to plant and animal communities at higher elevations. We propose a novel hypothesis for explaining elevational diversity gradients, which warrants further study; the ‘nutritional complexity hypothesis’, where consumer species coexist due to greater variation in the nutritional chemistry of plants.
A computational modeling approach based on random fields for short fiber-reinforced composites with experimental verification by nanoindentation and tensile tests
Authors: Rauter Natalie 
Published: January 2021

AbstractIn this study a modeling approach for short fiber-reinforced composites is presented which allows one to consider information from the microstructure of the compound while modeling on the component level. The proposed technique is based on the determination of correlation functions by the moving window method. Using these correlation functions random fields are generated by the Karhunen–Loève expansion. Linear elastic numerical simulations are conducted on the mesoscale and component level based on the probabilistic characteristics of the microstructure derived from a two-dimensional micrograph. The experimental validation by nanoindentation on the mesoscale shows good conformity with the numerical simulations. For the numerical modeling on the component level the comparison of experimentally obtained Young’s modulus by tensile tests with numerical simulations indicate that the presented approach requires three-dimensional information of the probabilistic characteristics of the microstructure. Using this information not only the overall material properties are approximated sufficiently, but also the local distribution of the material properties shows the same trend as the results of conducted tensile tests.
Disruptive technologies in agricultural operations: a systematic review of AI-driven AgriTech research
Authors: Spanaki Konstantina , Sivarajah Uthayasankar , Fakhimi Masoud , Despoudi Stella , Irani Zahir 
Published: January 2021

AbstractThe evolving field of disruptive technologies has recently gained significant interest in various industries, including agriculture. The fourth industrial revolution has reshaped the context of agricultural technology (AgriTech) with applications of artificial intelligence (AI) and a strong focus on data-driven analytical techniques. Motivated by the advances in AgriTech for agrarian operations, the study presents a state-of-the-art review of the research advances which are, evolving in a fast pace over the last decades (due to the disruptive potential of the technological context). Following a systematic literature approach, we develop a categorisation of the various types of AgriTech, as well as the associated AI-driven techniques which form the continuously shifting definition of AgriTech. The contribution primarily draws on the conceptualisation and awareness about AI-driven AgriTech context relevant to the agricultural operations for smart, efficient, and sustainable farming. The study provides a single normative reference for the definition, context and future directions of the field for further research towards the operational context of AgriTech. Our findings indicate that AgriTech research and the disruptive potential of AI in the agricultural sector are still in infancy in Operations Research. Through the systematic review, we also intend to inform a wide range of agricultural stakeholders (farmers, agripreneurs, scholars and practitioners) and to provide research agenda for a growing field with multiple potentialities for the future of the agricultural operations.
Differing impacts of two major plant invaders on urban plant-dwelling spiders (Araneae) during flowering season
Authors: Bauer Tobias , Bäte Daria Alison , Kempfer Fabian , Schirmel Jens 
Published: January 2021

AbstractPlant invasions can have major impacts on ecosystems and influence global species diversity. In Central Europe, Himalayan balsam (Impatiens glandulifera) and American goldenrods (Solidago canadensisandS. gigantea) are important invaders often establishing dense and homogeneous stands, especially in urban and other disturbed habitats. We investigated their impacts on plant-dwelling spiders (abundance, family structure, guild structure) and potential spider prey items during flowering season within an urbanized landscape using a paired design comparing invaded and native reference vegetation plots. In general, flowering American goldenrods and Himalayan balsam had no significant impacts on the spider family composition. Invasion of American goldenrods further had no effect on total spider abundance and potential prey item abundance. In contrast, goldenrods showed a significantly increased crab spider (Thomisidae) abundance while being less inhabited by web builders. Himalayan balsam negatively influenced free hunters and running crab spider (Philodromidae) abundance, while we found no effects on other groups and total spider abundance. For Himalayan balsam, potential prey item abundance was higher than in native vegetation stands. Notwithstanding that our results only represent a snapshot of the system, they suggest that large-scale removal of urban goldenrod stands during flowering season might negatively influence local spider abundance, especially of crab spiders. Management efforts should therefore be accompanied by compensation measures to avoid disruptive effects on local plant-dwelling spider communities.