bluuebunny/crossref_metadata_2025 huggingface dataset:
On the Fekete–Szegö Problem for Meromorphic Functions Associated with p,q-Wright Type Hypergeometric Function
Authors: Cătaş Adriana
Published: November 2021

Making use of a post-quantum derivative operator, we define two classes of meromorphic analytic functions. For the considered family of functions, we aim to investigate the sharp bounds’ values in the case of the Fekete–Szegö problem. The study of the well-known Fekete–Szegö functional in the post-quantum calculus case for meromorphic functions provides new outcomes for research in the field. With the extended p,q-operator, we establish certain inequalities’ relations concerning meromorphic functions. In the final part of the paper, a new p,q-analogue of the q-Wright type hypergeometric function is introduced. This function generalizes the classical and symmetrical Gauss hypergeometric function. All the obtained results are sharp.
Informational Measure of Symmetry vs. Voronoi Entropy and Continuous Measure of Entropy of the Penrose Tiling. Part II of the “Voronoi Entropy vs. Continuous Measure of Symmetry of the Penrose Tiling”
Authors: Bormashenko Edward , Legchenkova Irina , Frenkel Mark , Shvalb Nir , Shoval Shraga
Published: November 2021

The notion of the informational measure of symmetry is introduced according to: Hsym(G)=−∑i=1kP(Gi)lnP(Gi), where P(Gi) is the probability of appearance of the symmetry operation Gi within the given 2D pattern. Hsym(G) is interpreted as an averaged uncertainty in the presence of symmetry elements from the group G in the given pattern. The informational measure of symmetry of the “ideal” pattern built of identical equilateral triangles is established as Hsym(D3)= 1.792. The informational measure of symmetry of the random, completely disordered pattern is zero, Hsym=0. The informational measure of symmetry is calculated for the patterns generated by the P3 Penrose tessellation. The informational measure of symmetry does not correlate with either the Voronoi entropy of the studied patterns nor with the continuous measure of symmetry of the patterns. Quantification of the “ordering” in 2D patterns performed solely with the Voronoi entropy is misleading and erroneous.
Multifeature Detection of Microaneurysms Based on Improved SSA
Authors: Deng Liwei , Wang Xiaofei , Xu Jiazhong
Published: November 2021

The early diagnosis of retinopathy is crucial to the prevention and treatment of diabetic retinopathy. The low proportion of positive cases in the asymmetric microaneurysm detection problem causes preprocessing to treat microaneurysms as noise to be eliminated. To obtain a binary image containing microaneurysms, the object was segmented by a symmetry algorithm, which is a combination of the connected components and SSA methods. Next, a candidate microaneurysm set was extracted by multifeature clustering of binary images. Finally, the candidate microaneurysms were mapped to the Radon frequency domain to achieve microaneurysm detection. In order to verify the feasibility of the algorithm, a comparative experiment was conducted on the combination of the connected components and SSA methods. In addition, PSNR, FSIM, SSIM, fitness value, average CPU time and other indicators were used as evaluation standards. The results showed that the overall performance of the binary image obtained by the algorithm was the best. Last but not least, the accuracy of the detection method for microaneurysms in this paper reached up to 93.24%, which was better than that of several classic microaneurysm detection methods in the same period.
Multiobjective Convex Optimization in Real Banach Space
Authors: Lai Kin Keung , Hassan Mohd , Maurya Jitendra Kumar , Singh Sanjeev Kumar , Mishra Shashi Kant
Published: November 2021

In this paper, we consider convex multiobjective optimization problems with equality and inequality constraints in real Banach space. We establish saddle point necessary and sufficient Pareto optimality conditions for considered problems under some constraint qualifications. These results are motivated by the symmetric results obtained in the recent article by Cobos Sánchez et al. in 2021 on Pareto optimality for multiobjective optimization problems of continuous linear operators. The discussions in this paper are also related to second order symmetric duality for nonlinear multiobjective mixed integer programs for arbitrary cones due to Mishra and Wang in 2005. Further, we establish Karush–Kuhn–Tucker optimality conditions using saddle point optimality conditions for the differentiable cases and present some examples to illustrate our results. The study in this article can also be seen and extended as symmetric results of necessary and sufficient optimality conditions for vector equilibrium problems on Hadamard manifolds by Ruiz-Garzón et al. in 2019.
Packet Loss Measurement Based on Sampled Flow
Authors: Lan Haoliang , Xu Jie , Wang Qun , Ding Wei
Published: November 2021

This paper is devoted to further strengthening, in the current asymmetric information environment, the informed level of operators about network performance. Specifically, in view of the burst and perishability of a packet loss event, to better meet the real-time requirements of current high-speed backbone performance monitoring, a model for Packet Loss Measurement at the access network boundary Based on Sampled Flow (PLMBSF) is presented in this paper under the premise of both cost and real-time. The model overcomes problems such as the inability of previous estimation to distinguish between packet losses before and after the monitoring point, deployment difficulties and cooperative operation consistency. Drawing support from the Mathis equation and regression analysis, the measurement for packet losses before and after the monitoring point can be realized when using only the sampled flows generated by the access network boundary equipment. The comparison results with the trace-based passive packet loss measurement show that although the proposed model is easily affected by factors such as flow length, loss rate, sampling rate, the overall accuracy is still within the acceptable range. In addition, the proposed model PLMBSF, compared with the trace-based loss measurement is only different in the input data granularity. Therefore, PLMBSF and its advantages are also applicable to aggregated traffic.
The Echo Method for Axion Dark Matter Detection
Authors: Arza Ariel , Todarello Elisa
Published: November 2021

The axion is a dark matter candidate arising from the spontaneous breaking of the Peccei–Quinn symmetry, introduced to solve the strong CP problem. It has been shown that radio/microwave radiation sent out to space is backscattered in the presence of axion dark matter due to stimulated axion decay. This backscattering is a feeble and narrow echo signal centered at an angular frequency very close to one-half of the axion mass. In this article, we summarize all the relevant results found so far, including analytical formulas for the echo signal, as well as sensitivity prospects for possible near-future experiments.
In-Depth Verification of a Numerical Model for an Axisymmetric RC Dome
Authors: Czumaj Przemysław , Dudziak Sławomir , Kacprzyk Zbigniew
Published: November 2021

The designers of civil engineering structures often have to face the problem of the reliability of complex computational analyses performed most often with the Finite Element Method (FEM). Any assessment of reliability of such analyses is difficult and can only be approximate. The present paper puts forward a new method of verification and validation of the structural analyses upon an illustrative example of a dome strengthened by circumferential ribs along the upper and lower edges. Four computational systems were used, namely Abaqus, Autodesk Robot, Dlubal RFEM, and FEAS. Different models were also analyzed—two-dimensional (2D) and three-dimensional (3D) ones using continuum, bar, and shell finite elements. The results of the static (with two kinds of load—self-weight and load distributed along the upper ring) and modal analyses are presented. A detailed comparison between the systems’ and models’ predictions was made. In general, the spatial models predicted a less stiff behavior of the analyzed dome than the planar models. The good agreement between different models and systems was obtained for the first natural frequency with axisymmetric eigenmodes (except from the Autodesk Robot system). The presented approach to the verification of complex shell–bar models can be effectively applied by structural designers.
Channel Modeling and Analysis for the Sensor Network Inside Tower Buildings
Authors: Xie Wenping , Chen Xiaomin , Mao Kai , Liu Yuxin , Yin Lugao , Fang Sheng
Published: November 2021

Symmetry-based channel digital twin is a great technology which can reproduce the communication channel of real scenes for performance evaluation of the wireless sensor network (WSN) inside tower buildings, based on the ray tracing (RT) method and machine learning (ML) theories, a cluster-based channel model is proposed in this paper. Meanwhile, an improved k-means method, which considers the weight of different dimensions in the multipath component distance (MCD) is presented for clustering, which has better clustering performance over the sparsity-based algorithm and traditional k-means algorithm. Moreover, the channel parameters such as cluster delay and cluster power are also investigated. On this basis, the communication performance of WSN, i.e., bit error rate (BER) and channel capacity are derived and analyzed. The simulation and analysis results show that the cluster model based on the RT method can get approximately equivalent channel impulse response (CIR), and the BER of proposed model is consistent with the simulated one. These results can provide reference for the node layout and optimization of WSN inside tower buildings.
Machine Learning for Conservative-to-Primitive in Relativistic Hydrodynamics
Authors: Dieselhorst Tobias , Cook William , Bernuzzi Sebastiano , Radice David
Published: November 2021

The numerical solution of relativistic hydrodynamics equations in conservative form requires root-finding algorithms that invert the conservative-to-primitive variables map. These algorithms employ the equation of state of the fluid and can be computationally demanding for applications involving sophisticated microphysics models, such as those required to calculate accurate gravitational wave signals in numerical relativity simulations of binary neutron stars. This work explores the use of machine learning methods to speed up the recovery of primitives in relativistic hydrodynamics. Artificial neural networks are trained to replace either the interpolations of a tabulated equation of state or directly the conservative-to-primitive map. The application of these neural networks to simple benchmark problems shows that both approaches improve over traditional root finders with tabular equation-of-state and multi-dimensional interpolations. In particular, the neural networks for the conservative-to-primitive map accelerate the variable recovery by more than an order of magnitude over standard methods while maintaining accuracy. Neural networks are thus an interesting option to improve the speed and robustness of relativistic hydrodynamics algorithms.
A Social Recommendation Based on Metric Learning and Users’ Co-Occurrence Pattern
Authors: Zhang Xin , Qin Jiwei , Zheng Jiong
Published: November 2021

For personalized recommender systems, matrix factorization and its variants have become mainstream in collaborative filtering. However, the dot product in matrix factorization does not satisfy the triangle inequality and therefore fails to capture fine-grained information. Metric learning-based models have been shown to be better at capturing fine-grained information than matrix factorization. Nevertheless, most of these models only focus on rating data and social information, which are not sufficient for dealing with the challenges of data sparsity. In this paper, we propose a metric learning-based social recommendation model called SRMC. SRMC exploits users’ co-occurrence patterns to discover their potentially similar or dissimilar users with symmetric relationships and change their relative positions to achieve better recommendations. Experiments on three public datasets show that our model is more effective than the compared models.
Multi-Objective UAV Trajectory Planning in Uncertain Environment
Authors: Zheng Aoyu , Li Bingjie , Zheng Mingfa , Zhong Haitao
Published: November 2021

UAV trajectory planning is one of the research focuses in artificial intelligence and UAV technology. The asymmetric information, however, will lead to the uncertainty of the UAV trajectory planning; the probability theory as the most commonly used method to solve the trajectory planning problem in uncertain environment will lead to unrealistic conclusions under the condition of lacking samples, while the uncertainty theory based on uncertain measures is an efficient method to solve such problems. Firstly, the uncertainties in trajectory planning are sufficiently considered in this paper; the fuel consumption, concealment and threat degree with uncertain variables are taken as the objective functions; the constraints are analyzed according to the maneuverability; and the uncertain multi-objective trajectory planning (UMOTP) model is established. After that, this paper takes both the long-term benefits and its stability into account, and then, the expected-value and standard-deviation efficient trajectory model is established. What is more, this paper solves the Pareto front of the trajectory planning, satisfying various preferences, which avoids the defects of the trajectory obtained by traditional model only applicable to a certain specific situation. In order to obtain a better solution set, this paper proposes an improved backbones particle swarm optimization algorithm based on PSO and NSGA-II, which overcomes the shortcomings of the traditional algorithm such as premature convergence and poor robustness, and the efficiency of the algorithm is tested. Finally, the algorithm is applied to the UMOTP problem; then, the optimal trajectory set is obtained, and the effectiveness and reliability of the model is verified.
Study on the Rotor Strength of High-Speed Permanent Magnet Motor Considering the Influence of Assembly Pressing Force
Authors: Hu Yusheng , Li Liyi , Guo Weilin , Wang Shanshan
Published: November 2021

In engineering application, the hot press assembly technology is often used to improve the stability of the rotor structure, but the conventional design methods cannot effectively evaluate the influence of this process on the rotor strength, which easily causes the rotor strength to exceed its safety margin range, and seriously it will lead to the failure of the rotor structure. This paper takes the cylindrical magnet surface-mounted high-speed permanent magnet synchronous motor rotor as the research object. Firstly, the influence of the assembly pressing force on the rotor stresses and interference is analyzed; then, comprehensively considering the assembly pressing force, speed and temperature, the rotor strength’s design method with high structural stability is proposed. Finally, based on the proposed method, the rotor strength of a 100 kW/30,000 rpm high-speed motor is designed, and the feasibility of the design is verified by over-speed experiment.
A Two-Stage Differential Evolution Algorithm with Mutation Strategy Combination
Authors: Sun Xingping , Wang Da , Kang Hongwei , Shen Yong , Chen Qingyi
Published: November 2021

For most of differential evolution (DE) algorithm variants, premature convergence is still challenging. The main reason is that the exploration and exploitation are highly coupled in the existing works. To address this problem, we present a novel DE variant that can symmetrically decouple exploration and exploitation during the optimization process in this paper. In the algorithm, the whole population is divided into two symmetrical subpopulations by ascending order of fitness during each iteration; moreover, we divide the algorithm into two symmetrical stages according to the number of evaluations (FEs). On one hand, we introduce a mutation strategy, DE/current/1, which rarely appears in the literature. It can keep sufficient population diversity and fully explore the solution space, but its convergence speed gradually slows as iteration continues. To give full play to its advantages and avoid its disadvantages, we propose a heterogeneous two-stage double-subpopulation (HTSDS) mechanism. Four mutation strategies (including DE/current/1 and its modified version) with distinct search behaviors are assigned to superior and inferior subpopulations in two stages, which helps simultaneously and independently managing exploration and exploitation in different components. On the other hand, an adaptive two-stage partition (ATSP) strategy is proposed, which can adjust the stage partition parameter according to the complexity of the problem. Hence, a two-stage differential evolution algorithm with mutation strategy combination (TS-MSCDE) is proposed. Numerical experiments were conducted using CEC2017, CEC2020 and four real-world optimization problems from CEC2011. The results show that when computing resources are sufficient, the algorithm is competitive, especially for complex multimodal problems.
Slash Truncation Positive Normal Distribution and Its Estimation Based on the EM Algorithm
Authors: Gómez Héctor J. , Gallardo Diego I. , Santoro Karol I.
Published: November 2021

In this paper, we present an extension of the truncated positive normal (TPN) distribution to model positive data with a high kurtosis. The new model is defined as the quotient between two random variables: the TPN distribution (numerator) and the power of a standard uniform distribution (denominator). The resulting model has greater kurtosis than the TPN distribution. We studied some properties of the distribution, such as moments, asymmetry, and kurtosis. Parameter estimation is based on the moments method, and maximum likelihood estimation uses the expectation-maximization algorithm. We performed some simulation studies to assess the recovery parameters and illustrate the model with a real data application related to body weight. The computational implementation of this work was included in the tpn package of the R software.
Software Defect Prediction Using Wrapper Feature Selection Based on Dynamic Re-Ranking Strategy
Authors: Balogun Abdullateef Oluwagbemiga , Basri Shuib , Capretz Luiz Fernando , Mahamad Saipunidzam , Imam Abdullahi Abubakar , Almomani Malek A. , Adeyemo Victor Elijah , Alazzawi Ammar K. , Bajeh Amos Orenyi , Kumar Ganesh
Published: November 2021

Finding defects early in a software system is a crucial task, as it creates adequate time for fixing such defects using available resources. Strategies such as symmetric testing have proven useful; however, its inability in differentiating incorrect implementations from correct ones is a drawback. Software defect prediction (SDP) is another feasible method that can be used for detecting defects early. Additionally, high dimensionality, a data quality problem, has a detrimental effect on the predictive capability of SDP models. Feature selection (FS) has been used as a feasible solution for solving the high dimensionality issue in SDP. According to current literature, the two basic forms of FS approaches are filter-based feature selection (FFS) and wrapper-based feature selection (WFS). Between the two, WFS approaches have been deemed to be superior. However, WFS methods have a high computational cost due to the unknown number of executions available for feature subset search, evaluation, and selection. This characteristic of WFS often leads to overfitting of classifier models due to its easy trapping in local maxima. The trapping of the WFS subset evaluator in local maxima can be overcome by using an effective search method in the evaluator process. Hence, this study proposes an enhanced WFS method that dynamically and iteratively selects features. The proposed enhanced WFS (EWFS) method is based on incrementally selecting features while considering previously selected features in its search space. The novelty of EWFS is based on the enhancement of the subset evaluation process of WFS methods by deploying a dynamic re-ranking strategy that iteratively selects germane features with a low subset evaluation cycle while not compromising the prediction performance of the ensuing model. For evaluation, EWFS was deployed with Decision Tree (DT) and Naïve Bayes classifiers on software defect datasets with varying granularities. The experimental findings revealed that EWFS outperformed existing metaheuristics and sequential search-based WFS approaches established in this work. Additionally, EWFS selected fewer features with less computational time as compared with existing metaheuristics and sequential search-based WFS methods.
A Generalized Stochastic Cost–Volume–Profit Model
Authors: Liang Hongyan , Guiffrida Alfred L. , Liu Zilong , Patuwo Butje Eddy , Shanker Murali
Published: November 2021

Cost–volume–profit (CVP) analysis is a widely used decision tool across many business disciplines. The current literature on stochastic applications of the CVP model is limited in that the model is studied under the restrictive forms of the Gaussian and Lognormal distributions. In this paper we introduce the Mellin Transform as a methodology to generalize stochastic modeling of the CVP problem. We demonstrate the versatility of using the Mellin transform to model the CVP problem, and present a generalization of the CVP model when the contribution margin and sales volume are both defined by continuous random distributions.
Considerations for a Reliable In Vitro Model of Chemotherapy-Induced Peripheral Neuropathy
Authors: Eldridge Sandy , Scuteri Arianna , Jones Eugenia , Cavaletti Guido , Guo Liang , Glaze Elizabeth
Published: November 2021

Chemotherapy-induced peripheral neuropathy (CIPN) is widely recognized as a potentially severe toxicity that often leads to dose reduction or discontinuation of cancer treatment. Symptoms may persist despite discontinuation of chemotherapy and quality of life can be severely compromised. The clinical symptoms of CIPN, and the cellular and molecular targets involved in CIPN, are just as diverse as the wide variety of anticancer agents that cause peripheral neurotoxicity. There is an urgent need for extensive molecular and functional investigations aimed at understanding the mechanisms of CIPN. Furthermore, a reliable human cell culture system that recapitulates the diversity of neuronal modalities found in vivo and the pathophysiological changes that underlie CIPN would serve to advance the understanding of the pathogenesis of CIPN. The demonstration of experimental reproducibility in a human peripheral neuronal cell system will increase confidence that such an in vitro model is clinically useful, ultimately resulting in deeper exploration for the prevention and treatment of CIPN. Herein, we review current in vitro models with a focus on key characteristics and attributes desirable for an ideal human cell culture model relevant for CIPN investigations.
The Sharma–Mittal Model’s Implications on FRW Universe in Chern–Simons Gravity
Authors: Ali Sarfraz , Waheed Muhammad Hummad , Asjad Muhammad Imran , Khan Khuram Ali , Sitthiwirattham Thanin , Promsakon Chanon
Published: November 2021

The Sharma–Mittal holographic dark energy model is investigated in this paper using the Chern–Simons modified gravity theory. We investigate several cosmic parameters, including the deceleration, equation of state, square of sound speed, and energy density. According to the deceleration parameter, the universe is in an decelerating and expanding phase known as de Sitter expansion. The Sharma–Mittal HDE model supports a deceleration to acceleration transition that is compatible with the observational data. The EoS depicts the universe’s dominance era through a number of components, such as ω=0, 13, 1, which indicate that the universe is influenced by dust, radiation, and stiff fluid, while −1<ω<13, ω=−1, and ω<−1 are conditions for quintessence DE, ΛCDM, and Phantom era dominance. Our findings indicate that the universe is in an accelerated expansion phase, and this is similar to the observational data.
Transcriptomic Studies Suggest a Coincident Role for Apoptosis and Pyroptosis but Not for Autophagic Neuronal Death in TBEV-Infected Human Neuronal/Glial Cells
Authors: Fares Mazigh , Gorna Kamila , Berry Noémie , Cochet-Bernoin Marielle , Piumi François , Blanchet Odile , Haddad Nadia , Richardson Jennifer , Coulpier Muriel
Published: November 2021

Tick-borne encephalitis virus (TBEV), a member of the Flaviviridae family, Flavivirus genus, is responsible for neurological symptoms that may cause permanent disability or death. With an incidence on the rise, it is the major arbovirus affecting humans in Central/Northern Europe and North-Eastern Asia. Neuronal death is a critical feature of TBEV infection, yet little is known about the type of death and the molecular mechanisms involved. In this study, we used a recently established pathological model of TBEV infection based on human neuronal/glial cells differentiated from fetal neural progenitors and transcriptomic approaches to tackle this question. We confirmed the occurrence of apoptotic death in these cultures and further showed that genes involved in pyroptotic death were up-regulated, suggesting that this type of death also occurs in TBEV-infected human brain cells. On the contrary, no up-regulation of major autophagic genes was found. Furthermore, we demonstrated an up-regulation of a cluster of genes belonging to the extrinsic apoptotic pathway and revealed the cellular types expressing them. Our results suggest that neuronal death occurs by multiple mechanisms in TBEV-infected human neuronal/glial cells, thus providing a first insight into the molecular pathways that may be involved in neuronal death when the human brain is infected by TBEV.
Historical Investigation of Fowl Adenovirus Outbreaks in South Korea from 2007 to 2021: A Comprehensive Review
Authors: Mo Jongseo
Published: November 2021

Fowl adenoviruses (FAdVs) have long been recognized as critical viral pathogens within the poultry industry, associated with severe economic implications worldwide. This specific group of viruses is responsible for a broad spectrum of diseases in birds, and an increasing occurrence of outbreaks was observed in the last ten years. Since their first discovery forty years ago in South Korea, twelve antigenically distinct serotypes of fowl adenoviruses have been described. This comprehensive review covers the history of fowl adenovirus outbreaks in South Korea and updates the current epidemiological landscape of serotype diversity and replacement as well as challenges in developing effective broadly protective vaccines. In addition, transitions in the prevalence of dominant fowl adenovirus serotypes from 2007 to 2021, alongside the history of intervention strategies, are brought into focus. Finally, future aspects are also discussed.
Phylogenetic Characteristics of Canine Parvovirus Type 2c Variant Endemic in Shanghai, China
Authors: Liu Chengqian , Gao Jun , Li Hong , Sun Fengping , Liang Hongyu , Liu Huili , Yi Jianzhong
Published: November 2021

Canine parvovirus type 2 (CPV-2) has spread and mutated globally over the past 40 years. In the present study, 206 samples from dogs suspected of CPV-2 infection were collected from five veterinary clinics in Shanghai city, China. The average positive rate for CPV-2 was detected to be 40.78% using the PCR method. Using an F81 cell (feline kidney cell) culture, the isolates of three CPV-2c strains were obtained. The near full-length genome sequences of the isolates were determined and submitted to GenBank: CPV-SH2001 (MW650830), CPV-SH2002 (MW811188), and CPV-SH2003 (MW811189). By comparing the amino acid sequences of 12 CPV strains with those of 48 related strains retrieved from GenBank, all of the CPV strains from Shanghai were typed as belonging to a relatively new CPV-2c variant spreading in Asia, with typical amino acid residues (5Gly, 267Tyr, 324Ile, and 370Arg) in the VP2 protein. The divergence time of this new CPV-2c clade was estimated by the phylogenetic tree using the maximum likelihood and RelTime with Dated Tips (RTDT) approaches. Our results indicate that the 426 and 324 VP2 amino acid residues are under strong selection pressure with a posterior probability of 0.966 and 0.943, respectively. Therefore, this study provides insight into the phylogenetic characteristics of the current CPV-2c variant in Shanghai city, China.
CRISPR Screening: Molecular Tools for Studying Virus–Host Interactions
Authors: Chulanov Vladimir , Kostyusheva Anastasiya , Brezgin Sergey , Ponomareva Natalia , Gegechkori Vladimir , Volchkova Elena , Pimenov Nikolay , Kostyushev Dmitry
Published: November 2021

CRISPR/Cas is a powerful tool for studying the role of genes in viral infections. The invention of CRISPR screening technologies has made it possible to untangle complex interactions between the host and viral agents. Moreover, whole-genome and pathway-specific CRISPR screens have facilitated identification of novel drug candidates for treating viral infections. In this review, we highlight recent developments in the fields of CRISPR/Cas with a focus on the use of CRISPR screens for studying viral infections and identifying new candidate genes to aid development of antivirals.
Molecular Analysis of the Avian H7 Influenza Viruses Circulating in South Korea during 2018–2019: Evolutionary Significance and Associated Zoonotic Threats
Authors: Duong Bao Tuan , Bal Jyotiranjan , Sung Haan Woo , Yeo Seon-Ju , Park Hyun
Published: November 2021

Avian influenza virus (AIV) subtypes H5 and H7, possessing the ability to mutate spontaneously from low pathogenic (LP) to highly pathogenic (HP) variants, are major concerns for enormous socio-economic losses in the poultry industry, as well as for fatal human infections. Through antigenic drift and shift, genetic reassortments of the genotypes pose serious threats of increased virulence and pathogenicity leading to potential pandemics. In this study, we isolated the H7-subtype AIVs circulating in the Republic of Korea during 2018–2019, and perform detailed molecular analysis to study their circulation, evolution, and possible emergence as a zoonotic threat. Phylogenetic and nucleotide sequence analyses of these isolates revealed their distribution into two distinct clusters, with the HA gene sharing the highest nucleotide identity with either the A/common teal/Shanghai/CM1216/2017, isolated from wild birds in Shanghai, China, or the A/duck/Shimane/2014, isolated from Japan. Mutations were found in HA (S138A (H3 numbering)), M1 (N30D and T215A), NS1 (P42S), PB2 (L89V), and PA (H266R and F277S) proteins—the mutations had previously been reported to be related to mammalian adaptation and changes in the virulence of AIVs. Taken together, the results firmly put forth the demand for routine surveillance of AIVs in wild birds to prevent possible pandemics arising from reassortant AIVs.
Robust and Persistent B- and T-Cell Responses after COVID-19 in Immunocompetent and Solid Organ Transplant Recipient Patients
Authors: Zavaglio Federica , Frangipane Vanessa , Morosini Monica , Gabanti Elisa , Zelini Paola , Sammartino Josè Camilla , Ferrari Alessandro , Gregorini Marilena , Rampino Teresa , Asti Annalia , Seminari Elena , Di Matteo Angela , Cattadori Barbara , Pellegrini Carlo , Tonello Stelvio , Mallela Venkata Ramana , Minisini Rosalba , Rizzi Manuela , Sainaghi Pier Paolo , Meloni Federica , Lilleri Daniele , Baldanti Fausto
Published: November 2021

The development and persistence of SARS-CoV-2-specific immune response in immunocompetent (IC) and immunocompromised patients is crucial for long-term protection. Immune response to SARS-CoV-2 infection was analysed in 57 IC and 15 solid organ transplanted (TX) patients. Antibody responses were determined by ELISA and neutralization assay. T-cell response was determined by stimulation with peptide pools of the Spike, Envelope, Membrane, and Nucleocapsid proteins with a 20-h Activation Induced Marker (AIM) and 7-day lymphoproliferative assays. Antibody response was detected at similar levels in IC and TX patients. Anti-Spike IgG, IgA and neutralizing antibodies persisted for at least one year, while anti-Nucleocapsid IgG declined earlier. Patients with pneumonia developed higher antibody levels than patients with mild symptoms. Similarly, both rapid and proliferative T-cell responses were detected within the first two months after infection at comparable levels in IC and TX patients, and were higher in patients with pneumonia. T-cell response persisted for at least one year in both IC and TX patients. Spike, Membrane, and Nucleocapsid proteins elicited the major CD4+ and CD8+ T-cell responses, whereas the T-cell response to Envelope protein was negligible. After SARS-CoV-2 infection, antibody and T-cell responses develop rapidly and persist over time in both immunocompetent and transplanted patients.
Impact of Phage CDHS-1 on the Transcription, Physiology and Pathogenicity of a Clostridioides difficile Ribotype 027 Strain, R20291
Authors: Nale Janet Y. , Al-Tayawi Thekra Sideeq , Heaphy Shaun , Clokie Martha R. J.
Published: November 2021

All known Clostridioides difficile phages encode integrases rendering them potentially able to lyse or lysogenise bacterial strains. Here, we observed the infection of the siphovirus, CDHS-1 on a ribotype 027 strain, R20291 and determined the phage and bacterial gene expression profiles, and impacts of phage infection on bacterial physiology and pathogenicity. Using RNA-seq and RT-qPCR we analysed transcriptomic changes during early, mid-log and late phases of phage replication at an MOI of 10. The phage has a 20 min latent period, takes 80 min to lyse cells and a burst size of ~37. All phage genes are highly expressed during at least one time point. The Cro/C1-transcriptional regulator, ssDNA binding protein and helicase are expressed early, the holin is expressed during the mid-log phase and structural proteins are expressed from mid-log to late phase. Most bacterial genes, particularly the metabolism and toxin production/regulatory genes, were downregulated from early phage replication. Phage-resistant strains and lysogens showed reduced virulence during Galleria mellonella colonization as ascertained by the larval survival and expression of growth (10), reproduction (2) and infection (2) marker genes. These data suggest that phage infection both reduces colonization and negatively impacts bacterial pathogenicity, providing encouraging data to support the development of this phage for therapy to treat C. difficile infection.
Common Laboratory Mice Are Susceptible to Infection with the SARS-CoV-2 Beta Variant
Authors: Kant Ravi , Kareinen Lauri , Smura Teemu , Freitag Tobias L. , Jha Sawan Kumar , Alitalo Kari , Meri Seppo , Sironen Tarja , Saksela Kalle , Strandin Tomas , Kipar Anja , Vapalahti Olli
Published: November 2021

Small animal models are of crucial importance for assessing COVID-19 countermeasures. Common laboratory mice would be well-suited for this purpose but are not susceptible to infection with wild-type SARS-CoV-2. However, the development of mouse-adapted virus strains has revealed key mutations in the SARS-CoV-2 spike protein that increase infectivity, and interestingly, many of these mutations are also present in naturally occurring SARS-CoV-2 variants of concern. This suggests that these variants might have the ability to infect common laboratory mice. Herein we show that the SARS-CoV-2 beta variant attains infectibility to BALB/c mice and causes pulmonary changes within 2–3 days post infection, consistent with results seen in other murine models of COVID-19, at a reasonable virus dose (2 × 105 PFU). The findings suggest that common laboratory mice can serve as the animal model of choice for testing the effectiveness of antiviral drugs and vaccines against SARS-CoV-2.
Vaccine versus Variants (3Vs): Are the COVID-19 Vaccines Effective against the Variants? A Systematic Review
Authors: Hayawi Kadhim , Shahriar Sakib , Serhani Mohamed Adel , Alashwal Hany , Masud Mohammad M.
Published: November 2021

Background: With the emergence and spread of new SARS-CoV-2 variants, concerns are raised about the effectiveness of the existing vaccines to protect against these new variants. Although many vaccines were found to be highly effective against the reference COVID-19 strain, the same level of protection may not be found against mutation strains. The objective of this study is to systematically review relevant studies in the literature and compare the efficacy of COVID-19 vaccines against new variants. Methods: We conducted a systematic review of research published in Scopus, PubMed, and Google Scholar until 30 August 2021. Studies including clinical trials, prospective cohorts, retrospective cohorts, and test negative case-controls that reported vaccine effectiveness against any COVID-19 variants were considered. PRISMA recommendations were adopted for screening, eligibility, and inclusion. Results: 129 unique studies were reviewed by the search criteria, of which 35 met the inclusion criteria. These comprised of 13 test negative case-control studies, 6 Phase 1–3 clinical trials, and 16 observational studies. The study location, type, vaccines used, variants considered, and reported efficacies were highlighted. Conclusion: Full vaccination (two doses) offers strong protection against Alpha (B.1.1.7) with 13 out of 15 studies reporting more than 84% efficacy. The results are not conclusive against the Beta (B.1.351) variant for fully vaccinated individuals with 4 out of 7 studies reporting efficacies between 22 and 60% and 3 out of 7 studies reporting efficacies between 75 and 100%. Protection against Gamma (P.1) variant was lower than 50% according to two studies in fully vaccinated individuals. The data on Delta (B.1.617.2) variant is limited but indicates lower protection compared to other variants.
Thrombotic Events after COVID-19 Vaccination in the Over-50s: Results from a Population-Based Study in Italy
Authors: Baldi Ileana , Azzolina Danila , Francavilla Andrea , Bartolotta Patrizia , Lorenzoni Giulia , Vanuzzo Diego , Gregori Dario
Published: November 2021

Several European countries suspended or changed recommendations for the use of Vaxzevria (AstraZeneca) for suspected adverse effects due to atypical blood-clotting. This research aims to identify a reference point towards the number of thrombotic events expected in the Italian population over 50 years of age who received Vaxzevria from 22 January to 12 April 2021. The venous thromboembolism (VT) and immune thrombocytopenia (ITP) event rates were estimated from a population-based cohort. The overall VT rate was 1.15 (95% CI 0.93–1.42) per 1000 person-years, and the ITP rate was 2.7 (95% CI 0.7–11) per 100,000 person-years. These figures translate into 83 and two expected events of VT and ITP, respectively, in the 15 days following the first administration of Vaxzevria. The number of thrombotic events reported from the Italian Medicines Agency does not appear to have increased beyond that expected in individuals over 50 years of age.
Anti-COVID Vaccination for Adolescents: A Survey on Determinants of Vaccine Parental Hesitancy
Authors: Zona Stefano , Partesotti Simonetta , Bergomi Andrea , Rosafio Cristiano , Antodaro Francesco , Esposito Susanna
Published: November 2021

Vaccine hesitancy has been considered one of the most severe threats to global health, as it represents an obstacle to achieving adequate vaccination coverage. Recent research studies aimed at investigating the propensity for anti-COVID vaccination among adults have found a high prevalence of vaccine hesitancy, but few data are available on parental vaccine hesitancy. We therefore built an anonymous online survey to investigate the factors related to the vaccine hesitancy of parents of adolescents between 12 and 17 years of age, with a special focus on demographic factors and the domains of confidence and complacency. The online survey was conducted by using the Crowd Signal platform from 15 July to 16 August 2021, in Italy. A total of 1799 analyzable questionnaires were analyzed. Overall, Favorable and Doubtful parents declared a higher level of confidence on safety and efficacy of pediatric vaccines and on confidence in health institutions than Hesitant/Reluctant ones (p-values < 0.001). The univariate multinomial logistic regression analysis and the multivariate multinomial logistic regression analysis showed that the Hesitant/Reluctant parents were younger than 40 years of age, with a secondary-school or three-year degree, free-lance, with a family income below €28,000, with an erroneous perception of the risk of COVID-19 as disease and with fear of anti-COVID vaccination. These results, which should be confirmed in a larger population and in different geographical areas, should lead Institutions and stakeholders to identify targeted communication tools to improve trust in health institutions, especially by younger parents.
Defective Glyoxalase 1 Contributes to Pathogenic Inflammation in Cystic Fibrosis
Authors: Pariano Marilena , Costantini Claudio , Santarelli Ilaria , Puccetti Matteo , Giovagnoli Stefano , Talesa Vincenzo N. , Romani Luigina , Antognelli Cinzia
Published: November 2021

Cystic fibrosis (CF) is an autosomal recessive disorder that affects multiple organs, although a decline in respiratory function represents the major cause of morbidity and mortality. The airways of CF patients are characterized by a chronic inflammatory state to which the receptor for advanced glycation end-products greatly contributes. Glyoxalase 1 (GLO1) is the major enzyme metabolizing methylglyoxal, a potent precursor of advanced glycation end-products. Its role in CF has never been investigated. We herein resorted to murine and human preclinical models of CF to define the contribution of GLO1 to inflammatory pathology. We found that the expression and activity of GLO1, measured by real-time PCR and Western blot or a specific spectrophotometric assay, respectively, are defective in mice and human bronchial cells from CF patients exposed to Aspergillus fumigatus, a common pathogen in CF, but could be restored upon blockade of interleukin-1 receptor signaling by anakinra in mice. This study suggests that GLO1 contributes to pathology in CF and may be potentially targeted to mitigate inflammation.
First Report of Two Cases of Löfgren’s Syndrome after SARS-CoV-2 Vaccination-Coincidence or Causality?
Authors: Rademacher Jan-Gerd , Tampe Björn , Korsten Peter
Published: November 2021

Sarcoidosis can present as an acute form or take a chronic course. One of the acute presentations is Löfgren’s syndrome (LS), consisting of the symptom triad of bilateral hilar lymphadenopathy, erythema nodosum, and ankle periarthritis. In addition, there are occasional reports of sarcoid-like reactions following drug exposures. Nevertheless, reports of sarcoidosis or LS after vaccination have not been published. Here, we report two cases of de novo LS in a temporal association with different vaccines against the new coronavirus SARS-CoV-2. One patient developed the first symptoms three days after the second vaccination (first vaccination ChadOx-1, Astra Zeneca; second vaccination CX-024414, Moderna); in the second patient, symptoms started 28 days after the first vaccination (ChadOx-1, Astra Zeneca). Both patients eventually required treatment with glucocorticoids. Both patients achieved clinical improvement with treatment. In conclusion, we report the first two cases of LS shortly after SARS-CoV-2 vaccination.
COVID-19 Vaccine Acceptance among Liver Transplant Recipients
Authors: Costantino Andrea , Invernizzi Federica , Centorrino Erica , Vecchi Maurizio , Lampertico Pietro , Donato Maria Francesca
Published: November 2021

(1) Background: COVID-19 vaccination hesitancy is a threat for fragile patients. We aimed to evaluate COVID-19 vaccination hesitancy and its reasons in a population of liver transplant (LT) recipients. (2) Methods: In February 2021, a questionnaire on COVID-19 vaccines was sent to LT patients followed at our liver transplant outpatient clinic in Milan, Italy. Sociodemographic and clinical characteristics were recorded. Patients were defined as willing, hesitant, or refusing and their reasons were investigated. Associations between baseline characteristics and willingness were evaluated. Since March 2021, when the COVID-19 vaccines became available for LT candidates and recipients in Italy, the entire cohort of LT recipients was contacted by phone and called for vaccination, and the rate of refusals recorded. (3) Results: The web-based survey was sent to 583 patients, of whom 190 responded (response rate of 32.6%). Among the respondents to the specific question about hesitancy (184), 157 (85.3%) were willing to be vaccinated against COVID-19, while 27 (14.7%) were hesitant. Among the hesitant, three were totally refusing, for a refusal rate of 1.6%. Thirteen hesitant patients (48.1%) answered that their COVID-19 vaccination hesitancy was influenced by being a transplant recipient. The fear of adverse effects was the main reason for refusal (81.5%). Of the 711 LT patients followed at our center, 668 got fully vaccinated, while 43 (6.1%) of them refused the scheduled vaccination. (4) Conclusions: Most patients accepted COVID-19 vaccines, although 6.1% refused the vaccine. Since it is crucial to achieve adequate vaccination of LT patients, it is very important to identify the reasons influencing COVID-19 vaccination hesitancy so that appropriate and targeted communication strategies can be established and specific vaccination campaigns further implemented.
Optimizing a Protocol to Assess Immune Responses after SARS-CoV-2 Vaccination in Kidney-Transplanted Patients: In Vivo DTH Cutaneous Test as the Initial Screening Method
Authors: Barrios Yvelise , Rodriguez Aurelio , Franco Andrés , Alava-Cruz Cristina , Marrero-Miranda Domingo , Perez-Tamajon Lourdes , Matheu Victor
Published: November 2021

Previously, the delayed-type hypersensitivity (DTH) cutaneous test with the spike protein of SARS-CoV-2 has been shown to be a simple in vivo method to measure T-cell functionality after natural infection and in vaccinated individuals. Methods: Twenty-five kidney-transplanted recipients were immunized with two doses of the mRNA-based Pfizer–BioNTech COVID19 vaccine three weeks apart. Cell-immune response (CIR) was evaluated ten weeks later using an in vivo DTH skin test and in vitro with an interferon gamma release assay (IGRA). Humoral Immune Response (HIR) was determined by the measurement of specific IgG anti-S1 SARS-CoV-2. Results: Ten weeks after the second dose of the vaccine, 23 out of 25 transplanted patients had a positive DTH skin test, while in vitro CIR was considered positive in 20 patients. Unspecific stimulation was positive in all 25 patients, showing no T-cell defect. Seven out of twenty-five patients had a negative specific anti-spike IgG. CIR was positive in all immune-competent control patients. Conclusions: DTH is a useful, simple, and cheaper tool that can be used to assess cellular immune response, with an excellent correlation with the in vitro CIR. CIR assessment after vaccination in these immunocompromised patients is an excellent complement to HIR-based methods. This skin test could be used if classical in vitro methods cannot be applied.