bluuebunny/crossref_metadata_2025_split huggingface dataset:
B cell-specific knockout of AID protects against atherosclerosis
Authors: Ebrahimian Talin , Dierick France , Ta Vincent , Kotsiopriftis Maria , O’Connor Miranda Jonathan , Mann Koren K. , Orthwein Alexandre , Lehoux Stephanie 
Published: May 2023

AbstractAntigen-naive IgM-producing B cells are atheroprotective, whereas mature B cells producing class-switched antibodies promote atherosclerosis. Activation-induced cytidine deaminase (AID), which mediates class switch recombination (CSR), would thus be expected to foster atherosclerosis. Yet, AID also plays a major role in the establishment of B cell tolerance. We sought to define whether AID affects atherosclerotic plaque formation. We generated Ldlr-/- chimeras transplanted with bone marrow from Aicda-/- or wild-type (WT) mice, fed a HFD for 14 weeks. Decreased B cell maturation in Ldlr-/-Aicda-/- mice was demonstrated by 50% reduction in splenic and aortic BAFFR expression, a key signaling component of B2 cell maturation. This was associated with increased plasma IgM in Ldlr–/-Aicda-/- compared with Ldlr-/-WT animals. Importantly, Ldlr-/-Aicda-/- mice had reduced atherosclerotic lesion area (0.20 ± 0.03mm2) compared with Ldlr-/-WT (0.30 ± 0.04mm2, P < 0.05), although no differences in plaque composition were noted between groups. In addition, immunofluorescence analysis revealed increased splenic B and T cell areas independent of cell number. AID depletion directly inhibits atherosclerotic plaque formation.
Molecular identification of Phlebotomus kandelakii apyrase and assessment of the immunogenicity of its recombinant protein in BALB/c mice
Authors: Fayaz Shima , Raz Abbasali , Bahrami Fariborz , Fard-Esfahani Pezhman , Parvizi Parviz , Ajdary Soheila 
Published: May 2023

AbstractSand fly salivary proteins have immunomodulatory and anti-inflammatory features; hence, they are proven to perform important roles in the early establishment of Leishmania parasite in the vertebrate host. Among them, salivary apyrase with anti-hemostatic properties has a crucial role during the blood meal process. In the present study, a Genome-Walking method was used to characterize a full-length nucleotide sequence of Phlebotomus (P.) kandelakii apyrase (Pkapy). Bioinformatics analyses revealed that Pkapy is a ~ 36 kDa stable and hydrophilic protein that belongs to the Cimex family of apyrases. Moreover, recombinant proteins of Pkapy and P. papatasi apyrase (Ppapy) were over-expressed in Escherichia coli BL2 (DE3) and their antigenicity in BALB/c mice was evaluated. Dot-blot and ELISA results indicated that both recombinant apyrases could induce antibodies in BALB/c. Moreover, a partial cross-reactivity between Pkapy and Ppapy was found. In vitro stimulation of splenocytes from immunized mice with the recombinant proteins indicated cross-reactive T cell proliferative responses. Cytokine analysis revealed significant production of IFN-γ (p < 0.001) and IL-10 (p < 0.01) in response to Pkapy. In conclusion, the full-length nucleotide sequence and molecular characteristics of Pkapy were identified for the first time. Immunologic analyses indicated that Pkapy and Ppapy are immunogenic in BALB/c mice and show partial cross-reactive responses. The immunity to Pkapy was found to be a Th1-dominant response that highlights its potential as a component for an anti-Leishmania vaccine.
Fungal β-glucan-facilitated cross-feeding activities between Bacteroides and Bifidobacterium species
Authors: Fernandez-Julia Pedro , Black Gary W. , Cheung William , Van Sinderen Douwe , Munoz-Munoz Jose 
Published: May 2023

AbstractThe human gut microbiota (HGM) is comprised of a very complex network of microorganisms, which interact with the host thereby impacting on host health and well-being. β-glucan has been established as a dietary polysaccharide supporting growth of particular gut-associated bacteria, including members of the genera Bacteroides and Bifidobacterium, the latter considered to represent beneficial or probiotic bacteria. However, the exact mechanism underpinning β-glucan metabolism by gut commensals is not fully understood. We show that mycoprotein represents an excellent source for β-glucan, which is consumed by certain Bacteroides species as primary degraders, such as Bacteroides cellulosilyticus WH2. The latter bacterium employs two extracellular, endo-acting enzymes, belonging to glycoside hydrolase families 30 and 157, to degrade mycoprotein-derived β-glucan, thereby releasing oligosaccharides into the growth medium. These released oligosaccharides can in turn be utilized by other gut microbes, such as Bifidobacterium and Lactiplantibacillus, which thus act as secondary degraders. We used a cross-feeding approach to track how both species are able to grow in co-culture.
Probing electron localization during molecular dissociation by femtosecond strong-field ion momentum spectroscopy
Authors: Zhao Xinning , Xu Ting , Yu Xitao , Ren Dianxiang , Li Mingxuan , Zhang Xinyu , Li Xiaokai , Ma Pan , Zhang Dongdong , Wang Chuncheng , Wang Qinxin , Hu Xiaoqing , Luo Sizuo , Wu Yong , Wang Jianguo , Ding Dajun 
Published: May 2023

AbstractThe study of molecular valence electron dynamics and their coupling with nuclear motion is one of the frontiers of ultrafast physics and ultrafast chemistry. With time-resolved strong-field ion momentum spectroscopy, we study electron valence and nucleus wavepacket evolution on a femtosecond timescale. Two orientation-dependent bond-breaks of N2O molecules from the same electronic state are studied, and the influence of orbital hybridization and polarization effect during molecular breaking is analyzed based on the measured time-resolved asymmetric Pzsum distributions, allowing a visual representation of electron localization during the dissociation of molecules into ions and atoms. Comparison of experimental and theoretical results on orientation-dependent dissociation dynamics allows us to understand how nuclear motions evolve during fragmentation and to control ultrafast molecular reactions.
Needle detection and localisation for robot‐assisted subretinal injection using deep learning
Authors: Zhou Mingchuan , Guo Xiangyu , Grimm Matthias , Lochner Elias , Jiang Zhongliang , Eslami Abouzar , Ye Juan , Navab Nassir , Knoll Alois , Nasseri Mohammad Ali 
Published: May 2023

AbstractSubretinal injection is a complicated task for retinal surgeons to operate manually. In this paper we demonstrate a robust framework for needle detection and localisation in robot‐assisted subretinal injection using microscope‐integrated Optical Coherence Tomography with deep learning. Five convolutional neural networks with different architectures were evaluated. The main differences between the architectures are the amount of information they receive at the input layer. When evaluated on ex‐vivo pig eyes, the top performing network successfully detected all needles in the dataset and localised them with an Intersection over Union value of 0.55. The algorithm was evaluated by comparing the depth of the top and bottom edge of the predicted bounding box to the ground truth. This analysis showed that the top edge can be used to predict the depth of the needle with a maximum error of 8.5 μm.
A domain translation network with contrastive constraint for unpaired motion image deblurring
Authors: Zhao Bingxin , Li Weihong 
Published: May 2023

AbstractMost motion deblurring methods require a large amount of paired training data, which is nearly unreachable in practice. To overcome the limitation, a domain translation network with contrastive constraint for unpaired motion image deblurring is proposed. First, a domain translation network with two streams, a sharp domain translation stream and a blurred domain translation stream, to handle unpaired sharp and blurred images from the real world is presented. Second, a contrastive constraint loss in the deep intermediate level for the two streams to promote the network to produce deblurring results close to the real sharp image is proposed. Third, distinct loss functions for the two streams to preserve the edge and texture detail of the deblurring image is designed. Extensive experiments on several benchmark datasets demonstrate that the proposed network achieves better visual performance than the current state‐of‐the‐art methods for unpaired motion image deblurring.
Metabolomics and its applications in assisted reproductive technology
Authors: Gao Jingying , Xiao Yan 
Published: May 2023

AbstractMetabolomics, an emerging omics technology developed in the post‐gene age, is an important part of systems biology. It interprets the pathophysiological state of the subject by quantitatively describing the dynamic changes of metabolites through analytical methods, mainly mass spectrometry (MS) and nuclear magnetic resonance (NMR). Assisted reproductive technology (ART) is a method used to manipulate sperm, oocytes, and embryos to achieve conception. Recently, several studies have reported that metabolomics methods can be used to measure metabolites in ART samples; these metabolites can be used to evaluate the quality of gametes and embryos. This article reviews the progress of research on metabolomics and the application of this technology in the field of ART, thus providing a reference for research and development directions in the future.
Dynamic stability assessment of interconnected thermal‐SsGT‐solar photovoltaic‐EV power system with ARO optimized IDN‐FOID amalgamated controller
Authors: Saha Arindita , Babu Naladi Ram , Dash Puja , Acharya Biswaranjan , Bhaskar Mahajan Sagar , Khan Baseem 
Published: May 2023

AbstractTo succeed over the sudden load‐frequency variations in interlinked power systems, an equilibrium must be maintained between power generations and losses. The major problem associated to manifold interlinking arenas of power systems is load frequency control. In this paper, a multiple‐arena scheme is examined which encompasses thermal and split shaft gas turbine plants. Here, artificial rabbit optimization (ARO) is applied to procure the premium standards of the supplementary controller. The projected controller is the amalgamation of integer order integral‐derivative with filter (IDN) and fractional order integral‐derivative (FOID). So, the amalgamation is IDN‐FOID. Henceforth, the ARO augmented IDN‐FOID controller is recognized. The ARO augmented IDN‐FOID supplementary controller delivers enhanced outcomes related to additional secondary controllers like I, PI, and PIDN. Valuation articulates about the improved act of ARO over added algorithms using the IDN‐FOID controller related to converging nature, transient profile, and steady‐state assessment. Assessment is done in the presence of non‐linearities in generation rate constraints and time delay. It is also detected that scheme potent outcomes with the IDN‐FOID controller are superior when the scheme is instructed with solar photovoltaic, electric vehicles, solid oxide fuel cells, and ultra‐capacitor. The ARO optimized IDN‐FOID controller is the anticipated arrangement for the measured scheme.
Endoscopic features of low-grade dysplastic Barrett’s
Authors: He Tony , Iyer Kiran Gopinath , Lai Mark , House Eloise , Slavin John L , Holt Bronte , Tsoi Edward H , Desmond Paul , Taylor Andrew C F 
Published: May 2023

Abstract
Background and study aims Barrett’s esophagus (BE) with low-grade dysplasia (LGD) is considered usually endoscopically invisible and the endoscopic features are not well described. This study aimed to: 1) evaluate the frequency of visible BE-LGD; 2) compare rates of BE-LGD detection in the community versus a Barrett’s referral unit (BRU); and 3) evaluate the endoscopic features of BE-LGD.
Patients and methods This was a retrospective analysis of a prospectively observed cohort of 497 patients referred to a BRU with dysplastic BE between 2008 and 2022. BE-LGD was defined as confirmation of LGD by expert gastrointestinal pathologist(s). Endoscopy reports, images and histology reports were reviewed to evaluate the frequency of endoscopically identifiable BE-LGD and their endoscopic features.
Results A total of 135 patients (27.2%) had confirmed BE-LGD, of whom 15 (11.1%) had visible LGD identified in the community. After BRU assessment, visible LGD was detected in 68 patients (50.4%). Three phenotypes were observed: (A) Non-visible LGD; (B) Elevated (Paris 0-IIa) lesions; and (C) Flat (Paris 0-IIb) lesions with abnormal mucosal and/or vascular patterns with clear demarcation from regular flat BE. The majority (64.7%) of visible LGD was flat lesions with abnormal mucosal and vascular patterns. Endoscopic detection of BE-LGD increased over time (38.7% (2009–2012) vs. 54.3% (2018–2022)).
Conclusions In this cohort, 50.4% of true BE-LGD was endoscopically visible, with increased recognition endoscopically over time and a higher rate of visible LGD detected at a BRU when compared with the community. BRU assessment of BE-LGD remains crucial; however, improving endoscopy surveillance quality in the community is equally important.
Studying dimensions of representation: introducing the Belgian RepResent panel (2019–2021)
Authors: Michel Elie , Feitosa Fernando , Lefevere Jonas , Pilet Jean-Benoît , van Erkel Patrick , van Haute Emilie 
Published: May 2023

AbstractThis research note presents the RepResent Belgian Panel (RBP). The RBP is a voter panel survey consisting of four waves fielded to a sample of voters in Belgium around the May 2019 federal, regional, and European elections in Belgium. It provides unique data on about 250 variables for a quota sample of the same respondents, pre-2019 elections (N = 7351), post-2019 elections (N = 3909), one year after the elections (N = 1996), and 2 years after the elections (N = 1119). The RBP panel dataset was designed to analyse voters’ political attitudes and behaviours, notably on different dimensions of democratic representation, and with a specific focus on democratic resentment (e.g. citizens’ attitudes towards democracy such as distrust and alienation, but also behaviours such as abstention, protest, or voting for anti-establishment parties). Its longitudinal structure allows to explore the political dynamics at play in Belgium throughout the lengthy government formation process. Finally, the last two waves of the RBP were fielded during the Covid-19 pandemic, allowing to explore public opinion before and during this global crisis. The RBP should be of interest to scholars of public opinion and electoral studies.
Attacks and remedies in online public opinion reversal events
Authors: Wu Yiman , Ren Wei , Zhang Yi 
Published: May 2023

Abstract
Collective attacks related to controversial issues are pervasive in online communication. However, public opinion
is often reversed later when earlier reports are revealed to be misinformation, which may lead to remedies offered to the victim
by netizens. We call such phenomena online public opinion reversal (POR) events, which reflect group polarization from attack to
remedy. This paper explores the pragmatic strategies that netizens employ to launch attacks and offer remedies in such events,
examining a dataset including 300 netizen-generated attacking comments and 300 remedial comments collected on Weibo. The study
identified two main categories of online attack strategies and seven types of remedial strategies. Chinese netizens prefer to
employ on-record strategies when launching attacks. When an earlier report is revealed to be fake, they employ apology as the most
frequent remedial strategy. Preferences for different attacking and remedial strategies and potential influencing factors are also
discussed.
A review of plasma-induced defects: detection, kinetics and advanced management
Authors: Nunomura Shota 
Published: May 2023

Abstract
Plasma-induced defects are often recognized in state-of-the-art semiconductors, high-efficiency solar cells and high-sensitivity image sensors. These defects are in the form of a dangling bond, bond deformation, or impurity/residual, which impacts on the device performance and reliability. The defects are introduced via plasma-material interactions during manufacturing processes such as deposition, etching and implantation. So, the management of defects throughout the manufacturing is important for high-performance device fabrication. In this review, we overview the generation and recovery of plasma-induced defects in order to develop the defect-managed advanced plasma processing for further improving the device performances. The defect generation and recovery are described, based on the recent results of in-situ and real-time detection of plasma-induced defects. Two examples are presented: the growth of hydrogenated amorphous silicon and the surface passivation of crystalline silicon for high-efficiency solar cell applications.
Measurement and analysis of an optimized Jiles–Atherton model considering the influence of temperature applied in magnetic shielding devices
Authors: Sun Jinji , Ren Jianyi , Zhou Weiyong 
Published: May 2023

Abstract
Magnetic shielding devices work at different temperatures due to the influence of gas chamber and environmental temperature in the application of ultra-highly sensitive spin exchange relaxation free (SERF) magnetometers. To accurately evaluate the residual magnetic field (MF) of a magnetic shielding device at different temperatures, it is necessary to build a magnetization model considering temperature. However, the modeling of permalloy’s magnetization properties and the measurement of residual MF in magnetic shielding devices at different temperatures have not been considered. In this paper, an optimized Jiles–Atherton (JA) model of permalloy considering temperature is constructed, in which parameters are extracted using a particle swarm optimization algorithm. To further verify the effectiveness of the model in the magnetic shielding device, it is applied to the residual MF simulation of magnetic shielding devices and verified by measurement. The optimized JA model considering temperature improves the calculation accuracy of magnetic shielding devices, which is of great significance for the application of ultra-highly sensitive SERF magnetometers.
Intelligent fault diagnosis of gear crack based on side frequency feature under different working conditions
Authors: Xiao Yuanying , Chen Longting , Chen Siyu , Hu Zehua , Tang Jinyuan 
Published: May 2023

Abstract
Aiming at the problem of gear crack fault diagnosis, an intelligent diagnosis method based on side frequency feature is proposed. It enhances the fault information representation ability of the extracted features and the fault identification ability of the model. Firstly, according to the side frequency distribution characteristics of gear crack fault, the side frequency energy features are quantified, and a relatively complete feature set is constructed by combining the time domain features; Secondly, an evaluation method of feature effectiveness is designed to obtain the optimal feature subset; Finally, a three-stage training network is constructed to achieve an increase in fault diagnosis rate. The test results under different working conditions show that the proposed method can more completely represent the fault information and effectively improve the fault diagnosis rate when compared with the machine learning model of a general two-layer network and feature extraction methods based on entropy features.
Bicycling geodesics are Kirchhoff rods
Authors: Bor Gil , Jackman Connor , Tabachnikov Serge 
Published: May 2023

Abstract
A bicycle path is a pair of trajectories in

R

n

, the ‘front’ and ‘back’ tracks, traced out by the endpoints of a moving line segment of fixed length (the ‘bicycle frame’) and tangent to the back track. Bicycle geodesics are bicycle paths whose front track’s length is critical among all bicycle paths connecting two given placements of the line segment. We write down and study the associated variational equations, showing that for

n
⩾
3

each such geodesic is contained in a 3-dimensional affine subspace and that the front tracks of these geodesics form a certain subfamily of Kirchhoff rods, a class of curves introduced in 1859 by Kirchhoff, generalizing the planar elastic curves of Bernoulli and Euler.
Automated deep learning auto-segmentation of air volumes for MRI-guided online adaptive radiation therapy of abdominal tumors
Authors: Ahunbay Ergun , Parchur Abdul K , Xu Jiaofeng , Thill Dan , Paulson Eric S , Li X Allen 
Published: May 2023

Abstract

Objective. In the current MR-Linac online adaptive workflow, air regions on the MR images need to be manually delineated for abdominal targets, and then overridden by air density for dose calculation. Auto-delineation of these regions is desirable for speed purposes, but poses a challenge, since unlike computed tomography, they do not occupy all dark regions on the image. The purpose of this study is to develop an automated method to segment the air regions on MRI-guided adaptive radiation therapy (MRgART) of abdominal tumors. Approach. A modified ResUNet3D deep learning (DL)-based auto air delineation model was trained using 102 patients’ MR images. The MR images were acquired by a dedicated in-house sequence named ‘Air-Scan’, which is designed to generate air regions that are especially dark and accentuated. The air volumes generated by the newly developed DL model were compared with the manual air contours using geometric similarity (Dice Similarity Coefficient (DSC)), and dosimetric equivalence using Gamma index and dose-volume parameters. Main results. The average DSC agreement between the DL generated and manual air contours is 99% ± 1%. The gamma index between the dose calculations with overriding the DL versus manual air volumes with density of 0.01 is 97% ± 2% for a local gamma calculation with a tolerance of 2% and 2 mm. The dosimetric parameters from planning target volume—PTV and organs at risk—OARs were all within 1% between when DL versus manual contours were overridden by air density. The model runs in less than five seconds on a PC with 28 Core processor and NVIDIA Quadro® P2000 GPU. Significance: a DL based automated segmentation method was developed to generate air volumes on specialized abdominal MR images and generate results that are practically equivalent to the manual contouring of air volumes.
Lattice dynamics and pressure induced metallization of solid iodanil (C6I4O2) studied using density functional theory
Authors: Mondal S , Ayadi Tarek , Lebègue Sébastien , Gupta M K , Mittal R , Vaitheeswaran G 
Published: May 2023

Abstract
A detailed ab initio study addressing the structural, lattice dynamics and pressure induced metallization has been carried out for solid iodanil (C6I4O2). The computed ground state structural properties reveal the crucial role of considering van der Waals correction in determining these properties. An excellent agreement can be noticed between our computed zone centered phonon frequencies and experimentally reported results. Though computed phonon dispersion confirms the dynamical stability of solid iodanil in the P2

1
/c symmetry, a softening of the transverse acoustic phonon mode can be observed with pressure along the D-B direction. At 22 GPa, i.e. across insulator-metal transition, the TA branch along D-B directions hardened, where the role of optical phonon mode (A
u
) is prominent. In addition, the elastic constants were also calculated to ascertain the mechanical stability of the solid iodanil. Moreover, the electronic band structure has been calculated using the quasiparticle G

0
W0 approximation which results in a band gap of 2.49 eV. This value is significantly larger than the value obtained by the generalized gradient approximation, thus emphasizing the importance of quasiparticle correction in solid iodanil. This study clearly shows a reduction of the band gap under pressure and hence result in a band overlap eventually driving iodanil to metallize around 22 GPa. The pressure variation of the inter- and intramolecular bond lengths as well as the charge density plots explain the significant role of the intermolecular I-I distance in understanding the metallization of solid iodanil.