bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial Transcriptomics-correlated Electron Microscopy maps transcriptional and ultrastructural responses to brain injury
Authors: Androvic Peter , Schifferer Martina , Perez Anderson Katrin , Cantuti-Castelvetri Ludovico , Jiang Hanyi , Ji Hao , Liu Lu , Gouna Garyfallia , Berghoff Stefan A. , Besson-Girard Simon , Knoferle Johanna , Simons Mikael , Gokce Ozgun 
Published: July 2023

AbstractUnderstanding the complexity of cellular function within a tissue necessitates the combination of multiple phenotypic readouts. Here, we developed a method that links spatially-resolved gene expression of single cells with their ultrastructural morphology by integrating multiplexed error-robust fluorescence in situ hybridization (MERFISH) and large area volume electron microscopy (EM) on adjacent tissue sections. Using this method, we characterized in situ ultrastructural and transcriptional responses of glial cells and infiltrating T-cells after demyelinating brain injury in male mice. We identified a population of lipid-loaded “foamy” microglia located in the center of remyelinating lesion, as well as rare interferon-responsive microglia, oligodendrocytes, and astrocytes that co-localized with T-cells. We validated our findings using immunocytochemistry and lipid staining-coupled single-cell RNA sequencing. Finally, by integrating these datasets, we detected correlations between full-transcriptome gene expression and ultrastructural features of microglia. Our results offer an integrative view of the spatial, ultrastructural, and transcriptional reorganization of single cells after demyelinating brain injury.
Ketones from aldehydes via alkyl C(sp3)−H functionalization under photoredox cooperative NHC/palladium catalysis
Authors: Wang Hai-Ying , Wang Xin-Han , Zhou Bang-An , Zhang Chun-Lin , Ye Song 
Published: July 2023

AbstractDirect synthesis of ketones from aldehydes features high atom- and step-economy. Yet, the coupling of aldehydes with unactivated alkyl C(sp3)-H remains challenging. Herein, we develop the synthesis of ketones from aldehydes via alkyl C(sp3)-H functionalization under photoredox cooperative NHC/Pd catalysis. The two-component reaction of iodomethylsilyl alkyl ether with aldehydes gave a variety of β-, γ- and δ-silyloxylketones via 1,n-HAT (n = 5, 6, 7) of silylmethyl radicals to generate secondary or tertiary alkyl radicals and following coupling with ketyl radicals from aldehydes under photoredox NHC catalysis. The three-component reaction with the addition of styrenes gave the corresponding ε-hydroxylketones via the generation of benzylic radicals by the addition of alkyl radicals to styrenes and following coupling with ketyl radicals. This work demonstrates the generation of ketyl radical and alkyl radical under the photoredox cooperative NHC/Pd catalysis, and provides two and three component reactions for the synthesis of ketones from aldehydes with alkyl C(sp3)-H functionalization. The synthetic potential of this protocol was also further illustrated by the late-stage functionalization of natural products.
On the mechanisms of lysis triggered by perturbations of bacterial cell wall biosynthesis
Authors: Kawai Yoshikazu , Kawai Maki , Mackenzie Eilidh Sohini , Dashti Yousef , Kepplinger Bernhard , Waldron Kevin John , Errington Jeff 
Published: July 2023

AbstractInhibition of bacterial cell wall synthesis by antibiotics such as β-lactams is thought to cause explosive lysis through loss of cell wall integrity. However, recent studies on a wide range of bacteria have suggested that these antibiotics also perturb central carbon metabolism, contributing to death via oxidative damage. Here, we genetically dissect this connection in Bacillus subtilis perturbed for cell wall synthesis, and identify key enzymatic steps in upstream and downstream pathways that stimulate the generation of reactive oxygen species through cellular respiration. Our results also reveal the critical role of iron homeostasis for the oxidative damage-mediated lethal effects. We show that protection of cells from oxygen radicals via a recently discovered siderophore-like compound uncouples changes in cell morphology normally associated with cell death, from lysis as usually judged by a phase pale microscopic appearance. Phase paling appears to be closely associated with lipid peroxidation.
Safety and immunogenicity of a tetravalent and bivalent SARS-CoV-2 protein booster vaccine in men
Authors: Hannawi Suad , Saf Eldin Linda , Abuquta Alaa , Alamadi Ahmad , Mahmoud Sally A. , Hassan Aala , Xu Shuping , Li Jian , Liu Dongfang , Baidoo Adam Abdul Hakeem , Ibrahim Dima , Alhaj Mojtaba , Chen Yuanxin , Zhou Qiang , Xie Liangzhi 
Published: July 2023

AbstractThe safety and immunogenicity of a protein-based tetravalent vaccine SCTV01E that contains spike protein ectodomain (S-ECD) of Alpha, Beta, Delta and Omicron BA.1 are assessed and compared with bivalent protein vaccine SCTV01C (Alpha and Beta variants) and monovalent mRNA vaccine (NCT05323461). The primary endpoints are the geometric mean titers (GMT) of live virus neutralizing antibodies (nAb) to Delta (B.1.617.2) and Omicron BA.1 at day 28 post-injection. The secondary endpoints include the safety, day 180 GMTs against Delta and Omicron BA.1, day 28 GMTs to BA.5, and seroresponse rates of neutralizing antibodies and T cell responses at day 28 post-injection. 450 participants, comprising of 449 males and 1 female, with a median age (range) of 27 (18–62) years, are assigned to receive one booster dose of BNT162b2, 20 µg SCTV01C or 30 µg SCTV01E and completed 4-week follow-up. All SCTV01E related adverse events (AEs) are mild or moderate and no Grade ≥3 AE, serious AE or new safety concerns are identified. Day 28 GMT of live virus neutralizing antibodies and seroresponse against Omicron BA.1 and BA.5 with SCTV01E are significantly higher than those with SCTV01C and BNT162b2. These data indicate an overall neutralization superiority with tetravalent booster immunization in men.
Probing hyperbolic and surface phonon-polaritons in 2D materials using Raman spectroscopy
Authors: Bergeron Alaric , Gradziel Clément , Leonelli Richard , Francoeur Sébastien 
Published: July 2023

AbstractThe hyperbolic dispersion relation of phonon-polaritons (PhPols) in anisotropic van der Waals materials provides high-momentum states, directional propagation, subdiffractional confinement, large optical density of states, and enhanced light-matter interactions. In this work, we use Raman spectroscopy in the convenient backscattering configuration to probe PhPol in GaSe, a 2D material presenting two hyperbolic regions separated by a double reststrahlen band. By varying the incidence angle, dispersion relations are revealed for samples with thicknesses between 200 and 750 nm. Raman spectra simulations confirm the observation of one surface and two extraordinary guided polaritons and match the evolution of PhPol frequency as a function of vertical confinement. GaSe appears to provide relatively low propagation losses and supports confinement factors matching or exceeding those reported for other 2D materials. Resonant excitation close to the 1s exciton singularly exalts the scattering efficiency of PhPols, providing enhanced scattering signals and means to probe the coupling of PhPols to other solid-state excitations.
Blocking D2/D3 dopamine receptors in male participants increases volatility of beliefs when learning to trust others
Authors: Mikus Nace , Eisenegger Christoph , Mathys Christoph , Clark Luke , Müller Ulrich , Robbins Trevor W. , Lamm Claus , Naef Michael 
Published: July 2023

AbstractThe ability to learn about other people is crucial for human social functioning. Dopamine has been proposed to regulate the precision of beliefs, but direct behavioural evidence of this is lacking. In this study, we investigate how a high dose of the D2/D3 dopamine receptor antagonist sulpiride impacts learning about other people’s prosocial attitudes in a repeated Trust game. Using a Bayesian model of belief updating, we show that in a sample of 76 male participants sulpiride increases the volatility of beliefs, which leads to higher precision weights on prediction errors. This effect is driven by participants with genetically conferred higher dopamine availability (Taq1a polymorphism) and remains even after controlling for working memory performance. Higher precision weights are reflected in higher reciprocal behaviour in the repeated Trust game but not in single-round Trust games. Our data provide evidence that the D2 receptors are pivotal in regulating prediction error-driven belief updating in a social context.
Large depth-of-field ultra-compact microscope by progressive optimization and deep learning
Authors: Zhang Yuanlong , Song Xiaofei , Xie Jiachen , Hu Jing , Chen Jiawei , Li Xiang , Zhang Haiyu , Zhou Qiqun , Yuan Lekang , Kong Chui , Shen Yibing , Wu Jiamin , Fang Lu , Dai Qionghai 
Published: July 2023

AbstractThe optical microscope is customarily an instrument of substantial size and expense but limited performance. Here we report an integrated microscope that achieves optical performance beyond a commercial microscope with a 5×, NA 0.1 objective but only at 0.15 cm3 and 0.5 g, whose size is five orders of magnitude smaller than that of a conventional microscope. To achieve this, a progressive optimization pipeline is proposed which systematically optimizes both aspherical lenses and diffractive optical elements with over 30 times memory reduction compared to the end-to-end optimization. By designing a simulation-supervision deep neural network for spatially varying deconvolution during optical design, we accomplish over 10 times improvement in the depth-of-field compared to traditional microscopes with great generalization in a wide variety of samples. To show the unique advantages, the integrated microscope is equipped in a cell phone without any accessories for the application of portable diagnostics. We believe our method provides a new framework for the design of miniaturized high-performance imaging systems by integrating aspherical optics, computational optics, and deep learning.
Leveraging spatial transcriptomics data to recover cell locations in single-cell RNA-seq with CeLEry
Authors: Zhang Qihuang , Jiang Shunzhou , Schroeder Amelia , Hu Jian , Li Kejie , Zhang Baohong , Dai David , Lee Edward B. , Xiao Rui , Li Mingyao 
Published: July 2023

AbstractSingle-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity in health and disease. However, the lack of physical relationships among dissociated cells has limited its applications. To address this issue, we present CeLEry (Cell Location recovEry), a supervised deep learning algorithm that leverages gene expression and spatial location relationships learned from spatial transcriptomics to recover the spatial origins of cells in scRNA-seq. CeLEry has an optional data augmentation procedure via a variational autoencoder, which improves the method’s robustness and allows it to overcome noise in scRNA-seq data. We show that CeLEry can infer the spatial origins of cells in scRNA-seq at multiple levels, including 2D location and spatial domain of a cell, while also providing uncertainty estimates for the recovered locations. Our comprehensive benchmarking evaluations on multiple datasets generated from brain and cancer tissues using Visium, MERSCOPE, MERFISH, and Xenium demonstrate that CeLEry can reliably recover the spatial location information for cells using scRNA-seq data.
Pilot-scale drinking water distribution system to study water quality changes during transport
Authors: García-Timermans Cristina , Malfroot Bram , Dierendonck Cameron , Mol Zoë , Pluym Thomas , Waegenaar Fien , Arends Jan B. A. , Demeestere Kristof , Walgraeve Christophe , Boon Nico , De Gusseme Bart 
Published: July 2023

AbstractDrinking water (DW) quality can change during distribution, leading to taste and odor events and microbial regrowth. Pilot plants mimicking distribution networks are crucial for understanding these changes. We present a new pilot plant design, including piping material, sensors, and instrumentation. The three independent loops (100 m each) of the pilot exhibit identical behavior, allowing simultaneous testing of three conditions. Monitoring includes taste and odor compound formation, microorganism regrowth, and dissolved organic carbon changes. Real-time measurements enable continuous monitoring, and inner pipe biofilm sampling is feasible. The pilot’s modularity facilitates studying climate change effects, different piping materials, and source waters on DW quality in the distribution network.
De novo design of protein structure and function with RFdiffusion
Authors: Watson Joseph L. , Juergens David , Bennett Nathaniel R. , Trippe Brian L. , Yim Jason , Eisenach Helen E. , Ahern Woody , Borst Andrew J. , Ragotte Robert J. , Milles Lukas F. , Wicky Basile I. M. , Hanikel Nikita , Pellock Samuel J. , Courbet Alexis , Sheffler William , Wang Jue , Venkatesh Preetham , Sappington Isaac , Torres Susana Vázquez , Lauko Anna , De Bortoli Valentin , Mathieu Emile , Ovchinnikov Sergey , Barzilay Regina , Jaakkola Tommi S. , DiMaio Frank , Baek Minkyung , Baker David 
Published: July 2023

AbstractThere has been considerable recent progress in designing new proteins using deep-learning methods1–9. Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence–structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.
The European Tertiary Education Register, the reference dataset on European Higher Education Institutions
Authors: Lepori Benedetto , Lambrechts Agata A. , Wagner-Schuster Daniel , Zahradnik Georg 
Published: July 2023

AbstractThe European Tertiary Education Register (ETER) is the reference dataset on European Higher Education Institutions (HEIs). ETER provides data on nearly 3,500 HEIs in about 40 European countries, including descriptive information, geographical information, students and graduates (with various breakdowns), revenues and expenditures, personnel, and research activities; as of March 2023, data cover the years from 2011–2020. ETER complies with OECD-UNESCO-EUROSTAT standards for educational statistics; most data are collected from National Statistical Authorities (NSAs) or ministries of participating countries and are subject to extensive checks and harmonization. The development of ETER has been funded by the European Commission and is part of the current efforts to establish a European Higher Education Sector Observatory; it is closely connected to the establishment of a broader data infrastructure in the field of science and innovation studies (RISIS). The ETER dataset is widely used in the scholarly literature on higher education and science policy, as well as for policy reports and analyses.
Arteriovenous malformation Map2k1 mutation affects vasculogenesis
Authors: Sudduth Christopher L. , Smits Patrick J. , Vivero Matthew P. , Cheng Yu Sheng , Ad Michal , Konczyk Dennis J. , Bischoff Joyce , Warman Matthew L. , Greene Arin K. 
Published: July 2023

AbstractSomatic activating MAP2K1 mutations in endothelial cells (ECs) cause extracranial arteriovenous malformation (AVM). We previously reported the generation of a mouse line allowing inducible expression of constitutively active MAP2K1 (p.K57N) from the Rosa locus (R26GT-Map2k1-GFP/+) and showed, using Tg-Cdh5CreER, that EC expression of mutant MAP2K1 is sufficient for the development of vascular malformations in the brain, ear, and intestines. To gain further insight into the mechanism by which mutant MAP2K1 drives AVM development, we induced MAP2K1 (p.K57N) expression in ECs of postnatal-day-1 pups (P1) and investigated the changes in gene expression in P9 brain ECs by RNA-seq. We found that over-expression of MAP2K1 altered the transcript abundance of > 1600 genes. Several genes had > 20-fold changes between MAP2K1 expressing and wild-type ECs; the highest were Col15a1 (39-fold) and Itgb3 (24-fold). Increased expression of COL15A1 in R26GT-Map2k1-GFP/+; Tg-Cdh5CreER+/− brain ECs was validated by immunostaining. Ontology showed that differentially expressed genes were involved in processes important for vasculogenesis (e.g., cell migration, adhesion, extracellular matrix organization, tube formation, angiogenesis). Understanding how these genes and pathways contribute to AVM formation will help identify targets for therapeutic intervention.
A wideband and compact Quasi-Yagi antenna based on spoof surface plasmon polaritons
Authors: Arghandeh Farshad , Abbasi-Arand Bijan , Hesari-Shermeh Maryam 
Published: July 2023

AbstractIn this paper, a novel wideband end-fire antenna, based on a spoof surface plasmon polaritons (SSPP) transmission line, is proposed. Periodically modulated corrugated metal strips are used as a transmission line for quasi-TEM conversion in the microstrip line to the state of SSPP and the best impedance matching. Due to the strong confinement of the field in the SSPP waveguide and its high transmission performance, it has been used as a transmission line. The antenna consists of SSPP waveguides for the transmission line, a metal plate on the ground as the reflector of the antenna, a metal strip director, and two half-rings to realize the radiation, reaching a wide bandwidth in the range of 4.1 to 8.1 GHz. The simulation results show that this antenna achieves a gain of 6.5 dBi, a bandwidth of 65%, and an efficiency of 97% across a wide operating frequency band, from 4.1 to 8.1 GHz. The proposed end-fire antenna has been fabricated, and the measured results agree well with the simulated results. The end-fire antenna implemented on a dielectric layer also has the advantages of high efficiency, good directivity, high gain, a wide bandwidth, easy fabrication, and a compact size.
A novel neural network model with distributed evolutionary approach for big data classification
Authors: Haritha K. , Shailesh S. , Judy M. V. , Ravichandran K. S. , Krishankumar Raghunathan , Gandomi Amir H. 
Published: July 2023

AbstractThe considerable improvement of technology produced for various applications has resulted in a growth in data sizes, such as healthcare data, which is renowned for having a large number of variables and data samples. Artificial neural networks (ANN) have demonstrated adaptability and effectiveness in classification, regression, and function approximation tasks. ANN is used extensively in function approximation, prediction, and classification. Irrespective of the task, ANN learns from the data by adjusting the edge weights to minimize the error between the actual and predicted values. Back Propagation is the most frequent learning technique that is used to learn the weights of ANN. However, this approach is prone to the problem of sluggish convergence, which is especially problematic in the case of Big Data. In this paper, we propose a Distributed Genetic Algorithm based ANN Learning Algorithm for addressing challenges associated with ANN learning for Big data. Genetic Algorithm is one of the well-utilized bio-inspired combinatorial optimization methods. Also, it is possible to parallelize it at multiple stages, and this may be done in an extremely effective manner for the distributed learning process. The proposed model is tested with various datasets to evaluate its realizability and efficiency. The results obtained from the experiments show that after a specific volume of data, the proposed learning method outperformed the traditional methods in terms of convergence time and accuracy. The proposed model outperformed the traditional model by almost 80% improvement in computational time.
Field attraction of Eurydema ornata (Hemiptera: Pentatomidae) to allyl isothiocyanate
Authors: Koczor Sándor , Tóth Miklós 
Published: July 2023

AbstractSeveral Eurydema species (Hemiptera: Pentatomidae) are considered as pests, however, reports on their chemical ecology are scarce. In the current study we focused on Eurydema ornata (Linnaeus) a pentatomid pest of several brassicaceous crops. Since the species is known to feed preferably on generative parts of plants, a series of floral and green leaf volatiles were tested by electroantennography and compounds eliciting remarkable responses were also tested in the field. Three compounds elicited the most outstanding responses from antennae of E. ornata: allyl isothiocyanate, phenylacetaldehyde and ± linalool. Field experiments were conducted in Hungary between 2017 and 2021 to test the potential attractive effects of the compounds. Three Eurydema species were caught in the experiments E. ornata, E. oleracea (Linnaeus) and E. ventralis Kolenati. In the experiments combinations containing allyl isothiocyanate attracted both males and females of E. ornata. The compound was also attractive on its own, in a positive, dose-dependent manner. When presented alone, neither phenylacetaldehyde nor ± linalool was attractive to the species, furthermore, addition of these compounds to allyl isothiocyanate did not affect attraction considerably. To our knowledge this is the first demonstration of field attration of an Eurydema species to a semiochemical and one of the few reports on trapping of a pentatomid species with a synthetic plant volatile in the field. Perspectives regarding research and potential practical applications are discussed in the paper.