bluuebunny/crossref_metadata_2025_split huggingface dataset:
Noise-injected analog Ising machines enable ultrafast statistical sampling and machine learning
Authors: Böhm Fabian , Alonso-Urquijo Diego , Verschaffelt Guy , Van der Sande Guy 
Published: October 2022

AbstractIsing machines are a promising non-von-Neumann computational concept for neural network training and combinatorial optimization. However, while various neural networks can be implemented with Ising machines, their inability to perform fast statistical sampling makes them inefficient for training neural networks compared to digital computers. Here, we introduce a universal concept to achieve ultrafast statistical sampling with analog Ising machines by injecting noise. With an opto-electronic Ising machine, we experimentally demonstrate that this can be used for accurate sampling of Boltzmann distributions and for unsupervised training of neural networks, with equal accuracy as software-based training. Through simulations, we find that Ising machines can perform statistical sampling orders-of-magnitudes faster than software-based methods. This enables the use of Ising machines beyond combinatorial optimization and makes them into efficient tools for machine learning and other applications.
Multicellular immune dynamics implicate PIM1 as a potential therapeutic target for uveitis
Authors: Li He , Xie Lihui , Zhu Lei , Li Zhaohuai , Wang Rong , Liu Xiuxing , Huang Zhaohao , Chen Binyao , Gao Yuehan , Wei Lai , He Chang , Ju Rong , Liu Yizhi , Liu Xialin , Zheng Yingfeng , Su Wenru 
Published: October 2022

AbstractUveitis is a severe autoimmune disease, and a common cause of blindness; however, its individual cellular dynamics and pathogenic mechanism remain poorly understood. Herein, by performing single-cell RNA sequencing (scRNA-seq) on experimental autoimmune uveitis (EAU), we identify disease-associated alterations in cell composition and transcriptional regulation as the disease progressed, as well as a disease-related molecule, PIM1. Inhibiting PIM1 reduces the Th17 cell proportion and increases the Treg cell proportion, likely due to regulation of PIM1 to the protein kinase B (AKT)/Forkhead box O1 (FOXO1) pathway. Moreover, inhibiting PIM1 reduces Th17 cell pathogenicity and reduces plasma cell differentiation. Importantly, the upregulation of PIM1 in CD4+ T cells and plasma cells is conserved in a human uveitis, Vogt-Koyanagi-Harada disease (VKH), and inhibition of PIM1 reduces CD4+ T and B cell expansion. Collectively, a dynamic immune cellular atlas during uveitis is developed and implicate that PIM1 may be a potential therapeutic target for VKH.
Expression strategies for the efficient synthesis of antimicrobial peptides in plastids
Authors: Hoelscher Matthijs P. , Forner Joachim , Calderone Silvia , Krämer Carolin , Taylor Zachary , Loiacono F. Vanessa , Agrawal Shreya , Karcher Daniel , Moratti Fabio , Kroop Xenia , Bock Ralph 
Published: October 2022

AbstractAntimicrobial peptides (AMPs) kill microbes or inhibit their growth and are promising next-generation antibiotics. Harnessing their full potential as antimicrobial agents will require methods for cost-effective large-scale production and purification. Here, we explore the possibility to exploit the high protein synthesis capacity of the chloroplast to produce AMPs in plants. Generating a large series of 29 sets of transplastomic tobacco plants expressing nine different AMPs as fusion proteins, we show that high-level constitutive AMP expression results in deleterious plant phenotypes. However, by utilizing inducible expression and fusions to the cleavable carrier protein SUMO, the cytotoxic effects of AMPs and fused AMPs are alleviated and plants with wild-type-like phenotypes are obtained. Importantly, purified AMP fusion proteins display antimicrobial activity independently of proteolytic removal of the carrier. Our work provides expression strategies for the synthesis of toxic polypeptides in chloroplasts, and establishes transplastomic plants as efficient production platform for antimicrobial peptides.
Decoding the spatial chromatin organization and dynamic epigenetic landscapes of macrophage cells during differentiation and immune activation
Authors: Lin Da , Xu Weize , Hong Ping , Wu Chengchao , Zhang Zhihui , Zhang Siheng , Xing Lingyu , Yang Bing , Zhou Wei , Xiao Qin , Wang Jinyue , Wang Cong , He Yu , Chen Xi , Cao Xiaojian , Man Jiangwei , Reheman Aikebaier , Wu Xiaofeng , Hao Xingjie , Hu Zhe , Chen Chunli , Cao Zimeng , Yin Rong , Fu Zhen F. , Zhou Rong , Teng Zhaowei , Li Guoliang , Cao Gang 
Published: October 2022

AbstractImmunocytes dynamically reprogram their gene expression profiles during differentiation and immunoresponse. However, the underlying mechanism remains elusive. Here, we develop a single-cell Hi-C method and systematically delineate the 3D genome and dynamic epigenetic atlas of macrophages during these processes. We propose “degree of disorder” to measure genome organizational patterns inside topologically-associated domains, which is correlated with the chromatin epigenetic states, gene expression, and chromatin structure variability in individual cells. Furthermore, we identify that NF-κB initiates systematic chromatin conformation reorganization upon Mycobacterium tuberculosis infection. The integrated Hi-C, eQTL, and GWAS analysis depicts the atlas of the long-range target genes of mycobacterial disease susceptible loci. Among these, the SNP rs1873613 is located in the anchor of a dynamic chromatin loop with LRRK2, whose inhibitor AdoCbl could be an anti-tuberculosis drug candidate. Our study provides comprehensive resources for the 3D genome structure of immunocytes and sheds insights into the order of genome organization and the coordinated gene transcription during immunoresponse.
Recurrent neural networks with explicit representation of dynamic latent variables can mimic behavioral patterns in a physical inference task
Authors: Rajalingham Rishi , Piccato Aída , Jazayeri Mehrdad 
Published: October 2022

AbstractPrimates can richly parse sensory inputs to infer latent information. This ability is hypothesized to rely on establishing mental models of the external world and running mental simulations of those models. However, evidence supporting this hypothesis is limited to behavioral models that do not emulate neural computations. Here, we test this hypothesis by directly comparing the behavior of primates (humans and monkeys) in a ball interception task to that of a large set of recurrent neural network (RNN) models with or without the capacity to dynamically track the underlying latent variables. Humans and monkeys exhibit similar behavioral patterns. This primate behavioral pattern is best captured by RNNs endowed with dynamic inference, consistent with the hypothesis that the primate brain uses dynamic inferences to support flexible physical predictions. Moreover, our work highlights a general strategy for using model neural systems to test computational hypotheses of higher brain function.
Volcano-type relationship between oxidation states and catalytic activity of single-atom catalysts towards hydrogen evolution
Authors: Cao Dong , Xu Haoxiang , Li Hongliang , Feng Chen , Zeng Jie , Cheng Daojian 
Published: October 2022

AbstractTo date, the effect of oxidation state on activity remains controversial in whether higher or lower oxidation states benefit the enhancement of catalytic activity. Herein, we discover a volcanic relationship between oxidation state and hydrogen evolution reaction activity based on Os single-atom catalysts. Firstly, a series of Os SACs with oxidation states ranging from  + 0.9 to  + 2.9 are synthesized via modifying the coordination environments, including Os-N3S1, Os-N4, Os-S6, Os-C3, and Os-C4S2. A volcano-type relation between oxidation states and hydrogen evolution activity emerge with a summit at a moderate experimental oxidation state of  + 1.3 (Os-N3S1). Mechanism studies illustrate that with increasing oxidation states, the adsorption of H atoms on Os is strengthened due to increased energy level and decreased occupancy of anti-bonding states of Os-H bond until the anti-bonding states become empty. Further increasing the oxidation states weakens hydrogen adsorption because of the decreased occupancy of Os-H bonding states. In this work, we emphasize the essential role of oxidation state in manipulating activity, which offers insightful guidance for the rational design of single-atom catalysts.
Thermal management of chips by a device prototype using synergistic effects of 3-D heat-conductive network and electrocaloric refrigeration
Authors: Li Ming-Ding , Shen Xiao-Quan , Chen Xin , Gan Jia-Ming , Wang Fang , Li Jian , Wang Xiao-Liang , Shen Qun-Dong 
Published: October 2022

AbstractWith speeding up development of 5 G chips, high-efficient thermal structure and precise management of tremendous heat becomes a substantial challenge to the power-hungry electronics. Here, we demonstrate an interpenetrating architecture of electrocaloric polymer with highly thermally conductive pathways that achieves a 240% increase in the electrocaloric performance and a 300% enhancement in the thermal conductivity of the polymer. A scaled-up version of the device prototype for a single heat spot cooling of 5 G chip is fabricated utilizing this electrocaloric composite and electromagnetic actuation. The continuous three-dimensional (3-D) thermal conductive network embedded in the polymer acts as nucleation sites of the ordered dipoles under applied electric field, efficiently collects thermal energy at the hot-spots arising from field-driven dipolar entropy change, and opens up the high-speed conduction path of phonons. The synergy of two components, thus, tackles the challenge of sluggish heat dissipation of the electroactive polymers and their contact interfaces with low thermal conductivity, and more importantly, significantly reduces the electric energy for switching the dipolar states during the electrocaloric cycles, and increases the manipulable entropy at the low fields. Such a feasible solution is inevitable to the precisely fixed-point thermal management of next-generation smart microelectronic devices.
Two-particle time-domain interferometry in the fractional quantum Hall effect regime
Authors: Taktak I. , Kapfer M. , Nath J. , Roulleau P. , Acciai M. , Splettstoesser J. , Farrer I. , Ritchie D. A. , Glattli D. C. 
Published: October 2022

AbstractQuasi-particles are elementary excitations of condensed matter quantum phases. Demonstrating that they keep quantum coherence while propagating is a fundamental issue for their manipulation for quantum information tasks. Here, we consider anyons, the fractionally charged quasi-particles of the Fractional Quantum Hall Effect occurring in two-dimensional electronic conductors in high magnetic fields. They obey anyonic statistics, intermediate between fermionic and bosonic. Surprisingly, anyons show large quantum coherence when transmitted through the localized states of electronic Fabry-Pérot interferometers, but almost no quantum interference when transmitted via the propagating states of Mach-Zehnder interferometers. Here, using a novel interferometric approach, we demonstrate that anyons do keep quantum coherence while propagating. Performing two-particle time-domain interference measurements sensitive to the two-particle Hanbury Brown Twiss phase, we find 53 and 60% visibilities for anyons with charges e/5 and e/3. Our results give a positive message for the challenge of performing controlled quantum coherent braiding of anyons.
Clinical severity of SARS-CoV-2 Omicron BA.4 and BA.5 lineages compared to BA.1 and Delta in South Africa
Authors: Wolter Nicole , Jassat Waasila , Walaza Sibongile , Welch Richard , Moultrie Harry , Groome Michelle J. , Amoako Daniel Gyamfi , Everatt Josie , Bhiman Jinal N. , Scheepers Cathrine , Tebeila Naume , Chiwandire Nicola , du Plessis Mignon , Govender Nevashan , Ismail Arshad , Glass Allison , Mlisana Koleka , Stevens Wendy , Treurnicht Florette K. , Subramoney Kathleen , Makatini Zinhle , Hsiao Nei-yuan , Parboosing Raveen , Wadula Jeannette , Hussey Hannah , Davies Mary-Ann , Boulle Andrew , von Gottberg Anne , Cohen Cheryl 
Published: October 2022

AbstractOmicron lineages BA.4 and BA.5 drove a fifth wave of COVID-19 cases in South Africa. Here, we use the presence/absence of the S-gene target as a proxy for SARS-CoV-2 variant/lineage for infections diagnosed using the TaqPath PCR assay between 1 October 2021 and 26 April 2022. We link national COVID-19 individual-level data including case, laboratory test and hospitalisation data. We assess severity using multivariable logistic regression comparing the risk of hospitalisation and risk of severe disease, once hospitalised, for Delta, BA.1, BA.2 and BA.4/BA.5 infections. After controlling for factors associated with hospitalisation and severe outcome respectively, BA.4/BA.5-infected individuals had a similar odds of hospitalisation (aOR 1.24, 95% CI 0.98–1.55) and severe outcome (aOR 0.72, 95% CI 0.41–1.26) compared to BA.1-infected individuals. Newly emerged Omicron lineages BA.4/BA.5 showed similar severity to the BA.1 lineage and continued to show reduced clinical severity compared to the Delta variant.
Chiral superstructures of inorganic nanorods by macroscopic mechanical grinding
Authors: Yang Zhiwei , Wei Yanze , Wei Jingjing , Yang Zhijie 
Published: October 2022

AbstractThe development of mechanochemistry substantially expands the traditional synthetic realm at the molecular level. Here, we extend the concept of mechanochemistry from atomic/molecular solids to the nanoparticle solids, and show how the macroscopic grinding is being capable of generating chirality in self-assembled nanorod (NR) assemblies. Specifically, the weak van der Waals interaction is dominated in self-assembled NR assemblies when their surface is coated with aliphatic chains, which can be overwhelmed by a press-and-rotate mechanic force macroscopically. The chiral sign of the NR assemblies can be well-controlled by the rotating directions, where the clockwise and counter-clockwise rotation leads to the positive and negative Cotton effect in circular dichroism and circularly polarized luminescence spectra, respectively. Importantly, we show that the present approach can be applied to NRs of diverse inorganic materials, including CdSe, CdSe/CdS, and TiO2. Equally important, the as-prepared chiral NR assemblies could be served as porous yet robust chiral substrates, which enable to host other molecular materials and induce the chirality transfer from substrate to the molecular system.
Reference bioimaging to assess the phenotypic trait diversity of bryophytes within the family Scapaniaceae
Authors: Peters Kristian , König-Ries Birgitta 
Published: October 2022

AbstractMacro- and microscopic images of organisms are pivotal in biodiversity research. Despite that bioimages have manifold applications such as assessing the diversity of form and function, FAIR bioimaging data in the context of biodiversity are still very scarce, especially for difficult taxonomic groups such as bryophytes. Here, we present a high-quality reference dataset containing macroscopic and bright-field microscopic images documenting various phenotypic characters of the species belonging to the liverwort family of Scapaniaceae occurring in Europe. To encourage data reuse in biodiversity and adjacent research areas, we annotated the imaging data with machine-actionable metadata using community-accepted semantics. Furthermore, raw imaging data are retained and any contextual image processing like multi-focus image fusion and stitching were documented to foster good scientific practices through source tracking and provenance. The information contained in the raw images are also of particular interest for machine learning and image segmentation used in bioinformatics and computational ecology. We expect that this richly annotated reference dataset will encourage future studies to follow our principles.
Parasocial relationships on YouTube reduce prejudice towards mental health issues
Authors: Lotun Shaaba , Lamarche Veronica M. , Samothrakis Spyridon , Sandstrom Gillian M. , Matran-Fernandez Ana 
Published: October 2022

AbstractIntergroup contact has long been established as a way to reduce prejudice among society, but in-person interventions can be resource intensive and limited in reach. Parasocial relationships (PSRs) might navigate these problems by reaching large audiences with minimal resources and have been shown to help reduce prejudice in an extended version of contact theory. However, previous studies have shown inconsistent success. We assessed whether parasocial interventions reduce prejudice towards people with mental health issues by first creating a new PSR with a YouTube creator disclosing their experiences with borderline personality disorder. Our intervention successfully reduced explicit prejudice and intergroup anxiety. We corroborated these effects through causal analyses, where lower prejudice levels were mediated by the strength of parasocial bond. Preliminary findings suggest that this lower prejudice is sustained over time. Our results support the parasocial contact hypothesis and provide an organic method to passively reduce prejudice on a large scale.
Taming numerical errors in simulations of continuous variable non-Gaussian state preparation
Authors: Provazník Jan , Filip Radim , Marek Petr 
Published: October 2022

AbstractNumerical simulation of continuous variable quantum state preparation is a necessary tool for optimization of existing quantum information processing protocols. A powerful instrument for such simulation is the numerical computation in the Fock state representation. It unavoidably uses an approximation of the infinite-dimensional Fock space by finite complex vector spaces implementable with classical digital computers. In this approximation we analyze the accuracy of several currently available methods for computation of the truncated coherent displacement operator. To overcome their limitations we propose an alternative with improved accuracy based on the standard matrix exponential. We then employ the method in analysis of non-Gaussian state preparation scheme based on coherent displacement of a two mode squeezed vacuum with subsequent photon counting measurement. We compare different detection mechanisms, including avalanche photodiodes, their cascades, and photon number resolving detectors in the context of engineering non-linearly squeezed cubic states and construction of qubit-like superpositions between vacuum and single photon states.
Bioprocess development for biosurfactant production by Natrialba sp. M6 with effective direct virucidal and anti-replicative potential against HCV and HSV
Authors: Hegazy Ghada E. , Abu-Serie Marwa M. , Abou-elela G. M. , Ghozlan Hanan , Sabry Soraya A. , Soliman Nadia A. , Teleb Mohamed , Abdel-Fattah Yasser R. 
Published: October 2022

AbstractHalophilic archaea is considered an promising natural source of many important metabolites. This study focused on one of the surface-active biomolecules named biosurfactants produced by haloarchaeon Natrialba sp. M6. The production trend was optimized and the product was partially purified and identified using GC–Mass spectrometry. Sequential optimization approaches, Plackett–Burman (PB) and Box–Behnken Designs (BBD) were applied to maximize the biosurfactants production from M6 strain by using 14 factors; pH, NaCl, agitation and glycerol; the most significant factors that influenced the biosurfactant production were used for Response Surface Methodology (RSM). The final optimal production conditions were agitation (150 rpm), glycerol (3%), NaCl (20.8%), pH (12) and cultivation temperature (37°C). GC–Mass spectrometry for the recovered extract revealed the presence of a diverse group of bipolar nature, hydrophobic hydrocarbon chain and charged function group. The majority of these compounds are fatty acids. Based on results of GC–MS, compositional analysis content and Zetasizer, it was proposed that the extracted biosurfactant produced by haloarchaeon Natrialba sp. M6 could be a cationic lipoprotein. The antiviral activity of such biosurfactant was investigated against hepatitis C (HCV) and herpes simplex (HSV1) viruses at its maximum safe doses (20 μg/mL and 8 μg/mL, respectively). Its mode of antiviral action was declared to be primarily via deactivating viral envelopes thus preventing viral entry. Moreover, this biosurfactant inhibited RNA polymerase- and DNA polymerase-mediated viral replication at IC50 of 2.28 and 4.39 μg/mL, respectively also. Molecular docking studies showed that surfactin resided well and was bound to the specified motif with low and accepted binding energies (ΔG = − 5.629, − 6.997 kcal/mol) respectively. Therefore, such biosurfactant could be presented as a natural safe and effective novel antiviral agent.
Prediction of activity-related energy expenditure under free-living conditions using accelerometer-derived physical activity
Authors: Jeran Stephanie , Steinbrecher Astrid , Haas Verena , Mähler Anja , Boschmann Michael , Westerterp Klaas R. , Brühmann Boris A. , Steindorf Karen , Pischon Tobias 
Published: October 2022

AbstractThe purpose of the study was to develop prediction models to estimate physical activity (PA)-related energy expenditure (AEE) based on accelerometry and additional variables in free-living adults. In 50 volunteers (20–69 years) PA was determined over 2 weeks using the hip-worn Actigraph GT3X + as vector magnitude (VM) counts/minute. AEE was calculated based on total daily EE (measured by doubly-labeled water), resting EE (indirect calorimetry), and diet-induced thermogenesis. Anthropometry, body composition, blood pressure, heart rate, fitness, sociodemographic and lifestyle factors, PA habits and food intake were assessed. Prediction models were developed by context-grouping of 75 variables, and within-group stepwise selection (stage I). All significant variables were jointly offered for second stepwise regression (stage II). Explained AEE variance was estimated based on variables remaining significant. Alternative scenarios with different availability of groups from stage I were simulated. When all 11 significant variables (selected in stage I) were jointly offered for stage II stepwise selection, the final model explained 70.7% of AEE variance and included VM-counts (33.8%), fat-free mass (26.7%), time in moderate PA + walking (6.4%) and carbohydrate intake (3.9%). Alternative scenarios explained 53.8–72.4% of AEE. In conclusion, accelerometer counts and fat-free mass explained most of variance in AEE. Prediction was further improved by PA information from questionnaires. These results may be used for AEE prediction in studies using accelerometry