bluuebunny/crossref_metadata_2025_split huggingface dataset:
UAF1 deubiquitinase complexes facilitate NLRP3 inflammasome activation by promoting NLRP3 expression
Authors: Song Hui , Zhao Chunyuan , Yu Zhongxia , Li Qizhao , Yan Rongzhen , Qin Ying , Jia Mutian , Zhao Wei 
Published: November 2020

AbstractNOD-like receptor protein 3 (NLRP3) detects microbial infections or endogenous danger signals and activates the NLRP3 inflammasome, which has important functions in host defense and contributes to the pathogenesis of inflammatory diseases, and thereby needs to be tightly controlled. Deubiquitination of NLRP3 is considered a key step in NLRP3 inflammasome activation. However, the mechanisms by which deubiquitination controls NLRP3 inflammasome activation are unclear. Here, we show that the UAF1/USP1 deubiquitinase complex selectively removes K48-linked polyubiquitination of NLRP3 and suppresses its ubiquitination-mediated degradation, enhancing cellular NLRP3 levels, which are indispensable for subsequent NLRP3 inflammasome assembly and activation. In addition, the UAF1/USP12 and UAF1/USP46 complexes promote NF-κB activation, enhance the transcription of NLRP3 and proinflammatory cytokines (including pro-IL-1β, TNF, and IL-6) by inhibiting ubiquitination-mediated degradation of p65. Consequently, Uaf1 deficiency attenuates NLRP3 inflammasome activation and IL-1β secretion both in vitro and in vivo. Our study reveals that the UAF1 deubiquitinase complexes enhance NLRP3 and pro-IL-1β expression by targeting NLRP3 and p65 and licensing NLRP3 inflammasome activation.
Nanorods with multidimensional optical information beyond the diffraction limit
Authors: Wen Shihui , Liu Yongtao , Wang Fan , Lin Gungun , Zhou Jiajia , Shi Bingyang , Suh Yung Doug , Jin Dayong 
Published: November 2020

AbstractPrecise design and fabrication of heterogeneous nanostructures will enable nanoscale devices to integrate multiple desirable functionalities. But due to the diffraction limit (~200 nm), the optical uniformity and diversity within the heterogeneous functional nanostructures are hardly controlled and characterized. Here, we report a set of heterogeneous nanorods; each optically active section has its unique nonlinear response to donut-shaped illumination, so that one can discern each section with super-resolution. To achieve this, we first realize an approach of highly controlled epitaxial growth and produce a range of heterogeneous structures. Each section along the nanorod structure displays tunable upconversion emissions, in four optical dimensions, including color, lifetime, excitation wavelength, and power dependency. Moreover, we demonstrate a 210 nm single nanorod as an extremely small polychromatic light source for the on-demand generation of RGB photonic emissions. This work benchmarks our ability toward the full control of sub-diffraction-limit optical diversities of single heterogeneous nanoparticles.
A FN-MdV pathway and its role in cerebellar multimodular control of sensorimotor behavior
Authors: Wang Xiaolu , Yu Si-yang , Ren Zhong , De Zeeuw Chris I. , Gao Zhenyu 
Published: November 2020

AbstractThe cerebellum is crucial for various associative sensorimotor behaviors. Delay eyeblink conditioning (DEC) depends on the simplex lobule-interposed nucleus (IN) pathway, yet it is unclear how other cerebellar modules cooperate during this task. Here, we demonstrate the contribution of the vermis-fastigial nucleus (FN) pathway in controlling DEC. We found that task-related modulations in vermal Purkinje cells and FN neurons predict conditioned responses (CRs). Coactivation of the FN and the IN allows for the generation of proper motor commands for CRs, but only FN output fine-tunes unconditioned responses. The vermis-FN pathway launches its signal via the contralateral ventral medullary reticular nucleus, which converges with the command from the simplex-IN pathway onto facial motor neurons. We propose that the IN pathway specifically drives CRs, whereas the FN pathway modulates the amplitudes of eyelid closure during DEC. Thus, associative sensorimotor task optimization requires synergistic modulation of different olivocerebellar modules each provide unique contributions.
Genetic requirements and transcriptomics of Helicobacter pylori biofilm formation on abiotic and biotic surfaces
Authors: Hathroubi Skander , Hu Shuai , Ottemann Karen M. 
Published: November 2020

AbstractBiofilm growth is a widespread mechanism that protects bacteria against harsh environments, antimicrobials, and immune responses. These types of conditions challenge chronic colonizers such as Helicobacter pylori but it is not fully understood how H. pylori biofilm growth is defined and its impact on H. pylori survival. To provide insights into H. pylori biofilm growth properties, we characterized biofilm formation on abiotic and biotic surfaces, identified genes required for biofilm formation, and defined the biofilm-associated gene expression of the laboratory model H. pylori strain G27. We report that H. pylori G27 forms biofilms with a high biomass and complex flagella-filled 3D structures on both plastic and gastric epithelial cells. Using a screen for biofilm-defective mutants and transcriptomics, we discovered that biofilm cells demonstrated lower transcripts for TCA cycle enzymes but higher ones for flagellar formation, two type four secretion systems, hydrogenase, and acetone metabolism. We confirmed that biofilm formation requires flagella, hydrogenase, and acetone metabolism on both abiotic and biotic surfaces. Altogether, these data suggest that H. pylori is capable of adjusting its phenotype when grown as biofilm, changing its metabolism, and re-shaping flagella, typically locomotion organelles, into adhesive structures.
Machine learning the Hubbard U parameter in DFT+U using Bayesian optimization
Authors: Yu Maituo , Yang Shuyang , Wu Chunzhi , Marom Noa 
Published: November 2020

AbstractWithin density functional theory (DFT), adding a Hubbard U correction can mitigate some of the deficiencies of local and semi-local exchange-correlation functionals, while maintaining computational efficiency. However, the accuracy of DFT+U largely depends on the chosen Hubbard U values. We propose an approach to determining the optimal U parameters for a given material by machine learning. The Bayesian optimization (BO) algorithm is used with an objective function formulated to reproduce the band structures produced by more accurate hybrid functionals. This approach is demonstrated for transition metal oxides, europium chalcogenides, and narrow-gap semiconductors. The band structures obtained using the BO U values are in agreement with hybrid functional results. Additionally, comparison to the linear response (LR) approach to determining U demonstrates that the BO method is superior.
Environmental flexibility does not explain metabolic robustness
Authors: Libiseller-Egger Julian , Coltman Benjamin Luke , Gerstl Matthias P. , Zanghellini Jürgen 
Published: November 2020

AbstractCells show remarkable resilience against genetic and environmental perturbations. However, its evolutionary origin remains obscure. In order to leverage methods of systems biology for examining cellular robustness, a computationally accessible way of quantification is needed. Here, we present an unbiased metric of structural robustness in genome-scale metabolic models based on concepts prevalent in reliability engineering and fault analysis. The probability of failure (PoF) is defined as the (weighted) portion of all possible combinations of loss-of-function mutations that disable network functionality. It can be exactly determined if all essential reactions, synthetic lethal pairs of reactions, synthetic lethal triplets of reactions etc. are known. In theory, these minimal cut sets (MCSs) can be calculated for any network, but for large models the problem remains computationally intractable. Herein, we demonstrate that even at the genome scale only the lowest-cardinality MCSs are required to efficiently approximate the PoF with reasonable accuracy. Building on an improved theoretical understanding, we analysed the robustness of 489 E. coli, Shigella, Salmonella, and fungal genome-scale metabolic models (GSMMs). In contrast to the popular “congruence theory”, which explains the origin of genetic robustness as a byproduct of selection for environmental flexibility, we found no correlation between network robustness and the diversity of growth-supporting environments. On the contrary, our analysis indicates that amino acid synthesis rather than carbon metabolism dominates metabolic robustness.
Real-world longitudinal data collected from the SleepHealth mobile app study
Authors: Deering Sean , Pratap Abhishek , Suver Christine , Borelli A. Joseph , Amdur Adam , Headapohl Will , Stepnowsky Carl J. 
Published: November 2020

AbstractConducting biomedical research using smartphones is a novel approach to studying health and disease that is only beginning to be meaningfully explored. Gathering large-scale, real-world data to track disease manifestation and long-term trajectory in this manner is quite practical and largely untapped. Researchers can assess large study cohorts using surveys and sensor-based activities that can be interspersed with participants’ daily routines. In addition, this approach offers a medium for researchers to collect contextual and environmental data via device-based sensors, data aggregator frameworks, and connected wearable devices. The main aim of the SleepHealth Mobile App Study (SHMAS) was to gain a better understanding of the relationship between sleep habits and daytime functioning utilizing a novel digital health approach. Secondary goals included assessing the feasibility of a fully-remote approach to obtaining clinical characteristics of participants, evaluating data validity, and examining user retention patterns and data-sharing preferences. Here, we provide a description of data collected from 7,250 participants living in the United States who chose to share their data broadly with the study team and qualified researchers worldwide.
Pharmacological characterisation of novel adenosine A3 receptor antagonists
Authors: Barkan Kerry , Lagarias Panagiotis , Stampelou Margarita , Stamatis Dimitrios , Hoare Sam , Safitri Dewi , Klotz Karl-Norbert , Vrontaki Eleni , Kolocouris Antonios , Ladds Graham 
Published: November 2020

AbstractThe adenosine A3 receptor (A3R) belongs to a family of four adenosine receptor (AR) subtypes which all play distinct roles throughout the body. A3R antagonists have been described as potential treatments for numerous diseases including asthma. Given the similarity between (adenosine receptors) orthosteric binding sites, obtaining highly selective antagonists is a challenging but critical task. Here we screen 39 potential A3R, antagonists using agonist-induced inhibition of cAMP. Positive hits were assessed for AR subtype selectivity through cAMP accumulation assays. The antagonist affinity was determined using Schild analysis (pA2 values) and fluorescent ligand binding. Structure–activity relationship investigations revealed that loss of the 3-(dichlorophenyl)-isoxazolyl moiety or the aromatic nitrogen heterocycle with nitrogen at α-position to the carbon of carboximidamide group significantly attenuated K18 antagonistic potency. Mutagenic studies supported by molecular dynamic simulations combined with Molecular Mechanics—Poisson Boltzmann Surface Area calculations identified the residues important for binding in the A3R orthosteric site. We demonstrate that K18, which contains a 3-(dichlorophenyl)-isoxazole group connected through carbonyloxycarboximidamide fragment with a 1,3-thiazole ring, is a specific A3R (< 1 µM) competitive antagonist. Finally, we introduce a model that enables estimates of the equilibrium binding affinity for rapidly disassociating compounds from real-time fluorescent ligand-binding studies. These results demonstrate the pharmacological characterisation of a selective competitive A3R antagonist and the description of its orthosteric binding mode. Our findings may provide new insights for drug discovery.
Comparison of global end-diastolic volume index derived from jugular and femoral indicator injection: a prospective observational study in patients equipped with both a PiCCO-2 and an EV-1000-device
Authors: Herner Alexander , Heilmaier Markus , Mayr Ulrich , Schmid Roland M. , Huber Wolfgang 
Published: November 2020

AbstractTranspulmonary thermodilution (TPTD)-derived global end-diastolic volume index (GEDVI) is a static marker of preload which better predicted volume responsiveness compared to filling pressures in several studies. GEDVI can be generated with at least two devices: PiCCO and EV-1000. Several studies showed that uncorrected indicator injection into a femoral central venous catheter (CVC) results in a significant overestimation of GEDVI by the PiCCO-device. Therefore, the most recent PiCCO-algorithm corrects for femoral indicator injection. However, there are no systematic data on the impact of femoral indicator injection for the EV-1000 device. Furthermore, the correction algorithm of the PiCCO is poorly validated. Therefore, we prospectively analyzed 14 datasets from 10 patients with TPTD-monitoring undergoing central venous catheter (CVC)- and arterial line exchange. PiCCO was replaced by EV-1000, femoral CVCs were replaced by jugular/subclavian CVCs and vice-versa. For PiCCO, jugular and femoral indicator injection derived GEDVI was comparable when the correct information about femoral catheter site was given (p = 0.251). By contrast, GEDVI derived from femoral indicator injection using the EV-1000 was obviously not corrected and was substantially higher than jugular GEDVI measured by the EV-1000 (846 ± 250 vs. 712 ± 227 ml/m2; p = 0.001). Furthermore, measurements of GEDVI were not comparable between PiCCO and EV-1000 even in case of jugular indicator injection (p = 0.003). This is most probably due to different indexations of the raw value GEDV. EV-1000 could not be recommended to measure GEDVI in case of a femoral CVC. Furthermore, different indexations used by EV-1000 and PiCCO should be considered even in case of a jugular CVC when comparing GEDVI derived from PiCCO and EV-1000.
Variation in microparasite free-living survival and indirect transmission can modulate the intensity of emerging outbreaks
Authors: Ogbunugafor C. Brandon , Miller-Dickson Miles D. , Meszaros Victor A. , Gomez Lourdes M. , Murillo Anarina L. , Scarpino Samuel V. 
Published: November 2020

AbstractVariation in free-living microparasite survival can have a meaningful impact on the ecological dynamics of established and emerging infectious diseases. Nevertheless, resolving the importance of indirect and environmental transmission in the ecology of epidemics remains a persistent challenge. It requires accurately measuring the free-living survival of pathogens across reservoirs of various kinds and quantifying the extent to which interaction between hosts and reservoirs generates new infections. These questions are especially salient for emerging pathogens, where sparse and noisy data can obfuscate the relative contribution of different infection routes. In this study, we develop a mechanistic, mathematical model that permits both direct (host-to-host) and indirect (environmental) transmission and then fit this model to empirical data from 17 countries affected by an emerging virus (SARS-CoV-2). From an ecological perspective, our model highlights the potential for environmental transmission to drive complex, nonlinear dynamics during infectious disease outbreaks. Summarizing, we propose that fitting alternative models with indirect transmission to real outbreak data from SARS-CoV-2 can be useful, as it highlights that indirect mechanisms may play an underappreciated role in the dynamics of infectious diseases, with implications for public health.
MCPIP1 reduces HBV-RNA by targeting its epsilon structure
Authors: Li Yingfang , Que Lusheng , Fukano Kento , Koura Miki , Kitamura Kouichi , Zheng Xin , Kato Takanobu , Aly Hussein Hassan , Watashi Koichi , Tsukuda Senko , Aizaki Hideki , Watanabe Noriyuki , Sato Yuko , Suzuki Tadaki , Suzuki Hiroshi I. , Hosomichi Kazuyoshi , Kurachi Makoto , Wakae Kousho , Muramatsu Masamichi 
Published: November 2020

AbstractHepatitis B virus (HBV) is the major causative factor of chronic viral hepatitis, liver cirrhosis, and hepatocellular carcinoma. We previously demonstrated that a proinflammatory cytokine IL-1β reduced the level of HBV RNA. However, the mechanism underlying IL-1β-mediated viral RNA reduction remains incompletely understood. In this study, we report that immune regulator Monocyte chemotactic protein-1-induced protein 1 (MCPIP1) can reduce HBV RNA in hepatocytes. MCPIP1 expression level was higher in the liver tissue of HBV-infected patients and mice. Overexpression of MCPIP1 decreased HBV RNA, whereas ablating MCPIP1 in vitro enhanced HBV production. The domains responsible for RNase activity or oligomerization, were required for MCPIP1-mediated viral RNA reduction. The epsilon structure of HBV RNA was important for its antiviral activity and cleaved by MCPIP1 in the cell-free system. Lastly, knocking out MCPIP1 attenuated the anti-HBV effect of IL-1β, suggesting that MCPIP1 is required for IL-1β-mediated HBV RNA reduction. Overall, these results suggest that MCPIP1 may be involved in the antiviral effect downstream of IL-1β.
Electronic structure with direct diagonalization on a D-wave quantum annealer
Authors: Teplukhin Alexander , Kendrick Brian K. , Tretiak Sergei , Dub Pavel A. 
Published: November 2020

AbstractQuantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing. Although universal quantum computers of practical scale may be years away, various approaches are currently being pursued to solve quantum chemistry problems on near-term gate-based quantum computers and quantum annealers by developing the appropriate algorithm and software base. This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer. The approach is based on the matrix formulation, efficiently uses qubit resources based on a power-of-two encoding scheme and is hardware-dominant relying on only one classically optimized parameter. We demonstrate the use of D-Wave hardware for obtaining ground and excited electronic states across a variety of small molecular systems. The approach can be adapted for use by a vast majority of electronic structure methods currently implemented in conventional quantum-chemical packages. The results of this work will encourage further development of software such as qbsolv which has promising applications in emerging quantum information processing hardware and has expectation to address large and complex optimization problems intractable for classical computers.
Dated phylogeny suggests early Neolithic origin of Sino-Tibetan languages
Authors: Zhang Hanzhi , Ji Ting , Pagel Mark , Mace Ruth 
Published: November 2020

AbstractAn accurate reconstruction of Sino-Tibetan language evolution would greatly advance our understanding of East Asian population history. Two recent phylogenetic studies attempted to do so but several of their conclusions are different from each other. Here we reconstruct the phylogeny of the Sino-Tibetan language family, using Bayesian computational methods applied to a larger and linguistically more diverse sample. Our results confirm previous work in finding that the ancestral Sino-Tibetans first split into Sinitic and Tibeto-Burman clades, and support the existence of key internal relationships. But we find that the initial divergence of this group occurred earlier than previously suggested, at approximately 8000 years before the present, coinciding with the onset of millet-based agriculture and significant environmental changes in the Yellow River region. Our findings illustrate that key aspects of phylogenetic history can be replicated in this complex language family, and calls for a more nuanced understanding of the first Sino-Tibetan speakers in relation to the “early farming dispersal” theory of language evolution.
A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany
Authors: Shen Julia 
Published: November 2020

AbstractEarly forecasting of COVID-19 virus spread is crucial to decision making on lockdown or closure of cities, states or countries. In this paper we design a recursive bifurcation model for analyzing COVID-19 virus spread in different countries. The bifurcation facilitates recursive processing of infected population through linear least-squares fitting. In addition, a nonlinear least-squares fitting procedure is utilized to predict the future values of infected populations. Numerical results on the data from two countries (South Korea and Germany) indicate the effectiveness of our approach, compared to a logistic growth model and a Richards model in the context of early forecast. The limitation of our approach and future research are also mentioned at the end of this paper.
GHG displacement factors of harvested wood products: the myth of substitution
Authors: Leturcq Philippe 
Published: November 2020

AbstractA common idea is that substituting wood for fossil fuels and energy intensive materials is a better strategy in mitigating climate change than storing more carbon in forests. This opinion remains highly questionable for at least two reasons. Firstly, the carbon footprints of wood-products are underestimated as far as the “biomass carbon neutrality” assumption is involved in their determination, as it is often the case. When taking into account the forest carbon dynamics consecutive to wood harvest, and the limited lifetime of products, these carbon footprints are time-dependent and their presumed values under the carbon neutrality assumption are achieved only in steady-state conditions. Secondly, even if carbon footprints are correctly assessed, the benefit of substitutions is overestimated when all or parts of the wood products are supposed to replace non-wood products whatever the market conditions. Indeed, substitutions are effective only if an increase in wood product consumption implies verifiably a global reduction in non-wood productions. When these flaws in the evaluation of wood substitution effects are avoided, one must conclude that increased harvesting and wood utilization may be counter-productive for climate change mitigation objectives, especially when wood is used as a fuel.
Rab6 regulates recycling and retrograde trafficking of MR1 molecules
Authors: Huber Megan E. , Kurapova Regina , Heisler Chelsea M. , Karamooz Elham , Tafesse Fikadu G. , Harriff Melanie J. 
Published: November 2020

AbstractMucosal-associated invariant T (MAIT) cells are an innate-like T cell subset important in the early response to bacterial and viral lung pathogens. MAIT cells recognize bacterial small molecule metabolites presented on the Class I-like molecule MR1. As with other Class I and Class II molecules, MR1 can likely sample ligands in the intracellular environment through multiple cellular pathways. Rab6, a small GTPase that regulates a number of endosomal trafficking pathways including retrograde transport to the trans-Golgi network (TGN), is involved in the presentation of ligands fromMycobacterium tuberculosis(Mtb) to MAIT cells. The Rab6-mediated trafficking pathway contains endosomal compartments that share features with the Mtb intracellular compartment. Using inducible expression of MR1, this study demonstrates that Rab6 regulates the recycling of MR1 molecules from the cell surface through endosomal trafficking compartments to the TGN. This Rab6-dependent pool of recycled MR1, which is available for reloading with ligands from bacterial pathogens like Mtb, may be important for early recognition of infected cells by MAIT cells in the lung.