bluuebunny/crossref_metadata_2025_split huggingface dataset:
Role of Heat Wave‐Induced Biogenic VOC Enhancements in Persistent Ozone Episodes Formation in Pearl River Delta
Authors: Wang Haolin , Wu Kai , Liu Yiming , Sheng Bosi , Lu Xiao , He Yuanping , Xie Jielan , Wang Haichao , Fan Shaojia 
Published: June 2021

AbstractRegional ozone (O3) pollution is influenced by a combination of anthropogenic sources and biogenic volatile organic compounds (BVOC) emitted from vegetation. Under the influence of warming climate and projected expansion of urban green space, O3 pollution may get worse, especially during heat waves (HWs). However, HW‐induced changes in BVOC and subsequent effects on regional O3 pollution have not been adequately assessed. In this study, we used the Weather Research and Forecasting‐Community Multi‐scale Air Quality models to investigate the formation of a typical O3 episode and quantify the O3 response to BVOC in the Pearl River Delta during a HW in 2017. The results showed that the rate of increase of O3 during the HW was 27.1 µg m−3 °C−1, reflecting the rapid O3 formation under high temperature. Compared with the non‐HW (NHW), gas‐phase chemistry and vertical transport were dominant contributors to O3 formation. Sensitivity experiments indicate that the contribution of BVOC to ground‐level O3 formation in Pearl River Delta was up to 42.1 μg m−3 because BVOC emissions in HW were 430 mol d−1 higher than the NHW. Under northerly winds and strong sea‐land breezes, BVOC and oxidation products from rural areas were transported to downwind VOC‐limited regimes and result in severe O3 pollution owing to intense photochemical reactions and accumulated O3 precursors. These findings point to the essential role of BVOC enhancements induced by HWs to O3 formation and suggest the consideration of BVOC emission potential of planted trees in urban greening strategies for avoiding the offset effects from BVOC.
Roughness Calibration to Improve Flow Predictions in Coarse‐Bed Streams
Authors: Ferguson Robert I. 
Published: June 2021

AbstractLogarithmic and variable‐power equations that use the bed D84 grain size as a roughness metric reproduce the general trend of flow resistance in streams with coarse beds, but they are unreliable for predictions in individual reaches. For site‐specific application of these equations, I propose that an effective roughness height can be calibrated by making a single flow measurement. I test this idea using published velocity‐depth data for eight coarse‐bed reaches of varied character. In 52 trials (8 reaches × 2 equations × 3 or 4 alternative calibration measurements), single‐measurement calibration reduced the root‐mean‐square error in predicting velocity at all depths by up to 79% (median 66%) compared to using D84. This approach may be useful when prescribing environmental flows, estimating bankfull discharge, or predicting bedload transport in coarse‐bed channels in which Manning's n is likely to vary considerably with discharge.
IRE1α RIDD activity induced under ER stress drives neuronal death by the degradation of 14-3-3 θ mRNA in cortical neurons during glucose deprivation
Authors: Gómora-García Juan Carlos , Gerónimo-Olvera Cristian , Pérez-Martínez Xochitl , Massieu Lourdes 
Published: June 2021

AbstractAltered protein homeostasis is associated with neurodegenerative diseases and acute brain injury induced under energy depletion conditions such as ischemia. The accumulation of damaged or unfolded proteins triggers the unfolded protein response (UPR), which can act as a homeostatic response or lead to cell death. However, the factors involved in turning and adaptive response into a cell death mechanism are still not well understood. Several mechanisms leading to brain injury induced by severe hypoglycemia have been described but the contribution of the UPR has been poorly studied. Cell responses triggered during both the hypoglycemia and the glucose reinfusion periods can contribute to neuronal death. Therefore, we have investigated the activation dynamics of the PERK and the IRE1α branches of the UPR and their contribution to neuronal death in a model of glucose deprivation (GD) and glucose reintroduction (GR) in cortical neurons. Results show a rapid activation of the PERK/p-eIF2α/ATF4 pathway leading to protein synthesis inhibition during GD, which contributes to neuronal adaptation, however, sustained blockade of protein synthesis during GR promotes neuronal death. On the other hand, IRE1α activation occurs early during GD due to its interaction with BAK/BAX, while ASK1 is recruited to IRE1α activation complex during GR promoting the nuclear translocation of JNK and the upregulation of Chop. Most importantly, results show that IRE1α RNase activity towards its splicing target Xbp1 mRNA occurs late after GR, precluding a homeostatic role. Instead, IRE1α activity during GR drives neuronal death by positively regulating ASK1/JNK activity through the degradation of 14-3-3 θ mRNA, a negative regulator of ASK and an adaptor protein highly expressed in brain, implicated in neuroprotection. Collectively, results describe a novel regulatory mechanism of cell death in neurons, triggered by the downregulation of 14-3-3 θ mRNA induced by the IRE1α branch of the UPR.
Mechanical behavior predictions of additively manufactured microstructures using functional Gaussian process surrogates
Authors: Saunders Robert , Butler Celia , Michopoulos John , Lagoudas Dimitris , Elwany Alaa , Bagchi Amit 
Published: June 2021

AbstractRelational linkages connecting process, structure, and properties are some of the most sought after goals in additive manufacturing (AM). This is desired especially because the microstructural grain morphologies of AM components can be vastly different than their conventionally manufactured counterparts. Furthermore, data collection at the microscale is costly. Consequently, this work describes and demonstrates a methodology to link microstructure morphology to mechanical properties using functional Gaussian process surrogate models in a directed graphical network capable of achieving near real-time property predictions with single digit error magnitudes when predicting full stress–strain histories of a given microstructure. This methodology is presented and demonstrated using computationally generated microstructures and results from crystal plasticity simulations on those microstructures. The surrogate model uses grain-level microstructural descriptors rather than whole microstructure descriptors so that properties of new, arbitrary microstructures can be predicted. The developed network has the potential to scale to predict mechanical properties of grain structures that would be infeasible to simulate using finite element methods.
Accelerated discovery of a large family of quaternary chalcogenides with very low lattice thermal conductivity
Authors: Pal Koushik , Xia Yi , Shen Jiahong , He Jiangang , Luo Yubo , Kanatzidis Mercouri G. , Wolverton Chris 
Published: June 2021

AbstractThe development of efficient thermal energy management devices such as thermoelectrics and barrier coatings often relies on compounds having low lattice thermal conductivity (κl). Here, we present the computational discovery of a large family of 628 thermodynamically stable quaternary chalcogenides, AMM′Q3 (A = alkali/alkaline earth/post-transition metals; M/M′ = transition metals, lanthanides; Q = chalcogens) using high-throughput density functional theory (DFT) calculations. We validate the presence of low κl in these materials by calculating κl of several predicted stable compounds using the Peierls–Boltzmann transport equation. Our analysis reveals that the low κl originates from the presence of either a strong lattice anharmonicity that enhances the phonon-scatterings or rattler cations that lead to multiple scattering channels in their crystal structures. Our thermoelectric calculations indicate that some of the predicted semiconductors may possess high energy conversion efficiency with their figure-of-merits exceeding 1 near 600 K. Our predictions suggest experimental research opportunities in the synthesis and characterization of these stable, low κl compounds.
Materials property prediction for limited datasets enabled by feature selection and joint learning with MODNet
Authors: De Breuck Pierre-Paul , Hautier Geoffroy , Rignanese Gian-Marco 
Published: June 2021

AbstractIn order to make accurate predictions of material properties, current machine-learning approaches generally require large amounts of data, which are often not available in practice. In this work, MODNet, an all-round framework, is presented which relies on a feedforward neural network, the selection of physically meaningful features, and when applicable, joint-learning. Next to being faster in terms of training time, this approach is shown to outperform current graph-network models on small datasets. In particular, the vibrational entropy at 305 K of crystals is predicted with a mean absolute test error of 0.009 meV/K/atom (four times lower than previous studies). Furthermore, joint learning reduces the test error compared to single-target learning and enables the prediction of multiple properties at once, such as temperature functions. Finally, the selection algorithm highlights the most important features and thus helps to understand the underlying physics.
Benchmarking graph neural networks for materials chemistry
Authors: Fung Victor , Zhang Jiaxin , Juarez Eric , Sumpter Bobby G. 
Published: June 2021

AbstractGraph neural networks (GNNs) have received intense interest as a rapidly expanding class of machine learning models remarkably well-suited for materials applications. To date, a number of successful GNNs have been proposed and demonstrated for systems ranging from crystal stability to electronic property prediction and to surface chemistry and heterogeneous catalysis. However, a consistent benchmark of these models remains lacking, hindering the development and consistent evaluation of new models in the materials field. Here, we present a workflow and testing platform, MatDeepLearn, for quickly and reproducibly assessing and comparing GNNs and other machine learning models. We use this platform to optimize and evaluate a selection of top performing GNNs on several representative datasets in computational materials chemistry. From our investigations we note the importance of hyperparameter selection and find roughly similar performances for the top models once optimized. We identify several strengths in GNNs over conventional models in cases with compositionally diverse datasets and in its overall flexibility with respect to inputs, due to learned rather than defined representations. Meanwhile several weaknesses of GNNs are also observed including high data requirements, and suggestions for further improvement for applications in materials chemistry are discussed.
Quantum simulations with multiphoton Fock states
Authors: Sturges T. J. , McDermott T. , Buraczewski A. , Clements W. R. , Renema J. J. , Nam S. W. , Gerrits T. , Lita A. , Kolthammer W. S. , Eckstein A. , Walmsley I. A. , Stobińska M. 
Published: June 2021

AbstractQuantum simulations are becoming an essential tool for studying complex phenomena, e.g. quantum topology, quantum information transfer and relativistic wave equations, beyond the limitations of analytical computations and experimental observations. To date, the primary resources used in proof-of-principle experiments are collections of qubits, coherent states or multiple single-particle Fock states. Here we show a quantum simulation performed using genuine higher-order Fock states, with two or more indistinguishable particles occupying the same bosonic mode. This was implemented by interfering pairs of Fock states with up to five photons on an interferometer, and measuring the output states with photon-number-resolving detectors. Already this resource-efficient demonstration reveals topological matter, simulates non-linear systems and elucidates a perfect quantum transfer mechanism which can be used to transport Majorana fermions.
Imaging the formation and surface phase separation of the CE phase
Authors: Zhou Haibiao , Feng Qiyuan , Hou Yubin , Nakamura Masao , Tokura Yoshinori , Kawasaki Masashi , Sheng Zhigao , Lu Qingyou 
Published: June 2021

AbstractThe CE phase is an extraordinary phase exhibiting the simultaneous spin, charge, and orbital ordering due to strong electron correlation. It is an ideal platform to investigate the role of the multiple orderings in the phase transitions and discover emergent properties. Here, we use a cryogenic high-field magnetic force microscope to image the phase transitions and properties of the CE phase in a Pr0.5Ca0.5MnO3 thin film. In a high magnetic field, we observed a clear suppression of magnetic susceptibility at the charge-ordering insulator transition temperature (TCOI), whereas, at the Néel temperature (TN), no significant change is observed. This observation favors the scenario of strong antiferromagnetic correlation developed below TCOI but raises questions about the Zener polaron paramagnetic phase picture. Besides, we discoverd a phase-separated surface state in the CE phase regime. Ferromagnetic phase domains residing at the surface already exist in zero magnetic field and show ultra-high magnetic anisotropy. Our results provide microscopic insights into the unconventional spin- and charge-ordering transitions and revealed essential attributes of the CE phase, highlighting unusual behaviors when multiple electronic orderings are involved.
Characterization and RNA-seq transcriptomic analysis of a Scenedesmus obliqnus mutant with enhanced photosynthesis efficiency and lipid productivity
Authors: Xi Yimei , Yin Liang , Chi Zhan you , Luo Guanghong 
Published: June 2021

AbstractMicroalgae have received significant attention as potential next-generation microbiologic cell factories for biofuels. However, the production of microalgal biofuels is not yet sufficiently cost-effective for commercial applications. To screen higher lipid-producing strains, heavy carbon ion beams are applied to induce a genetic mutant. An RNA-seq technology is used to identify the pathways and genes of importance related to photosynthesis and biofuel production. The deep elucidation of photosynthesis and the fatty acid metabolism pathway involved in lipid yield is valuable information for further optimization studies. This study provided the photosynthetic efficiency and transcriptome profiling of a unicellular microalgae, Scenedesmus obliqnus mutant SO120G, with enhanced lipid production induced by heavy carbon ion beams. The lipid yield (52.5 mg L−1) of SO120G mutant were enhanced 2.4 fold compared with that of the wild strain under the nitrogen deficient condition. In addition, the biomass and growth rate were 57% and 25% higher, respectively, in SO120G than in the wild type, likely owing to an improved maximum quantum efficiency (Fv/Fm) of photosynthesis. As for the major pigment compositions, the content of chlorophyll a and carotenoids was higher in SO120G than in the wild type. The transcriptome data confirmed that a total of 2077 genes with a change of at least twofold were recognized as differential expression genes (DEGs), of which 1060 genes were up-regulated and 1017 genes were down-regulated. Most of the DEGs involved in lipid biosynthesis were up-regulated with the mutant SO120G. The expression of the gene involved in the fatty acid biosynthesis and photosynthesis of SO120G was upregulated, while that related to starch metabolism decreased compared with that of the wild strain. This work demonstrated that heavy-ion irradiation is an promising strategy for quality improvement. In addition, the mutant SO120G was shown to be a potential algal strain for enhanced lipid production. Transcriptome sequencing and annotation of the mutant suggested the possible genes responsible for lipid biosynthesis and photosynthesis, and identified the putative target genes for future genetic manipulation and biotechnological applications.
Tumor necroptosis is correlated with a favorable immune cell signature and programmed death-ligand 1 expression in cholangiocarcinoma
Authors: Lomphithak Thanpisit , Akara-amornthum Perawatt , Murakami Keigo , Hashimoto Masatoshi , Usubuchi Hajime , Iwabuchi Erina , Unno Michiaki , Cai Zhenyu , Sasano Hironobu , Jitkaew Siriporn 
Published: June 2021

AbstractNecroptosis, a regulated form of necrosis, has emerged as a novel therapeutic strategy that could enhance cancer immunotherapy. However, its role in tumorigenesis is still debated because recent studies have reported both anti- and pro-tumoral effects. Here, we aimed to systematically evaluate the associations between tumor necroptosis (mixed lineage kinase domain-like protein, MLKL; phosphorylated MLKL, pMLKL; and receptor-interacting protein kinase 1–receptor-interacting protein kinase 3, RIPK1–RIPK3 interaction) and tumor-infiltrating immune cells (CD8+ and FOXp3+ T cells and CD163+ M2 macrophages) and tumor PD-L1 by immunohistochemistry in 88 cholangiocarcinoma (CCA) patients who had undergone surgical resection. Their associations with clinicopathological characteristics, survival data, and prognosis were evaluated. MLKL was found to be an unfavorable prognostic factor (p-value = 0.023, HR = 2.070) and was inversely correlated with a clinically favorable immune cell signature (high CD8+/high FOXp3+/low CD163+). Both pMLKL and RIPK1–RIPK3 interaction were detected in CCA primary tissues. In contrast to MLKL, pMLKL status was significantly positively correlated with a favorable immune signature (high CD8+/high FOXp3+/low CD163+) and PD-L1 expression. Patients with high pMLKL-positive staining were significantly associated with an increased abundance of CD8+ T cell intratumoral infiltration (p-value = 0.006). Patients with high pMLKL and PD-L1 expressions had a longer overall survival (OS). The results from in vitro experiments showed that necroptosis activation in an RMCCA-1 human CCA cell line selectively promoted proinflammatory cytokine and chemokine expression. Jurkat T cells stimulated with necroptotic RMCCA-1-derived conditioned medium promoted PD-L1 expression in RMCCA-1. Our findings demonstrated the differential associations of necroptosis activation (pMLKL) and MLKL with a clinically favorable immune signature and survival rates and highlighted a novel therapeutic possibility for combining a necroptosis-based therapeutic approach with immune checkpoint inhibitors for more efficient treatment of CCA patients.
Effects of colistin and tigecycline on multidrug-resistant Acinetobacter baumannii biofilms: advantages and disadvantages of their combination
Authors: Sato Yoshinori , Ubagai Tsuneyuki , Tansho-Nagakawa Shigeru , Yoshino Yusuke , Ono Yasuo 
Published: June 2021

AbstractWe investigated the antimicrobial effects of colistin (CST) and tigecycline (TGC), either alone or in combination, on biofilm-dispersed and biofilm-embedded multidrug-resistant Acinetobacter baumannii (MDRAB) strains R1 and R2. The bacterial growth of biofilm-dispersed MDRAB was inhibited by CST or TGC. However, the inhibitory effects were attenuated by a combination of CST and low concentrations of TGC. The bactericidal effects of CST, but not TGC, were observed on biofilm-dispersed MDRAB. Notably, the bactericidal effects increased with a combination of CST and high concentrations of TGC, whereas they were attenuated with the combination of CST and low concentrations of TGC. Although biofilm formation by MDRAB decreased with increasing concentrations of CST or TGC, there was no complete disruption of the biofilms. Additionally, the biofilms increased with a combination of 1–2 μg/mL CST and TGC at 2 μg/mL and 2–4 μg/mL for strains R1 and R2, respectively. Biofilm-embedded MDRAB was eradicated with CST, but not TGC. Notably, the eradication effects increased with a combination of CST and high concentrations of TGC, whereas attenuation happened with the combination of CST and low concentrations of TGC. These results provide information on the combined effects of CST and TGC in the treatment of biofilm-associated MDRAB infection.
Insulin micro-secretion in Type 1 diabetes and related microRNA profiles
Authors: Januszewski Andrzej S. , Cho Yoon Hi , Joglekar Mugdha V. , Farr Ryan J. , Scott Emma S. , Wong Wilson K. M. , Carroll Luke M. , Loh Yik W. , Benitez-Aguirre Paul Z. , Keech Anthony C. , O’Neal David N. , Craig Maria E. , Hardikar Anandwardhan A. , Donaghue Kim C. , Jenkins Alicia J. 
Published: June 2021

AbstractThe aim of this cross-sectional study was to compare plasma C-peptide presence and levels in people without diabetes (CON) and with Type 1 diabetes and relate C-peptide status to clinical factors. In a subset we evaluated 50 microRNAs (miRs) previously implicated in beta-cell death and associations with clinical status and C-peptide levels. Diabetes age of onset was stratified as adult (≥ 18 y.o) or childhood (< 18 y.o.), and diabetes duration was stratified as ≤ 10 years, 10–20 years and > 20 years. Plasma C-peptide was measured by ultrasensitive ELISA. Plasma miRs were quantified using TaqMan probe-primer mix on an OpenArray platform. C-peptide was detectable in 55.3% of (n = 349) people with diabetes, including 64.1% of adults and 34.0% of youth with diabetes, p < 0.0001 and in all (n = 253) participants without diabetes (CON). C-peptide levels, when detectable, were lower in the individuals with diabetes than in the CON group [median lower quartile (LQ)–upper quartile (UQ)] 5.0 (2.6–28.7) versus 650.9 (401.2–732.4) pmol/L respectively, p < 0.0001 and lower in childhood versus adult-onset diabetes [median (LQ–UQ) 4.2 (2.6–12.2) pmol/L vs. 8.0 (2.3–80.5) pmol/L, p = 0.02, respectively]. In the childhood-onset group more people with longer diabetes duration (> 20 years) had detectable C-peptide (60%) than in those with shorter diabetes duration (39%, p for trend < 0.05).
Nine miRs significantly correlated with detectable C-peptide levels in people with diabetes and 16 miRs correlated with C-peptide levels in CON. Our cross-sectional study results are supportive of (a) greater beta-cell function loss in younger onset Type 1 diabetes; (b) persistent insulin secretion in adult-onset diabetes and possibly regenerative secretion in childhood-onset long diabetes duration; and (c) relationships of C-peptide levels with circulating miRs. Confirmatory clinical studies and related basic science studies are merited.