bluuebunny/crossref_metadata_2025_split huggingface dataset:
Green Preparation of CNTs/Graphite Supported NiFe Carbonate Hydroxides for Oxygen Evolution Reaction
Authors: Liu Yang , Wang Yangchen , Wen He , Han Yuqi , Deng Shuwei 
Published: June 2022

AbstractDeveloping durable and highly active non‐noble electrocatalysts for oxygen evolution reaction (OER) is highly desirable for water splitting. Herein, we report a NiFe carbonate hydroxides embedded in a carbon nanotubes and graphite composite material (NiFe CHs‐CNT/G) by a facile and green precipitation method. The NiFe CHs are in‐situ grown on CNT/G using NH3⋅H2O as precipitant and CO2 in air as the source of CO32− under room temperature and pressure. The introduction of CNT/G not only improves the conductivity of material, but also enhances the combination of CNT/G and NiFe CHs nanosheets, thereby accelerating the transfer of electrons and reactants. Meanwhile, the catalyst with a special sandwich morphology provides larger active area to expose more active sites. Moreover, the effective interaction within the Ni and Fe in NiFe CHs‐CNT/G is benefiting for improving OER performance. All these lead to the optimized NiFe CHs‐CNT/G catalyst delivers an outstanding OER performance with a low overpotential of 300 mV at 10 mA cm−2 and a small Tafel slope of 60.13 mV dec−1.
A Happy Get‐Together – Probing Electrochemical Interfaces by Non‐Linear Vibrational Spectroscopy
Authors: De Ratnadip , Dietzek‐Ivanšić Benjamin 
Published: June 2022

AbstractElectrochemical interfaces are key structures in energy storage and catalysis. Hence, a molecular understanding of the active sites at these interfaces, their solvation, the structure of adsorbates, and the formation of solid‐electrolyte interfaces are crucial for an in‐depth mechanistic understanding of their function. Vibrational sum‐frequency generation (VSFG) spectroscopy has emerged as an operando spectroscopic technique to monitor complex electrochemical interfaces due to its intrinsic interface sensitivity and chemical specificity. Thus, this review discusses the happy get‐together between VSFG spectroscopy and electrochemical interfaces. Methodological approaches for answering core issues associated with the behavior of adsorbates on electrodes, the structure of solvent adlayers, the transient formation of reaction intermediates, and the emergence of solid electrolyte interphase in battery research are assessed to provide a critical inventory of highly promising avenues to bring optical spectroscopy to use in modern material research in energy conversion and storage.
Chemoselective Acylation of Nucleosides
Authors: Tang Yu , Grange Rebecca L. , Engl Oliver D. , Miller Scott J. 
Published: June 2022

AbstractAcylated nucleoside analogues play an important role in medicinal chemistry and are extremely useful precursors to various other nucleoside analogues. However, chemoselective acylation of nucleosides usually requires several protection and deprotection steps due to the competing nucleophilicity of hydroxy and amino groups. In contrast, direct protecting‐group‐free chemoselective acylation of nucleosides is a preferred strategy due to lower cost and fewer overall synthetic steps. Herein, a simple and efficient chemoselective acylation of nucleosides and nucleotides under mild reaction conditions, giving either O‐ or N‐acylated products respectively with excellent chemoselectivity is reported.
A Reference‐Scaled Average Bioequivalence Study of Azithromycin Tablets Manufactured in China and the United States: An Open‐Label, Randomized, Single‐Dose, 3‐Way Crossover Study in Healthy Chinese Subjects Under Fasted and Fed Conditions
Authors: Ge Beikang , Li Cuiyun , Wei Hua , Ding Yanhua , Wu Min , Liu Yuwang , Zhang Kaiting , Peng Ao 
Published: June 2022

AbstractAzithromycin (Zithromax) is an azalide antibiotic that binds to the 50S ribosomal subunit of the susceptible organism and thereby interferes with its protein synthesis. An open‐label, randomized, single‐dose, 3‐way crossover bioequivalence study was conducted to compare the rate and extent of absorption of the azithromycin 250‐mg tablet manufactured at Pfizer Dalian (China) and that at Pfizer Barceloneta (United States) under fasted and fed conditions in healthy Chinese subjects. This study aimed to support a generic consistency evaluation program, initiated by the National Medical Products Administration, for evaluating the quality and efficacy of the products manufactured in China. In the study, the within‐subject standard deviation for area under the serum concentration–time profile from time 0 to 72 hours after dosing in the fasted condition was <0.294, and the 90%CI for the ratio was within 80% to 125%; the within‐subject SDs for serum peak concentration in the fasted condition, area under the serum concentration–time profile from time 0 to 72 hours after dosing in the fed condition, and serum peak concentration in the fed condition, were all >0.294, with the upper confidence bounds being <0.00, and the point estimates of the ratios being within 80% to 125%. The results support the bioequivalence between azithromycin tablets manufactured in China and the United States in fasted and fed conditions, with both tablets showing an acceptable safety/tolerability profile in the studied population.
Vulnerability cloud: A novel approach to assess the vulnerability of critical infrastructure systems
Authors: Meng Lingpeng , Yao Xiaobo , Chen Qian , Han Chuanfeng 
Published: June 2022

SummaryCritical infrastructures provide citizens with lifeline functions such as water, electricity and energy and so forth. These interdependent infrastructure systems require reliable models for vulnerability measurement and topological controllability against usual disruptions and unusual hazards. This article proposes a novel approach, named vulnerability cloud, to describe vulnerability distribution and assess the vulnerability of critical infrastructure systems. A vulnerability distribution network is developed for simulation of negative impact on each node, with which the results are represented in vulnerability cloud by three metrics of vulnerability. The vulnerability cloud of single‐service and multiservice infrastructure system are proposed, respectively. This approach is applied to a case study of “electric‐gas” interdependent critical infrastructure system. Results show that a node's vulnerability and serviceability is closely related to the node's degree, especially the out‐degree, while overall system's vulnerability is greatly affected by descent rate of coverage of each infrastructural service node. This approach, at the same time, generates probabilistic simulation diagrams to show continuous vulnerability distribution in areas covered by the specified critical infrastructure systems.
Application analysis of digital fund prediction model based on neural network
Authors: Liu Yu , Xiao Jing 
Published: June 2022

SummaryWith the development of the economy, digital funds have developed rapidly, and traditional big data processing technologies have been unable to effectively solve the update of digital funds information. This research uses neural network to study the digital fund forecasting model based on big data technology and deep learning algorithm. First, on the basis of the feedforward neural network model, the network structure and network parameters are optimized to effectively improve the algorithm's ability to learn the characteristics of digital capital information. Through the first‐order approximation, the number of iterations in the model parameter update is effectively reduced, and the computational efficiency of the algorithm is improved. By improving the model network structure, increasing the number of neurons in the hidden layer, and improving the dynamic change learning ability of the algorithm, the dynamic characteristics of the incremental file information can be effectively obtained. Through the experimental simulation calculation, it can be seen that compared with the traditional algorithm, the algorithm proposed in this study has certain advantages in terms of convergence speed, convergence ability and solution error, and the algorithm has good stability and strong inheritance, and is suitable for digital capital forecasting aspects of research.
Visible‐Light‐Induced Oxidative α‐keto‐Dichlorination of Arylalkynes by CuCl2 at Room Temperature
Authors: Pramod Charpe Vaibhav , Gupta Mahima , Chu Hwang Kuo 
Published: June 2022

AbstractA visible light‐induced oxidative α‐keto‐dichlorination of terminal and internal aryl alkynes was developed to form dichloroacetophenones (DCAPs) and dichlorophenyl‐acetophenones (DCPAPs), respectively, by using CuCl2 as a photoredox catalyst in the presence of air at room temperature (without using any exogenous photocatalyst). Here, photoexcited CuCl2 underwent ligand‐to‐metal charge transfer to generate a Cl radical, which readily added to the alkynes to form DCAPs or DCPAPs in the presence of O2. This α‐keto‐dichlorination reaction is a green and mild protocol as it produced water as the only by‐product. Moreover, the evaluation of green chemistry metrics indicated that the E‐factor (mass of wastes/mass of products) of the current α‐keto‐chlorination method is around 10.1 times lower than that of a literature‐reported photochemical method. The Eco Scale value (score 55, which on a scale of 0–100 indicates an acceptable synthesis) signifies that this process is simple, highly efficient, eco‐friendly, and cost‐effective.
Prognostic implication and immunological value of contactin 1 expression in pan‐cancer
Authors: Zhang Lingyun , Zhang Jiayu , Liu Tianshu , Zhang Jinguo , Cui Yuehong 
Published: June 2022

AbstractObjectiveContactin 1 (CNTN1) is associated with developing the cancer progression and nervous system. Although increasing evidence suggests a crucial role for CNTN1 in many research areas, it is still no detailed systematic analysis of CNTN1 and the human pan‐cancer spectrum. Here, our purpose is to make a thorough investigation of CNTN1 properties across pan‐cancer types.MethodsCNTN1 mRNA expression and genomic alteration were dissected by GTEX, TCGA, and the cBioPortal database. CNTN1 expression in human organic tissues was performed via human multiple organ tissue microarrays. Furthermore, the correlations between CNTN1 and survival periods, clinical characteristics, and immune‐associated cells infiltration were performed through the TCGA database. Additionally, GSEA was carried out to delve into the biological actions of CNTN1 in pan‐cancer.ResultsWe discovered that CNTN1 expression was abnormal in pan‐cancer expression analysis and could predict the survival period of cancers. The primary alteration type of CNTN1 was a genomic mutation. In addition, the aberrant CNTN1 expression was found to be related to MSI, MMR, and TMB in pan‐cancer. CNTN1 was significantly related to the infiltration of immune‐associated cells in certain kinds of cancer through the ESTIMATE algorithm and TIMER database. In particular, the cancer‐associated fibroblasts indicate a negative regulation of the tumor immune microenvironment. Next, we found the most frequent signaling pathway of CNTN1 in human pan‐cancer was neuroactive ligand–receptor interaction from GSEA analysis.ConclusionIn conclusion, the investigation highlights the predictive function of CNTN1 in human pan‐cancer and affords novel insights for drawing a landscape of CNTN1 in tumorigenesis and immune regulation.
Preclinical platforms to study therapeutic efficacy of human γδ T cells
Authors: Ou Lingling , Wang Huaishan , Huang Hui , Zhou Zhiyan , Lin Qiang , Guo Yeye , Mitchell Tara , Huang Alexander C. , Karakousis Giorgos , Schuchter Lynn , Amaravadi Ravi , Guo Wei , Salvino Joseph , Herlyn Meenhard , Xu Xiaowei 
Published: June 2022

AbstractBackgroundGamma delta (γδ) T lymphocytes are promising candidate for adoptive T cell therapy, however, their treatment efficacy is not satisfactory. Vδ2 T cells are unique to primates and few suitable models are available to assay their anti‐tumour function.MethodsWe tested human γδ T cell activation, tumour infiltration, and tumour‐killing in four three‐dimensional (3D) models, including unicellular, bicellular and multicellular melanoma spheroids, and patient‐derived melanoma organoids. We studied the effects of checkpoint inhibitors on γδ T cells and performed a small molecule screen using these platforms.Resultsγδ T cells rapidly responded to melanoma cells and infiltrated melanoma spheroids better than αβ T cells in PBMCs. Cancer‐associated fibroblasts (CAFs) in bicellular spheroids, stroma cells in multicellular melanoma spheroids and inhibitory immune cells in organoids significantly inhibited immune cell infiltrates including γδ T cells and lessened their cytotoxicity to tumour cells. Tumour‐infiltrating γδ T cells showed exhausted immunophenotypes with high checkpoints expression (CTLA‐4, PD‐1 and PD‐L1). Immune checkpoint inhibitors increased γδ T cell infiltration of 3D models and killing of melanoma cells in all four 3D models. Our small molecule screen assay and subsequent mechanistic studies demonstrated that epigenetic modifiers enhanced the chemotaxis and cytotoxicity of γδ T cells through upregulating MICA/B, inhibiting HDAC6/7 pathway and downregulating the levels of PD‐L1 and PD‐L2 in CAFs and tumour cells. These compounds increased CXCR4 and CD107a expression, IFN‐γ production and decreased PD‐1 expression of γδ T cells.ConclusionsTumour‐infiltrating γδ T cells show exhausted immunophenotypes and limited anti‐tumour capacity in melanoma 3D models. Checkpoint inhibitors and epigenetic modifiers enhance anti‐tumour functions of γδ T cells. These four 3D models provided valuable preclinical platforms to test γδ T cell functions for immunotherapy.
Native generalist natural enemies and an introduced specialist parasitoid together control an invasive forest insect
Authors: Broadley Hannah J. , Boettner George H. , Schneider Brenda , Elkinton Joseph S. 
Published: June 2022

AbstractSpecialized natural enemies have long been used to implement the biological control of invasive insects. Although research tracking populations following biological control introductions has traditionally focused on the impact of the introduced agent, recent studies and reviews have reflected an appreciation of the complex interactions of the introduced specialist agents with native generalist natural enemies. These interactions can be neutral, antagonistic, or complementary. Here we studied the invasive defoliator winter moth (Operophtera brumata) in the Northeast USA to investigate the role of native, generalist pupal predators along with the introduced, host‐specific parasitoid Cyzenis albicans. Prior research in Canada has shown that predation of winter moth pupae from native generalists increased after C. albicans was established as a biological control agent. To explain this phenomenon, the following hypotheses were suggested: (H1) parasitoids suppress the winter moth population to a density that can be maintained by generalist predators, (H2) unparasitized pupae are preferred by predators and therefore experience higher mortality rates, or (H3) C. albicans sustains higher predator populations throughout the year more effectively than winter moth alone. We tested these hypotheses by deploying winter moth pupae over 6 years spanning 2005 to 2017 and by modeling pupal predation rates as a function of winter moth density and C. albicans establishment. We also compared predation rates of unparasitized and parasitized pupae and considered additional mortality by a native pupal parasitoid. We found support for the first hypothesis; we detected both temporal and spatial density dependence, but only in the latter years of the study when winter moth densities were low. We found no evidence for the latter two hypotheses. Our findings suggest that pupal predators have a regulatory effect on winter moth populations only after populations have been reduced, presumably by the introduction of the host‐specific parasitoid C. albicans.
HOXA cluster antisense RNA 2 elevates KIAA1522 expression through microRNA‐520d‐3p and insulin like growth factor 2 mRNA binding protein 3 to promote the growth of vascular smooth muscle cells in thoracic aortic aneurysm
Authors: Ou Minghui , Chu Yaonan , Zhang Qian , Zhao Huidong , Song Qiang 
Published: June 2022

AbstractAimsRecently, long non‐coding RNAs (lncRNAs) have been revealed to mediate smooth muscle dysfunction in thoracic aortic aneurysm (TAA). LncRNA HOXA‐AS2 has been proposed to engage in the regulation of diverse diseases. However, its function in TAA remains unknown. This study aimed to reveal the role and mechanism of HOXA‐AS2 in VSMCs which were implicated in TAA formation.Methods and resultsRT‐qPCR or western blot was performed to detect RNA or protein expression levels. The role of HOXA‐AS2 in VSMCs was explored by functional assays. The relationship among HOXA‐AS2/miR‐520d‐3p/KIAA1522/IGF2BP3 was analysed via mechanism assays. HOXA‐AS2 was detected to have significantly high expression in TAA tissues and function as an oncogene to promote proliferation of VSMCs, while inhibiting cell apoptosis (Figure 1, **P < 0.01). HOXA‐AS2 was unveiled to bind with miR‐520d‐3p (Figure 2, *P < 0.05, **P < 0.01) and further up‐regulate KIAA1522 to facilitate the growth of VSMCs (Figure 3–4, *P < 0.05, **P < 0.01). HOXA‐AS2 was also found to recruit IGF2BP3 to stabilize KIAA1522 mRNA (Figure 5, **P < 0.01). All data were displayed as mean ± standard deviation.ConclusionsHOXA‐AS2 up‐regulates KIAA1522 through targeting miR‐520d‐3p/IGF2BP3 to drive VSMC growth in TAA.
Organocatalytic Synthesis of Thiiranes from Alkenes
Authors: Tsoukaki Anna , Skolia Elpida , Triandafillidi Ierasia , Kokotos Christoforos G. 
Published: June 2022

AbstractThiiranes, the corresponding sulfur analogues of epoxides, are less studied and less encountered in literature. This might be due to the limited existing synthetic approaches for their synthesis. Herein, a mild, sustainable and efficient organocatalytic synthesis of thiiranes has been developed. Starting from olefins and utilizing the epoxidation protocol developed in the Kokotos’ group, which employs 2,2,2‐trifluoroacetophenone as the organocatalyst and H2O2 as the oxidant, followed by ring opening by thiourea, a variety of thiiranes were synthesized. Both aromatic and aliphatic moieties are well tolerated, leading to thiiranes in moderate to excellent yields.
Acute Toxicity Assay Based on Electrochemical Method for Detection of Antibiotic Residues in Water
Authors: Dong Jia , Chang Xin , Li Donghui , Liu Chang 
Published: June 2022

AbstractIn this work, the bacteria suspended in solution or immobilized in the biofilm were employed to study whether bacterial electrochemistry can reflect the impacts of the antibiotic residues in water on microorganisms. In the sensing system with immobilized bacteria, the tested antibiotics of 10∼40 mg/L showed an opportunity to inhibit respiration over a short time and the combined effect of these antibiotics exhibited a complex dose‐dependence. The resistance was induced for the immobilized bacteria in the repeated measurement over a long‐term period, which was fortunately solved by refreshing the biofilm via a nutrient supplementation. In the solution system, bacterial respirations were promoted by the tested antibiotics even at concentrations up to 160 mg/L, but β‐glucosidase activity was inhibited by only 0.05 mg/L antibiotic. Cu2+ and Zn2+ were further inducted in the suspended system, and the combination of metals and antibiotics showed an obvious antagonistic effect. Real water detection indicated that the bacterial electrochemical method was expected to warn the water qualities with a sudden change by an appropriate testing condition.
Addressing the different sources of excitation variability in seismic response distribution estimation using kriging metamodeling
Authors: Kyprioti Aikaterini P. , Taflanidis Alexandros A. 
Published: June 2022

AbstractThis paper investigates the impact of the different sources of excitation variability within the stochastic kriging framework recently developed by the authors for the estimation of the distribution of engineering demand parameters (EDPs) in applications that the seismic hazard is described through stochastic ground motion models. For a given seismic event, described by seismicity characteristics such as the moment magnitude and the distance to source, one can distinguish two type of uncertainties in the excitation description: (g.i) the stochastic sequence utilized within the excitation model; (g.ii) the predictive models relating the ground motion parameters, such as significant duration, arias intensity, or frequency properties of seismic waves, to the seismicity characteristics. The original formulation of the authors treats (g.i) as aleatoric uncertainty and (g.ii) as parametric uncertainty, including the latter in the model parameters for the risk characterization, representing the metamodel input. Implementation establishes the EDP distribution approximation by utilizing a database of EDP estimates for a set of different input parameters, considering replications of these estimates for different stochastic sequences for some small part of this database. The database with replications is first leveraged to approximate the heteroscedastic behavior with respect to the aleatoric uncertainty, and the entire database is subsequently used, coupled with the previous heteroscedasticity approximation, to establish the stochastic kriging predictions for the EDP distribution. For excitation models with a large number of ground motion parameters, the original formulation leads to a significant increase of the input dimensionality for the metamodel development, requiring a larger database for facilitating accurate EDP approximations. Here, an alternative formulation is investigated, considering some (or perhaps even all) of the ground motion parameters to be part of the aleatoric uncertainty of the excitation description. It is shown that careful selection is needed for the exact ground motion parameters that can be treated as part of this aleatoric uncertainty, to accommodate an accurate overall EDP approximation. Similarities are discussed for applications that consider the description of the seismic hazard through the selection of ground motions based on intensity measures. An extensive validation of this new approach is presented considering two different stochastic ground motion models.
Entropy generation analysis for mixed convective flow of Casson fluid in a vertical microchannel with the influence of nonlinear radiation by maintaining inconstant viscosity
Authors: Manthesha  , Jayaprakash M. C. , Patil Mallikarjun B. 
Published: June 2022

AbstractThe study of entropy generation in the fluid flow has great importance in the field of engineering. The present analysis is to investigate the entropy production in Casson fluid flow in a vertically placed porous‐filled microchannel. The flow is influenced by the nonlinear radiation and exponential heat source. Viscosity is kept varying throughout the flow. The equations which govern the considered flow are nonlinear and are nondimensionalized by considering the appropriate nondimensional variables. The flow problem is tackled by converting the ordinary differential equation (ODE) by assigning the new variables. The flow problem is tackled by using the effective mechanism which involves the finite difference technique by converting the equations into a set of first‐order ODE. The results attained are discussed using the graphs. It is noted that by maintaining the lesser values for the Casson parameter and mixed convection parameter, entropy production can be reduced. The Bejan number profile has the highest magnitude for the variation of mixed convection parameter and the same is found to be less for the nonlinear radiation parameter.