bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rational Design of a Novel Tubulin Inhibitor with a Unique Mechanism of Action
Authors: Mühlethaler Tobias , Milanos Lampros , Ortega Jose Antonio , Blum Thorsten B. , Gioia Dario , Roy Bibhas , Prota Andrea E. , Cavalli Andrea , Steinmetz Michel O. 
Published: April 2022

AbstractIn this study, we capitalized on our previously performed crystallographic fragment screen and developed the antitubulin small molecule Todalam with only two rounds of straightforward chemical synthesis. Todalam binds to a novel tubulin site, disrupts microtubule networks in cells, arrests cells in G2/M, induces cell death, and synergizes with vinblastine. The compound destabilizes microtubules by acting as a molecular plug that sterically inhibits the curved‐to‐straight conformational switch in the α‐tubulin subunit, and by sequestering tubulin dimers into assembly incompetent oligomers. Our results describe for the first time the generation of a fully rationally designed small molecule tubulin inhibitor from a fragment, which displays a unique molecular mechanism of action. They thus demonstrate the usefulness of tubulin‐binding fragments as valuable starting points for innovative antitubulin drug and chemical probe discovery campaigns.
Entschlüsselung chemischer Mediatoren zur Regulierung des spezialisierten Stoffwechsels in einem symbiotischen Cyanobakterium
Authors: Krumbholz Julia , Ishida Keishi , Baunach Martin , Teikari Jonna E. , Rose Magdalena M. , Sasso Severin , Hertweck Christian , Dittmann Elke 
Published: April 2022

AbstractCyanobakterielle Genome weisen eine Vielzahl unbekannter Biosynthesewege für komplexe Naturstoffe auf, allerdings sind die Besonderheiten, die die Entdeckung und Nutzung unbekannter Stoffwechselwege einschränken, nicht hinreichend verstanden. Hier beschreiben wir die Entdeckung zweier von der Zelldichte abhängiger chemischer Mediatoren, Nostoclid und Nostovalerolacton, welche im symbiotischen Modellstamm Nostoc punctiforme vorkommen und demonstrieren ihren ausgeprägten Einfluss auf die Regulation des spezialisierten Stoffwechsels. Mithilfe von Transkriptions‐, Bioinformatik‐ und Markierungsstudien konnten wir die Biosynthese der beiden Polyketid‐Mediatoren zwei benachbarten biosynthetischen Genclustern zuordnen. Unsere Ergebnisse geben einen Einblick in die Produktionsmechanismen spezialisierter Metabolite und liefern wertvolle Erkenntnisse für das Genomic Mining und die Hochtiter‐Produktion von cyanobakteriellen bioaktiven Substanzen.
Deciphering Chemical Mediators Regulating Specialized Metabolism in a Symbiotic Cyanobacterium
Authors: Krumbholz Julia , Ishida Keishi , Baunach Martin , Teikari Jonna E. , Rose Magdalena M. , Sasso Severin , Hertweck Christian , Dittmann Elke 
Published: April 2022

AbstractGenomes of cyanobacteria feature a variety of cryptic biosynthetic pathways for complex natural products, but the peculiarities limiting the discovery and exploitation of the metabolic dark matter are not well understood. Here we describe the discovery of two cell density‐dependent chemical mediators, nostoclide and nostovalerolactone, in the symbiotic model strain Nostoc punctiforme, and demonstrate their pronounced impact on the regulation of specialized metabolism. Through transcriptional, bioinformatic and labeling studies we assigned two adjacent biosynthetic gene clusters to the biosynthesis of the two polyketide mediators. Our findings provide insight into the orchestration of specialized metabolite production and give lessons for the genomic mining and high‐titer production of cyanobacterial bioactive compounds.
Biomimetic chromatography—A novel application of the chromatographic principles
Authors: Valko Klara L 
Published: April 2022

AbstractBiomimetic chromatography is the name of the High Performance Liquid Chromatography (HPLC) methods that apply stationary phases containing proteins and phospholipids that can mimic the biological environment where drug molecules distribute. The applied mobile phases are aqueous organic with a pH of 7.4 to imitate physiological conditions that would be encountered in the human body. The calibrated retention of molecules on biomimetic stationary phases reveals a compound's affinity to proteins and phospholipids, which can be used to model the biological and environmental fate of molecules. This technology, when standardised, enables the prediction of in vivo partition and distribution behaviour of compounds and aids the selection of the best compounds for further studies to become a drug molecule. Applying biomimetic chromatographic measurements helps reduce the number of animal experiments during the drug discovery process. New biomimetic stationary phases, such as sphingomyelin and phosphatidylethanolamine, widen the application to the modelling of blood–brain barrier distribution and lung tissue binding. Recently, the measured properties have also been used to predict toxicity, such as phospholipidosis and cardiotoxicity. The aquatic toxicity of drugs and pesticides can be predicted using biomimetic chromatographic data. Biomimetic chromatographic separation methods may also be extended in the future to predict protein and receptor binding kinetics. The development of new biomimetic stationary phases and new prediction models will further accelerate the widespread application of this analytical method.
Chiral Assembly and Recognition of Seven Copper (II) Coordination Polymers from Tartaric Acid Derivative Ligands
Authors: Li Zong‐Ying , Yuan Bin , Wang Hai‐Xian , He Tian‐Sheng , Lan Yan‐Long , Wang Si‐Yu , Zhu Li‐Na , Kong DeMing , Li Xiao‐Zeng 
Published: April 2022

AbstractA pair of enantiomeric ligands, (2R,3R)‐dibenzyl‐2,3‐bis(isonicotinoyloxy)succinate ((R,R)‐L) and (2S,3S)‐dibenzyl‐2,3‐bis(isonicotinoyloxy)succinate ((S,S)‐L), are designed and synthesized. Seven copper (II) coordination polymers {[Cu((R,R)‐L)Br2(THF)] ⋅ CH3CN} n (1 a) and {[Cu((S,S)‐L)Br2(THF)] ⋅ CH3CN}n (1 b), {[Cu((R,R)‐L)Cl2(THF)] ⋅ CH3CN}n (2 a) and {[Cu((S,S)‐L)Cl2(THF)] ⋅ CH3CN}n (2 b), {[Cu((R,R)‐L)(NO3)2(CH3CN)]}n (3 a) and {[Cu((S,S)‐L)(NO3)2(CH3CN)]}n (3 b), {[Cu((R,R)‐L)2(CH3CN)2](ClO4)2 ⋅ 3CH3CN}n (4) were obtained through the assemblies with CuBr2, CuCl2 ⋅ 2H2O, Cu(NO3)2 ⋅ 3H2O, Cu(ClO4)2 ⋅ 6H2O, respectively. Single‐crystal X‐ray diffraction and circular dichroism analysis demonstrate that 1 a–3 a, 1 b–3 b have a mono chiral one‐dimensional (1D) chain‐like spiral structure, while 4 have 1D chain‐like structure whose metal centers have chiral propeller coordination environment. Ligand structure, anions and solvent systems have a regulatory effect on the formation of chiral helical structure. Further investigation has proved that 1 a can be used as circular dichroism spectrum probe for monitoring L‐/D‐cysteine and L‐/D‐penicillamine configuration and concentration in aqueous media based on ligand interchange mechanism.
Blockchain‐based recycling and its impact on recycling performance: A network theory perspective
Authors: Gong Yu , Xie Shenghao , Arunachalam Deepak , Duan Jiang , Luo Jianli 
Published: April 2022

AbstractThe purpose of this study is to explore the application of blockchain technology (BCT) in recycling. This research applies a multiple case study approach with six pioneer organisations, based on secondary data. We found that BCT is an effective approach to promote recycling performance: it can provide tokenisation, waste flow tracking and recycling chain integration. The benefits include ‘Eco‐friendly’, ‘Stimulate participation’, ‘Social inclusion’, ‘Transparent recycling chains’ and ‘Extended producer responsibility accountability’. However, the majority of existing BCT‐based initiatives are in the pilot stage and face cognitive, technology, internal and external barriers. Our research is one of the first studies on blockchain‐based recycling. We applied the network theory of ‘Reachability’, ‘Richness’ and ‘Receptivity’ and ‘network formation’ barriers to propose a conceptual framework of BCT‐based recycling, which serves as a practical reference for the recycling industry.
Between impact and returns: Private investors and the sustainable development goals
Authors: Paetzold Falko , Busch Timo , Utz Sebastian , Kellers Anne 
Published: April 2022

AbstractWe investigate the expectations of wealthy private investors regarding the impact and financial return of sustainable investments. Our paper focuses on the sustainable development goals (SDGs) as a framework for investors' attempts to create impact. We analyze the behavior of 60 high‐net‐worth individuals (HNWIs), a powerful yet overlooked investor segment. Our results show large allocations in line with the SDGs, which demonstrates these investors' aim of achieving real‐word changes. Furthermore, we show that these “impact investors” have a clear preference for SDGs that are associated with high financial returns. As such, we confirm that both impact and attractive financial returns are expected. Our findings provide rich, deep insights into how HNWIs practice impact investing and their underlying motivations. We outline practical implications for different stakeholders, notably regarding the fact that financially attractive SDGs are likely to attract substantial amounts of capital, with other SDGs remaining underfunded.
HS‐IDEOR—A tool for conceptual modeling and designing of hardware architectures focused on object recognition
Authors: Guzmán‐Ramírez Enrique , García Iván , Arroyo‐Fernández Ignacio , Santos‐Villalobos Alberto 
Published: April 2022

AbstractConsidering the increasing demand for object recognition systems, it is crucial that modern engineering courses include tools and methods to ensure that students acquire the theoretical and practical skills necessary to become specialists in designing such systems. This paper introduces a hardware‐software integrated development environment to support and accelerate the teaching/learning process of conceptual modeling and hardware architectures design focused on object recognition. In addition, our proposal facilitates the implementation of modular and hybrid object recognition schemes, offering great flexibility in the study of such systems. An empirical evaluation was conducted with 30 fourth‐year undergraduate students who designed and implemented an object recognition system in the Computer Vision course of the Bachelor's Degree in Computer Science and Engineering at the Universidad Tecnológica de la Mixteca, Mexico. The results achieved from designing, modeling, and implementing a hardware architecture of the convolution process applied to edge detection in an image provided evidence that this approach empowered students with a more dynamic learning process.
Insights into Fe Species Structure‐Performance Relationship for Direct Methane Conversion toward Oxygenates over Fe‐MOR Catalysts
Authors: Fang Zhihao , Huang Mengyuan , Liu Bing , Chen Jie , Jiang Feng , Xu Yuebing , Liu Xiaohao 
Published: April 2022

AbstractDirect oxidation of methane to value‐added products under mild conditions remains a grand challenge due to the problem of selective CH4 activation. Here we report a Fe‐MOR‐F catalyst prepared via freeze‐drying method, indicating excellent catalytic performance for the direct partial oxidation of methane using H2O2 under mild conditions. Various characterizations including XRD, NH3‐TPD, H2‐TPR, UV‐Vis, XPS, and EPR studies revealed that Fe‐MOR‐F catalyst possesses more highly dispersed monomeric and dimeric iron species, which is strongly correlated to its high catalytic activity for direct methane oxidation. The DFT calculations indicate the highly dispersed monomeric and dimeric iron species can effectively homogenize H2O2 into active hydroxyl groups, while iron clusters can decompose H2O2 into inactive O2. The EPR experiments show more ⋅OH was generated on Fe‐MOR‐F catalyst, which is in line with DFT calculation results. These structural characteristics endow Fe‐MOR‐F catalyst with superior catalytic performance for direct methane oxidation in terms of oxygenates yield (9.8 mol kgcat−1 h−1) and selectivity (91.8 %) at 80 °C. This work not only highlights the excellent catalytic performance of methane activation on the highly dispersed monomeric and dimeric iron species, but also promotes the potential application by freeze‐drying method for the preparation of the highly dispersed active species.
Promoted MoxCy‐based Catalysts for the CO2 Oxidative Dehydrogenation of Ethane
Authors: Marquart Wijnand , Raseale Shaine , Claeys Michael , Fischer Nico 
Published: April 2022

AbstractThe CO2 oxidative dehydrogenation reaction has the potential to play a role in the advancement of CO2‐utilizing catalytic reactions, co‐activating CO2 and short‐chained alkanes. Transition metal carbides are promising catalysts for this reaction, in particular MoxCy, however catalytic stability is a major challenge. In this study, the addition of a promoter (Fe, K, Ni or Pt) has shown to significantly influence the crystal structure of the carbide system as well as the acid‐base characteristics. K promotion decreased the number of acid sites, limiting ethane activation and the removal of the oxygen surface species formed in CO2 activation. The catalysts deactivate due to oxidation to MoOx. Fe decreased the initial activity, but it increased the stability of the oxygen surface species, which enhanced the stability of the catalyst and ethylene selectivity to outperform the unpromoted sample. Oxidation of the carbide and carbon deposition during the reaction could not be prevented. Ni promotion increases the number of basic sites, enhancing the CO2 activation, shown by the highest activity obtained during the reverse water‐gas‐shift experiments. At higher CO2 content in the feed the dry‐reforming reaction becomes the dominant reaction pathway. Pt suppressed the dry‐reforming reaction, but instead increased the direct dehydrogenation activity, accompanied by a high degree of carbon deposition. No oxidation to MoOx was observed at a stoichiometric CO2 to C2H6 feed ratio.
Statistical Analysis of the Measurement Noise in Dynamic Impedance Spectra
Authors: Chukwu Richard , Mugisa John , Brogioli Doriano , Mantia Fabio La 
Published: April 2022

AbstractDifferent strategies can be used to acquire dynamic impedance spectra during a cyclic voltammetry experiment. The spectra are then analyzed by fitting them with a model using a weighted non‐linear least‐squares minimization algorithm. The choice of the weighting factors is not trivial and influences the value of the extracted parameters. At variance with the classic electrochemical impedance spectroscopy, dynamic impedance measurements are performed under non‐stationary conditions, making them typically more prone to errors arising from the voltage and current analog‐to‐digital conversion. Under the assumption that the noise in the voltage and current signals have a constant variance along the measurement and that it is uncorrelated between distinct samples, we calculate an expression for the expected variance of the error of the resulting immittances, which considers the specific procedure used to extract the spectra under the time‐varying nature of the measurements. The calculated variance of the error is then used as a rigorous way to evaluate the weighting factors of the least‐squares minimization, assuming that the fitted model is ideally exact and that there are no systematic errors. By exploring two classical electrochemical systems and fitting the measured spectra with a transfer function measurement model, namely with the Padé approximants, we show that the variance evaluated with our method captures the frequency dependence of the resulting residuals and can be used for reliably performing the complex non‐linear least‐squares fitting procedure.
Structure and Electrochemical Properties of LaMn1‐XNixO3
Authors: Li Jiayun , Luo Wangting , Wang Xiaoqian , Yu Chao , Zhang YuJie , Meng FanBin 
Published: April 2022

AbstractLaMn1‐xNixO3nanoparticles were synthesized through hydrothermal synthesis and calcinations. The structural and electrochemical properties were studied to evaluate the effect of Ni doping on the materials as supercapacitor electrodes. The LaMn0.5Ni0.5O3sample presented a capacitance of 183 F ⋅ g−1(current density of 1 A ⋅ g−1) and a capacity retention of 83.5 % after 2000 charge‐discharge cycles. Theoretical calculations were performed to provide more insight into the electrochemical performance.
Advances in Z‐scheme semiconductor photocatalysts for the photoelectrochemical applications: A review
Authors: Li Jiaxin , Yuan Hao , Zhang Wenjie , Jin Bingjun , Feng Qi , Huang Jan , Jiao Zhengbo 
Published: April 2022

AbstractWith continuous consumption of nonrenewable energy, solar energy has been predicted to play an essential role in meeting the energy demands and mitigating environmental issues in the future. Despite being green, clean and pollution‐free energy, solar energy cannot be adopted directly as it cannot provide sufficiently high energy density to work in the absence of machinery. Thus, it is necessary to develop an effective strategy to convert and store solar energy into chemical energy to achieve social sustainable development using solar energy as the main power source. Photocatalysis, in which semiconductor photocatalysts play a key role, is one of the most promising candidates for realising the effective utilisation of sunlight in a green, low‐cost and environmentally friendly method. The photocatalytic efficiency of photocatalysts is considerably influenced by their compositions. Among the various heterostructures, Z‐scheme heterojunction is one of the most interesting architecture due to its outstanding performance and excellent artificial imitation of photosynthesis. Z‐scheme photocatalysts have attracted considerable attention in the past few decades. Herein, we review contemporary Z‐scheme systems, with a particular focus on mechanistic breakthroughs, and highlight current state‐of‐the‐art systems. Z‐type photocatalysts are classified as traditional, all‐solid‐state, direct Z‐schemes and S‐scheme photocatalysts. The morphology, characterisation and working mechanism of each type of Z‐scheme are discussed in detail. Furthermore, the applications of Z‐scheme in photoelectrochemical water splitting, nitrogen fixation, pollutant degradation and carbon dioxide reduction are illustrated. Finally, we outline the main challenges and potential advances in Z‐scheme architectures, as well as their future development directions.
Highly stretchable, durable, and breathable thermoelectric fabrics for human body energy harvesting and sensing
Authors: He Xinyang , Shi Jia , Hao Yunna , He Mantang , Cai Jiaxin , Qin Xiaohong , Wang Liming , Yu Jianyong 
Published: April 2022

AbstractStretchable thermoelectrics have recently attracted widespread attention in the field of self‐powered wearable electronics due to their unique capability of harvesting body heat. However, it remains challenging to develop thermoelectric materials with excellent stretchability, durable thermoelectric properties, wearable comfort, and multifunctional sensing properties simultaneously. Herein, an advanced preparation strategy combining electrospinning and spraying technology is proposed to prepare carbon nanotube (CNT)/polyvinyl pyrrolidone (PVP)/polyurethane (PU) composite thermoelectric fabrics that have high air permeability and stretchability (~250%) close to those of pure PU nanofiber fabrics. Furthermore, PVP can not only improve the dispersion of CNTs but also act as interfacial binders between the CNT and the elastic PU skeleton. Consequently, both the electrical conductivity and the Seebeck coefficient remain unchanged even after bending 1000 times. In addition, self‐powered sensors for the mutual conversion of finger temperature and language and detection of the movement of joints to optimize an athlete's movement state were successfully fabricated. This study paves the way for stretchable thermoelectric fabrics with fascinating applications in smart wearable fields such as power generation, health monitoring, and human–computer interaction.
The association between systemic inflammatory response index and in‐hospital mortality in patients with infective endocarditis
Authors: Cai Zhenzhen , Qiao Tengfei , Chen Ying , Xie Mengxiao , Zhou Jun 
Published: April 2022

AbstractBackgroundInfective endocarditis (IE) has a significant mortality, and early identification of high‐risk patients and prediction of poor outcomes is of great significance. In recent years, increasing research has revealed the predictors associated with infective endocarditis prognosis. Systemic inflammatory response index (SIRI) is an important new indicator of inflammation. So far, there have been no reports on the relationship between SIRI and the prognosis of IE patients.HypothesisThe purpose of this study was to explore the value of SIRI in predicting in‐hospital death for patients with infective endocarditis (IE), so as to provide reference for improving the prognosis of patients with IE.MethodA retrospective analysis was performed on the clinical data of patients with IE admitted to the First Affiliated Hospital of Nanjing Medical University from January 2017 to December 2019. SIRI was calculated according to the blood routine results of patients at admission; receiver operating characteristic curve was employed to determined the optimal cutoff value of SIRI. Patients were divided into groups (low SIRI group and high SIRI group; nonsurvivor group and survivor group) according to the levels of SIRI or their prognosis, and the general clinical features of the two groups were compared. Univariate and multivariate logistic regression analysis were performed to analyze the independent prognostic factors of in‐hospital death in IE patients.ResultsA total of 147 IE patients meeting the diagnostic criteria were included, including 102 males (69.4%) and 45 females (30.6%). There was statistically significant difference in SIRI level between nonsurvivor group and survivor group (p < .05). After adjusting for the related factors, the risk of in‐hospital death in the high SIRI was still a risk of in‐hospital death with statistical significance (hazard ratio = 5.053, 95% confidence interval: 1.426‒17.905, p = .012).ConclusionsHigher SIRI level is independently associated with the risk of in‐hospital death in IE patients, and can be an independent predictor of poor outcome in IE patients.
On the performance of link functions in the beta ridge regression model: Simulation and application
Authors: Mustafa Sidra , Amin Muhammad , Akram Muhammad Nauman , Afzal Nimra 
Published: April 2022

AbstractThe beta regression model (BRM) is appropriate when the response variable is continuous and is in the form of ratios and proportions. For the estimation of the BRM, the maximum likelihood estimation (MLE) method is used with a specific link function. However, the MLE provides unstable results when the explanatory variables are correlated. In this study, we consider some ridge parameters for the beta ridge regression estimator (BRRE) under different link functions. However, mostly the researchers do not pay much attention to the suitable link function. So, we consider five link functions to see the performance of ridge parameters in the BRRE. For the performance assessment of ridge parameters and different link functions, a Monte Carlo simulation and a real application are considered, where mean squared error is used as the evaluation criterion. Both the simulation and example findings demonstrate that the BRRE with the log–log link function provides efficient results.