bluuebunny/crossref_metadata_2025_split huggingface dataset:
Imputing missing covariates in time‐to‐event analysis within distributed research networks: A simulation study
Authors: Li Dongdong , Wong Jenna , Li Xiaojuan , Toh Sengwee , Wang Rui 
Published: November 2022

AbstractPurposeIn distributed research network (DRN) settings, multiple imputation cannot be directly implemented because pooling individual‐level data are often not feasible. The performance of multiple imputation in combination with meta‐analysis is not well understood within DRNs.MethodsTo evaluate the performance of imputation for missing baseline covariate data in combination with meta‐analysis for time‐to‐event analysis within DRNs, we compared two parametric algorithms including one approximated linear imputation model (Approx), and one nonlinear substantive model compatible imputation model (SMC), as well as two non‐parametric machine learning algorithms including random forest (RF), and classification and regression trees (CART), through simulation studies motivated by a real‐world data set.ResultsUnder the setting with small effect sizes (i.e., log‐Hazard ratios [logHR]) and homogeneous missingness mechanisms across sites, all imputation methods produced unbiased and more efficient estimates while the complete‐case analysis could be biased and inefficient; and under heterogeneous missingness mechanisms, estimates with RF method could have higher efficiency. Estimates from the distributed imputation combined by meta‐analysis were similar to those from the imputation using pooled data. When logHRs were large, the SMC imputation algorithm generally performed better than others.ConclusionsThese findings suggest the validity and feasibility of imputation within DRNs in the presence of missing covariate data in time‐to‐event analysis under various settings. The performance of the four imputation algorithms varies with the effect sizes and level of missingness.
Epoxy adhesive shear mechanism on the molecular level
Authors: Song Jingfu , Wang Guoqing , Zhao Gai 
Published: November 2022

AbstractThe tensile and shear performances of epoxy adhesive were evaluated both experimentally and using molecular dynamics (MD) simulations to understand the shear mechanism operating at the atomic level. A sandwich structure composed of pure epoxy and two copper layers was established based on the standard stretching mode. This three‐layer model was first stretched in the perpendicular direction to examine the dynamic evolution of the epoxy molecules. The epoxy was then adhered onto both smooth and rough copper surfaces to determine their shear strengths. Adhesive failure involving interfacial slippage and slight shear deformation of the epoxy matrix was observed on the smooth copper surface, while the epoxy was strongly bound to the rough surface and fractured under shear stress. MD simulations provided data that are consistent with experimental values. Finally, the shear mechanism was investigated by calculating the interaction energies between the epoxy and copper. This study provides significant insight into the shear‐failure mechanisms of epoxy adhered to copper surfaces.
Fatalism and metaphor in Confucianism: A qualitative study of barriers to genetic testing among first‐degree relatives of hereditary cancer patients from China
Authors: Jiang Chaonan , Liu Li , Wang Ye , Wu Liangzheng , Zhang Wenxia , Wu Xiaodan 
Published: November 2022

AbstractObjectiveDespite the benefits, the rate of genetic testing among first‐degree relatives (FDRs; parents, children, and siblings) remains low, and the barriers to undergoing testing among FDRs in China are not clear. We explored the reasons why FDRs refused genetic testing.MethodsSemi‐structured face‐to‐face interviews were conducted with 22 patients and 27 FDRs. Participants were recruited at an urban tertiary hospital in Guangzhou, South China. We used qualitative content analysis to analyse the transcripts of audio recordings and identify major themes and subthemes.ResultsThree major themes emerged related to FDRs' low rate of participation in genetic testing. First, there is cognitive distance from genetic testing/cancer and a lack of knowledge of preventive medicine that deepens the ‘fatalistic’ attitude towards cancer among FDRs, which leads to an enormous gap between their knowledge and understanding of genetic testing. Second, medical consultation is not valued in Confucianism, and the view of cancer as ‘bad news’ and the risk of cancer as a curse makes cancer a metaphor, which leads to exhausting arguments when persuading FDRs to undergo genetic testing. Third, physical distance from the hospital, loss of privacy, possible discrimination in many social activities and genetic testing as a source of stress and anxiety lead FDRs to fear the disruption of their daily lives.ConclusionsThere are many barriers to genetic testing among the FDRs of hereditary cancer patients originating from the national social and cultural context. Healthcare professionals should develop interventions rooted in culture and promote cancer risk communication between hereditary cancer patients and FDRs.
From passenger to citizen—portraits of learning to be a physiotherapist
Authors: Barradell Sarah 
Published: November 2022

AbstractBackground and PurposeUnderstanding the experiences of learners—and future graduates—is integral to their professional development and to the development of the profession. This paper adds to understanding of physiotherapy student experiences by exploring the ways students and recent graduates approach, learn about, connect with and form a relationship with their chosen profession of physiotherapy.MethodsHeuristic inquiry, a form of phenomenology, was used. Thirteen participants (11 students and 2 new graduates) were interviewed.ResultsThe findings are presented as four portraits: passenger, tourist, resident and citizen. These represent four particular and prominent ways that the participants connected with specific situations and/or to the profession as a whole, the sense they made of those situations (or the broader profession) and the identity formed.DiscussionThe portraits help educators to think about how students are navigating the process of becoming a physiotherapist and might act as a tool to help foster students' professional development. Educators who understand students' motivations and struggles are better prepared to help students to see themselves and the profession in sophisticated ways.
Phage‐assisted, active site‐directed ligand evolution of a potent and selective histone deacetylase 8 inhibitor
Authors: Morse Jared S. , Sheng Yan J. , Hampton Joshua Trae , Sylvain Lauralee D. , Das Sukant , Alugubelli Yugendar R. , Chen Peng‐Hsun Chase , Yang Kai S. , Xu Shiqing , Fierke Carol A. , Liu Wenshe Ray 
Published: November 2022

AbstractPhage‐assisted, active site‐directed ligand evolution (PADLE) is a recently developed technique that uses an amber codon‐encoded noncanonical amino acid (ncAA) as an anchor to direct phage‐displayed peptides to a target for an enhanced ligand identification process. 2‐Amino‐8‐oxodecanoic acid (Aoda) is a ketone‐containing ncAA residue in the macrocyclic peptide natural product apicidin that is a pan‐inhibitor of Zn2+‐dependent histone deacetylases (HDACs). Its ketone serves as an anchoring point to coordinate the catalytic zinc ion in HDACs. Using a previously evolved N𝜀‐acetyl‐lysyl‐tRNA synthetase in combination with tRNAPyl, we showed that Aoda was efficiently incorporated into proteins in Escherichia coli by amber suppression. By propagating an amber codon‐obligate phagemid library in E. coli encoding Aoda, we generated an Aoda‐containing phage‐displayed peptide library. Using this library to conduct PADLE against HDAC8 revealed a 7‐mer peptide GH8P01F1 with Aoda‐flanking amino acid residues that matched existing peptide sequences in identified HDAC8 substrates. Switching Aoda in GH8P01F1 to a more Zn2+‐chelating ncAA S‐2‐amino‐8‐hydroxyamino‐8‐oxooctanoic acid (Asuha) led to an extremely potent compound GH8HA01, which has an HDAC8‐inhibition Ki value of 0.67 nM. GH8HA01 and its 5‐mer truncation analogue Ac‐GH8HA01Δ1Δ7 that has an HDAC8‐inhibition Ki value of 0.31 nM are two of the most potent HDAC8 inhibitors that have been developed. Furthermore, both are highly selective against HDAC8 compared with other HDACs tested, demonstrating the great potential of using PADLE to identify highly potent and selective ligands for targets with conserved active sites among homologues.
Snapshots of urea‐induced early structural changes and unfolding of an ankyrin repeat protein at atomic resolution
Authors: Medur Gurushankar Mukund Sudharsan , Dalvi Somavally , Venkatraman Prasanna 
Published: November 2022

AbstractProtein folding and unfolding is a complex process, underscored by the many proteotoxic diseases associated with misfolded proteins. Mapping pathways from a native structure to an unfolded protein or vice versa, identifying the intermediates, and defining the role of sequence and structure en route remain outstanding problems in the field. It is even more challenging to capture the events at atomistic resolution. X‐ray diffraction has so far been used to understand how urea interacts with and unfolds two stable globular proteins. Here, we present the case study on PSMD10Gankyrin, a prototype for a moderately stable, non‐globular repeat protein, long and rigid, with its termini located at either end. We define structural changes in the time dimension using low urea concentrations to arrive at the following conclusions. (a) Unfolding is rapidly initiated at the C‐terminus, slowly at the N‐terminus, and proceeds inwards from both ends. (b) C‐terminus undergoes an α to 310 helix transition, representing the structure of a potential early unfolding intermediate before disorder sets in. (c) Distinct and progressive changes in the electrostatic landscape of PSMD10Gankyrin were observed, indicative of conformational changes in the seemingly inflexible motif involved in protein–protein interaction. We believe this unique study will open up the field for better and bolder queries and increase the choice of model proteins for a better understanding of the challenging problems of protein folding, protein interactions, protein degradation, and diseases associated with misfolding.
Evaluating the performance of machine‐learning regression models for pharmacokinetic drug–drug interactions
Authors: Gill Jaidip , Moullet Marie , Martinsson Anton , Miljković Filip , Williamson Beth , Arends Rosalinda H. , Pilla Reddy Venkatesh 
Published: November 2022

AbstractCombination therapy or concomitant drug administration can be associated with pharmacokinetic drug–drug interactions, increasing the risk of adverse drug events and reduced drug efficacy. Thus far, machine‐learning models have been developed that can classify drug–drug interactions. However, to enable quantification of the pharmacokinetic effects of a drug–drug interaction, regression‐based machine learning should be explored. Therefore, this study investigated the use of regression‐based machine learning to predict changes in drug exposure caused by pharmacokinetic drug–drug interactions. Fold changes in exposure relative to substrate drug monotherapy were collected from 120 clinical drug–drug interaction studies extracted from the Washington Drug Interaction Database and SimCYP compound library files. Drug characteristics (features) were collected such as structure, physicochemical properties, in vitro pharmacokinetic properties, cytochrome P450 metabolic activity, and population characteristics. Three different regression‐based supervised machine‐learning models were then applied to the prediction task: random forest, elastic net, and support vector regressor. Model performance was evaluated using fivefold cross‐validation. Strongest performance was observed with support vector regression, with 78% of predictions within twofold of the observed exposure changes. The results show that changes in drug exposure can be predicted with reasonable accuracy using regression‐based machine‐learning models trained on data available early in drug discovery. This has potential applications in enabling earlier drug–drug interaction risk assessment for new drug candidates.
Hydroxy levamisole and its phase II conjugates as potential indicators of levamisole doping in thoroughbred horses
Authors: Philip Moses , Karakka Kal Abdul Khader , Subhahar Michael Benedict , Karatt Tajudheen K. , Mathew Binoy , Perwad Zubair , Graiban Fatma Mohammed , Caveney Marina Rodriguez , Sayed Ramy , Kadry Ahmed Mahmoud 
Published: November 2022

RationaleAccording to previous research, aminorex is the major metabolite of levamisole; however, in the screening of levamisole‐positive racehorse urine and plasma samples, aminorex could only be detected in trace amounts or not at all. In forensic laboratories, hydroxy levamisole and its phase II conjugates make it easier to confirm levamisole misuse and to differentiate between the abuse of levamisole and aminorex. This study aimed to identify the major levamisole metabolites that can be detected along with the parent drug.MethodsThe study describes levamisole and its metabolites in thoroughbred horses following oral administration and in vitro with equine liver microsomes. The plausible structures of the detected metabolites were postulated using liquid chromatography combined with high‐resolution mass spectrometry.ResultsUnder the experimental conditions 26 metabolites (17 phase I, 2 phase II, and 7 conjugates of phase I metabolites) were detected (M1–M26). The major phase I metabolites identified were formed by hydroxylation. In phase II, the glucuronic acid conjugates of levamisole and hydroxy levamisole were detected as the major metabolites. In plasma, the parent drug and major metabolites are detectable for up to eight days, while in urine, they are detectable for up to twenty days. Levamisole levels rapidly increased at 45 min following administration, then declined gradually until detectable levels were reached approximately 8 days after administration, according to a pharmacokinetics study.ConclusionsA prolonged elimination profile and relatively high concentration of hydroxy metabolites suggest that the detection of hydroxy metabolites is imperative for investigating levamisole doping in horses.
High‐temperature mass spectrometric study and modeling of ceramics based on the Al2O3‐SiO2‐ZrO2 system
Authors: Stolyarova Valеntina L. , Shilov Andrey L. , Lopatin Sergey I. , Vorozhtcov Viktor A. , Yurchenko Dmitrii A. , Knyazyan Nikolay B. , Manukyan Goharik G. 
Published: November 2022

RationaleMaterials based on the Al2O3‐SiO2‐ZrO2 system are promising for a wide range of high‐temperature technological applications, such as thermal barrier coatings in the aviation and space industry or advanced materials in nuclear power reactors. Experimental studies of the ceramics based on this system by the Knudsen effusion mass spectrometric (KEMS) method are of significant interest in designing technological processes for the synthesis and exploitation of the Al2O3‐SiO2‐ZrO2 materials.MethodsSamples of ceramics in the Al2O3‐SiO2‐ZrO2 system, including the Al2O3‐ZrO2 and SiO2‐ZrO2 binaries, were prepared by solid‐state synthesis. Analysis of the samples was performed by X‐ray fluorescence and diffraction techniques. The vapor composition and thermodynamic properties of the components in this system were determined by KEMS. The derived thermodynamic functions were optimized within the generalized lattice theory of associated solutions (GLTAS).ResultsIn the temperature range 1900–2600 K, the SiO, Al, AlO, Al2O, ZrO, ZrO2, and O vapor species were identified over the samples in the systems under study. For the thermodynamic properties to be determined correctly, the samples of the Al2O3‐SiO2‐ZrO2 system had to be vaporized at temperatures less than 2000 K, where data could be obtained only for the SiO species. The SiO2 activities obtained were taken as the experimental basis for the modeling within the GLTAS approach. This allowed evaluation of the component activities and excess Gibbs energy, and assessment of the relative number of bonds of different types.ConclusionsAt 1920 K, the Al2O3‐SiO2‐ZrO2 system is characterized by negative deviations of its thermodynamic properties from the ideal behavior. The consistency of the obtained modeling results was illustrated by comparison of the values derived from the data for the ternary and the boundary binary systems and thereby indicates the reasonable uniformity of the energy parameters of the lattice model derived in the calculations, which may be used in further modeling of multicomponent systems.
Bilateral pneumothoraces with apical consolidations
Authors: Kinoshita Yoshiaki , Utsunomiya Takuhide , Kushima Hisako , Ishii Hiroshi 
Published: November 2022

AbstractBilateral pneumothoraces are extremely rare. Patients with pleuroparenchymal fibroelastosis are frequently complicated by pneumothorax, which is sometimes bilateral. Pleuroparenchymal fibroelastosis should be considered a cause of bilateral pneumothoraces with apical fibrosis.
Resource scheduling in mobile edge computing using improved ant colony algorithm for space information network
Authors: Wang Yufei , Liu Jun , Tong Yu , Yang Qingwen , Liu Yanyi , Mou Hanbo 
Published: November 2022

SummaryWith the development of space information network (SIN), new network applications are emerging. Satellites are not only used for storage and transmission but also gradually used for calculation and analysis, so the demand for resources is increasing. But satellite resources are still limited. Mobile edge computing (MEC) is considered an effective technique to reduce the pressure on satellite resources. To solve the problem of task execution delay caused by limited satellite resources, we designed Space Mobile Edge Computing Network (SMECN) architecture. According to this architecture, we propose a resource scheduling method. First, we decompose the user tasks in SMECN, so that the tasks can be assigned to different servers. An improved ant colony resource scheduling algorithm for SMECN is proposed. The heuristic factors and pheromones of the ant colony algorithm are improved through time and resource constraints, and the roulette algorithm is applied to route selection to avoid falling into the local optimum. We propose a dynamic scheduling algorithm to improve the contract network protocol to cope with the dynamic changes of the SIN and dynamically adjust the task execution to improve the service capability of the SIN. The simulation results show that when the number of tasks reaches 200, the algorithm proposed in this paper takes 17.52% less execution time than the Min‐Min algorithm, uses 9.58% less resources than the PSO algorithm, and achieves a resource allocation rate of 91.65%. Finally, introducing dynamic scheduling algorithms can effectively reduce task execution time and improve task availability.
Research Progress on Cu2O‐based Type‐II Heterojunction Photocatalysts for Photocatalytic Removal of Antibiotics
Authors: Wang Kai , Yu Xiaojiao , Yang Fan , Liu Zongbin , Li Zongyang , Zhang Ting , Niu Jinfen , Yao Binhua 
Published: November 2022

AbstractPhotocatalytic degradation technology, using solar energy as the driving force, is considered the most possible alternative to remediate environmental pollution. And it is essential to find a stable and efficient photocatalyst. As promising semiconductor‐based photocatalysts, Cu2O has acquired massive attention owning to its high conduction band energy, superior visible‐light response‐ability, low cost, eco‐friendly, and abundance. However, the application of origin Cu2O faces severe problems due to its photocorrosion and low photoinduced carrier separation. Consequently, it is necessary to improve its photostability and photocatalytic activity by carrying out numerous modification strategies, such as heterostructure construction. Herein, we first summarize the classification and operation principles of Cu2O‐based type‐II heterojunction. Then, the application of the Cu2O‐based type‐II heterojunction photocatalysts for the removal of tetracyclines, quinolones, and sulfonamides have been discussed. Finally, the pressing issues and perspectives in Cu2O‐based type‐II heterojunction photocatalysts application for degrading antibiotics have prospected.
Controlling Size Distribution of Silver Nanoparticles using Natural Reducing Agents in MCM‐41@Ag
Authors: Bravo de Luciano Gerardo‐Miguel , Panecatl‐Bernal Yesmin , Soto‐Cruz Blanca‐Susana , Méndez‐Rojas Miguel Ángel , López‐Salazar Primavera , Alcántara‐Iniesta Salvador , Portillo Melissa Chávez , Romero‐López Anabel , Mejía‐Silva Jesús‐Israel , Alvarado Joaquin , Domínguez‐Jiménez Miguel Ángel 
Published: November 2022

AbstractIt is by reported the effect of natural reducing agents such as plant extracts (Equisetum myriochaetum leaves, Cymbopogon citratus, Camellia sinensis, Syzygium aromaticum), fruits (orange, apple), and biopolymers (arabic gum, and chitosan) on the size distribution of silver nanoparticles, obtained by green synthesis, to be incorporated in a MCM‐41@Ag nanocomposite. The aim is to determine the influence of temperature, agitation time, concentration, atmosphere, and nature of the reducing agent on the MCM‐41@Ag particle size. According to the DLS analysis, the extract of Syzygium aromaticum produced silver nanoparticles in the range of 8–80 nm. Further structural, morphological, optical, and surface characterization confirmed the obtention of the desired MCM‐41@Ag nanocomposite. Our results show the potential of MCM‐41@Ag to be incorporated in Metal‐insulator‐semiconductor capacitors for detection purposes.
Using Both Classical and Chemometric Chromatographic Measurements to Quantify and Monitor the in‐vitro Dissolution Profiles of Lamivudine and Zidovudine in Combined Tablets
Authors: Dinç Erdal , Özdemir Nurten , Tilkan M. Günseli , Rouhani Ghazal , Büker Eda , Hoang Vu Dang 
Published: November 2022

AbstractClassical and chemometric calibration strategies based‐Ultra Performance Liquid Chromatography‐Photodiode Array (UPLC‐PDA) measurements were improved to monitor the in‐vitro dissolution profiles of lamivudine (LAM) and zidovudine (ZID) in tablets and to quantify drugs. To generate UPLC‐PDA data, UPLC analysis was done using the mobile phase containing acetonitrile‐acetate buffer pH 5.0 (18 : 82, v/v). In the classical strategy, calibration curves were obtained by using the peak area ratios detected at 274 nm for LAM and 268 nm for ZID, respectively. Principal component regression (PCR) and partial least squares (PLS) strategies were used to solve the same problem using UPLC‐PDA measurements obtained at eight different wavelengths. Both classical and chemometric approaches were successfully applied for drugs assay and in‐vitro dissolution testing. Assay results showed that the proposed chemometric tools gave better results because they helped to minimize the effect of chromatographic issues that commonly occur with the classical UPLC approach, such as the higher standard deviation of the assay results.