bluuebunny/crossref_metadata_2025_split huggingface dataset:
The first genome for the Cape Primrose Streptocarpus rexii (Gesneriaceae), a model plant for studying meristem‐driven shoot diversity
Authors: Nishii Kanae , Hart Michelle , Kelso Nathan , Barber Sadie , Chen Yun‐Yu , Thomson Marian , Trivedi Urmi , Twyford Alex D. , Möller Michael 
Published: April 2022

AbstractCape Primroses (Streptocarpus, Gesneriaceae) are an ideal study system for investigating the genetics underlying species diversity in angiosperms. Streptocarpus rexii has served as a model species for plant developmental research for over five decades due to its unusual extended meristem activity present in the leaves. In this study, we sequenced and assembled the complete nuclear, chloroplast, and mitochondrial genomes of S. rexii using Oxford Nanopore Technologies long read sequencing. Two flow cells of PromethION sequencing resulted in 32 billion reads and were sufficient to generate a draft assembly including the chloroplast, mitochondrial and nuclear genomes, spanning 776 Mbp. The final nuclear genome assembly contained 5,855 contigs, spanning 766 Mbp of the 929‐Mbp haploid genome with an N50 of 3.7 Mbp and an L50 of 57 contigs. Over 70% of the draft genome was identified as repeats. A genome repeat library of Gesneriaceae was generated and used for genome annotation, with a total of 45,045 genes annotated in the S. rexii genome. Ks plots of the paranomes suggested a recent whole genome duplication event, shared between S. rexii and Primulina huaijiensis. A new chloroplast and mitochondrial genome assembly method, based on contig coverage and identification, was developed, and successfully used to assemble both organellar genomes of S. rexii. This method was developed into a pipeline and proved widely applicable. The nuclear genome of S. rexii and other datasets generated and reported here will be invaluable resources for further research to aid in the identification of genes involved in morphological variation underpinning plant diversification.
Solvent effect on cycloaddition of C20 nanofullerene with indoline‐2‐one, at density functional theory
Authors: Asnaashariisfahani Manzarbanou , Mahmood Evan Abdulkareem , Poor Heravi Mohammad Reza , Habibzadeh Sepideh , Ebadi Abdol Ghaffar , Mohammadi‐Aghdam Sarvin 
Published: April 2022

AbstractThe biologically active (E)‐3‐(furan‐2‐yl)methylene‐indoline‐2‐one (I) is studied, in the gas phase, C6H6, C2H4Cl2, EtOH, MeNO2, DMSO, and H2O using the self‐consistent reaction field (SCRF)—density functional theory (DFT). This species has been used in tumor growth, metastasis, and angiogenesis. A mainly interesting issue is the solvent effect on the stability, geometry, and energy of intermolecular hetero‐Diels–Alder cycloaddition of I with C20 to yield drug delivery (Ia). By optimization of adduct (Ia) from gas phase to nonpolar and then polar solvent, the following results is obtained: (1) The trend of thermodynamic and kinetic stability and also polarity seem proportional to the dielectric constant of the used solvent and formation of the hydrogen bonding. (2) In contrast to general belief that the endo isomer appears more stable than exo isomer, here, the exo isomer appears more stable than endo isomer. (3) The exo cycloaddition can be carried out thermally at room temperature and currently hold responsible for regioselectivity. (4) The possibility of endo cycloaddition is favorable by the lowest energy barrier of 4.2 kcal/mol probed in benzene, while the highest energy barrier of 7.3 kcal/mol is estimated in water. (5) Nonbonding electrostatic interaction between the sulfur heteroatom and nanocage, as well as the π–π aromatic stacking, appears to have significant destabilizing effect on the endo isomer. (6) In going from exo transition state (TS) and endo TS to and Ia cycloadduct, the molecular electrostatic potential is changed as a function of shape, size, symmetry, and regioselectivity.
A flexible mixed‐data model applied to claims data for post‐market surveillance of prescription drug safety behavior
Authors: Butler Harris , Rice John D. , Carlson Nichole E. , Morrato Elaine H. 
Published: April 2022

AbstractWe develop a new modeling framework for jointly modeling first prescription times and the presence of risk‐mitigating behavior for prescription drugs using real‐world data. We are interested in active surveillance of clinical quality improvement programs, especially for drugs which enter the market under an FDA‐mandated Risk Evaluation and Mitigation Strategy (REMS). Our modeling framework attempts to jointly model two important aspects of prescribing, the time between a drug's initial marketing and a patient's first prescription of that drug, and the presence of risk‐mitigating behavior at the first prescription. First prescription times can be flexibly modeled as a mixture of component distributions to accommodate different subpopulations and allow the proportion of prescriptions that exhibit risk‐mitigating behavior to change for each component. Risk‐mitigating behavior is defined in the context of each drug. We develop a joint model using a mixture of positive unimodal distributions to model first prescription times, and a logistic regression model conditioned on component membership to model the presence of risk‐mitigating behavior. We apply our model to two recently approved extended release/long‐acting (ER/LA) opioids, which have an FDA‐approved blueprint for best prescribing practices to inform our definition of risk‐mitigating behavior. We also apply our methods to simulated data to evaluate their performance under various conditions such as clustering.
Topotecan reduces sepsis‐induced acute lung injury and decreases the inflammatory response via the inhibition of the NF‐κB signaling pathway
Authors: Wang Xiaoxia , Xu Tianxiang , Jin Jiajia , Ting Gao M. M. , Wan Bing , Gong Mei , Bai Lingxiao , Lv Tangfeng , Song Yong 
Published: April 2022

AbstractThis study aims to determine the function of topotecan (TPT) in acute lung injury (ALI) induced by sepsis. The mouse sepsis model was constructed through cecal ligation and puncture (CLP). The ALI score and lung wet/dry (W/D) weight ratio were applied to evaluate the level of lung injury. Hematoxylin–eosin staining was used to examine the role of TPT in lung tissue in a CLP‐induced ALI mouse model. Enzyme‐linked immunosorbent assay and quantitative real‐time polymerase chain reaction were used to detect the concentrations of inflammatory factors, such as interleukin‐6 (IL‐6), IL‐1β, and tumor necrosis factor‐α. Western blot was used to detect relevant protein levels in the nuclear factor‐κB (NF‐κB) pathway. Moreover, 10‐day survival was recorded by constructing the CLP model. The results indicated that TPT could improve lung tissue damage in mice and could significantly reduce lung injury scores (p < 0.01) and the W/D ratio (p < 0.05). Treatment with ammonium pyrrolidinedithiocarbamate obtained the similar results with the TPT treatment. Both significantly reduced the inflammatory response in the lungs, including reducing the number of neutrophils and total cells in the bronchoalveolar lavage fluid (BALF), significantly reducing the total protein concentration of the BALF, and significantly inhibiting the activity of MPO. Both also inhibited inflammatory cytokine expression and the levels of NF‐κB pathway proteins induced by sepsis. Furthermore, TPT significantly improved survival in sepsis. TPT improves ALI in the CLP model by inhibiting the NF‐κB pathway, preventing fatal inflammation.
Using the GenCut core biopsy tool with the radial endobronchial ultrasound guide sheath enables a high‐quality histology sample capable of programmed cell death ligand 1 (PD‐L1) testing
Authors: Herath Samantha , Bashirzadeh Farzad , Mahajan Hema , Ing Alvin , Fielding David 
Published: April 2022

AbstractRadial EndoBronchial UltraSound (R‐EBUS)‐guided biopsies are a promising biopsy technique for pulmonary nodules suspected of lung cancer with great safety profile. Programmed cell death ligand 1 (PD‐L1) testing is increasingly demanded from lung biopsies. GenCut is a novel blunt tool that can be used to obtain core biopsies. This case series explores prospective performance of the GenCut core biopsy with R‐EBUS. Once Peripheral Pulmonary Lesion was located, GenCut biopsy was performed followed by conventional (forceps ± cytology brush) R‐EBUS biopsies. The overall diagnostic yield for the 16 patients with a mean peripheral pulmonary lesion (PPL) size of 4.1 cm was 100% from multi‐modal R‐EBUS sampling. The diagnostic yield for GenCut tool alone was 13/16 (81.2%) and the ability to perform PD‐L1 from GenCut was 10/16 (62.5%). There were no adverse events recorded. GenCut tool is a novel blunt instrument that can be used safely to obtain a core biopsy suitable for PD‐L1 in combination with R‐EBUS without compromising the high safety profile.
Overall recursive least squares and overall stochastic gradient algorithms and their convergence for feedback nonlinear controlled autoregressive systems
Authors: Wei Chun , Zhang Xiao , Xu Ling , Ding Feng , Yang Erfu 
Published: April 2022

AbstractThis article deals with the problems of the parameter estimation for feedback nonlinear controlled autoregressive systems (i.e., feedback nonlinear equation‐error systems). The bilinear‐in‐parameter identification model is formulated to describe the feedback nonlinear system. An overall recursive least squares algorithm is developed to handle the difficulty of the bilinear‐in‐parameter. For the purpose of avoiding the heavy computational burden, an overall stochastic gradient algorithm is deduced and the forgetting factor is introduced to improve the convergence rate. Furthermore, the convergence analysis of the proposed algorithms are established by means of the stochastic process theory. The effectiveness of the proposed algorithms are illustrated by the simulation example.
Evaluation of discharge measurements methods in a natural river of low or middle flow using an electromagnetic flow meter
Authors: Pantelakis Dimitrios , Doulgeris Charalampos , Hatzigiannakis Evangelos , Arampatzis George 
Published: April 2022

AbstractMeasurement of river discharge should be accurate, as it is key environmental data and essential for hydrologic simulations, regardless of whether the flow is high, medium, or low. Herein, conventional methods based on velocity measurements at different depths (i.e., one‐point method, two‐point method, and three‐point method) are evaluated with a method using a surface velocity index and a method based on the entropy theory to estimate river discharge. All the methods were implemented to calculate the discharge of Agios Germanos River, located in Northern Greece, based on 2 years of measurement. Considering that the uncertainty in flow measurement is decreasing by increasing the number of velocity measurements points (EN ISO, 2007), in this work, the reference method is the conventional three‐point method. Results show that the other two conventional methods (the one‐point and the two‐point) estimate the discharge with an error of about 3%, while the error of the other two methods ranges between 11 and 14%. Nevertheless, the nonconventional methods could be considered acceptable and could be used safely to minimize time and subsequently, the cost of field measurements.
A study of the impact of COVID‐19 on the Chinese stock market based on a new textual multiple ARMA model
Authors: Xu Weijun , Fu Zhineng , Li Hongyi , Huang Jinglong , Xu Weidong , Luo Yiyang 
Published: April 2022

AbstractCoronavirus 2019 (COVID‐19) has caused violent fluctuation in stock markets, and led to heated discussion in stock forums. The rise and fall of any specific stock is influenced by many other stocks and emotions expressed in forum discussions. Considering the transmission effect of emotions, we propose a new Textual Multiple Auto Regressive Moving Average (TM‐ARMA) model to study the impact of COVID‐19 on the Chinese stock market. The TM‐ARMA model contains a new cross‐textual term and a new cross‐auto regressive (AR) term that measure the cross impacts of textual emotions and price fluctuations, respectively, and the adjacent matrix which measures the relationships among stocks is updated dynamically. We compute the textual sentiment scores by an emotion dictionary‐based method, and estimate the parameter matrices by a maximum likelihood method. Our dataset includes the textual posts from the Eastmoney Stock Forum and the price data for the constituent stocks of the FTSE China A50 Index. We conduct a sliding‐window online forecast approach to simulate the real‐trading situations. The results show that TM‐ARMA performs very well even after the attack of COVID‐19.
The Synthesis of New Triazole‐Linked Supramolecules Based on Bis‐[1,3]‐Naphthodioxocines
Authors: Ozukanar Ozge , Talinli Naciye , Kumbaraci Volkan 
Published: April 2022

AbstractIn this study, the synthesis of novel three molecular cages based on bis‐structure of 8,16‐methano‐16H‐dinaphtho[2,1‐d: 1’,2’‐g][1,3]dioxocine (DNDO) is reported. The linkers between bis‐DNDO structures are bearing both etheric structures and bis(1,2,3‐triazole) moieties that are acting also as coordination ligands. The cavities of the molecular cages change depending of the position of dioxocine ring oxygens.
A Dual‐Modal Single‐Antibody Plasmonic Spectro‐Immunoassay for Detection of Small Molecules
Authors: Zheng Peng , Wu Lintong , Raj Piyush , Mizutani Takayuki , Szabo Miklos , Hanson William A. , Barman Ishan 
Published: April 2022

AbstractSmall molecules play a pivotal role in regulating physiological processes and serve as biomarkers to uncover pathological conditions and the effects of therapeutic treatments. However, it remains a significant challenge to detect small molecules given the size as compared to macromolecules. Recently, the newly emerging plasmonic immunoassays based on surface‐enhanced Raman scattering (SERS) offer great promise to deliver extraordinary sensitivity. Nevertheless, they are limited by the intrinsic SERS intensity fluctuations associated with the SERS uncertainty principle. The single transducer that relies on the intensity change is also prone to false signals. Additionally, the prevailing sandwich immunoassay format proves less effective towards detecting small molecules. To circumvent these critical issues, a dual‐modal single‐antibody approach that synergizes both the intensity and shift of the peak‐based immunoassay with Raman enhancement, coined as the INSPIRE assay, is developed for small molecules detection. With two independent transduction mechanisms, it allows better prediction of analyte concentration and attenuation of signal artifacts, providing a new and robust strategy for molecular analysis. With a proof‐of‐concept demonstration for detection of free T4 and testosterone in serum matrix, the authors envision that the INSPIRE assay could be expanded for a wide spectrum of applications in biomedical diagnosis, discovery of new biopharmaceuticals, food safety, and environmental monitoring.
Facilitating Reversible Cation Migration and Suppressing O2 Escape for High Performance Li‐Rich Oxide Cathodes
Authors: Chai Ke , Zhang Jicheng , Li Qingyuan , Wong Deniz , Zheng Lirong , Schulz Christian , Bartkowiak Maciej , Smirnov Dmitry , Liu Xiangfeng 
Published: April 2022

AbstractHigh‐capacity Li‐rich Mn‐based oxide cathodes show a great potential in next generation Li‐ion batteries but suffer from some critical issues, such as, lattice oxygen escape, irreversible transition metal (TM) cation migration, and voltage decay. Herein, a comprehensive structural modulation in the bulk and surface of Li‐rich cathodes is proposed through simultaneously introducing oxygen vacancies and P doping to mitigate these issues, and the improvement mechanism is revealed. First, oxygen vacancies and P doping elongates OO distance, which lowers the energy barrier and enhances the reversible cation migration. Second, reversible cation migration elevates the discharge voltage, inhibits voltage decay and lattice oxygen escape by increasing the Li vacancy‐TM antisite at charge, and decreasing the trapped cations at discharge. Third, oxygen vacancies vary the lattice arrangement on the surface from a layered lattice to a spinel phase, which deactivates oxygen redox and restrains oxygen gas (O2) escape. Fourth, P doping enhances the covalency between cations and anions and elevates lattice stability in bulk. The modulated Li‐rich cathode exhibits a high‐rate capability, a good cycling stability, a restrained voltage decay, and an elevated working voltage. This study presents insights into regulating oxygen redox by facilitating reversible cation migration and suppressing O2 escape.
Full‐Color Long‐Lived Room Temperature Phosphorescence in Aqueous Environment
Authors: Zheng Yan , Zhou Qian , Yang Yan , Chen Xiaohong , Wang Chang , Zheng Xian , Gao Liang , Yang Chaolong 
Published: April 2022

AbstractLong‐lived room temperature phosphorescence (RTP) materials are widely utilized in the field of biological and chemical sensing, due to their unique characteristics of long‐lived luminescence and no background autofluorescence. However, the realization of full‐color RTP in aqueous solution still remains a great challenge. Herein, a feasible strategy for achieving high stability and full‐color RTP of carbon dots (CDs)‐based composite materials in aqueous environment is reported by constructing a rigid hydrogen bonds’ network. The obtained m,p‐CDs@CA composite materials exhibit deep‐blue RTP with phosphorescence quantum yield of 23.2% and lifetime of 1.74 s, and the afterglow can last for over 12 s. More importantly, the m,p‐CDs@CA composite materials are desirable in the detection of biomarkers, because of excellent stability, dispersion, and long‐lived RTP properties. The m,p‐CDs@CA suspension also displays excellent sensitivity, and a limitation of detection as low as 5.61 and 550 nm for biomarkers 5‐hydroxyindole‐3‐acetic acid (HIAA) and serotonin (5‐hydroxytryptamine, HT), respectively. Meanwhile, the sensing performance exhibits excellent selectivity even in the presence of other competitive species in blood plasma and urine. With superior selectivity, the long‐lived phosphorescence probe based on m,p‐CDs@CA suspension can be as an effective biomarker for carcinoid identification, which has potential application in clinical analysis.
3D Nanoscale Mapping of Short‐Range Order in GeSn Alloys
Authors: Liu Shang , Covian Alejandra Cuervo , Wang Xiaoxin , Cline Cory T. , Akey Austin , Dong Weiling , Yu Shui‐Qing , Liu Jifeng 
Published: April 2022

AbstractGeSn on Si has attracted much research interest due to its tunable direct bandgap for mid‐infrared applications. Recently, short‐range order (SRO) in GeSn alloys has been theoretically predicted, which profoundly impacts the band structure. However, characterizing SRO in GeSn is challenging. Guided by physics‐informed Poisson statistical analyses of k‐nearest neighbors (KNN) in atom probe tomography (APT), a new approach is demonstrated here for 3D nanoscale SRO mapping and semi‐quantitative strain mapping in GeSn. For GeSn with ≈14 at. % Sn, the SRO parameters of Sn–Sn 1NN in 10 × 10 × 10 nm3 nanocubes can deviate from that of the random alloys by ±15 %. The relatively large fluctuation of the SRO parameters contributes to band‐edge softening observed optically. Sn–Sn 1NN also tends to be more favored toward the surface, less favored under strain relaxation or tensile strain, while almost independent of local Sn composition. An algorithm based on least square fit of atomic positions further verifies this Poisson‐KNN statistical method. Compared to existing macroscopic spectroscopy or electron microscopy techniques, this new APT statistical analysis uniquely offers 3D SRO mapping at nanoscale resolution in a relatively large volume with millions of atoms. It can also be extended to investigate SRO in other alloy systems.
A Robust Method for Perfusable Microvascular Network Formation In Vitro
Authors: Wan Zhengpeng , Zhong Amy X. , Zhang Shun , Pavlou Georgios , Coughlin Mark F. , Shelton Sarah E. , Nguyen Huu Tuan , Lorch Jochen H. , Barbie David A. , Kamm Roger D. 
Published: April 2022

AbstractMicropost‐based microfluidic devices are widely used for microvascular network (MVN) formation in diverse research fields. However, consistently generating perfusable MVNs of physiological morphology and dimension has proven to be challenging. Here, how initial seeding parameters determine key characteristics of MVN formation is investigated and a robust two‐step seeding strategy to generate perfusable physiological MVNs in microfluidic devices is established.
A work of art in concrete
Authors: Niens Michiel , Loosjes Myrte , Peters Pim 
Published: April 2022

AbstractThe precious collection of the Museum Boijmans van Beuningen in Rotterdam has regularly suffered from floods in the past. When the depot in the museum's basement flooded for the umpteenth time in 2004, it was time for action and the idea for the “Depot Boijmans van Beuningen” was born. Initially conceived as a traditional depot, the decision was later made to make the building fully accessible to the public, thus providing insight into the preservation and management of the important art collection. This concept, unique in the world, does, however, involve considerable challenges, such as maintaining the indoor climate and guaranteeing the security of the public building. For the client and the architect, it was a major task to define the design for the Boijmans van Beuningen Depot and the indoor usage as well. For the structural engineer, it was a challenge to design a rational and functional construction. Concrete plays an important role in addressing this challenge. Obviously, all options had to be examined and alternatives had to be proposed to achieve the most optimal integral result.
Structural and load parameter estimation of a real‐world reinforced concrete slab bridge using measurements and Bayesian statistics
Authors: Rózsás Árpád , Slobbe Arthur , Martini Giulia , Jansen Rob 
Published: April 2022

AbstractThis paper describes a static diagnostic load testing and measurement campaign of a reinforced concrete road bridge in Amsterdam. We consider 29 vertical translation sensors and 37 strain sensors. Multiple Bayesian parameter estimations are performed to estimate two structural and two load parameters of a three‐dimensional finite element (FE) model. The structural parameters are the concrete elastic modulus of the deck and the rotational spring stiffness at the piers. The load (truck) parameters are the load mass and position, which are estimated from separate measurements. We found that estimating (updating) the two selected structural parameters considerably improves the vertical translation model prediction accuracy over the FE model that was built before the measurement campaign, that is, the R2 score increases from 0.90 to 0.98. Moreover, the load (truck) mass and position parameters can be estimated with high accuracy and high precision. When all measurements are used, the load mass and position are estimated with an error, respectively, less than 1.5 tonnes and 0.5 m with respect to the ground truth. On the negative side: when only certain strain measurements are used, the 90% posterior credible interval is about 3 m and 10 tonnes off the ground truth. Although the results are promising, they are restricted to the considered case and, more importantly, to operational loading conditions where the loading is well controlled. All data, models, and code are freely available upon request.