bluuebunny/crossref_metadata_2025_split huggingface dataset:
Serum CD109 levels reflect the node metastasis status in head and neck squamous cell carcinoma
Authors: Hagiwara Sumitaka , Sasaki Eiichi , Hasegawa Yasuhisa , Suzuki Hidenori , Nishikawa Daisuke , Beppu Shintaro , Terada Hoshino , Sawabe Michi , Takahashi Masahide , Hanai Nobuhiro 
Published: February 2021

AbstractBackgroundVarious biomarkers are being developed for the early diagnosis of cancer and for predicting its prognosis. The aim of this study is to evaluate the diagnostic significance of serum CD109 in head and neck squamous cell carcinoma (HNSCC).MethodsThe serum CD109 levels in a total of 112 serum samples collected before and after surgery from 56 HNSCC patients were analyzed with an enzyme‐linked immunosorbent assay (ELISA). The clinical factor that showed a statistically significant association with both the preoperative serum CD109 level, and the CD109 index: which was defined as the ratio of the preoperative serum CD109 level to the postoperative serum CD109 level, were assessed. The correlations between the serum CD109 levels and lymph node density (LND), pathological features such as lymphatic invasion, and serum SCC antigen levels were also assessed.ResultsThe ELISA measurement revealed that preoperative serum CD109 levels were elevated in patients with node metastasis‐positive and stage IV disease, in comparison to those with node metastasis‐negative and Stage I+II+III disease, respectively. A multiple regression analysis indicated that serum CD109 level was significantly associated with the node metastasis status. A Spearman's rank correlation analysis also revealed a positive correlation between the preoperative serum CD109 level and LND. Furthermore, the probabilities of the overall and relapse‐free survival were significantly lower in patients with a preoperative serum CD109 level of ≥38.0 ng/ml and a CD109 index of ≥1.6, respectively, than in others. There was no significant correlation between the serum CD109 and SCC antigen levels.ConclusionsThe serum CD109 levels were elevated in patients with advanced stage disease, reflecting the node metastasis status. CD109 in sera could be a novel prognostic marker for HNSCC involving lymph node metastasis.
DNA‐Targeted Metallodrugs: An Untapped Source of Artificial Gene Editing Technology
Authors: Fantoni Nicolò Zuin , Brown Tom , Kellett Andrew 
Published: February 2021

AbstractDNA binding metal complexes are synonymous with anticancer drug discovery. Given the array of structural and chemical reactivity properties available through careful design, metal complexes have been directed to bind nucleic acid structures through covalent or noncovalent binding modes. Several recognition modes – including crosslinking, intercalation, and oxidation – are central to the clinical success of broad‐spectrum anticancer metallodrugs. However, recent progress in nucleic acid click chemistry coupled with advancement in our understanding of metal complex–nucleic acid interactions has opened up new avenues in genetic engineering and targeted therapies. Several of these applications are enabled by the hybridisation of oligonucleotide or polyamine probes to discrete metal complexes, which facilitate site‐specific reactivity at the nucleic acid interface under the guidance of the probe. This Review focuses on recent advancements in hybrid design and, by way of an introduction to this topic, we provide a detailed overview of nucleic acid structures and metal complex–nucleic acid interactions. Our aim is to provide readers with an insight on the rational design of metal complexes with DNA recognition properties and an understanding of how the sequence‐specific targeting of these interactions can be achieved for gene engineering applications.
Liquid film thickness of two‐phase slug flows in capillary microchannels: A review paper
Authors: Etminan Amin , Muzychka Yuri S. , Pope Kevin 
Published: February 2021

AbstractTwo‐phase Taylor flow has received considerable attention from researchers in recent decades due to its potential use in a wide variety of industrial and medical applications. A large number of experimental, analytical, and numerical efforts have been taken by researchers to understand the fundamental characteristics of two‐phase flows and the relevant transport phenomena. This paper presents a comprehensive review of the hydrodynamics, flow pattern, and liquid film thickness in two‐phase flows through mini‐ and microchannels with different cross‐sectional geometry. This paper also reviews correlations that predict liquid film thickness in microchannels for gas‐liquid and liquid‐liquid flows. The variations of liquid film thickness are plotted over a wide range of capillary numbers for both experimental and computational studies. This study shows that the effects of cross‐sectional area on the flow patterns and flow characteristics have not been sufficiently investigated by researchers, particularly for rectangular cross‐sectional areas with different aspect ratios.
Genetic‐based multi‐objective optimization of alkylation process by a hybrid model of statistical and artificial intelligence approaches
Authors: Mahmoudian Farimah , Moghaddam Amin Hedayati , Davachi Seyed Mohammad 
Published: February 2021

AbstractThe purpose of this research is to find the optimal operating point in the production process of the cumene. Therefore, the production process was optimized through statistical and genetic algorithm‐based methods. The performance of an alkylation reactor was optimized through maximizing the yield of cumene production. Response surface methodology (RSM) with design type of central composite was applied for design of experiment, modelling, and optimizing the process. The analysis of variance (ANOVA) was performed for finding the important operative parameters as well as their effects. The effects of three parameters including temperature, reactor length, and pressure on the alkylation process were investigated. Further, two types of feed‐forward neural network were applied to model the alkylation reactor. To develop the neural network model, leave‐one‐out method was used. The best prediction performance belonged to a fitting network with 2 and 8 neurons in the hidden layer, respectively. This model was used for optimizing the performance of the alkylation reactor. The statistical and artificial intelligence systems were capable of prediction of cumene production yield in different conditions with R2 of 0.9098 and 0.9986, respectively. Genetic algorithm‐based optimization was performed by the developed neural network model. The maximum accessible value of cumene production yield was 0.7771, which can be achieved when the temperature, length of reactor, and column pressure are 160°C, 2 m, and 4000 kPa, respectively. By finding the optimal operating point in the cumene production process, capital cost, energy consumption, and other operating costs can be significantly reduced.
Alkoxyl side‐chain effects of acidic ionic liquids catalysts for the esterification of n‐butyl butyrate
Authors: Feng Xiantao , Wang Qiannan , Wang Mengyang , Liu Liang 
Published: February 2021

AbstractThree kinds of alkoxy group‐functionalized acidic ionic liquids (ILs) are reported in this work, namely, 1‐(methoxyethyl)‐3‐methylimidazolium hydrogen sulphate [MOE‐MIM]HSO4, 1‐(ethyoxyethyl)‐3‐methylimidazolium hydrogen sulphate [EOE‐MIM]HSO4, and 1‐(propyoxyethyl)‐3‐methylimidazolium hydrogen sulphate [POE‐MIM]HSO4. The short side chain on the cation of [MOE‐MIM]HSO4decreases the solubility of the IL in butanol and butyric acid and facilitates the separation of the IL from a reaction medium. The yield of butyl butyrate is up to 99.5%. After 10 rounds of recycling, the catalytic performance of [MOE‐MIM]HSO4shows no significant changes.
Prediction and analysis of thermal‐hydraulic performance of tubes with teardrop dimples based on artificial neural networks
Authors: Lei Xiang‐shu , Li Jin‐bo , Qi Xin , Liu Ying‐wen 
Published: February 2021

AbstractIn this study, the prediction and analysis of the thermal‐hydraulic performance of tubes with teardrop dimples were carried out. First, a numerical model of dimpled tubes using ANSYS 17.0 was established and verified by comparison with the Nusselt number (Nu) and friction factor (f) in the literature. Second, artificial neural networks (ANNs) were developed with five neurons in the input layer, the hidden layers of various neurons, and one neuron in the output layer. The five neurons are the diameter of the windward sphere (d1), diameter of the leeward sphere (d2), dimple depth (hd), spacing between two axially adjacent dimples (l), and quantity of dimples in a transverse cross‐section (N). After careful comparison, the model with the 5‐2‐6‐1 structure was selected for predicting both f and Nu, while the model with the 5‐6‐1 structure was selected for performance evaluation criteria (PEC). Finally, the influence of d2/d1 on the heat transfer and pressure drop is discussed when l/d1 or N changes. The results showed when N is moderate or l/d1 is large within the scope of the design, the heat transfer performance in the windward part of the teardrop dimples is better than that of the spherical dimples. In addition, as N increases or l/d1 decreases, the influence of dimples on the main flow increases, making the mixture of hot and cold working fluid better but causing a greater pressure drop. This study may provide ideas and guidance for the design, selection, and optimization of dimpled tubes.
Root coverage stability: A systematic overview of controlled clinical trials with at least 5 years of follow‐up
Authors: Bertl Kristina , Spineli Loukia M. , Mohandis Khalid , Stavropoulos Andreas 
Published: February 2021

AbstractObjectivesTo systematically assess the long‐term outcome (≥5 years) of root coverage procedures reported in controlled clinical trials.Material and MethodsLiterature search was performed according to the PRISMA guidelines with the following eligibility criteria: (a) English or German language; (b) controlled (CT) or randomised controlled clinical trials (RCT); (c) root coverage procedure with ≥5 years follow‐up; and (d) clinical treatment effect size and/or patient‐related outcome measures (PROMs) reported.ResultsFour CT and 14 RCT with a follow‐up of 5–20 years fulfilled the eligibility criteria; sample size per study ranged from 8 to 70 patients contributing with 18–149 sites. Coronally advanced flap (CAF) and CAF + connective tissue graft (CTG) were the prevalent treatments (i.e., in 24 and 38% of the groups, respectively), while other flap designs and adjuncts (i.e., enamel matrix derivative, bone graft, collagen membrane) were represented only once. For single Miller class I/II gingival recessions (GR), CAF + CTG appeared advantageous compared to other techniques, and provided low residual recession depths (i.e., ≤0.5 mm), and complete root coverage in ≥2/3 of the patients; similar tendency was observed for multiple GR. No data on Miller class III/IV GR is available. No meta‐analysis was feasible due to lack of similarity in the clinical and methodological characteristics across the trials and observed comparisons of interventions.ConclusionsCAF + CTG appears to be the ‘gold standard’ technique for the treatment of single and multiple Miller class I/II GR also in regard to long‐term (i.e., ≥5 years of follow‐up) treatment outcomes. There is little information regarding the performance, on the long‐term, of other techniques and adjuncts.
Kernel weight responses to the photothermal environment in maize dent × flint and flint × flint hybrids
Authors: Hisse Ignacio R. , D’Andrea Karina E. , Otegui María E. 
Published: February 2021

AbstractMaize (Zea mays L.) grain yield is assumed to be source limited during the flowering period but sink limited during grain growth; however, environmental restrictions during active grain filling may strongly affect final kernel weight (KW). In this study, we evaluated the effect of natural changes in photothermal conditions during lag phase (LP) and effective grain‐filling period (EGFP) on KW, its physiological determinants, and the post‐flowering source–sink relationships of flint and semident germplasm. F1 hybrids of flint × flint and dent × flint background were tested during four seasons (Y1, Y2, Y3, and Y4). Across years, the highest KW (286 mg) was obtained under the maximum photothermal quotients during LP (PTQLP = 1.18 MJ m−2 °C−1) and EGFP (PTQEGFP = 1.07 MJ m−2 °C−1) of Y2, whereas the smallest KW (252 mg) and source–sink ratio during grain filling was obtained under the lowest PTQEGFP (.79 MJ m−2 °C−1) of Y3. Supra‐optimum temperatures during LP of Y3 negatively affected potential KW determination, and hence kernel growth rate (P < .001) as a result of reduced assimilate availability per kernel. Hybrids dent × flint exhibited higher grain yield, kernel number, and plant growth around flowering than flint × flint throughout evaluated seasons but had reduced source–sink relationship during grain filling (P < .05) and increased KW sensitivity (P < .001) to changes in the photothermal conditions. Results emphasized the importance of the photothermal environment during grain filling on KW determination (particularly for seasons with great photothermal imbalance between filling subphases) as well as the dependency of KW responses on the genetic background.
Asymmetrical multilevel inverter topology with low total standing voltage and reduced switches count
Authors: Arif M. Saad Bin , Sarwer Zeeshan , Siddique Marif Daula , Md. Ayob Shahrin , Iqbal Atif , Mekhilef Saad 
Published: February 2021

SummaryThis paper presented an improved asymmetrical multilevel inverter module with reduced switches count. The basic module is capable of producing 15 level outputs with four dc sources and 10 switches. The proposed topology has an inherent ability to generate negative voltage levels, made it possible to utilize lower rating switches, and has lower total standing voltage. To have more number of levels, a series‐connected cascade extension of the module has been done. The three different algorithms for selecting the magnitude of dc sources are proposed. The generalized relations for different parameters are based on the number of added basic units and the number of presented levels for each source selection algorithm. Nearest level control (NLC) is used as the modulation technique. A comparative study shows that the developed topology outperformed other selected existing topologies on many parameters. The performance of the module is evaluated through detailed simulation and power loss analysis. Accuracy of the obtained simulation results is validated through proper experimental testing of the circuit in the laboratory.
A quick approach for medetomidine enantiomer determination in dog plasma by chiral liquid chromatography–tandem mass spectrometry and application to a pharmacokinetic study
Authors: Bardhi Anisa , Zaghini Anna , Levionnois Olivier , Barbarossa Andrea 
Published: February 2021

AbstractIn the present study, a rapid, sensitive and high‐throughput liquid chromatography–tandem mass spectrometry (LC–MS/MS) method for the determination of medetomidine enantiomers in dog plasma was developed and validated. The separation and individual quantification of chiral compounds can be a tricky task in LC. This is particularly true when target analytes have a relatively small mass, as is the case with medetomidine, a potent and highly specific α2‐adrenoceptor agonist widely used in both human and veterinary medicine. The proposed approach is based on a quick liquid–liquid extraction with ethyl acetate and filtration prior to injection. The optimized mobile phase composition allowed to perfectly separate the two enantiomers of medetomidine in a short chromatographic run time, using a cellulose tris(4‐methylbenzoate)‐based chiral column. A lower limit of quantification of 0.1 ng/mL was reached for both analytes thanks to the high sensitivity and selectivity of MS/MS and the use of racemic medetomidine‐d3 as internal standard prevented potential matrix effect. Linearity was satisfying (R2 > 0.99) over the range 0.1–25 ng/mL, as well as within‐ and between‐session accuracy and precision, both always <15%. This method was also applied with success to a series of samples from a pharmacokinetic (PK) study aimed at comparing dex‐ and levomedetomidine behaviour after administration of the racemic mixture in dogs. The simple extraction procedure, which allows reduced solvent and time consumption without compromising analytical performances, makes this technique a useful tool for this kind of applications even when small animals are involved, due to the small amount of sample required.
First phylogenetic analysis of Dryophthorinae (Coleoptera, Curculionidae) based on structural alignment of ribosomal DNA reveals Cenozoic diversification
Authors: Chamorro Maria Lourdes , de Medeiros Bruno A. S. , Farrell Brian D. 
Published: February 2021

AbstractDryophthorinae is an economically important, ecologically distinct, and ubiquitous monophyletic group of pantropical weevils with more than 1,200 species in 153 genera. This study provides the first comprehensive phylogeny of the group with the aim to provide insights into the process and timing of diversification of phytophagous insects, inform classification and facilitate predictions. The taxon sampling is the most extensive to date and includes representatives of all five dryophthorine tribes and all but one subtribe. The phylogeny is based on secondary structural alignment of 18S and 28S rRNA totaling 3,764 nucleotides analyzed under Bayesian and maximum likelihood inference. We used a fossil‐calibrated relaxed clock model with two approaches, node‐dating and fossilized birth‐death models, to estimate divergence times for the subfamily. All tribes except the species‐rich Rhynchophorini were found to be monophyletic, but higher support is required to ascertain the paraphyly of Rhynchophorini with more confidence. Nephius is closely related to Dryophthorini and Stromboscerini, and there is strong evidence for paraphyly of Sphenophorina. We find a large gap between the divergence of Dryophthorinae from their sister group Platypodinae in the Jurassic‐Cretaceous boundary and the diversification of extant species in the Cenozoic, highlighting the role of coevolution with angiosperms in this group.
A geographical perspective on the relationship between Impatiens spur lengths and bill lengths of sunbirds in Afrotropical mountains
Authors: Hořák David , Janeček Štěpán 
Published: February 2021

AbstractTrait matching—a correlation between the morphology of plants and their pollinators—has been frequently observed in pollination interactions. Different intensities of natural selection in individual regions should cause such correlations to be observable across different local assemblages. In this study, we focused on matching between spur lengths of the genus Impatiens and bill lengths of sunbirds in tropical Africa. For 25 mountain and island locations, we compiled information about the composition and traits of local Impatiens and sunbird assemblages. We found that assemblage mean and maximum values of bill lengths were positively correlated with mean and maximum spur lengths across locations. Moreover, our results suggest that the positive correlations hold only for forest sunbird assemblages sharing the same habitat with Impatiens species. We further show that long‐billed sunbirds seem to locally match the morphology of multiple Impatiens plant species, not vice versa. Our observation implies that trait matching significantly contributes to structuring of Impatiens–sunbird pollination systems. We suggest that special habitat preferences together with spatial isolation of mountain environment might play a role in this case.
Sensitivity of productivity to precipitation amount and pattern varies by topographic position in a semiarid grassland
Authors: Hoover David L. , Lauenroth William K. , Milchunas Daniel G. , Porensky Lauren M. , Augustine David J. , Derner Justin D. 
Published: February 2021

AbstractAboveground net primary productivity (ANPP) in grasslands is an important integrator of terrestrial ecosystem function, a key driver of global biogeochemical cycles, and a critical source of food for wild and domesticated herbivores. ANPP exhibits high spatial and temporal variability, driven by a suite of factors including precipitation amount and pattern, biotic and abiotic legacies, and topographic heterogeneity. Global climate models forecast an altered hydrological cycle due to climate change, including higher precipitation variability and more extreme events, which may further increase spatiotemporal variability in ANPP. Therefore, it is essential to understand the sensitivity of this central ecosystem function to various precipitation metrics, legacies, and topographic positions to better inform sustainable grassland management. In this study, we analyzed long‐term (36‐yr) ANPP data collected across a topographic sequence in the semiarid shortgrass steppe of North America to examine patterns and drivers of spatiotemporal variability in ANPP. We observed that (1) ANPP varied substantially by topographic position, with greater divergence during years with high production, (2) ANPP variability was higher temporally (16‐fold maximum difference across years) than spatially (4‐fold maximum difference across topographic positions), (3) warm‐season perennial grasses were the dominant plant functional type across all topographic positions and strongly influenced total ANPP dynamics, and (4) ANPP had strong sensitivities to current year precipitation amount and pattern that varied by plant functional type, as well as weaker sensitivities to precipitation and productivity legacies. Overall, the lowest topographic position had the highest sensitivity to precipitation, likely due to higher resource availability via the downhill movement of water and nutrients during years with high precipitation and large rainfall events. These results suggest that temporal and spatial ANPP variability in shortgrass steppe is primarily driven by the combined effects of precipitation amount and pattern during the current year, with the dominant warm‐season perennial grasses governing these responses.
Resolving trained immunity with systems biology
Authors: Koeken Valerie A.C.M. , van Crevel Reinout , Netea Mihai G. , Li Yang 
Published: February 2021

AbstractTrained immunity is characterized by long‐term functional reprogramming of innate immune cells following challenge with pathogens or microbial ligands during infection or vaccination. This cellular reprogramming leads to increased responsiveness upon restimulation, and is mediated through epigenetic and metabolic modifications. In this review, we describe how molecular mechanisms underlying trained immunity, for example, induced by β‐glucan or Bacille Calmette‐Guérin (BCG) vaccination, can be investigated by using and integrating different layers of information including genome, epigenome, transcriptome, proteome, metabolome, microbiome, immune cell phenotyping, and function. We also describe the most commonly used experimental and computational techniques. Finally, we provide a number of examples of how a systems biology approach was applied to study trained immunity to understand interindividual variation or the complex interplay between molecular layers. In conclusion, trained immunity represents an opportunity for regulating innate immune function, and understanding the complex interplay of mechanisms that mediate trained immunity might enable us to employ it as a clinical tool in the future.