bluuebunny/crossref_metadata_2025_split huggingface dataset:
2,2,2‐Trifluoroethanol‐mediated hydroarylation of fluorinated alkynes with indoles: Application to diindolylmethanes
Authors: Flury Philipp , Eppler Olga , Schollmeyer Dieter , Laufer Stefan , Pillaiyar Thanigaimalai 
Published: April 2022

AbstractA new mild and practically simple alkyne hydroarylation protocol for the synthesis of 3‐(indol‐3‐yl)‐3‐(trifluoromethyl)acrylic acid esters by the reaction of indole derivatives with ethyl/methyl 4,4,4‐trifluoro‐3‐(indol‐3‐yl)but‐2‐enoates in trifluoroethanol was developed. This method has the following advantages: no catalyst, atom economy, high yields, broad substrate scope, and large‐scale synthesis. The potential application of this protocol was further demonstrated by the synthesis of a variety of CF3‐substituted synthons and a new class of (un)symmetrical 3,3ʹ‐diindolylmethanes with a quaternary carbon core that might be biologically active.
Multiomics approaches and genetic engineering of metabolism for improved biorefinery and wastewater treatment in microalgae
Authors: Kuo Eva YuHua , Yang Ru‐Yin , Chin Yuan Yu , Chien Yi‐Lin , Chen Yu Chu , Wei Cheng‐Yu , Kao Li‐Jung , Chang Yi‐Hua , Li Yu‐Jia , Chen Te‐Yuan , Lee Tse‐Min 
Published: April 2022

AbstractMicroalgae, a group of photosynthetic microorganisms rich in diverse and novel bioactive metabolites, have been explored for the production of biofuels, high value‐added compounds as food and feeds, and pharmaceutical chemicals as agents with therapeutic benefits. This article reviews the development of omics resources and genetic engineering techniques including gene transformation methodologies, mutagenesis, and genome‐editing tools in microalgae biorefinery and wastewater treatment (WWT). The introduction of these enlisted techniques has simplified the understanding of complex metabolic pathways undergoing microalgal cells. The multiomics approach of the integrated omics datasets, big data analysis, and machine learning for the discovery of objective traits and genes responsible for metabolic pathways was reviewed. Recent advances and limitations of multiomics analysis and genetic bioengineering technology to facilitate the improvement of microalgae as the dual role of WWT and biorefinery feedstock production are discussed.
Predicting student performance in computing courses based on programming behavior
Authors: Araya Ignacio , Beas Victor , Stamulis Katrina , Allende‐Cid Héctor 
Published: April 2022

AbstractIn the context of programming language courses, offering early and personalized assistance to students with difficulties in solving code exercises is fundamental to helping them improve their performance. To this end, it is desirable to detect those students with behavioral patterns that could potentially result in poor performance in a timely manner. In this study, we analyze different behavioral metrics for predicting the performance of students in a 2nd‐year computer science course. Metrics are extracted from practical sessions, that is, code exercise labs that may be finished online during a period of 5–7 days. In addition to well‐known metrics (e.g., the relative time spent solving compilation/execution errors or skills for removing compilation errors), we also incorporate metrics that take into account the work habits of students (e.g., timestamps in which the student has undertaken 25%, 50%, and 75% of the exercise lab) and similarity between codes. With a sample of 224 students from seven different course groups, we construct robust predictors by training different machine learning models, reaching an R2 value of up to 0.40. We also perform a machine learning‐based analysis for detecting the most relevant response variables and analyze their relations to the final grades of students. The results show that the newly considered metrics have enough predictive power to be considered in the model. Finally, we graphically illustrate the nonlinear and seemingly interdependent relations that exist between predictor and response variables.
Germline mutations in penetrant cancer predisposition genes are rare in men with prostate cancer selecting active surveillance
Authors: Brady Lauren , Newcomb Lisa F. , Zhu Kehao , Zheng Yingye , Boyer Hilary , Sarkar Navonil De , McKenney Jesse K. , Brooks James D. , Carroll Peter R. , Dash Atreya , Ellis William J. , Filson Christopher P. , Gleave Martin E. , Liss Michael A. , Martin Frances , Morgan Todd M. , Thompson Ian M. , Wagner Andrew A. , Pritchard Colin C. , Lin Daniel W. , Nelson Peter S. 
Published: April 2022

AbstractBackgroundPathogenic germline mutations in several rare penetrant cancer predisposition genes are associated with an increased risk of aggressive prostate cancer (PC). Our objectives were to determine the prevalence of pathogenic germline mutations in men with low‐risk PC on active surveillance, and assess whether pathogenic germline mutations associate with grade reclassification or adverse pathology, recurrence, or metastases, in men treated after initial surveillance.MethodsMen prospectively enrolled in the Canary Prostate Active Surveillance Study (PASS) were retrospectively sampled for the study. Germline DNA was sequenced utilizing a hereditary cancer gene panel. Mutations were classified according to the American College of Clinical Genetics and Genomics' guidelines. The association of pathogenic germline mutations with grade reclassification and adverse characteristics was evaluated by weighted Cox proportional hazards modeling and conditional logistic regression, respectively.ResultsOverall, 29 of 437 (6.6%) study participants harbored a pathogenic germline mutation of which 19 occurred in a gene involved in DNA repair (4.3%). Eight participants (1.8%) had pathogenic germline mutations in three genes associated with aggressive PC: ATM, BRCA1, and BRCA2. The presence of pathogenic germline mutations in DNA repair genes did not associate with adverse characteristics (univariate analysis HR = 0.87, 95% CI: 0.36–2.06, p = 0.7). The carrier rates of pathogenic germline mutations in ATM, BRCA1, and BRCA2did not differ in men with or without grade reclassification (1.9% vs. 1.8%).ConclusionThe frequency of pathogenic germline mutations in penetrant cancer predisposition genes is extremely low in men with PC undergoing active surveillance and pathogenic germline mutations had no apparent association with grade reclassification or adverse characteristics.
2‐Aminopurine Fluorescence Spectroscopy for Probing a Glucose Binding Aptamer
Authors: Lu Chang , Jimmy Huang Po‐Jung , Zheng Jingkai , Liu Juewen 
Published: April 2022

AbstractGlucose is the most important analyte for biosensors. Recently a DNA aptamer was reported allowing binding‐based detection. However, due to a relatively weak binding affinity, it is difficult to perform binding assays to understand the property of this aptamer. In this work, we replaced the only adenine base in the aptamer binding pocket with a 2‐aminopurine (2AP) and used fluorescence spectroscopy to study glucose binding. In the selection buffer, glucose increased the 2AP fluorescence with a Kd of 15.0 mM glucose, which was comparable with the 10 mM Kd previously reported using the strand displacement assay. The binding required two Na+ ions or one Mg2+ that cannot be replaced by Li+ or K+. The binding was weaker at higher temperature and its van't Hoff plot indicated enthalpy‐driven binding. While other monosaccharides failed to achieve saturated binding even at high concentrations, two glucose‐containing disaccharides, namely trehalose and sucrose, reached a similar fluorescence level as glucose although with over 10‐fold higher Kd values. Detection limits in both the selection buffer (0.9 mM) and in artificial interstitial fluids (6.0 mM) were measured.
Adult‐onset noncirrhotic hyperammonemic encephalopathy probably caused by splenorenal shunts
Authors: Yoshizawa Kazuhiro , Yonezawa Naoki , Takei Tetsuhiro , Sugiki Kei 
Published: April 2022

AbstractThis case illustrates adult‐onset noncirrhotic hyperammonemic encephalopathy, which is most likely caused by splenorenal shunts and is a rare but potentially fatal cause of altered mentation in the critical care setting. Splenorenal shunts should be considered as a differential in cases of hyperammonemic encephalopathy without liver cirrhosis.
Emotional state recognition from text data using machine learning and deep learning algorithm
Authors: Shah Vandana , Mehta Meet 
Published: April 2022

AbstractEmotional state recognition is a process to identify user's feelings and emotions for various purposes. Emotional state examination from text comprises of extricating data about feelings, opinions, and even feelings passed on by scholars toward subjects of interest. Web‐based media is producing a tremendous measure of assessment rich information as remarks, notices, blog entries, and so forth. It is trying to comprehend the most recent patterns and rundowns the state or general feelings about items because of the enormous variety and size of web‐based media information, and this makes the need of computerized and ongoing conclusion extraction and mining. Sentiment analysis is difficult because of the existence of bad or abusive language with misspellings words. One of the major natural language processing research area is inclined toward understanding human emotions. Emotional state analysis acts like an amazing treasure and powerful tool, which renders its service to the field of deep learning. It can help service providers to fetch the requisite information to collect and identify the sentiments of the database. Principle issues that exist in the current procedures are: powerlessness to perform well in various areas, deficient exactness and execution in assessment examination dependent on lacking named information, inadequacy to manage complex sentences that require more than emotional words and basic examining. It is as yet hard for a greater part of instruments to decisively assess what genuinely is a negative, unbiased and a positive articulation. It is not advanced enough to successfully deal with sarcasm or context. So there is requirement to develop a machine learning algorithm to analyze the text data and give more better and accurate results.
A improved detection method for lung nodule based on multi‐scale 3Dconvolutional neural network
Authors: Tan Yumeng , Fu Xupeng , Zhu Jianbo , Chen Lina 
Published: April 2022

AbstractLow detection sensitivity and high false positives are two main challenges from traditional lung nodule detection model. In order to improve reliability of detection model, we proposed a multi‐scale three‐dimensional convolutional neural network lung nodule detection method which can simultaneously detect lung nodules and reduce false positives. First, a 3D UNet++‐like architecture with an encoding‐decoding structure is regarded as a feature extraction network and combines it with the region proposal network. The multi‐feature fusion method can fully learn features at different levels through the cross‐layer connection between the encoder and the decoder. Second, the layers of the 3D UNet++‐like architecture are connected by residual blocks, which enhance feature reuse and speeds up the convergence speed of the network. Finally, the three input sizes are input into the 3D neural network, and their classification results are merged, thus to find the final nodule determination result. Based on the LUNA16 dataset, the experiment result shows that average sensitivity is 87.3% and be increased 7.8% than the UNet++ network in our model. And if the number of candidate nodules is 48, the sensitivity is as high as 96.2%, it increases 8.1% than the VGG16 network. Obviously, that the improved model can significantly improve detection sensitivity and reduce false positives, which can provide a valuable theoretical reference for clinical medicine.
Model‐Based Prediction of Irinotecan‐Induced Grade 4 Neutropenia in Advanced Cancer Patients: Influence of Demographic and Clinical Factors
Authors: Karas Spinel , Mathijssen Ron H. J. , van Schaik Ron H. N. , Forrest Alan , Wiltshire Tim , Innocenti Federico , Bies Robert R. 
Published: April 2022

Severe neutropenia is the major dose‐liming toxicity of irinotecan‐based chemotherapy. The objective was to assess to what extent a population pharmacokinetic/pharmacodynamic model including patient‐specific demographic/clinical characteristics, individual pharmacokinetics, and absolute neutrophil counts (ANCs) can predict irinotecan‐induced grade 4 neutropenia. A semimechanistic population pharmacokinetic/pharmacodynamic model was developed to describe neutrophil response over time in 197 patients with cancer receiving irinotecan. For covariate analysis, sex, race, age, pretreatment total bilirubin, and body surface area were evaluated to identify significant covariates on system‐related parameters (mean transit time (MTT) and ɣ) and sensitivity to neutropenia effects of irinotecan and SN‐38 (SLOPE). The model‐based simulation was performed to assess the contribution of the identified covariates, individual pharmacokinetics, and baseline ANC alone or with incremental addition of weekly ANC up to 3 weeks on predicting irinotecan‐induced grade 4 neutropenia. The time course of neutrophil response was described using the model assuming that irinotecan and SN‐38 have toxic effects on bone marrow proliferating cells. Sex and pretreatment total bilirubin explained 10.5% of interindividual variability in MTT. No covariates were identified for SLOPE and γ. Incorporating sex and pretreatment total bilirubin (area under the receiver operating characteristic curve (AUC‐ROC): 50%, 95% CI 50–50%) or with the addition of individual pharmacokinetics (AUC‐ROC: 62%, 95% CI 53–71%) in the model did not result in accurate prediction of grade 4 neutropenia. However, incorporating ANC only at baseline and week 1 in the model achieved a good prediction (AUC‐ROC: 78%, 95% CI 69–88%). These results demonstrate the potential applicability of a model‐based approach to predict irinotecan‐induced neutropenia, which ultimately allows for personalized intervention to maximize treatment outcomes.
Simultaneous analysis of antigen‐specific B and T cells after SARS‐CoV‐2 infection and vaccination
Authors: Newell Krista L. , Waldran Mitchell J. , Thomas Stephen J. , Endy Timothy P. , Waickman Adam T. 
Published: April 2022

AbstractConventional methods for quantifying and phenotyping antigen‐specific lymphocytes can rapidly deplete irreplaceable specimens. This is due to the fact that antigen‐specific T and B cells have historically been analyzed in independent assays each requiring millions of cells. A technique that facilitates the simultaneous detection of antigen‐specific T and B cells would allow for more thorough immune profiling with significantly reduced sample requirements. To this end, we developed the B and T cell tandem lymphocyte evaluation (BATTLE) assay, which allows for the simultaneous identification of SARS‐CoV‐2 Spike reactive T and B cells using an activation induced marker (AIM) T cell assay and dual‐color B cell antigen probes. Using this assay, we demonstrate that antigen‐specific B and T cell subsets can be identified simultaneously using conventional flow cytometry platforms and provide insight into the differential effects of mRNA vaccination on B and T cell populations following natural SARS‐CoV‐2 infection.
Capacity and turbo equalization for truncated root‐raise cosine‐pulsed modulation systems in the presence of timing offset
Authors: Chiang Wei‐I , Hung Fu‐Chuan , Chung Char‐Dir 
Published: April 2022

SummaryIn communication systems, in order to increase spectrum efficiency, pulses with limited bandwidth that meet the Nyquist zero intersymbol interference criterion are usually used for transmission. However, the truncated pulse is conducive to the realization of the partial response signal transmission system. The actual method is to cut the finite bandwidth pulse into a finite and sufficient length in the time domain. This will make the overall impulse response no longer meet the Nyquist criterion and at the receiving end will produce intentional intersymbol interference, so demodulation requires complex sequence detection. In this paper, we consider the truncated root raised cosine modulation system with timing offset and compare the channel capacity of partial response signals with different parameters. At the receiving end, demodulation uses the turbo equalization with different equalization methods to eliminate the intersymbol interference of partial response signals. Among them, we use fewer symbol paths in the BCJR algorithm to calculate the maximum posterior probability to construct low‐complexity equalization and compare according to the computational complexity and performance results of different equalizations.
Population genomics and phylogeography of Colletes gigas, a wild bee specialized on winter flowering plants
Authors: Su Tianjuan , He Bo , Zhao Fang , Jiang Kai , Lin Gonghua , Huang Zuhao 
Published: April 2022

AbstractDiet specialization may affect the population genetic structure of pollinators by reducing gene flow and driving genetic differentiation, especially in pollen‐specialist bees. Colletes gigas is a pollen‐specialist pollinator of Camellia oleifera, one of the most important staple oil crops in China. Ca. oleifera blooms in cold climates and contains special compounds that make it an unusable pollen source to other pollinators. Thus, C. gigas undoubtedly plays a key role as the main pollinator of Ca. oleifera, with biological and economic significance. Here, we use a population genomic approach to analyze the roles of geography and climate on the genetic structure, genetic diversity, and demographic history of C. gigas. A total of 1,035,407 SNPs were identified from a 582.77 Gb dataset. Clustering and phylogenetic analyses revealed a marked genetic structure, with individuals grouped into nine local clusters. A significant isolation by distance was detected by both the Mantel test (R = .866, p = .008) and linear regression (R2 = .616, p < .001). Precipitation and sunshine duration were positively and significantly (R ≥ .765, p ≤ .016) correlated with observed heterozygosity (Ho) and expected heterozygosity (He). These results showed that C. gigas populations had a distinct phylogeographic pattern determined by geographical distance and environmental factors (precipitation and sunshine duration). In addition, an analysis of paleogeographic dynamics indicated that C. gigas populations exhibited patterns of glacial expansion and interglacial contraction, likely resulting from post‐glacial habitat contraction and fragmentation. Our results indicated that the peculiar phylogeographic patterns in C. gigas populations may be related to their specialization under long‐term adaptation to host plants. This work improves our understanding of the population genetics in pollen‐specialist bees. The distinct genetic clusters identified in this study should be taken into consideration for the protection and utilization of this specialized crop pollinator.
Effects of inorganic fillers on the performance of the water‐based intumescent fire‐retardant coating
Authors: Nasirzadeh Mohammadreza , Yahyaei Hossein , Mohseni Mohsen 
Published: April 2022

SummaryThe purpose of this research was to evaluate the influences of filler type and its content on the performance of a water‐based intumescent fire‐retardant coating. Three fillers (vermiculite, celite, and aluminum hydroxide) were added to the intumescent paint formulation. The thermal and fire protective properties were studied with thermogravimetric analysis (TGA), torch test, electrical furnace, scanning electron microscopy (SEM), and Fourier transform infrared analysis (FTIR). The results showed that adding fillers into coatings up to 3% could improve the intumescent coating's behavior and increase its endurance against flames. Of the three fillers used, vermiculite showed a better performance in the torch test, attributed to its chemical and physical structure. Vermiculite has low thermal conductivity and is considered an appropriate filler for heat‐insulation. The final back‐plate temperatures in the torch test for the vermiculite‐containing samples were around 100°C–150°C lower than that of other samples. Moreover, vermiculite's addition improved the coating's expansion by 10% compared with the control sample's. The vermiculite sample's char layer morphology showed a uniform cell size distribution, indicating structural robustness. The coating samples successfully transformed polypropylene flammability from highly flammable to V0 level in the UL 94 vertical burning test standard. The results showed that vermiculite could improve intumescent paint's fire resistance and be used as an enhancer in intumescent coating formulations.
Re‐examination of the 1928 Parral, Mexico earthquake (M6.3) using a new multiplatform graphical vectorization and correction software for legacy seismic data
Authors: Corona‐Fernández Raúl Daniel , Santoyo Miguel Ángel 
Published: April 2022

AbstractModern analysis of earthquakes depends on digital time series; however, only about 30% of the timespan of recorded seismicity is available in digital format. During the first half of the 20th century, most of the earthquake ground motions in Mexico were recorded by Wiechert mechanical instruments on smoked paper. In this work, we developed and use Tiitba, a new portable multiplatform graphical user interface (GUI) open‐source software coded on python, to vectorize and correct old analogue seismograms. Using this software, we vectorized the 11/1/1928 Parral (M6.3) earthquake seismograms to obtain the constant time‐interval digitized time series for each component and station of the seismogram. Then, we obtained its source focal mechanism using a genetic algorithm methodology. Also, with an auxiliary Tiitba module, we constructed a SEISAN S‐file to relocate the hypocentre of this earthquake. The obtained relocation is about 125 km south of a recently recorded seismic swarm that occurred in 2013, which has a similar focal mechanism to the one that we obtained in this work.
Treatment of a severe distal thoracic and abdominal coarctation with cutting balloon and stent implantation in an infant: From fetal diagnosis to adolescence
Authors: Carbonez Karlien , Kefer Joëlle , Sluysmans Thierry , Moniotte Stephane 
Published: April 2022

AbstractBackground and AimsAbdominal coarctations are rare. Surgical treatment is difficult and requires re‐interventions to adjust the graft material to patient growth. We report effective treatment by interventional catheterization in an infant with the concern to allow adjustment for growth and prevention of vessel damage.Methods and ResultsAfter the diagnosis of abdominal coarctation at 27 weeks of gestation, an infant developed hypertension (170/70 mmHg) at 3 months of age despite medical therapy. Angio CT confirmed a 2 mm diameter, 2.3‐cm‐long coarctation of the descending aorta. At 4 months, a dilatation was performed using a 3 mm cutting balloon and a 5 mm Opta® balloon, Cordis®. Two noncovered Palmaz® Genesis™ XD PG1910P stents were required to keep the aortic lumen open. At 15 months, an Adventa™ V12 vascular 12 × 61 mm long covered stent was implanted to exclude an aneurysm which developed between the two stents. At 3 and 9.5 years, the stents were further dilated with a high‐pressure balloon to reach 11 mm aortic diameter with no residual pressure gradient, and normal blood pressure.ConclusionsThe use of cutting balloons and stent implantation is an effective way to relieve severe obstruction in middle aortic syndrome in neonates. The technical issues encountered were the need for a low profile sheath and material to avoid femoral artery damage, and the need to use stents that can be further expanded to adult size.