bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electrochemical determination of L-tryptophan in food samples on graphite electrode prepared from waste batteries
Authors: Tasić Žaklina Z. , Mihajlović Marija B. Petrović , Radovanović Milan B. , Simonović Ana T. , Medić Dragana V. , Antonijević Milan M. 
Published: March 2022

AbstractOne of the goals of this research was to develop an electrochemical sensor that had the ability to determine the target analyte and was both cheap and non-toxic. Another goal was to influence the reduction of electronic waste. In accordance with these, a graphite rod from zinc-carbon batteries was used to prepare an electrochemical sensor for the determination of L-tryptophan in Britton–Robinson buffer solution. Two electrochemical methods were used in the experimental research, differential pulse voltammetry and cyclic voltammetry. The effect of different parameters, including the pH value of supporting solution, scan rate, as well as the concentration of L-tryptophan on the current response, was studied. The pH value of Britton–Robinson buffer influenced the intensity of L-tryptophan oxidation peak, as well as the peak potential. The intensity of the current response was the highest at pH 4.0, while the peak potential value became lower as the pH increased, indicating that protons also participated in the redox reaction. Based on the obtained data, electrochemical oxidation of L-tryptophan at the graphite electrode was irreversible, two electron/two proton reaction. In addition, it was observed that the oxidation peak increased as the scan rate increased. According to the obtained electrochemical data, it was suggested that the oxidation of L-tryptophan was mixed controlled by adsorption and diffusion. The linear correlation between oxidation peak and L-tryptophan concentration was investigated in the range 5.0–150.0 µM and the obtained values of limit of detection and limit of quantification were 1.73 µM and 5.78 µM, respectively. Also, the prepared electrochemical sensor was successful in determination of target analyte in milk and apple juice samples.
High adsorption capacity of phenol and methylene blue using activated carbon derived from lignocellulosic agriculture wastes
Authors: El-Bery Haitham M. , Saleh Moushira , El-Gendy Reem A. , Saleh Mahmoud R. , Thabet Safinaz M. 
Published: March 2022

AbstractThe resources of clean water worldwide are very limited, and climate change is already affecting the available supplies. Therefore, developing a low-cost, highly efficient, and recyclable adsorbent to upgrade water quality has become an essential task. Herein, we report the fabrication of activated carbon (AC) adsorbents derived from lignocellulosic wastes. Both physical and chemical activation were investigated to modify the surface texture properties. The results indicated that increasing the activation temperature, whether physically or chemically, increases the specific surface area (SBET). On the contrary, increasing the amount of the chemical activating agent significantly decreases the SBETvalues. The SBETof 1771, 2120, and 2490 m2 g−1were obtained for water vapor, K2CO3and KOH, at activation temperatures of 950 °C, 800 °C, and 800 °C, respectively. Methylene blue (MB) and phenol were used as adsorbates for the adsorption experiment. Adsorption of methylene blue dye revealed the ability of the water activated carbon to remove more than 95% of the dye (100 ppm) within 5 min with an adsorption capacity of 148.8 mg g−1. For phenol adsorption, Several parameters were investigated, including initial concentration (50–250 ppm), pH (2–10), contact time (5–60 min), and temperature (25–45 °C). The highest adsorption capacity of phenol achieved was 158.9 mg g−1. The kinetics of adsorption of phenol was better described by pseudo-second-order reaction while the isotherm process using Langmuir model. This study presents a roadmap for conversion of lignocellulosic biomass waste into highly efficient porous carbon adsorbents.
Machine learning modeling for solubility prediction of recombinant antibody fragment in four different E. coli strains
Authors: Hashemi Atieh , Basafa Majid , Behravan Aidin 
Published: March 2022

AbstractThe solubility of proteins is usually a necessity for their functioning. Recently an emergence of machine learning approaches as trained alternatives to statistical models has been evidenced for empirical modeling and optimization. Here, soluble production of anti-EpCAM extracellular domain (EpEx) single chain variable fragment (scFv) antibody was modeled and optimized as a function of four literature based numerical factors (post-induction temperature, post-induction time, cell density of induction time, and inducer concentration) and one categorical variable using artificial neural network (ANN) and response surface methodology (RSM). Models were established by the CCD experimental data derived from 232 separate experiments. The concentration of soluble scFv reached 112.4 mg/L at the optimum condition and strain (induction at cell density 0.6 with 0.4 mM IPTG for 24 h at 23 °C in Origami). The predicted value obtained by ANN for the response (106.1 mg/L) was closer to the experimental result than that obtained by RSM (97.9 mg/L), which again confirmed a higher accuracy of ANN model. To the author’s knowledge this is the first report on comparison of ANN and RSM in statistical optimization of fermentation conditions of E.coli for the soluble production of recombinant scFv.
Spatio-temporal inhabitation of settlements by Hystrix cristata L., 1758
Authors: Coppola Francesca , Grignolio Stefano , Brivio Francesca , Giunchi Dimitri , Felicioli Antonio 
Published: March 2022

AbstractSettlements are usually shared at different times by semi-fossorial mammals. Porcupine reproductive pair shows high den-site fidelity, but no data are available on the spatio-temporal inhabitation of settlements. In this investigation, the spatio-temporal inhabitation of settlements by crested porcupine families was investigated using camera-trapping as well as the ethological factors affecting the settlements selection. The crested porcupine resulted to be the main inhabitant of settlements surveyed in the present study. Each settlement was inhabited exclusively by one porcupine family. Five out of six porcupine families, each alternatively and complementarily inhabited the same two settlements. In all the five monitored families, settlements selection doesn’t follow a seasonal pattern. Settlement inhabitation of porcupines resulted positively affected by cohabitation with badger, while presence of porcupettes did not affect settlements selection. Long periods of settlement inhabitation were positively affected both by the presence of porcupettes and cohabitation with badger. The pattern of settlements inhabitation in relation to their availability and porcupine population density as well as factors promoting porcupine-badger cohabitation should be further investigated. New ethological knowledge obtained in this investigation could be involved in the evaluation of the ecological epidemiology of infectious diseases between porcupine and badger within a one health approach and may be a useful tool for a sustainable management of semi-fossorial mammals.
Nonlinear statistical damage constitutive model of granite based on the energy dissipation ratio
Authors: Wang Xianliang , Zhang Jianhai , Qian Li , Yao Tianzhi , Mo Zuguo , He Jianhua , Zhang Ru 
Published: March 2022

AbstractThe stress–strain curves and mechanical properties of Shuangjiangkou granite were obtained using five groups of conventional triaxial tests under various confining pressures using MTS815 rock test equipment. From the microscale, mesoscale, and macroscale perspectives, four types of mechanisms that contribute to energy dissipation during granite deformation were investigated. Based on the energy dissipation ratio, a new approach for estimating crack closure stress and damage stress is proposed. The energy dissipation ratio was substituted into the Weibull distribution function, and then a new nonlinear statistical damage constitutive model of granite based on the energy dissipation ratio was constructed after Biot’s theory was modified per the Lemaitre strain equivalence principle. By comparing experimental data with theoretical values estimated by the model, the model’s rationality and correctness were confirmed.
Multivariate genomic and transcriptomic determinants of imaging-derived personalized therapeutic needs in Parkinson’s disease
Authors: Lenglos Christophe , Lin Sue-Jin , Zeighami Yashar , Baumeister Tobias R. , Carbonell Felix , Iturria-Medina Yasser 
Published: March 2022

AbstractDue to the marked interpersonal neuropathologic and clinical heterogeneity of Parkinson's disease (PD), current interventions are not personalized and fail to benefit all patients. Furthermore, we continue to lack well-established methods and clinical tests to tailor interventions at the individual level in PD. Here, we identify the genetic determinants of individual-tailored treatment needs derived from longitudinal multimodal neuroimaging data in 294 PD patients (PPMI data). Advanced multivariate statistical analysis revealed that both genomic and blood transcriptomic data significantly explain (P < 0.01, FWE-corrected) the interindividual variability in therapeutic needs associated with dopaminergic, functional, and structural brain reorganization. We confirmed a high overlap between the identified highly predictive molecular pathways and determinants of levodopa clinical responsiveness, including well-known (Wnt signaling, angiogenesis, dopaminergic activity) and recently discovered (immune markers, gonadotropin-releasing hormone receptor) pathways/components. In addition, the observed strong correspondence between the identified genomic and baseline-transcriptomic determinants of treatment needs/response supports the genome's active role at the time of patient evaluation (i.e., beyond individual genetic predispositions at birth). This study paves the way for effectively combining genomic, transcriptomic and neuroimaging data for implementing successful individually tailored interventions in PD and extending our pathogenetic understanding of this multifactorial and heterogeneous disorder.
AngioJet rheolytic thrombectomy in patients with thrombolysis in myocardial infarction thrombus grade 5: an observational study
Authors: Huang Yi-xiong , Cao Yi , Chen Yu , Qiu Yi-gang , Zheng Jian-yong , Liu Ying-ming , He Jiang-chun , Zhao Li , Li Tian-chang 
Published: March 2022

AbstractThe aim of this study was to evaluate the effectiveness and safety of AngioJet rheolytic thrombectomy among patients with high thrombus burden. Routine manual thrombus aspiration in patients with ST-segment elevation myocardial infarction (STEMI) does not improve clinical outcomes and was associated with an increased rate of stroke. However, the safety of mechanical thrombus aspiration is still unknown. This was a retrospective, single-center study involving 621 patients with Thrombolysis In Myocardial Infarction thrombus grade 5. The primary outcome was the composite of major adverse cardiovascular events (MACE) within 12 months. The safety outcome was stroke within 1-year. Propensity matching score was calculated due to the significant baseline differences between the AngioJet rhelytic thrombectomy group and the routine treatment group. AngioJet rheolytic thrombectomy was performed in 117 patients. After propensity-score matching, there was no significant difference both in the incidence of MACE (11.1% vs 17.9%, hazard ratio, 1.641; 95% confidence interval [CI] 0.822 to 3.277, p = 0.161) and the incidences of stroke (1.7% vs 2.6%, hazard ratio 1.522; 95% confidence interval [CI] 0.254 to 9.107, p = 0.646) between two groups at 1-year follow-up. In patients with Thrombolysis In Myocardial Infarction thrombus grade 5, AngioJet rheolytic thrombectomy did not improve clinical outcomes at 1 year. However, AngioJet rheolytic thrombectomy did not increase the risk of stroke in patients with high thrombus burden.
Indistinguishability of temporally separated pairwise two-photon state of thermal photons in Franson-type interferometry
Authors: Park Jiho , Kim Heonoh , Moon Han Seb 
Published: March 2022

AbstractThe phenomenon of Franson interference with time–energy entangled photon pairs beyond the single-photon coherence length observed upon nonlocal measurement at two space-like separated locations is of particular research interest. Herein, we determine the coherence length of temporally separated pairwise two-photon (TSPT) states of thermal photons emitted from a warm atomic ensemble in Franson-type interferometry, with the setup consisting of two spatially separated unbalanced Michelson interferometers beyond the coherence length of a thermal photon. Using a novel method of square-modulated thermal photons, we show that the sinusoidal Franson-type interference fringe of thermal photons is determined by the presence or absence of TSPT states (corresponding to the time delay between the long and short paths in Franson-type interferometry). We find that the indistinguishability of the TSPT state in the Franson-type interference is independent of the temporal separation of the thermal photons in the TSPT states.
The prevalence of virulence determinants in methicillin-resistant Staphylococcus aureus isolated from different infections in hospitalized patients in Poland
Authors: Kot Barbara , Piechota Małgorzata , Jakubczak Andrzej , Gryzińska Magdalena , Witeska Małgorzata , Grużewska Agata , Baran Katarzyna , Denkiewicz Paulina 
Published: March 2022

AbstractMethicillin-resistant Staphylococcus aureus (MRSA) is responsible for hard-to-treat infections. The presence of 19 virulence genes in 120 MRSA isolates obtained from hospitalized patients and genetic relationships of these isolates were investigated. The eno (100%) and ebps (93.3%) genes encoding laminin- and elastin binding proteins, respectively, were ubiquitous. Other adhesion genes: fib (77.5%), fnbB (41.6%), bbp (40.8%), cna (30.8%) encoding proteins binding fibrinogen, fibronectin, bone sialoprotein and collagen, respectively, and map/eap (62.5%), encoding Eap, were also frequent. The etB and etD genes, encoding exfoliative toxins, were present in 15.6% and 12.5% isolates, respectively. The splA, splE and sspA, encoding serine protease were detected in 100%, 70.8% and 94.2% isolates, respectively. The tst gene, encoding toxic shock syndrome toxin-1 was found in 75% isolates. The cna, map/eap and tst genes were the most common in wound isolates and much less common in blood isolates. We identified 45 different spa types, t003 (21.7%) and t008 (18.8%) being the most common. The t003 was the most frequent among isolates from the respiratory tract (35.5%), while t008 in blood isolates (40%). Identification of virulence factors of MRSA is important for evaluation of pathogen transmission rate and disease development.
Human activity recognition of children with wearable devices using LightGBM machine learning
Authors: Csizmadia Gábor , Liszkai-Peres Krisztina , Ferdinandy Bence , Miklósi Ádám , Konok Veronika 
Published: March 2022

AbstractHuman activity recognition (HAR) using machine learning (ML) methods has been a continuously developed method for collecting and analyzing large amounts of human behavioral data using special wearable sensors in the past decade. Our main goal was to find a reliable method that could automatically detect various playful and daily routine activities in children. We defined 40 activities for ML recognition, and we collected activity motion data by means of wearable smartwatches with a special SensKid software. We analyzed the data of 34 children (19 girls, 15 boys; age range: 6.59–8.38; median age = 7.47). All children were typically developing first graders from three elementary schools. The activity recognition was a binary classification task which was evaluated with a Light Gradient Boosted Machine (LGBM) learning algorithm, a decision tree based method with a threefold cross validation. We used the sliding window technique during the signal processing, and we aimed at finding the best window size for the analysis of each behavior element to achieve the most effective settings. Seventeen activities out of 40 were successfully recognized with AUC values above 0.8. The window size had no significant effect. In summary, the LGBM is a very promising solution for HAR. In line with previous findings, our results provide a firm basis for a more precise and effective recognition system that can make human behavioral analysis faster and more objective.
Compositions of gut microbiota before and shortly after hepatitis C viral eradication by direct antiviral agents
Authors: Hsu Yao-Chun , Chen Chih-Cheng , Lee Wei-Hsiang , Chang Chi-Yang , Lee Fu-Jen , Tseng Cheng-Hao , Chen Tzu-Haw , Ho Hsiu J. , Lin Jaw-Town , Wu Chun-Ying 
Published: March 2022

AbstractIt is unclear whether dysbiosis in hepatitis C virus (HCV) infected patients results from the viral infection per se or develops as a result of hepatic dysfunction. We aimed to characterize compositions in gut microbiome before and shortly after HCV clearance. In this prospective cohort study, adult patients with confirmed HCV viremia were screened before receiving direct antiviral agents. Those with recent exposure to antibiotics or probiotics (within one month), prior abdominal surgery, or any malignancy were ineligible. Stool was collected before antiviral therapy started and at 12 weeks after the treatment completed. From the extracted bacterial DNA, 16 s rRNA gene was amplified and sequenced. Each patient was matched 1:2 in age and sex with uninfected controls. A total of 126 individuals were enrolled into analysis. The gut microbiome was significantly different between HCV-infected patients (n = 42), with or without cirrhosis, and their age-and sex-matched controls (n = 84) from the levels of phylum to amplicon sequence variant (all p values < 0.01 by principal coordinates analysis). All patients achieved viral eradication and exhibited no significant changes in the overall composition of gut microbiome following viral eradication (all p values > 0.5), also without significant difference in alpha diversity (all p values > 0.5). For the purpose of exploration, we also reported bacteria found differently abundant before and after HCV eradication, including Coriobacteriaceae, Peptostreptococcaceae, Staphylococcaceae, Morganellaceae, Pasteurellaceae, Succinivibrionaceae, and Moraxellaceae. Gut microbiota is altered in HCV-infected patients as compared with uninfected controls, but the overall microbial compositions do not significantly change shortly after HCV eradication.
Wheat growth monitoring and yield estimation based on remote sensing data assimilation into the SAFY crop growth model
Authors: Ma Chunyan , Liu Mingxing , Ding Fan , Li Changchun , Cui Yingqi , Chen Weinan , Wang Yilin 
Published: March 2022

AbstractCrop growth monitoring and yield estimate information can be obtained via appropriate metrics such as the leaf area index (LAI) and biomass. Such information is crucial for guiding agricultural production, ensuring food security, and maintaining sustainable agricultural development. Traditional methods of field measurement and monitoring typically have low efficiency and can only give limited untimely information. Alternatively, methods based on remote sensing technologies are fast, objective, and nondestructive. Indeed, remote sensing data assimilation and crop growth modeling represent an important trend in crop growth monitoring and yield estimation. In this study, we assimilate the leaf area index retrieved from Sentinel-2 remote sensing data for crop growth model of the simple algorithm for yield estimation (SAFY) in wheat. The SP-UCI optimization algorithm is used for fine-tuning for several SAFY parameters, namely the emergence date (D0), the effective light energy utilization rate (ELUE), and the senescence temperature threshold (STT) which is indicative of biological aging. These three sensitive parameters are set in order to attain the global minimum of an error function between the SAFY model predicted values and the LAI inversion values. This assimilation of remote sensing data into the crop growth model facilitates the LAI, biomass, and yield estimation. The estimation results were validated using data collected from 48 experimental plots during 2014 and 2015. For the 2014 data, the results showed coefficients of determination (R2) of the LAI, biomass and yield of 0.73, 0.83 and 0.49, respectively, with corresponding root-mean-squared error (RMSE) values of 0.72, 1.13 t/ha and 1.14 t/ha, respectively. For the 2015 data, the estimated R2 values of the LAI, biomass, and yield were 0.700, 0.85, and 0.61, respectively, with respective RMSE values of 0.83, 1.22 t/ha, and 1.39 t/ha, respectively. The estimated values were found to be in good agreement with the measured ones. This shows high applicability of the proposed data assimilation scheme in crop monitoring and yield estimation. As well, this scheme provides a reference for the assimilation of remote sensing data into crop growth models for regional crop monitoring and yield estimation.
Discrete element modeling of particles sphericity effect on sand direct shear performance
Authors: Chen Chunhui , Gu Jiayu , Peng Zesen , Dai Xianyao , Liu Qingbing , Zhu Guo-Qiang 
Published: March 2022

AbstractParticle surface morphology is an important factor influencing sand structure and mechanical properties. In this study, the effect of sand particle sphericity on sand direct shear performance is investigated by using the discrete element method (DEM). Two ways are adapted to simulate different approaching methods from round particles to irregular sand. The macroresponse shows that irregular sand has a higher shear strength at lower normal stress than round particles. The shape of the particle has less influence on shear strength at higher normal stress. The irregular shape of sand leads to an increase in the shear band proportion. However, the shear band proportion is not related to the sphericity. Under all conditions, particles within the shear band have a larger average rotation angle than those outside the shear band. When the particle shape approaches round (regardless of the round particle proportion and particle shape), the average rotation angle of particles within and without shear bands increase, while the coordinate number and contact anisotropy decrease.
Serum IL-28A/IFN-λ2 is linked to disease severity of COVID-19
Authors: Fukuda Yosuke , Homma Tetsuya , Inoue Hideki , Goto Yuiko , Sato Yoko , Ikeda Hitoshi , Onitsuka Chisato , Sato Hiroki , Akimoto Kaho , Ebato Takaya , Suganuma Hiromitsu , Kawahara Tomoko , Mikuni Hatsuko , Uchida Yoshitaka , Suzuki Shintaro , Tanaka Akihiko , Sagara Hironori 
Published: March 2022

AbstractType III interferons (IFNs) play an important role in respiratory viral infections, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This study aimed to determine whether the expression of serum type III IFNs predicted disease severity among patients with the coronavirus disease (COVID-19). A retrospective cohort study was conducted of patients admitted to a single hospital between March 21, 2020, and March 31, 2021. Patients were divided into mild to moderate I (MM) and moderate II to severe (MS) groups based on the COVID-19 severity classification developed by the Japanese Ministry of Health, Labor and Welfare. A total of 257 patients were included in the analysis. Human interleukin-28A (IL-28A/IFN-λ2) expression was significantly lower, and interleukin (IL)-6 expression was significantly higher in the MS group than in the MM group (both p < 0.001). In addition, IL-28A/IFN-λ2 was statistically significantly inversely correlated with the time from disease onset to negative SARS-CoV-2 PCR results (p = 0.049). Multivariable logistic regression analysis showed that IL-28A/IFN-λ2 was an independent predictor of disease severity (p = 0.021). The low expression of IL-28A/IFN-λ2 may serve as a serum biomarker that predicts the severity of COVID-19, possibly through the mechanism of delayed viral elimination.