bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterizing the mucin-degrading capacity of the human gut microbiota
Authors: Glover Janiece S. , Ticer Taylor D. , Engevik Melinda A. 
Published: May 2022

AbstractMucin-degrading microbes are known to harbor glycosyl hydrolases (GHs) which cleave specific glycan linkages. Although several microbial species have been identified as mucin degraders, there are likely many other members of the healthy gut community with the capacity to degrade mucins. The aim of the present study was to systematically examine the CAZyme mucin-degrading profiles of the human gut microbiota. Within the Verrucomicrobia phylum, all Akkermansia glycaniphila and muciniphila genomes harbored multiple gene copies of mucin-degrading GHs. The only representative of the Lentisphaerae phylum, Victivallales, harbored a GH profile that closely mirrored Akkermansia. In the Actinobacteria phylum, we found several Actinomadura, Actinomyces, Bifidobacterium, Streptacidiphilus and Streptomyces species with mucin-degrading GHs. Within the Bacteroidetes phylum, Alistipes, Alloprevotella, Bacteroides, Fermenitomonas Parabacteroides, Prevotella and Phocaeicola species had mucin degrading GHs. Firmicutes contained Abiotrophia, Blautia, Enterococcus, Paenibacillus, Ruminococcus, Streptococcus, and Viridibacillus species with mucin-degrading GHs. Interestingly, far fewer mucin-degrading GHs were observed in the Proteobacteria phylum and were found in Klebsiella, Mixta, Serratia and Enterobacter species. We confirmed the mucin-degrading capability of 23 representative gut microbes using a chemically defined media lacking glucose supplemented with porcine intestinal mucus. These data greatly expand our knowledge of microbial-mediated mucin degradation within the human gut microbiota.
Behavioural and electrophysiological responses of Philaenus spumarius to odours from conspecifics
Authors: Sevarika Milos , Rondoni Gabriele , Ganassi Sonia , Pistillo Onofrio Marco , Germinara Giacinto Salvatore , De Cristofaro Antonio , Romani Roberto , Conti Eric 
Published: May 2022

AbstractThe meadow spittlebug, Philaenus spumarius L. (Hemiptera: Auchenorrhyncha: Aphrophoridae), is the main vector of Xylella fastidiosa subsp. pauca strain ST53, the causal agent of the Olive Quick Decline Syndrome. Philaenus spumarius and other Auchenorrhyncha are known to communicate via vibrations, whereas the possible occurrence of semiochemical communication has been poorly investigated so far. Through a chemical ecology approach, we provide evidence of intraspecific chemical communication in P. spumarius. In Y-tube olfactometer bioassays, males were attracted to unmated females as well as toward the headspace volatile extracts collected from unmated females. Conversely, females did not respond to unmated male volatiles or their extracts, nor did males and females respond to volatiles from individuals of the same sex. Electroantennography assays of unmated male and female headspace extracts elicited measurable responses in the antennae of both sexes. Male responses to body wash extracts from both sexes were stronger compared to female responses. Thus, suggesting the presence of compounds that are highly detected by the male’s olfactory system. The female head seemed to be the source of such compounds. This is the first record of intraspecific chemical communication in P. spumarius and one of the very few records in Auchenorrhyncha. Possible biological roles are under investigation.
The standardisation of the approach to metagenomic human gut analysis: from sample collection to microbiome profiling
Authors: Szóstak Natalia , Szymanek Agata , Havránek Jan , Tomela Katarzyna , Rakoczy Magdalena , Samelak-Czajka Anna , Schmidt Marcin , Figlerowicz Marek , Majta Jan , Milanowska-Zabel Kaja , Handschuh Luiza , Philips Anna 
Published: May 2022

AbstractIn recent years, the number of metagenomic studies increased significantly. Wide range of factors, including the tremendous community complexity and variability, is contributing to the challenge in reliable microbiome community profiling. Many approaches have been proposed to overcome these problems making hardly possible to compare results of different studies. The significant differences between procedures used in metagenomic research are reflected in a variation of the obtained results. This calls for the need for standardisation of the procedure, to reduce the confounding factors originating from DNA isolation, sequencing and bioinformatics analyses in order to ensure that the differences in microbiome composition are of a true biological origin. Although the best practices for metagenomics studies have been the topic of several publications and the main aim of the International Human Microbiome Standard (IHMS) project, standardisation of the procedure for generating and analysing metagenomic data is still far from being achieved. To highlight the difficulties in the standardisation of metagenomics methods, we thoroughly examined each step of the analysis of the human gut microbiome. We tested the DNA isolation procedure, preparation of NGS libraries for next-generation sequencing, and bioinformatics analysis, aimed at identifying microbial taxa. We showed that the homogenisation time is the leading factor impacting sample diversity, with the recommendation for a shorter homogenisation time (10 min). Ten minutes of homogenisation allows for better reflection of the bacteria gram-positive/gram-negative ratio, and the obtained results are the least heterogenous in terms of beta-diversity of samples microbial composition. Besides increasing the homogenisation time, we observed further potential impact of the library preparation kit on the gut microbiome profiling. Moreover, our analysis revealed that the choice of the library preparation kit influences the reproducibility of the results, which is an important factor that has to be taken into account in every experiment. In this study, a tagmentation-based kit allowed for obtaining the most reproducible results. We also considered the choice of the computational tool for determining the composition of intestinal microbiota, with Kraken2/Bracken pipeline outperforming MetaPhlAn2 in our in silico experiments. The design of an experiment and a detailed establishment of an experimental protocol may have a serious impact on determining the taxonomic profile of the intestinal microbiome community. Results of our experiment can be helpful for a wide range of studies that aim to better understand the role of the gut microbiome, as well as for clinical purposes.
Protective effect of bee pollen in acute kidney injury, proteinuria, and crystalluria induced by ethylene glycol ingestion in rats
Authors: Elghouizi Asmae , Al-Waili Noori , Elmenyiy Nawal , Elfetri Salma , Aboulghazi Abderrazak , Al-Waili Ahmed , Lyoussi Badiaa 
Published: May 2022

AbstractOxidative stress plays a role in hyperoxaluria-induced kidney injury and crystallization. Bee pollen is a hive product with a high content of antioxidants. The antioxidant content and protective effect of bee pollen extract (BPE) against ethylene glycol (EG) induced crystalluria, and acute kidney injury (AKI) were investigated. The effect of BPE on the EG-induced liver injury and proteinuria was also examined. Ten groups of male Wister rats were treated daily with vehicle, cystone, BPE (100, 250, and 500 mg/kg b.wt.), and group 6–9 treated with EG, EG + BPE (100, 250, and 500 mg/kg b.wt.) and group 10 EG + cystone. The dose of EG was 0.75% v/v, and the dose of cystone was 500 mg/kg b.wt. On day 30, blood and urine samples were collected for analysis. Kidneys were removed for histopathological study. The antioxidant activity of BPE was assessed, and its total phenols and flavonoids were determined. EG significantly increased urine parameters (pH, volume, calcium, phosphorus, uric acid, and protein), blood urea, creatinine, and liver enzymes (P < 0.05). EG decreased creatinine clearance and urine magnesium and caused crystalluria. Treatment with BPE or cystone mitigates EG's effect; BPE was more potent than cystone (P < 0.05). BPE increases urine volume, sodium, and magnesium compared to the control and EG treated groups. BPE reduces proteinuria and prevents AKI, crystalluria, liver injury, and histopathological changes in the kidney tissue caused by EG. BPE might have a protective effect against EG-induced AKI, crystalluria, proteinuria, and stone deposition, most likely by its antioxidant content and activity.
Endometrial microbiome: sampling, assessment, and possible impact on embryo implantation
Authors: Reschini Marco , Benaglia Laura , Ceriotti Ferruccio , Borroni Raffaella , Ferrari Stefania , Castiglioni Marta , Guarneri Davide , Porcaro Luigi , Vigano’ Paola , Somigliana Edgardo , Uceda Renteria Sara 
Published: May 2022

AbstractThere is growing interest on the potential clinical relevance of the endometrial microbiome. However, insufficient attention has been given to the methodology of sampling. To minimize contamination, we advocate the use of the double-lumen catheters commonly employed for the embryo transfer. Endometrial fluid samples obtained from 53 women scheduled for IVF were studied for microbiome characterization. Control samples from the vagina of these same women were concomitantly obtained. Samples were analysed by V3–V4–V6 regions of 16S rRNA gene sequencing with Next Generation Sequencing technique. Endometrial Lactobacillus-dominant cases were uncommon compared to previous evidence, being observed in only 4 (8%) women. Taxonomy markedly differed between the endometrial and vaginal microbiomes composition. The most common bacterial genera coincided in only 4 (8%) women. The comparison between women who did and did not subsequently become pregnant failed to identify any microorganism associated with the success of the procedure. However, the endometrial biodiversity resulted higher among pregnant women. Shannon’s Equitability index in pregnant and non pregnant women was 0.76 [0.57–0.87] and 0.55 [0.51–0.64], respectively (p = 0.002). In conclusion, the use of embryo transfer catheters for testing the endometrial microbiome is promising. The scant concordance with vaginal samples supports the validity of this approach. Moreover, our study highlighted a possible beneficial role of a higher biodiversity on endometrial receptivity.
Analysis of fuzzified boundary value problems for MHD Couette and Poiseuille flow
Authors: Siddique Imran , Nadeem Muhammad , Khan Ilyas , Jamil Raja Noshad , Shamseldin Mohamed A. , Akgül Ali 
Published: May 2022

AbstractIn an uncertain atmosphere, the magnetohydrodynamics (MHD) flow in three principal flows of the third grade fluid across two parallel plates is presented. Fuzzy differential equations are constructed by manipulating dimensionless differential equations. The prime purpose of the current article is to use a semi-analytical approach fuzzy-based Adomian decomposition method to achieve numerical results for nonlinear FDEs with fuzzy boundary conditions. Triangular fuzzy numbers are used in fuzzy BCs with help of $$\alpha {\text{-cut}}$$

α
-cut

approach. This strategy is linked to the membership function. In a graphic and tabular depiction, the effect of $$\alpha$$
α
and other constraints on fuzzy velocity profiles is explored. The current findings are in good agreement with their previous numerical and analytical results in a crisp environment.
Human induced mesenchymal stem cells display increased sensitivity to matrix stiffness
Authors: Gultian Kirstene A. , Gandhi Roshni , Sarin Khushi , Sladkova-Faure Martina , Zimmer Matthew , de Peppo Giuseppe Maria , Vega Sebastián L. 
Published: May 2022

AbstractThe clinical translation of mesenchymal stem cells (MSCs) is limited by population heterogeneity and inconsistent responses to engineered signals. Specifically, the extent in which MSCs respond to mechanical cues varies significantly across MSC lines. Although induced pluripotent stem cells (iPSCs) have recently emerged as a novel cell source for creating highly homogeneous MSC (iMSC) lines, cellular mechanosensing of iMSCs on engineered materials with defined mechanics is not well understood. Here, we tested the mechanosensing properties of three human iMSC lines derived from iPSCs generated using a fully automated platform. Stiffness-driven changes in morphology were comparable between MSCs and iMSCs cultured atop hydrogels of different stiffness. However, contrary to tissue derived MSCs, no significant changes in iMSC morphology were observed between iMSC lines atop different stiffness hydrogels, demonstrating a consistent response to mechanical signals. Further, stiffness-driven changes in mechanosensitive biomarkers were more pronounced in iMSCs than MSCs, which shows that iMSCs are more adaptive and responsive to mechanical cues than MSCs. This study reports that iMSCs are a promising stem cell source for basic and applied research due to their homogeneity and high sensitivity to engineered mechanical signals.
Long-term caries prevention of dental sealants and fluoride varnish in children with autism spectrum disorders: a retrospective cohort study
Authors: Balian Araxi , Campus Guglielmo , Bontà Giuliana , Esteves-Oliveira Marcella , Salerno Claudia , Cirio Silvia , D’Avola Valeria , Cagetti Maria Grazia 
Published: May 2022

AbstractThe aim was to compare two strategies for caries prevention in children with Autism Spectrum Disorders (ASDs). Participants were retrospectively retrieved and divided in two groups. Group one had first permanent molars treated with fluoride varnishes, FA group (n = 92, 9.43 ± 2.44 years) whilst the second, with dental sealant plus fluoride varnishes, FA + S group (n = 140, 7.77 ± 2.57 years). Logistic and multivariate analysis were run to evaluate the caries incidence, the retention rate of sealants, and background factors associated with caries risk over a period of at least 11 years. Survival rates from dental caries were statistically significantly higher in the FA + S group compared to the FA group (LogRank test p < 0.01). Dental sealant plus fluoride varnish played as a protective factor towards the development of caries (HR = 0.25 95%CI = 0.00/0.55 and HR = 0.34 95%CI = 0.00/0.66 in the upper right and left first molars; HR = 0.32 95%CI = 0.00/0.66 and HR = 0.26 95%CI = 0.00/0.58 in the lower right and left first molars). Dental sealants retention rate was high, ranging between 58.02% and 64.29%. No baseline variable was statistically significantly associated to the risk of caries development. Combined dental sealant and fluoride varnish application was more effective in reducing caries risk in first permanent molars of ASDs children than fluoride varnish alone. This preventive strategy should be therefore routinely applied in high caries risk patients as ASDs children.
Prediction of protein–protein interaction using graph neural networks
Authors: Jha Kanchan , Saha Sriparna , Singh Hiteshi 
Published: May 2022

AbstractProteins are the essential biological macromolecules required to perform nearly all biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation but interact with other proteins (known as protein–protein interaction) present in their surroundings to complete biological activities. The knowledge of protein–protein interactions (PPIs) unravels the cellular behavior and its functionality. The computational methods automate the prediction of PPI and are less expensive than experimental methods in terms of resources and time. So far, most of the works on PPI have mainly focused on sequence information. Here, we use graph convolutional network (GCN) and graph attention network (GAT) to predict the interaction between proteins by utilizing protein’s structural information and sequence features. We build the graphs of proteins from their PDB files, which contain 3D coordinates of atoms. The protein graph represents the amino acid network, also known as residue contact network, where each node is a residue. Two nodes are connected if they have a pair of atoms (one from each node) within the threshold distance. To extract the node/residue features, we use the protein language model. The input to the language model is the protein sequence, and the output is the feature vector for each amino acid of the underlying sequence. We validate the predictive capability of the proposed graph-based approach on two PPI datasets: Human andS. cerevisiae. Obtained results demonstrate the effectiveness of the proposed approach as it outperforms the previous leading methods. The source code for training and data to train the model are available athttps://github.com/JhaKanchan15/PPI_GNN.git.
Prediction and variability mapping of some physicochemical characteristics of calcareous topsoil in an arid region using Vis–SWNIR and NIR spectroscopy
Authors: Alomar Samer , Mireei Seyed Ahmad , Hemmat Abbas , Masoumi Amin Allah , Khademi Hossein 
Published: May 2022

AbstractSite-specific management of soils needs continuous measurements of soil physicochemical characteristics. In this study, Vis–NIR spectroscopy with two spectroscopic instruments, including charge-coupled device (CCD) and indium-gallium-arsenide (InGaAs) spectrometers, was adopted to estimate some physicochemical characteristics of a calcareous topsoil in an arid climate. Partial least squares (PLS) as linear and artificial neural networks (ANN) as nonlinear multivariate techniques were utilized to enhance the accuracy of prediction. The best predictive models were then used to extract the variability maps of physicochemical characteristics. Diffuse reflectance spectra of 151 samples, collected from the calcareous topsoil, were acquired in the visible and short-wavelength near-infrared (Vis–SWNIR) (400–1100 nm) and near-infrared (NIR) (950–1650 nm) spectral ranges using CCD and InGaAs spectrometers, respectively. The results showed that NIR spectral data of the InGaAs spectrometer was necessary to reach the best predictions for all selected soil properties. The best predictive models based on the optimum spectral range could allow us the excellent predictions of sand (RPD = 2.63) and silt (RPD = 2.52), and very good estimations of clay (RPD = 2.35) and electrical conductivity (EC) (RPD = 2.224) by ANN and very good prediction of calcium carbonate equivalent (CCE) (RPD = 2.01) by PLS. The CCD device, however, resulted in acceptable predictions of sand (RPD = 2.13, very good) and clay (RPD = 1.66, fair) by ANN, and silt (RPD = 1.78, good), EC (RPD = 1.84, good) and CCE (RPD = 1.67, fair) by PLS. Similar variability was attained between pairs of predicted maps by best models and reference-measured maps for all studied soil properties. For clay, sand, silt, and CCE, the Vis/SWNIR-predicted and equivalent reference-measured maps had acceptable similarities, indicating the potential application of low-cost CCD spectrometers for prediction and the variability mapping of these parameters.
Geospatial characterization of rural settlements and potential targets for revitalization by geoinformation technology
Authors: Liu Yixuan , Ke Xinxin , Wu Weicheng , Zhang Ming , Fu Xiao , Li Jie , Jiang Jingheng , He Yecheng , Zhou Cuimin , Li Wenjing , Li Yuan , Song Yifei , Zhou Xiaoting 
Published: May 2022

AbstractTo better implement the Strategy of Rural Revitalization, it is essential to characterize the rural settlements and understand their roles in the socio-environmental interactive system. This paper is hence aimed at achieving such a study using different spatial analysis such as kernel density and spatial autocorrelation (SA) and modeling approaches, e.g., simple and multiple linear regression analyses taking Jiangxi, a province in China as an example. Remote sensing, topographic and socioeconomic data were employed for this purpose. Through these analyses, it is found that the rural settlements in the study area appear to have a spatial distribution pattern of “dense north and sparse south” as an “F” type, and are quantitatively characterized as low elevations, flat terrain, high river and road densities, rich cultivated land resources and susceptible to the impact of urban radiation with a R2 of 0.520–0.748. Based on this understanding, a new inequality evaluation indicator of rural development, i.e., socio-environmental evaluation index (SEI), was developed. Areas with SEI lower than 0.40 should be given a priority to implement the revitalization strategy in the province. This index can also be extended to study of the imbalance of rural development in other regions and countries.
Proactive approach for preamble detection in 5G-NR PRACH using supervised machine learning and ensemble model
Authors: Zehra Syeda Sundus , Magarini Maurizio , Qureshi Rehan , Mustafa Syed Muhammad Nabeel , Farooq Faiza 
Published: May 2022

AbstractThe physical random access channel (PRACH) is used in the uplink of cellular systems for initial access requests from the users. It is very hard to achieve low latency by implementing conventional methods in 5G. The performance of the system degrades when multiple users try to access the PRACH receiver with the same preamble signature, resulting in a collision of request signals and dual peak occurrence. In this paper, we used two machine learning classification technique models with signals samples as big data to obtain the best proactive approach. First, we implemented three supervised learning algorithms, Decision Tree Classification (DTC), naïve bayes (NB), and K-nearest neighbor (KNN) to classify the outcome based on two classes, labeled as ‘peak’ and ‘false peak’. For the second approach, we constructed a Bagged Tree Ensembler, using multiple learners which contributes to the reduction of the variance of DTC and comparing their asymptotes. The comparison shows that Ensembler method proves to be a better proactive approach for the stated problem.
A self-organized critical model and multifractal analysis for earthquakes in Central Alborz, Iran
Authors: Rahimi-Majd M. , Shirzad T. , Najafi M. N. 
Published: May 2022

AbstractThis paper is devoted to a phenomenological study of the earthquakes in central Alborz, Iran. Using three observational quantities, namely the weight function, the quality factor, and the velocity model in this region, we develop a modified dissipative sandpile model which captures the main features of the system, especially the average activity field over the region of study. The model is based on external stimuli, the location of which is chosen (I) randomly, (II) on the faults, (III) on the low active points, (IV) on the moderately active points, and (V) on the highly active points in the region. We uncover some universal behaviors depending slightly on the method of external stimuli. A multi-fractal detrended fluctuation analysis is exploited to extract the spectrum of the Hurst exponent of the time series obtained by each of these schemes. Although the average Hurst exponent depends slightly on the method of stimuli, we numerically show that in all cases it is lower than 0.5, reflecting the anti-correlated nature of the system. The lowest average Hurst exponent is found to be associated with the case (V), in such a way that the more active the stimulated sites are, the lower the average Hurst exponent is obtained, i.e. the large earthquakes are more anticorrelated. Moreover, we find that the activity field achieved in this study provide information about the depth and topography of the basement, and also the area that can potentially be the location of the future large events. We successfully determine a high activity zone on the Mosha Fault, where the mainshock occurred on May 7th, 2020 (M$$_W$$

W

4.9).