bluuebunny/crossref_metadata_2025 huggingface dataset:
RNA splicing is a key mediator of tumour cell plasticity and a therapeutic vulnerability in colorectal cancer
Authors: Hall Adam E. , Pohl Sebastian Öther-Gee , Cammareri Patrizia , Aitken Stuart , Younger Nicholas T. , Raponi Michela , Billard Caroline V. , Carrancio Alfonso Bolado , Bastem Aslihan , Freile Paz , Haward Fiona , Adams Ian R. , Caceres Javier F. , Preyzner Paula , von Kriegsheim Alex , Dunlop Malcolm G. , Din Farhat V. , Myant Kevin B.
Published: May 2022

Tumour cell plasticity is a major barrier to the efficacy of targeted cancer therapies but the mechanisms that mediate it are poorly understood. Here, we identify dysregulated RNA splicing as a key driver of tumour cell dedifferentiation in colorectal cancer (CRC). We find that Apc-deficient CRC cells have dysregulated RNA splicing machinery and exhibit global rewiring of RNA splicing. We show that the splicing factor SRSF1 controls the plasticity of tumour cells by controlling Kras splicing and is required for CRC invasion in a mouse model of carcinogenesis. SRSF1 expression maintains stemness in human CRC organoids and correlates with cancer stem cell marker expression in human tumours. Crucially, partial genetic downregulation of Srsf1 does not detrimentally affect normal tissue homeostasis, demonstrating that tumour cell plasticity can be differentially targeted. Thus, our findings link dysregulation of the RNA splicing machinery and control of tumour cell plasticity.
Kilometer-scale structure on the core–mantle boundary near Hawaii
Authors: Li Zhi , Leng Kuangdai , Jenkins Jennifer , Cottaar Sanne
Published: May 2022

The lowermost mantle right above the core-mantle boundary is highly heterogeneous containing multiple poorly understood seismic features. The smallest but most extreme heterogeneities yet observed are ‘Ultra-Low Velocity Zones’ (ULVZ). We exploit seismic shear waves that diffract along the core-mantle boundary to provide new insight into these enigmatic structures. We measure a rare core-diffracted signal refracted by a ULVZ at the base of the Hawaiian mantle plume at unprecedentedly high frequencies. This signal shows remarkably longer time delays at higher compared to lower frequencies, indicating a pronounced internal variability inside the ULVZ. Utilizing the latest computational advances in 3D waveform modeling, here we show that we are able to model this high-frequency signal and constrain high-resolution ULVZ structure on the scale of kilometers, for the first time. This new observation suggests a chemically distinct ULVZ with increasing iron content towards the core-mantle boundary, which has implications for Earth’s early evolutionary history and core-mantle interaction.
Scalable super hygroscopic polymer films for sustainable moisture harvesting in arid environments
Authors: Guo Youhong , Guan Weixin , Lei Chuxin , Lu Hengyi , Shi Wen , Yu Guihua
Published: May 2022

Extracting ubiquitous atmospheric water is a sustainable strategy to enable decentralized access to safely managed water but remains challenging due to its limited daily water output at low relative humidity (≤30% RH). Here, we report super hygroscopic polymer films (SHPFs) composed of renewable biomasses and hygroscopic salt, exhibiting high water uptake of 0.64–0.96 g g−1 at 15–30% RH. Konjac glucomannan facilitates the highly porous structures with enlarged air-polymer interfaces for active moisture capture and water vapor transport. Thermoresponsive hydroxypropyl cellulose enables phase transition at a low temperature to assist the release of collected water via hydrophobic interactions. With rapid sorption-desorption kinetics, SHPFs operate 14–24 cycles per day in arid environments, equivalent to a water yield of 5.8–13.3 L kg−1. Synthesized via a simple casting method using sustainable raw materials, SHPFs highlight the potential for low-cost and scalable atmospheric water harvesting technology to mitigate the global water crisis.
Addressing the quantitative conversion bottleneck in single-atom catalysis
Authors: Chen Zhongxin , Song Jingting , Zhang Rongrong , Li Runlai , Hu Qikun , Wei Pingping , Xi Shibo , Zhou Xin , Nguyen Phuc T. T. , Duong Hai M. , Lee Poh Seng , Zhao Xiaoxu , Koh Ming Joo , Yan Ning , Loh Kian Ping
Published: May 2022

Single-atom catalysts (SACs) offer many advantages, such as atom economy and high chemoselectivity; however, their practical application in liquid-phase heterogeneous catalysis is hampered by the productivity bottleneck as well as catalyst leaching. Flow chemistry is a well-established method to increase the conversion rate of catalytic processes, however, SAC-catalysed flow chemistry in packed-bed type flow reactor is disadvantaged by low turnover number and poor stability. In this study, we demonstrate the use of fuel cell-type flow stacks enabled exceptionally high quantitative conversion in single atom-catalyzed reactions, as exemplified by the use of Pt SAC-on-MoS2/graphite felt catalysts incorporated in flow cell. A turnover frequency of approximately 8000 h−1 that corresponds to an aniline productivity of 5.8 g h−1 is achieved with a bench-top flow module (nominal reservoir volume of 1 cm3), with a Pt1-MoS2 catalyst loading of 1.5 g (3.2 mg of Pt). X-ray absorption fine structure spectroscopy combined with density functional theory calculations provide insights into stability and reactivity of single atom Pt supported in a pyramidal fashion on MoS2. Our study highlights the quantitative conversion bottleneck in SAC-mediated fine chemicals production can be overcome using flow chemistry.
From radial to unidirectional water pumping in zeta-potential modulated Nafion nanostructures
Authors: Esplandiu María J. , Reguera David , Romero-Guzmán Daniel , Gallardo-Moreno Amparo M. , Fraxedas Jordi
Published: May 2022

Chemically propelled micropumps are promising wireless systems to autonomously drive fluid flows for many applications. However, many of these systems are activated by nocuous chemical fuels, cannot operate at high salt concentrations, or have difficulty for controlling flow directionality. In this work we report on a self-driven polymer micropump fueled by salt which can trigger both radial and unidirectional fluid flows. The micropump is based on the cation-exchanger Nafion, which produces chemical gradients and local electric fields capable to trigger interfacial electroosmotic flows. Unidirectional pumping is predicted by simulations and achieved experimentally by nanostructuring Nafion into microarrays with a fine tune modulation of surrounding surface zeta potentials. Nafion micropumps work in a wide range of salt concentrations, are reusable, and can be fueled by different salt cations. We demonstrate that they work with the common water-contaminant cadmium, using the own capture of this ion as fuel to drive fluid pumping. Thus, this system has potential for efficient and fast water purification strategies for environmental remediation. Unidirectional Nafion pumps also hold promise for effective analyte delivery or preconcentration for (bio)sensing assays.
Target receptor identification and subsequent treatment of resected brain tumors with encapsulated and engineered allogeneic stem cells
Authors: Bhere Deepak , Choi Sung Hugh , van de Donk Pim , Hope David , Gortzak Kiki , Kunnummal Amina , Khalsa Jasneet , Revai Lechtich Esther , Reinshagen Clemens , Leon Victoria , Nissar Nabil , Bi Wenya Linda , Feng Cheng , Li Hongbin , Zhang Yu Shrike , Liang Steven H. , Vasdev Neil , Essayed Walid Ibn , Quevedo Pablo Valdes , Golby Alexandra , Banouni Naima , Palagina Anna , Abdi Reza , Fury Brian , Smirnakis Stelios , Lowe Alarice , Reeve Brock , Hiller Arthur , Chiocca E. Antonio , Prestwich Glenn , Wakimoto Hiroaki , Bauer Gerhard , Shah Khalid
Published: May 2022

Cellular therapies offer a promising therapeutic strategy for the highly malignant brain tumor, glioblastoma (GBM). However, their clinical translation is limited by the lack of effective target identification and stringent testing in pre-clinical models that replicate standard treatment in GBM patients. In this study, we show the detection of cell surface death receptor (DR) target on CD146-enriched circulating tumor cells (CTC) captured from the blood of mice bearing GBM and patients diagnosed with GBM. Next, we developed allogeneic “off-the-shelf” clinical-grade bifunctional mesenchymal stem cells (MSCBif) expressing DR-targeted ligand and a safety kill switch. We show that biodegradable hydrogel encapsulated MSCBif (EnMSCBif) has a profound therapeutic efficacy in mice bearing patient-derived invasive, primary and recurrent GBM tumors following surgical resection. Activation of the kill switch enhances the efficacy of MSCBif and results in their elimination post-tumor treatment which can be tracked by positron emission tomography (PET) imaging. This study establishes a foundation towards a clinical trial of EnMSCBif in primary and recurrent GBM patients.
Analog–digital hybrid computing with SnS2 memtransistor for low-powered sensor fusion
Authors: Rehman Shania , Khan Muhammad Farooq , Kim Hee-Dong , Kim Sungho
Published: May 2022

Algorithms for intelligent drone flights based on sensor fusion are usually implemented using conventional digital computing platforms. However, alternative energy-efficient computing platforms are required for robust flight control in a variety of environments to reduce the burden on both the battery and computing power. In this study, we demonstrated an analog–digital hybrid computing platform based on SnS2 memtransistors for low-power sensor fusion in drones. The analog Kalman filter circuit with memtransistors facilitates noise removal to accurately estimate the rotation of the drone by combining sensing data from the gyroscope and accelerometer. We experimentally verified that the power consumption of our hybrid computing-based Kalman filter is only 1/4th of that of the traditional software-based Kalman filter.
Mapping the global opinion space to explain anti-vaccine attraction
Authors: Carpentras Dino , Lüders Adrian , Quayle Michael
Published: May 2022

Vaccines save millions of lives every year. They are recommended by experts, trusted by the majority of people, and promoted by expensive health campaigns. Even so, people with neutral attitudes are more persuaded by people holding anti-vaccine than pro-vaccine attitudes. Our analysis of vaccine-related attitudes in more than 140 countries makes sense of this paradox by including approaches from social influence. Specifically, we show that neutral people are positioned closer to anti- than to pro-vaccine people in the opinion space, and therefore more persuadable by them. We use dynamic social simulations seeded with vaccine survey data, to show how this effect results in a drift towards anti-vaccine opinions. Linking this analysis to data from two other multi-country datasets, we found that countries in which the pro-vaccine people are less associated to the neutrals (and so less able to influence them) exhibit lower vaccination rates and stronger increase in distrust. We conclude our paper by showing how taking social influence into account in vaccine-related policy-making can possibly reduce waves of distrust towards vaccination.
Another operator-theoretical proof for the second-order phase transition in the BCS-Bogoliubov model of superconductivity
Authors: Watanabe Shuji
Published: May 2022

In the preceding papers, imposing certain complicated and strong conditions, the present author showed that the solution to the BCS-Bogoliubov gap equation in superconductivity is twice differentiable only on the neighborhoods of absolute zero temperature and the transition temperature so as to show that the phase transition is of the second order from the viewpoint of operator theory. Instead, we impose a certain simple and weak condition in this paper, and show that there is a unique nonnegative solution and that the solution is indeed twice differentiable on a closed interval from a certain positive temperature to the transition temperature as well as pointing out several properties of the solution. We then give another operator-theoretical proof for the second-order phase transition in the BCS-Bogoliubov model. Since the thermodynamic potential has the squared solution in its form, we deal with the squared BCS-Bogoliubov gap equation. Here, the potential in the BCS-Bogoliubov gap equation is a function and need not be a constant.
Characterizing the mucin-degrading capacity of the human gut microbiota
Authors: Glover Janiece S. , Ticer Taylor D. , Engevik Melinda A.
Published: May 2022

Mucin-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

The 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

In 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

Oxidative 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

There 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

In 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

The 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

The 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

Proteins 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

Site-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

To 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

The 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

This 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).
In situ process quality monitoring and defect detection for direct metal laser melting
Authors: Felix Sarah , Ray Majumder Saikat , Mathews H. Kirk , Lexa Michael , Lipsa Gabriel , Ping Xiaohu , Roychowdhury Subhrajit , Spears Thomas
Published: May 2022

Quality control and quality assurance are challenges in direct metal laser melting (DMLM). Intermittent machine diagnostics and downstream part inspections catch problems after undue cost has been incurred processing defective parts. In this paper we demonstrate two methodologies for in-process fault detection and part quality prediction that leverage existing commercial DMLM systems with minimal hardware modification. Novel features were derived from the time series of common photodiode sensors along with standard machine control signals. In one methodology, a Bayesian approach attributes measurements to one of multiple process states as a means of classifying process deviations. In a second approach, a least squares regression model predicts severity of certain material defects.
Performance of PROPELLER FSE T2WI in reducing metal artifacts of material porcelain fused to metal crown: a clinical preliminary study
Authors: Li Wenjin , Shi Jing , Bian Wenjin , Li Jianting , Chen Xiaoqing , Feng Juan , Yu Jiali , Wang Jun , Niu Jinliang
Published: May 2022

This study aimed to compare MRI quality between conventional fast spin echo T2 weighted imaging (FSE T2WI) with periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) FSE T2WI for patients with various porcelain fused to metal (PFM) crown and analyze the value of PROPELLER technique in reducing metal artifacts. Conventional FSE T2WI and PROPELLER FSE T2WI sequences for axial imaging of head were applied in participants with different PFM crowns: cobalt-chromium (Co–Cr) alloy, pure titanium (Ti), gold–palladium (Au–Pd) alloy. Two radiologists evaluated overall image quality of section in PFM using a 5-point scale qualitatively and measured the maximum artifact area and artifact signal-to-noise ratio (SNR) quantitatively. Fifty-nine participants were evaluated. The metal crown with the least artifacts and the optimum image quality shown in conventional FSE T2WI and PROPELLER FSE T2WI were in Au–Pd alloy, Ti, and Co–Cr alloy order. PROPELLER FSE T2WI was superior to conventional FSE T2WI in improving image quality and reducing artifact area for Co-Cr alloy (17.0 ± 0.2% smaller artifact area, p < 0.001) and Ti (11.6 ± 0.7% smaller artifact area, p = 0.005), but had similar performance compared to FSE T2WI for Au–Pd alloy. The SNRs of the tongue and masseter muscle were significantly higher on PROPELLER FSE T2WI compared with conventional FSE T2WI (tongue: 29.76 ± 8.45 vs. 21.54 ± 9.31, p = 0.007; masseter muscle: 19.11 ± 8.24 vs. 15.26 ± 6.08, p = 0.016). Therefore, the different PFM crown generate varying degrees of metal artifacts in MRI, and the PROPELLER can effectively reduce metal artifacts especially in the PFM crown of Co-Cr alloy.
Genetic identification and diversity of stocks of the African bonytongue, Heterotis niloticus (Osteoglossiformes: Arapaiminae), in Nigeria, West Africa
Authors: Oladimeji Tofunmi E. , Caballero Isabel C. , Mateos Mariana , Awodiran Michael O. , Winemiller Kirk O. , Adite Alphonse , Hurtado Luis A.
Published: May 2022

Inland fisheries are an important source of protein and income for people in Africa. Their sustainable management can greatly benefit from identification of regional genetic stocks and characterization of their genetic diversity, but such information is lacking for most African freshwater fisheries. The African bonytongue,Heterotis niloticus, is an important component of inland fisheries in West Africa. Nigeria has the largest fishery for African bonytongues, representing ~ 86% of the global total. Recent declines in yields at some Nigerian locations, however, suggest current levels of exploitation may be unsustainable. Habitat degradation also may be impacting some stocks. Despite its commercial and nutritional importance, the African bonytongue has been the subject of scant genetic research to support management. We examined patterns of genetic diversity in natural populations ofH. niloticusat four locations in Nigeria, including Kainji Lake, a reservoir on the Niger River in north-central Nigeria, and three southern localities (Ethiope River, Igbokoda River, and Epe Lagoon), as well fish from the Ouémé River delta near Porto Novo, Benin. Eighty-five specimens were genotyped for nine microsatellite-loci. Genetic diversity estimates were highest at Kainji Lake, and substantially lower at southern localities. High levels of genetic differentiation were detected between samples from Kainji Lake and those from southern localities. Low, yet significantFSTvalues were observed among samples from southern Nigerian localities that were more differentiated from the sample from nearby coastal Benin. We thus recommend that African bonytongues from the five locations be considered distinct genetic stocks and managed accordingly.
Development of an artificial intelligence-assisted computed tomography diagnosis technology for rib fracture and evaluation of its clinical usefulness
Authors: Niiya Akifumi , Murakami Kouzou , Kobayashi Rei , Sekimoto Atsuhito , Saeki Miho , Toyofuku Kosuke , Kato Masako , Shinjo Hidenori , Ito Yoshinori , Takei Mizuki , Murata Chiori , Ohgiya Yoshimitsu
Published: May 2022

Artificial intelligence algorithms utilizing deep learning are helpful tools for diagnostic imaging. A deep learning-based automatic detection algorithm was developed for rib fractures on computed tomography (CT) images of high-energy trauma patients. In this study, the clinical effectiveness of this algorithm was evaluated. A total of 56 cases were retrospectively examined, including 46 rib fractures and 10 control cases from our hospital, between January and June 2019. Two radiologists annotated the fracture lesions (complete or incomplete) for each CT image, which is considered the “ground truth.” Thereafter, the algorithm’s diagnostic results for all cases were compared with the ground truth, and the sensitivity and number of false positive (FP) results per case were assessed. The radiologists identified 199 images with a fracture. The sensitivity of the algorithm was 89.8%, and the number of FPs per case was 2.5. After additional learning, the sensitivity increased to 93.5%, and the number of FPs was 1.9 per case. FP results were found in the trabecular bone with the appearance of fracture, vascular grooves, and artifacts. The sensitivity of the algorithm used in this study was sufficient to aid the rapid detection of rib fractures within the evaluated validation set of CT images.
Green synthesis and characterization of silver nanoparticles using Eugenia roxburghii DC. extract and activity against biofilm-producing bacteria
Authors: Giri Alok Kumar , Jena Biswajit , Biswal Bhagyashree , Pradhan Arun Kumar , Arakha Manoranjan , Acharya Saumyaprava , Acharya Laxmikanta
Published: May 2022

The green synthesis of silver nanoparticles (AgNPs) and their applications have attracted many researchers as the AgNPs are used effectively in targeting specific tissues and pathogenic microorganisms. The purpose of this study is to synthesize and characterize silver nanoparticles from fully expanded leaves of Eugenia roxburghii DC., as well as to test their effectiveness in inhibiting biofilm production. In this study, at 0.1 mM concentration of silver nitrate (AgNO3), stable AgNPs were synthesized and authenticated by monitoring the color change of the solution from yellow to brown, which was confirmed with spectrophotometric detection of optical density. The crystalline nature of these AgNPs was detected through an X-Ray Diffraction (XRD) pattern. AgNPs were characterized through a high-resolution transmission electron microscope (HR-TEM) to study the morphology and size of the nanoparticles (NPs). A new biological approach was undertaken through the Congo Red Agar (CRA) plate assay by using the synthesized AgNPs against biofilm production. The AgNPs effectively inhibit biofilm formation and the biofilm-producing bacterial colonies. This could be a significant achievement in contending with many dynamic pathogens.
Impact of educational level and travel burden on breast cancer stage at diagnosis in the state of Sao Paulo, Brazil
Authors: de Almeida Raissa Janine , de Moraes Luizaga Carolina Terra , Eluf-Neto José , de Carvalho Nunes Hélio Rubens , Pessoa Eduardo Carvalho , Murta-Nascimento Cristiane
Published: May 2022

We describe the characteristics of cases of breast cancer among women assisted at hospitals affiliated to the public health system in the state of São Paulo (Brazil), analysing the effects of level of education and travel burden to point of treatment. We conducted a retrospective analysis of invasive breast cancer among women diagnosed between 2000 and 2015. Data were extracted from the hospital-based cancer registries of Fundação Oncocentro de São Paulo—FOSP. The outcome was clinical stage at diagnosis (stage III–IV versus I–II). The explanatory variables were educational level and travel burden. Odds ratios (OR) and 95% confidence intervals (95% CI) were estimated. Multiple imputations were used for missing educational level (31%). The study included 81,669 women with invasive breast cancer diagnosed between 2000 and 2015. The mean age of patients at diagnosis was 56.8 years (standard deviation 13.6 years). 38% of patients were at an advanced stage at diagnosis (stage III–IV). Women with lower levels of education and those who received cancer care in municipalities other than where they lived were more likely to be diagnosed at an advanced stage. In conclusion, promotion of breast cancer awareness and improving pathways to expedite breast cancer diagnosis and treatment could help identify breast tumors at earlier stages.
Leveraging clinical data across healthcare institutions for continual learning of predictive risk models
Authors: Amrollahi Fatemeh , Shashikumar Supreeth P. , Holder Andre L. , Nemati Shamim
Published: May 2022

The inherent flexibility of machine learning-based clinical predictive models to learn from episodes of patient care at a new institution (site-specific training) comes at the cost of performance degradation when applied to external patient cohorts. To exploit the full potential of cross-institutional clinical big data, machine learning systems must gain the ability to transfer their knowledge across institutional boundaries and learn from new episodes of patient care without forgetting previously learned patterns. In this work, we developed a privacy-preserving learning algorithm named WUPERR (Weight Uncertainty Propagation and Episodic Representation Replay) and validated the algorithm in the context of early prediction of sepsis using data from over 104,000 patients across four distinct healthcare systems. We tested the hypothesis, that the proposed continual learning algorithm can maintain higher predictive performance than competing methods on previous cohorts once it has been trained on a new patient cohort. In the sepsis prediction task, after incremental training of a deep learning model across four hospital systems (namely hospitals H-A, H-B, H-C, and H-D), WUPERR maintained the highest positive predictive value across the first three hospitals compared to a baseline transfer learning approach (H-A:39.27%vs.31.27%, H-B:25.34%vs.22.34%, H-C:30.33% vs.28.33%). The proposed approach has the potential to construct more generalizable models that can learn from cross-institutional clinical big data in a privacy-preserving manner.