bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificial Image Objects for Classification of Breast Cancer Biomarkers with Transcriptome Sequencing Data and Convolutional Neural Network Algorithms
Authors: Chen Xiangning , CHEN Daniel G , Zhao Zhongming , Balko Justin M , CHEN Jingchun 
Published: February 2021

Abstract
Background: Transcriptome sequencing has been broadly available in clinical studies. However, it remains a challenge to utilize these data effectively to due to the high dimension of the data and the high correlation of gene expression. Methods: We propose a novel method that transforms RNA sequencing data into artificial image objects (AIOs) and apply convolutional neural network (CNN) algorithm to classify these AIOs. The AIO technique considers each gene as a pixel in digital image, standardizes and rescales gene expression levels into a range suitable for image display. Using the GSE81538 (n = 405) and GSE96058 (n = 3,373) datasets, we create AIOs for the subjects and design CNN models to classify biomarker Ki67 and Nottingham histologic grade (NHG). Results: With 5-fold cross validation, we accomplish a classification accuracy and AUC of 0.797 ± 0.034 and 0.820 ± 0.064 for Ki67 status. For NHG, the weighted average of categorical accuracy is 0.726 ± 0.018, and the weighted average of AUC is 0.848 ± 0.019. With GSE81538 as training data and GSE96058 as testing data, the accuracy and AUC for Ki67 are 0.772 ± 0.014 and 0.820 ± 0.006, and that for NHG are 0.682 ± 0.013 and 0.808 ± 0.003 respectively. These results are comparable to or better than the results reported in the original study. For both Ki67 and NHG, the calls from our models have similar predictive power for survival as the calls from trained pathologists in survival analyses. Comparing the calls from our models and the pathologists, we find that the discordant subjects for Ki67 are a group of patients for whom estrogen receptor, progesterone receptor, PAM50 and NHG could not predict their survival rate, and their responses to chemotherapy and endocrine therapy are also different from the concordant subjects. Conclusions: RNA sequencing data can be transformed into AIOs and be used to classify the status of Ki67 and NHG by CNN algorithm. The AIO method can handle high dimension data with highly correlated variables with no requirement for variable selection, leading to a data-driven, consistent and automation-ready approach to model RNA sequencing data.
Martian Moons Exploration MMX: Sample Return Mission to Phobos Elucidating Formation Processes of Habitable Planets
Authors: Kuramoto Kiyoshi , Kawakatsu Yasuhiro , Fujimoto Masaki , Araya Akito , Barucci Maria Antonietta , Genda Hidenori , Hirata Naru , Ikeda Hitoshi , Imamura Takeshi , Helbert Jörn , Kameda Shingo , Kobayashi Masanori , Kusano Hiroki , Lawrence David J. , Matsumoto Koji , Michel Patrick , Miyamoto Hideaki , Morota Tomokatsu , Nakagawa Hiromu , Nakamura Tomoki , Ogawa Kazunori , Otake Hisashi , Ozaki Masanobu , Russel Sara , Sasaki Sho , Sawada Hirotaka , Senshu Hiroki , Tachibana Shogo , Terada Naoki , Ulamec Stephan , Usui Tomohiro , Wada Koji , Watababe Sei-ichiro , Yokota Shoichiro 
Published: February 2021

Abstract
Martian moons exploration, MMX, is the new sample return mission planned by the Japan Aerospace Exploration Agency (JAXA) targeting the two Martian moons with a scheduled launch in 2024 and a return to the Earth in 2029. The major scientific objectives of this mission are to determine the origin of Phobos and Deimos, to elucidate the early Solar System evolution in terms of volatile delivery across the snow line to the terrestrial planets having habitable surface environments, and to explore the evolutionary processes of both moons and Mars surface environment. To achieve these objectives, during a stay in circum-Martian space over about 3 years MMX will collect samples from Phobos along with close-up observations of this inner moon and carry out multiple flybys of Deimos to make comparative observations of this outer moon. Simultaneously, successive observations of the Martian atmosphere will also be made by utilizing the advantage of quasi-equatorial spacecraft orbits along the moons’ orbits.
Effect of Predation by Colpoda sp. in Nitrogen Fixation Rate of Two Free-Living Bacteria
Authors: Martínez-Reyes Carlos Manuel , Zaragoza Salvador Rodríguez , Cabirol Nathalie , Alarcón Alejandro , Mendoza-López Ma. Remedios 
Published: February 2021

Abstract
Biological nitrogen fixation (BNF) is limited to several groups of prokaryotes, which can reduce nitrogen through complex endosymbiotic relationships or as free-living nitrogen-fixing bacteria (FLNFB). Predation of FLNFB by protozoa releases reduced nitrogen, enhancing the formation of plant and bacterial biomass as well as nitrogen (N) mineralization within soil microbial communities. We aim to evaluate the predation effect of Colpoda sp. on two FLNFB Azospirillum lipoferum and Stenotrophomonas sp. during their exponential and lag phase. The likelihood of Colpoda sp. to feed on the former species was needed to ensure there is a predation effect. The kinetics of bacterial population growth was determined in the predators’ presence or absence and the effect of predation on the biological fixation of N was evaluated through the reduction of acetylene to ethylene technique. Colpoda sp. showed a non-significant difference in preferences between the two species offered as prey. Consequently, the abundance of A. lipoferum and Stenotrophomonas sp. decreased significantly due to predator’s pressure. However, it had a higher positive effect on the formation of new bacterial biomass on Stenotrophomonas sp.as revealed by the increase of its specific growth rate. Likewise, predation promoted greater nitrogen fixation in A. lipoferum and Stenotrophomonas sp. during the lag phase (0.34 nM and 0.38 nM) than in the exponential phase (0.27 nM and 0.17 nM). We concluded that predation by Colpodasp stimulates the rate of nitrogen fixation of A. lipoferum and Stenotrophomonas sp.
The Wild Emmer Wheat Gene PmG16, Conferring Resistance to Powdery Mildew, is an Orthologue of Pm60 from Triticum Urartu
Authors: Li Yinghui , Wei Zhen-Zhen , Fatiukha Andrii , Jaiwar Samidha , Wang Hanchao , Hasan Samiha , Liu Zhiyong , Sela Hanan , Krugman Tamar , Fahima Tzion 
Published: February 2021

Abstract
Wild emmer wheat (WEW), the tetraploid progenitor of durum and bread wheat, is a valuable genetic resource for resistance to powdery mildew fungal disease caused by Blumeria graminis f. sp. tritici (Bgt). PmG16 gene, derived from WEW, confers high resistance to most tested Bgt isolates. We mapped PmG16 to a 1.4 cM interval between the flanking markers uhw386 and uhw390 on Chromosome 7AL. Based on gene annotation of WEW reference genome Zavitan_V1, 34 predicted genes were identified within the ~3.48 Mb target region. Six genes were annotated as associated with disease resistance, of which TRIDC7AG077150.1 was found to be highly similar to Pm60, previously cloned from Triticum urartu and residing in the same syntenic region. A functional molecular marker (FMM) for Pm60 (M-Pm60-S1) co-segregated with PmG16, suggesting that WEW PmG16 is probably an orthologue of Pm60 from Triticum urartu (designated here as TdPm60). Sequence alignment identified only eight SNPs that differentiate between TdPm60 and TuPm60. Furthermore, our results suggest that other WEW powdery mildew resistance genes MlIW172 and MlIW72, that also mapped to the same region of Chromosome 7AL, might be identical or allelic to TdPm60. Screening of 230 WEW accessions with Pm60 specific markers, 58 resistant accessions were identified from Southern Levant harboring the TdPm60 allele, while all the susceptible accessions showed no PCR amplifications. Deployment of TdPm60 is clearly more advantageous over TuPm60 since it can be rapidly introgressed by classical breeding approaches into bread wheat genetic background.
Does Institutional Quality Strengthen the Globalization-growth Nexus? A Cross Country Analysis
Authors: Ali Shahid , Ahmad Naved 
Published: February 2021

Abstract
In this study, we examine the role of institutional development in the globalization growth nexus. We have used the System GMM technique for a sample of 124 countries from 1996 to 2019. We found that countries with improved quality of institutions get more benefited from economic globalization. Hence, policy complementarities are the pre-requisites for the relationship between economic globalization and growth. Through analysis of the marginal effect, we found a minimum threshold level of institutional quality. This study also performs sensitivity analysis by comparing the results of the different econometric techniques. Consequently, we have run hundreds of regressions with various growth models to get the most stable and robust model.
Model-based evaluation of the contribution of partial denitrification (PD) on the one-stage autotrophic nitrogen removal process
Authors: Zhang Chi , Yu Lianze , Zhang Miao , Wu Jun 
Published: February 2021

Abstract
The nitrate produced by the one-stage partial nitritation-anammox (PN/A) process can be removed through partial denitrification (PD) by adding carbon source. In this study, a 1D multi-population biofilm model was developed to evaluate the contribution of partial denitrification on the one-stage autotrophic nitrogen removal process at influent NH4+ = 100 mg N/L. The dynamic simulation that was carried out to investigate the effect of nitrite-oxidizing bacteria (NOB) revealed that PD contributed to the reactor to obtain total nitrogen removal efficiency (TNR) of above 90% and the effluent nitrate was significantly decreased with the absence of NOB. However, PD decreased TNR of the one-stage PN/A process with the presence of NOB. Increased influent chemical oxygen demand (COD) widened the dissolved oxygen (DO) range required for high TNR whether NOB were present or not. The steady-state simulation results showed that NOB were always absent in the granules at high DO and COD levels and the optimum DO > 0.5 mg/L when influent COD was over 50 mg/L. Besides, higher influent COD/NH4+ (C/N) and larger granule diameter (diameter > 1600 µm) were contributed to widening the range of DO required for high TNR. The nitrogen removal contribution of anammox bacteria (AMX) was significantly higher than denitrification in the reactor.
Circadian Misalignment Leads to Changes in Cortisol Rhythms, Blood Biochemical Variables and Serum miRNA Profiles
Authors: Huang Guo-Bin , Ma Huan , Gan Xi-Hui , Li Si-Lin , Ma Xiao-Hong , Chen Si-Yu , Yang Hui-Ying , Zhou Tuo-Yang , Zhang Liang , Tian Zhi-Qiang , Wang Xin , Liao Zhen , Zhu Xin-Hai , Jiang Hong-Mei , Shao Yong-Cong , Yang Ye-Bing , Guo Jin-Hu 
Published: February 2021

Abstract
Background: Circadian clock plays a critical role in synchronizing the inner molecular, metabolic and physiological processes to the environmental cues which cycle with a period of 24 h. Misalignment in the circadian rhythms leads to decrease in adaptation, performance and increased risk of associated disorders. The non-24-h schedules and shift schedules are commonly used in maritime operations, both of which could result in disturbance in circadian rhythms. The comprehensive effects of these schedules remain to be further elucidated.Methods: In this study, we firstly conducted an experiment in which the volunteers followed a 3-d rotary schedule with consecutive shift in sleep time (rotatory schedule), and analyzed the changes in salivary cortisol rhythms and blood variables. Next we conducted another experiment in which the volunteers followed an 8 h on and 4 h off schedule (non-24-h schedule) to compare the changes in blood/serum variables. Furthermore, the plasma miRNAs from the volunteers following the rotatory schedule were subject for miRNA sequencing. Results: The rotatory schedule led to elevated levels of serum cortisol during the early stage, and the phase became delayed during the early and stages. The results show both of the schedules caused comprehensive changes in blood/serum biochemical variable, and consistently, the increase in phosphate levels. In addition, a subset of serum miRNAs targeting genes involved in circadian rhythms, sleep homeostasis and multiple important physiological processes or pathways were identified in the experiment with rotatory schedule.Conclusions: This study revealed an increased stress during the rotatory schedule. Circadian misalignment caused by either non-24-h or rotatory schedule lead to extensive changes in blood/serum variables. As to the rotatory schedule, altered expression of serum miRNAs may account for the consequences of circadian misalignment. These findings would help understand the deleterious effects of shift schedules and optimize to enhance performance and welfare of the personnel working with similar schedules.
Gibberellin and spermidine synergistically regulate polyamine metabolism during Rhododendron flower development
Authors: Xu Qian , Li Huaxiong , Liu Shiliang , Huang Wenpei , Xian Xiaolin , Li Qing , Long Yue , Chen Rui , Sun Zechen , Pan Yuanzhi 
Published: February 2021

Abstract
Polyamines (PAs) are involved in various plants developmental processes, especially in flowering. Their significant influence has been established, but the exact mechanisms by which PAs modulate flowering are not yet understood. To understand the PA metabolism during flowering/senescence in Rhododendron simsii ‘Zichendian’ plants, exogenous gibberellin (GA3, 0-2400 mg L− 1) and spermidine (Spd, 0–1 mM) were applied separately or in combination during the early stage of flower bud formation. The application of GA3 alone advanced the initial flowering by promoting the free Put (F) fraction and decreasing the Spd/Put ratio at the squaring stage, whereas Spd alone delayed the initial flowering by increasing the soluble conjugated (C) form, insoluble bound Put (B) fraction and Spd/Put ratio. When GA3 plus Spd was applied, the initial flowering advanced by 2 days. Furthermore, endogenous PA levels as well as the C and B fractions of PAs and key enzymes (diamine oxidase, PA oxidase, arginine decarboxylase, ornithine decarboxylase and S-adenosylmethionine decarboxylase) of PA metabolism increased, while the Spd/Spm ratio decreased by GA3 and Spd applications during flowering, resulting in delayed flower senescence. In addition, the structural equation model (SEM) showed that Spd directly participated in PA metabolism, while GA3 regulated flowering by modulating PA metabolism via Spd (c.f. 0.27). Taken together, our study provides comprehensive evidence regarding the clear relationships between GA3, Spd and flowering time, supporting the positive effect of PA metabolism on delaying flower senescence, and helps to provide a thorough understanding of the PA interconversions, biosynthesis and catabolism during flowering and senescence.
Cellulose Based Cation-Exchange Fiber as Filtration Material for the Rapid Removal of Methylene Blue from Wastewater
Authors: Shao Xinyi , Wang Jian , Liu Zetan , Hu Na , Liu Min , Duan Chao , Zhang Ruimin , Quan Cailin 
Published: February 2021

Abstract
The development of eco-friendly adsorbent with perfect solid/liquid separation performance is of great practical importance for the efficient purification of dye-containing wastewater. Herein, cellulose based cation-exchange fibrous bio-adsorbent (CEF) was successfully obtained via an industrialized cellulose etherification process. The fiber morphology can be maintained with the average degree substitution (DS) of CEF as about 0.19. The CEF showed high efficiency adsorption for methylene blue (MB): achieving 82% of equilibrium uptake (447.69 mg·g-1) within 5 min. Especially, the non-woven porous filter material, formed by CEFs and glass fibers, showed the praisable solid/liquid separation characteristics, fast water filtration rate (≈ 6.3 m3·m-2·h-1) and high removal rate (≈ 99.2%) when it was used to adsorb MB (150 ppm) from wastewater. In addition, CEFs filter material can be regenerated via a simple method. This study demonstrates that green natural fiber materials are promising for the economical and efficient purification of dye-containing wastewater.
Histone H3K27me3 Demethylase act as Key Regulator of Stem Cell Markers in Matrix Detached Cancer Cells
Authors: Razeeth Mohammed , Zamzami Mazin , Choudhry Hani , Ahmed Firoz , Ateeq Bushra , Khan Mohammad Imran 
Published: February 2021

Abstract
Metastasis of cancer cells requires detachment from matrix (Extra Cellular Matrix) to seed cancer cells in a distant organ. Hypoxia is prevalent in matrix detached cancer cells, are bound for metastasis. Studies have established hypoxia as chromatin modifier, as it transcriptionally controls expression of various histone demethylases (KDMs), therefore we hypothesized that hypoxia can modulate the expression of KDMs in matrix detached cancer cells. Results from our study showed that in hypoxic matrix detached cancer cells of different origins, expression and activity of KDM6B (a H3K27me3 histone demethylase) was consistently increased. Simultaneously, we found increased expression of cancer stem cells (CSCs) markers in hypoxic matrix detached cancer cells. Targeting KDM6B by using a specific inhibitor reduces the expression of CSCs markers namely SOX-2, SOX-9 and CD44 in matrix detached cancer cells. We found that KDM6B occupies the promoter region of both SOX-2 and CD44 and thereby regulate their expression. Surprisingly, we also noticed that in a feedback loop HIF1α was transcriptionally regulated by KDM6B in matrix detached cancer cells. Lastly, we observed a significant positive association between KDM6B and HIF1α in various cancer types. Overall, we found, that matrix detachment induces hypoxia, modulates epigenome to promote KDM6B activity to positively regulate expression of SOX2, CD44 and HIF1α in matrix detached conditions. We believe that KDM6B can be developed as a therapeutic target for elimination of matrix detached cancer cells, bound for metastatic events.
Bibliometric analysis of document flow on academic social networks in Web of Science
Authors: Busygina Tatyana , Yuklyaevskaya Anna 
Published: February 2021

Abstract
Analysis of a document array on academic social networks (ASNs) in Web of Science for the period from 2005 to 2020 was carried out with use of analytical services data of the WoS and CiteSpace (the program for visualization of patterns and trends in scientific literature). The following parameters of the array were analyzed: publication dynamics; document types structure; countries, organizations and authors leading in the number of publications; thematic categories to which documents of the array are assigned; publications (journals, monographs) in which the documents of the array are published; most cited publications. An increase in the number of publications on the ASNs in WoS was established since 2005. The largest number of ASNs studies is conducted in the USA (University of Pittsburgh), UK (Wolverhampton University, Manchester University), China, Spain (University of Granada), Germany (Max Planck Society for Scientific Research), Canada, India and the Netherlands (Leiden University). The ASNs were studied in the main thematic areas: Computer Science, Computer Science and Librarianship, Mechanical Engineering, Engineering and Technology. Four out of the first ten highly cited publications, are devoted to altmetrics. Using the CiteSpace, it was shown that when ASNs started rise, their organizational structure was beeing studed. Later, altmetrics used in the ASNs became the main subjects of ASNs research. The keywords occurrence revealed that the most frequent terms are “altmetrics”, “impact”, “citation”. As part of the document flow, also identified publications in which the ASNs are used as a source of bibliographic data for systematic or meta-analysis (in medicine predominantly), or as a platform for experimental data discussion.
Enhanced removal of Cr(III), Mn(II), Cd(II), Pb(II) and Cu(II) from aqueous solution by N-functionalized ordered silica
Authors: Kobylinska Natalia , Kessler Vadim , Seisenbaeva Gulaim , Dudarko Oksana 
Published: February 2021

Abstract
Chelating and ion-exchange N-functionalized mesoporous silicas (SBA-15) as selective adsorbents for removal of heavy metals were synthesized using template method. Fourier transform infrared spectroscopy, TEM analysis, N2 adsorption/desorption isotherms and titration analysis conﬁrmed successful functionalisation of the tri-sodium salt of N-(triethoxysilylpropyl)ethylenediaminetriacetic acid (EDTA), protonated primary amine (NH3+Cl-) and its combinations onto the mesoporous silica (SBA-EDTA/NH2). The obtained materials featured beneﬁcial properties of mesoporous silica SBA-15 with its high surface area and were successfully fictionalized with N-containing groups. The synthesized series of silicas were investigated for removal of Cr(III), Mn(III), Pb(II), Cd(II) and Cu(II) from model water solutions. The adsorption of target ions increased with the increase pH and its concentration in solution. The adsorption equilibrium data were well ﬁtted to Langmuir isotherm model and maximum monolayer adsorption capacities for cations Pb(II), Cd(II), Cr(III) and Mn(II) were 185.6 mg g-1, 111.2 mg g-1, 57.7 mg g-1 and 49.4 mg g-1, respectively. The chelating interaction was considered as the main adsorption mechanism for metal ions (Cr(III), Mn(II), Pb(II), Cd(II), and Cu(II)). The adsorption capacities of SBA-EDTA and SBA-EDTA/NH2 samples toward studied metal ions were consistent with the Lewis ‘hard and soft acids and bases’ theory. The metal removal efficiency of adsorbents was near 96-92 % during three regeneration cycles. All these results indicated that the produced N-functionalized silica were promising for applications in environmental and analytical separation ﬁelds.
COVID-19 outbreak and control in Kenya- Insights from a mathematical model
Authors: Mbogo Rachel Waema , Orwa Titus Okello 
Published: February 2021

Abstract
The coronavirus disease 2019 (COVID-19) pandemic reached Kenya in March 2020 with the initial cases reported in the capital city Nairobi and in the coastal area Mombasa. As reported by the World Health Organization, the outbreak of COVID-19 has spread across the world, killed many, collapsed economies and changed the way people live since it was first reported in Wuhan, China, in the end of 2019. As of May 25,2020 It had led to over 100,000 confirmed cases in Africa with over 3000 deaths. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.We employed a SEIHCRD mathematical transmission model with reported Kenyan data on cases of COVID-19 to estimate how transmission varies over time. The model is concise in structure, and successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak. The next generation matrix approach was adopted to calculate the basic reproduction number (R0) from the model to assess the factors driving the infection . The results from the model analysis shows that non-pharmaceutical interventions over a relatively long period is needed to effectively get rid of the COVID-19 epidemic otherwise the rate of infection will continue to increase despite the increased rate of recovery.