bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epithelial cell plasticity drives endoderm formation during gastrulation
Authors: Scheibner Katharina , Schirge Silvia , Burtscher Ingo , Büttner Maren , Sterr Michael , Yang Dapeng , Böttcher Anika , Ansarullah  , Irmler Martin , Beckers Johannes , Cernilogar Filippo M. , Schotta Gunnar , Theis Fabian J. , Lickert Heiko 
Published: June 2021

AbstractIt is generally accepted that epiblast cells ingress into the primitive streak by epithelial-to-mesenchymal transition (EMT) to give rise to the mesoderm; however, it is less clear how the endoderm acquires an epithelial fate. Here, we used embryonic stem cell and mouse embryo knock‐in reporter systems to combine time-resolved lineage labelling with high-resolution single-cell transcriptomics. This allowed us to resolve the morphogenetic programs that segregate the mesoderm from the endoderm germ layer. Strikingly, while the mesoderm is formed by classical EMT, the endoderm is formed independent of the key EMT transcription factor Snail1 by mechanisms of epithelial cell plasticity. Importantly, forkhead box transcription factor A2 (Foxa2) acts as an epithelial gatekeeper and EMT suppressor to shield the endoderm from undergoing a mesenchymal transition. Altogether, these results not only establish the morphogenetic details of germ layer formation, but also have broader implications for stem cell differentiation and cancer metastasis.
Probiotics: their action against pathogens can be turned around
Authors: Gan Lian , Xu Wei-Hua , Xiong Yuanyan , Lv Zhaolin , Zheng Jianwei , Zhang Yu , Lin Jianhao , Liu Jingshu , Chen Shijun , Chen Mengqiu , Guo Qingqi , Wu Junfeng , Chen Jingjie , Su Zhenhua , Sun Jijia , He Yuhui , Liu Chuanhe , Wang Weifang , Verstraete Willy , Sorgeloos Patrick , Defoirdt Tom , Qin Qiwei , Liu Yiying 
Published: June 2021

AbstractProbiotics when applied in complex evolving (micro-)ecosystems, might be selectively beneficial or detrimental to pathogens when their prophylactic efficacies are prone to ambient interactions. Here, we document a counter-intuitive phenomenon that probiotic-treated zebrafish (Danio rerio) were respectively healthy at higher but succumbed at lower level of challenge with a pathogenic Vibrio isolate. This was confirmed by prominent dissimilarities in fish survival and histology. Based upon the profiling of the zebrafish microbiome, and the probiotic and the pathogen shared gene orthogroups (genetic niche overlaps in genomes), this consequently might have modified the probiotic metabolome as well as the virulence of the pathogen. Although it did not reshuffle the architecture of the commensal microbiome of the vertebrate host, it might have altered the probiotic-pathogen inter-genus and intra-species communications. Such in-depth analyses are needed to avoid counteractive phenomena of probiotics and to optimise their efficacies to magnify human and animal well-being. Moreover, such studies will be valuable to improve the relevant guidelines published by organisations such as FAO, OIE and WHO.
Preparation and characterization of ancient recipe of organic Lime Putty-Evaluation for its suitability in restoration of Padmanabhapuram Palace, India
Authors: Shivakumar M. , Selvaraj Thirumalini , Dhassaih Magesh Peter 
Published: June 2021

AbstractThe study aims at preparation and characterization of six organic lime putty (hydraulic Lime + fermented plant extract) using regionally available plants namelyTerminalia Chebula (kadukkai), Rosa Sinensis(hibiscus), Palm jaggery(refined sugar),Xanthorrhoeaceae(aloe vera), andIndigofera Tinctoria(neelamari) as per the methods given in the ancient palm leaf of Padmanabhapuram Palace, India. Advanced analytical techniques like Gas chromatography-mass spectroscopy (GC–MS), UV-Spectrophotometer and carbon dioxide quantification were used to study the fermented plant extracts and Fourier transform-infrared spectroscopy (FT-IR), X-ray Diffraction (XRD), Field emission-scanning electron microscopy (FESEM) to study hydrated phases and microstructure of organic lime putty. GC–MS recorded the phytochemical compounds like fatty acids, traces of proteins, polysaccharides and carbohydrates. Fermented kadukkai and neelamari extracts reported as fatty acid, palm jaggery as carbohydrate, hibiscus as polysaccharide and aloevera rich in all the biomolecules. The detection limit of Quantification:0.013 and limit of detection:0.067 for polysaccharides, 0.026 and 0.088 for unsaturated fatty acids was reported through a U.V spectrophotometer for all the herbs. Aloevera and neelamari fermented extracts recorded the CO2release around 96,000 and 90,000 ppm on 4th day of fermentation, whereas for other herbs it ranged below the recorded readings. Supply of CO2has initiated the internal carbonation of the lime putty and precipitation of calcite in three different forms aragonite, calcite and vaterite minerals. The addition of organics resulted in high-intensity portlandite peaks and calcium carbonate polymorphs as reported in XRD graphs in agreement with FT-IR analysis. FESEM morphology validated the early formation of carbonate polymorphs, and EDX. has shown that kadukkai lime putty, jaggery lime putty and reference lime putty. mixes have calcium around 35–45%. From the overall results, 3% addition of eco-friendly biopolymers has altered the properties like setting time, water repellency and higher carbonation rate, which is the main reason behind longevity of the structure.
Venom duct origins of prey capture and defensive conotoxins in piscivorous Conus striatus
Authors: Himaya S. W. A. , Jin Ai-Hua , Hamilton Brett , Rai Subash K. , Alewood Paul , Lewis Richard J. 
Published: June 2021

AbstractThe venom duct origins of predatory and defensive venoms has not been studied for hook-and-line fish hunting cone snails despite the pharmacological importance of their venoms. To better understand the biochemistry and evolution of injected predatory and defensive venoms, we compared distal, central and proximal venom duct sections across three specimens of C. striatus (Pionoconus) using proteomic and transcriptomic approaches. A total of 370 conotoxin precursors were identified from the whole venom duct transcriptome. Milked defensive venom was enriched with a potent cocktail of proximally expressed inhibitory α-, ω- and μ-conotoxins compared to milked predatory venom. In contrast, excitatory κA-conotoxins dominated both the predatory and defensive venoms despite their distal expression, suggesting this class of conotoxin can be selectively expressed from the same duct segment in response to either a predatory or defensive stimuli. Given the high abundance of κA-conotoxins in the Pionoconus clade, we hypothesise that the κA-conotoxins have evolved through adaptive evolution following their repurposing from ancestral inhibitory A superfamily conotoxins to facilitate the dietary shift to fish hunting and species radiation in this clade.
Can wood-decaying urban macrofungi be identified by using fuzzy interference system? An example in Central European Ganoderma species
Authors: Michalíková Alžbeta , Beck Terézia , Gáper Ján , Pristaš Peter , Gáperová Svetlana 
Published: June 2021

AbstractGanoderma is a cosmopolitan genus of wood-decaying basidiomycetous macrofungi that can rot the roots and/or lower trunk. Among the standing trees, their presence often indicates that a hazard assessment may be necessary. These bracket fungi are commonly known for the crust-like upper surfaces of their basidiocarps and formation of white rot. Six species occur in central European urban habitats. Several of them, such as Ganoderma adspersum, G. applanatum, G. resinaceum and G. pfeifferi, are most hazardous fungi causing extensive horizontal stem decay in urban trees. Therefore, their early identification is crucial for correct management of trees. In this paper, a fast technique is tested for the determination of phytopathologically important urban macrofungi using fuzzy interference system of Sugeno type based on 13 selected traits of 72 basidiocarps of six Ganoderma species and compared to the ITS sequence based determination. Basidiocarps features were processed for the following situations: At first, the FIS of Sugeno 2 type (without basidiospore sizes) was used and 57 Ganoderma basidiocarps (79.17%) were correctly determined. Determination success increased to 96.61% after selecting basidiocarps with critical values (15 basidiocarps). These undeterminable basidiocarps must be analyzed by molecular methods. In a case, that basidiospore sizes of some basidiocarps were known, a combination of Sugeno 1 (31 basidiocarps with known basidiospore size) and Sugeno 2 (41 basidiocarps with unknown basidiospore size) was used. 84.72% of Ganoderma basidiocarps were correctly identified. Determination success increased to 96.83% after selecting basidiocarps with critical values (11 basidiocarps).
Analysing Twitter semantic networks: the case of 2018 Italian elections
Authors: Radicioni Tommaso , Saracco Fabio , Pavan Elena , Squartini Tiziano 
Published: June 2021

AbstractSocial media play a key role in shaping citizens’ political opinion. According to the Eurobarometer, the percentage of EU citizens employing online social networks on a daily basis has increased from 18% in 2010 to 48% in 2019. The entwinement between social media and the unfolding of political dynamics has motivated the interest of researchers for the analysis ofusers online behavior—with particular emphasis ongroup polarizationduring debates andecho-chambers formation. In this context,semantic aspectshave remained largely under-explored. In this paper, we aim at filling this gap by adopting a two-steps approach. First, we identify thediscursive communitiesanimating the political debate in the run up of the 2018 Italian Elections as groups of users with a significantly-similar retweeting behavior. Second, we study the mechanisms that shape their internal discussions by monitoring, on a daily basis, the structural evolution of the semantic networks they induce. Above and beyond specifying the semantic peculiarities of the Italian electoral competition, our approach innovates studies of online political discussions in two main ways. On the one hand, it grounds semantic analysis within users’ behaviors by implementing a method, rooted in statistical theory, that guarantees that our inference of socio-semantic structures is not biased by any unsupported assumption about missing information; on the other, it is completely automated as it does not rest upon any manual labelling (either based on the users’ features or on their sharing patterns). These elements make our method applicable to any Twitter discussion regardless of the language or the topic addressed.
In silico comparison of SARS-CoV-2 spike protein-ACE2 binding affinities across species and implications for virus origin
Authors: Piplani Sakshi , Singh Puneet Kumar , Winkler David A. , Petrovsky Nikolai 
Published: June 2021

AbstractThe devastating impact of the COVID-19 pandemic caused by SARS–coronavirus 2 (SARS-CoV-2) has raised important questions about its origins and the mechanism of its transfer to humans. A further question was whether companion or commercial animals could act as SARS-CoV-2 vectors, with early data suggesting susceptibility is species specific. To better understand SARS-CoV-2 species susceptibility, we undertook an in silico structural homology modelling, protein–protein docking, and molecular dynamics simulation study of SARS-CoV-2 spike protein’s ability to bind angiotensin converting enzyme 2 (ACE2) from relevant species. Spike protein exhibited the highest binding to human (h)ACE2 of all the species tested, forming the highest number of hydrogen bonds with hACE2. Interestingly, pangolin ACE2 showed the next highest binding affinity despite having a relatively low sequence homology, whereas the affinity of monkey ACE2 was much lower despite its high sequence similarity to hACE2. These differences highlight the power of a structural versus a sequence-based approach to cross-species analyses. ACE2 species in the upper half of the predicted affinity range (monkey, hamster, dog, ferret, cat) have been shown to be permissive to SARS-CoV-2 infection, supporting a correlation between binding affinity and infection susceptibility. These findings show that the earliest known SARS-CoV-2 isolates were surprisingly well adapted to bind strongly to human ACE2, helping explain its efficient human to human respiratory transmission. This study highlights how in silico structural modelling methods can be used to rapidly generate information on novel viruses to help predict their behaviour and aid in countermeasure development.
An information theoretic approach to link prediction in multiplex networks
Authors: Jafari Seyed Hossein , Abdolhosseini-Qomi Amir Mahdi , Asadpour Masoud , Rahgozar Maseud , Yazdani Naser 
Published: June 2021

AbstractThe entities of real-world networks are connected via different types of connections (i.e., layers). The task of link prediction in multiplex networks is about finding missing connections based on both intra-layer and inter-layer correlations. Our observations confirm that in a wide range of real-world multiplex networks, from social to biological and technological, a positive correlation exists between connection probability in one layer and similarity in other layers. Accordingly, a similarity-based automatic general-purpose multiplex link prediction method—SimBins—is devised that quantifies the amount of connection uncertainty based on observed inter-layer correlations in a multiplex network. Moreover, SimBins enhances the prediction quality in the target layer by incorporating the effect of link overlap across layers. Applying SimBins to various datasets from diverse domains, our findings indicate that SimBins outperforms the compared methods (both baseline and state-of-the-art methods) in most instances when predicting links. Furthermore, it is discussed that SimBins imposes minor computational overhead to the base similarity measures making it a potentially fast method, suitable for large-scale multiplex networks.
Differences in in vitro microglial accumulation of the energy metabolism tracers [18F]FDG and [18F]BCPP-EF during LPS- and IL4 stimulation
Authors: Suzuki Chie , Han Sarina , Kesavamoorthy Gandhervin , Kosugi Mutsumi , Araki Kaori , Harada Norihiro , Kanazawa Masakatsu , Tsukada Hideo , Magata Yasuhiro , Ouchi Yasuomi 
Published: June 2021

AbstractThe positron emission tomography probes 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) and 2-tert-butyl-4-chloro-5-{6-[2-(2-[18F]fluoroethoxy)-ethoxy]-pyridin-3-ylmethoxy}-2H-pyridazin-3-one ([18F]BCPP-EF) are designed to evaluate glycolysis and oxidative phosphorylation, respectively, and are both used to estimate neuronal activity. However, previous studies have shown a discrepancy in these probes’ accumulation in the compromised region, possibly due to the presence of activated microglia acting like deleterious or neuroprotective phenotypes. Hence, we evaluated lipopolysaccharide (LPS)- and interleukin 4 (IL4)-stimulated microglial uptake of [14C]2DG and [18F]BCPP-EF to give a new insight into the hypothesis that different uptake of [18F]FDG and [18F]BCPP-EF can be ascribed to the different metabolic pathways activated during microglial activation. LPS or IL4 stimulation increased the proinflammatory or anti-inflammatory marker gene expression in microglial cells. In LPS-stimulated cells, [14C]2DG uptake and glycolysis related gene expression were elevated, and [18F]BCPP-EF uptake was reduced. In IL4-stimulated cells, [18F]BCPP-EF uptake was increased, and [14C]2DG uptake was decreased. The expression of genes involved in glycolysis and mitochondrial complex I subunits was not changed by IL4 stimulation. The uptake of [14C]2DG and [18F]BCPP-EF differs in LPS- and IL4-stimulated polarized microglial cells. The present results suggest that the in vivo accumulation of metabolic tracers [18F]FDG and [18F]BCPP-EF can be influenced by the different aspects of neuroinflammation.
Association of serum bilirubin levels with risk of cancer development and total death
Authors: Inoguchi Toyoshi , Nohara Yasunobu , Nojiri Chinatsu , Nakashima Naoki 
Published: June 2021

AbstractSerum levels of bilirubin, a strong antioxidant, may influence cancer risk. We aimed to assess the association between serum bilirubin levels and cancer risk. Data were retrieved from 10-year electronic medical records at Kyushu University Hospital (Japan) for patients aged 20 to 69 years old. The associations of baseline bilirubin levels with cancer risk (lung, colon, breast, prostate, and cervical) were evaluated using a gradient boosting decision tree (GBDT) model, a machine learning algorithm, and Cox proportional hazard regression model, adjusted for age, smoking, body mass index, and diabetes. The number of study subjects was 29,080. Median follow-up time was 4.7 years. GBDT models illustrated that baseline bilirubin levels were negatively and non-linearly associated with the risk of lung (men), colon, and cervical cancer. In contrast, a U-shaped association was observed for breast and prostate cancer. Cox hazard regression analyses confirmed that baseline bilirubin levels (< 1.2 mg/dL) were negatively associated with lung cancer risk in men (HR = 0.474, 95% CI 0.271–0.828, P = 0.009) and cervical cancer risk (HR = 0.365, 95% CI 0.136–0.977, P = 0.045). Additionally, low bilirubin levels (< 0.6 mg/dL) were associated with total death (HR = 1.744, 95% CI 1.369–2.222, P < 0.001). Serum bilirubin may have a beneficial effect on the risk of some types of cancers.
Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia
Authors: Lichtner Gregor , Balzer Felix , Haufe Stefan , Giesa Niklas , Schiefenhövel Fridtjof , Schmieding Malte , Jurth Carlo , Kopp Wolfgang , Akalin Altuna , Schaller Stefan J. , Weber-Carstens Steffen , Spies Claudia , von Dincklage Falk 
Published: June 2021

AbstractIn a pandemic with a novel disease, disease-specific prognosis models are available only with a delay. To bridge the critical early phase, models built for similar diseases might be applied. To test the accuracy of such a knowledge transfer, we investigated how precise lethal courses in critically ill COVID-19 patients can be predicted by a model trained on critically ill non-COVID-19 viral pneumonia patients. We trained gradient boosted decision tree models on 718 (245 deceased) non-COVID-19 viral pneumonia patients to predict individual ICU mortality and applied it to 1054 (369 deceased) COVID-19 patients. Our model showed a significantly better predictive performance (AUROC 0.86 [95% CI 0.86–0.87]) than the clinical scores APACHE2 (0.63 [95% CI 0.61–0.65]), SAPS2 (0.72 [95% CI 0.71–0.74]) and SOFA (0.76 [95% CI 0.75–0.77]), the COVID-19-specific mortality prediction models of Zhou (0.76 [95% CI 0.73–0.78]) and Wang (laboratory: 0.62 [95% CI 0.59–0.65]; clinical: 0.56 [95% CI 0.55–0.58]) and the 4C COVID-19 Mortality score (0.71 [95% CI 0.70–0.72]). We conclude that lethal courses in critically ill COVID-19 patients can be predicted by a machine learning model trained on non-COVID-19 patients. Our results suggest that in a pandemic with a novel disease, prognosis models built for similar diseases can be applied, even when the diseases differ in time courses and in rates of critical and lethal courses.
Pairwise interact-and-imitate dynamics
Authors: Bilancini Ennio , Boncinelli Leonardo , Campigotto Nicola 
Published: June 2021

AbstractThis paper introduces and studies a class of evolutionary dynamics—pairwise interact-and-imitate dynamics (PIID)—in which agents are matched in pairs, engage in a symmetric game, and imitate the opponent with a probability that depends on the difference in their payoffs. We provide a condition on the underlying game, named supremacy, and show that the population state in which all agents play the supreme strategy is globally asymptotically stable. We extend the framework to allow for payoff uncertainty, and check the robustness of our results to the introduction of some heterogeneity in the revision protocol followed by agents. Finally, we show that PIID can allow the survival of strictly dominated strategies, leads to the emergence of inefficient conventions in social dilemmas, and makes assortment ineffective in promoting cooperation.
High-throughput 16S rRNA gene sequencing of the microbial community associated with palm oil mill effluents of two oil processing systems
Authors: Aka Benedicte Ella Zranseu , Djeni Theodore N’dede , Amoikon Simon Laurent Tiemele , Kannengiesser Jan , Ouazzani Naaila , Dje Marcellin Koffi 
Published: June 2021

AbstractPalm Oil Mill Effluents (POME) are complex fermentative substrates which habour diverse native microbial contaminants. However, knowledge on the microbiota community shift caused by the anthropogenic effects of POME in the environment is up to date still to be extensively documented. In this study, the bacterial and archaeal communities of POME from two palm oil processing systems (artisanal and industrial) were investigated by Illumina MiSeq Platform. Despite the common characteristics of these wastewaters, we found that their microbial communities were significantly different with regard to their diversity and relative abundance of their different Amplicon Sequence Variants (ASV). Indeed, POME from industrial plants harboured as dominant phylaFirmicutes(46.24%),Bacteroidetes(34.19%),Proteobacteria(15.11%), with the particular presence ofSpirochaetes,verrucomicrobiaandSynergistetes, while those from artisanal production were colonized byFirmicutes(92.06%),Proteobacteria(4.21%) andActinobacteria(2.09%). Furthermore, 43 AVSs of archaea were detected only in POME from industrial plants and assigned toCrenarchaeota,Diapherotrites,EuryarchaeotaandNanoarchaeaeotaphyla, populated mainly by many methane-forming archaea. Definitively, the microbial community composition of POME from both type of processing was markedly different, showing that the history of these ecosystems and various processing conditions have a great impact on each microbial community structure and diversity. By improving knowledge about this microbiome, the results also provide insight into the potential microbial contaminants of soils and rivers receiving these wastewaters.