bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating node embeddings of complex networks
Authors: Dehghan-Kooshkghazi Arash , Kamiński Bogumił , Kraiński Łukasz , Prałat Paweł , Théberge François 
Published: August 2022

Abstract
Graph embedding is a transformation of nodes of a graph into a set of vectors. A good embedding should capture the graph topology, node-to-node relationship and other relevant information about the graph, its subgraphs and nodes. If these objectives are achieved, an embedding is a meaningful, understandable, compressed representations of a network that can be used for other machine learning tools such as node classification, community detection or link prediction. In this article, we do a series of extensive experiments with selected graph embedding algorithms, both on real-world networks as well as artificially generated ones. Based on those experiments, we formulate the following general conclusions. First, we confirm the main problem of node embeddings that is rather well-known to practitioners but less documented in the literature. There exist many algorithms available to choose from which use different techniques and have various parameters that may be tuned, the dimension being one of them. One needs to ensure that embeddings describe the properties of the underlying graphs well but, as our experiments confirm, it highly depends on properties of the network at hand and the given application in mind. As a result, selecting the best embedding is a challenging task and very often requires domain experts. Since investigating embeddings in a supervised manner is computationally expensive, there is a need for an unsupervised tool that is able to select a handful of promising embeddings for future (supervised) investigation. A general framework, introduced recently in the literature and easily available on GitHub repository, provides one of the very first tools for an unsupervised graph embedding comparison by assigning the ‘divergence score’ to embeddings with a goal of distinguishing good from bad ones. We show that the divergence score strongly correlates with the quality of embeddings by investigating three main applications of node embeddings: node classification, community detection and link prediction.
Modeling and integration of N-glycan biomarkers in a comprehensive biomarker data model
Authors: Lyman Daniel F , Bell Amanda , Black Alyson , Dingerdissen Hayley , Cauley Edmund , Gogate Nikhita , Liu David , Joseph Ashia , Kahsay Robel , Crichton Daniel J , Mehta Anand , Mazumder Raja 
Published: August 2022

Abstract
Molecular biomarkers measure discrete components of biological processes that can contribute to disorders when impaired. Great interest exists in discovering early cancer biomarkers to improve outcomes. Biomarkers represented in a standardized data model, integrated with multi-omics data, may improve the understanding and use of novel biomarkers such as glycans and glycoconjugates. Among altered components in tumorigenesis, N-glycans exhibit substantial biomarker potential, when analyzed with their protein carriers. However, such data are distributed across publications and databases of diverse formats, which hamper their use in research and clinical application. Mass spectrometry measures of 50 N-glycans on 7 serum proteins in liver disease were integrated (as a panel) into a cancer biomarker data model, providing a unique identifier, standard nomenclature, links to glycan resources, and accession and ontology annotations to standard protein, gene, disease, and biomarker information. Data provenance was documented with a standardized United States Food and Drug Administration-supported BioCompute Object. Using the biomarker data model allows the capture of granular information, such as glycans with different levels of abundance in cirrhosis, hepatocellular carcinoma, and transplant groups. Such representation in a standardized data model harmonizes glycomics data in a unified framework, making glycan–protein biomarker data exploration more available to investigators and to other data resources. The biomarker data model we describe can be used by researchers to describe their novel glycan and glycoconjugate biomarkers; it can integrate N-glycan biomarker data with multi-source biomedical data and can foster discovery and insight within a unified data framework for glycan biomarker representation, thereby making the data FAIR (Findable, Accessible, Interoperable, Reusable) (https://www.go-fair.org/fair-principles/).
Development and applications of sialoglycan-recognizing probes (SGRPs) with defined specificities: exploring the dynamic mammalian sialoglycome
Authors: Srivastava Saurabh , Verhagen Andrea , Sasmal Aniruddha , Wasik Brian R , Diaz Sandra , Yu Hai , Bensing Barbara A , Khan Naazneen , Khedri Zahra , Secrest Patrick , Sullam Paul , Varki Nissi , Chen Xi , Parrish Colin R , Varki Ajit 
Published: August 2022

Abstract
Glycans that are abundantly displayed on vertebrate cell surface and secreted molecules are often capped with terminal sialic acids (Sias). These diverse 9-carbon-backbone monosaccharides are involved in numerous intrinsic biological processes. They also interact with commensals and pathogens, while undergoing dynamic changes in time and space, often influenced by environmental conditions. However, most of this sialoglycan complexity and variation remains poorly characterized by conventional techniques, which often tend to destroy or overlook crucial aspects of Sia diversity and/or fail to elucidate native structures in biological systems, i.e. in the intact sialome. To date, in situ detection and analysis of sialoglycans has largely relied on the use of plant lectins, sialidases, or antibodies, whose preferences (with certain exceptions) are limited and/or uncertain. We took advantage of naturally evolved microbial molecules (bacterial adhesins, toxin subunits, and viral hemagglutinin-esterases) that recognize sialoglycans with defined specificity to delineate 9 classes of sialoglycan recognizing probes (SGRPs: SGRP1–SGRP9) that can be used to explore mammalian sialome changes in a simple and systematic manner, using techniques common in most laboratories. SGRP candidates with specificity defined by sialoglycan microarray studies were engineered as tagged probes, each with a corresponding nonbinding mutant probe as a simple and reliable negative control. The optimized panel of SGRPs can be used in methods commonly available in most bioscience labs, such as ELISA, western blot, flow cytometry, and histochemistry. To demonstrate the utility of this approach, we provide examples of sialoglycome differences in tissues from C57BL/6 wild-type mice and human-like Cmah−/− mice.
AAV-mediated gene-replacement therapy restores viability of BCD patient iPSC derived RPE cells and vision of Cyp4v3 knockout mice
Authors: Jia Ruixuan , Meng Xiang , Chen Shaohong , Zhang Fan , Du Juan , Liu Xiaozhen , Yang Liping 
Published: August 2022

Abstract
Bietti crystalline corneoretinal dystrophy (BCD) is an autosomal recessive retinal degenerative disease characterized by yellow-white crystal deposits in the posterior pole, degeneration of the retinal pigment epithelium (RPE), and sclerosis of the choroid. Mutations in the cytochrome P450 4V2 gene (CYP4V2) cause BCD, which is associated with lipid metabolic disruption. The use of gene-replacement therapy in BCD has been hampered by the lack of disease models. To advance CYP4V2 gene-replacement therapy, we generated BCD patient-specific induced pluripotent stem cell (iPSC)–RPE cells and Cyp4v3 knockout (KO) mice as disease models and AAV2/8-CAG-CYP4V2 as treatment vectors. We demonstrated that after adeno-associated virus (AAV)-mediated CYP4V2 gene-replacement therapy BCD–iPSC–RPE cells presented restored cell survival and reduced lipid droplets accumulation; restoration of vision in Cyp4v3 KO mice was revealed by elevated electroretinogram amplitude and ameliorated RPE degeneration. These results suggest that AAV-mediated gene-replacement therapy in BCD patients is a promising strategy.
Glycine-rich RNA-binding cofactor RZ1AL is associated with tomato ripening and development
Authors: Li Xindi , Yang Yongfang , Zeng Ni , Qu Guiqin , Fu Daqi , Zhu Benzhong , Luo Yunbo , Ostersetzer-Biran Oren , Zhu Hongliang 
Published: August 2022

Abstract
Tomato ripening is a complex and dynamic process coordinated by many regulatory elements, including plant hormones, transcription factors, and numerous ripening-related RNAs and proteins. Although recent studies have shown that some RNA-binding proteins are involved in the regulation of the ripening process, understanding of how RNA-binding proteins affect fruit ripening is still limited. Here, we report the analysis of a glycine-rich RNA-binding protein, RZ1A-Like (RZ1AL), which plays an important role in tomato ripening, especially fruit coloring. To analyze the functions of RZ1AL in fruit development and ripening, we generated knockout cr-rz1al mutant lines via the CRISPR/Cas9 gene-editing system. Knockout of RZ1AL reduced fruit lycopene content and weight in the cr-rz1al mutant plants. RZ1AL encodes a nucleus-localized protein that is associated with Cajal-related bodies. RNA-seq data demonstrated that the expression levels of genes that encode several key enzymes associated with carotenoid biosynthesis and metabolism were notably downregulated in cr-rz1al fruits. Proteomic analysis revealed that the levels of various ribosomal subunit proteins were reduced. This could affect the translation of ripening-related proteins such as ZDS. Collectively, our findings demonstrate that RZ1AL may participate in the regulation of carotenoid biosynthesis and metabolism and affect tomato development and fruit ripening.
Pleural solitary fibrous tumour with brain metastasis: an aggressive tumour and pathologic conundrum
Authors: Williams Catherine , French Daniel , Christie Sean , Castonguay Mathieu , Wallace Alison 
Published: August 2022

Abstract
Solitary fibrous tumours of the pleura are a rare finding; those with brain metastases are rarer still. Here, we present the evolution of a pleural solitary fibrous tumour in a 70-year-old male treated surgically, and subsequent brain metastasis requiring emergent craniotomy and excision. The patient received adjuvant radiotherapy to the brain and had no recurrence of brain metastases; however, 1 year surveillance imaging demonstrated metastases to the lungs, liver and spleen for which he received chemotherapy but eventually succumbed to the disease process. Solitary fibrous tumours are most often slow-growing, relatively benign neoplasms. However, up to 10% are malignant. This case highlights the importance of surgical resection of these benign tumours with malignant potential.
The protein phosphatase 2A catalytic subunit StPP2Ac2b is involved in the control of potato tuber sprouting and source–sink balance in tubers and sprouts
Authors: Muñiz García María N , Cortelezzi Juan I , Capiati Daniela A 
Published: August 2022

Abstract
Sprouting negatively affects the quality of stored potato tubers. Understanding the molecular mechanisms that control this process is important for the development of potato varieties with desired sprouting characteristics. Serine/threonine protein phosphatase type 2A (PP2A) has been implicated in several developmental programs and stress responses in plants. PP2A comprises a catalytic (PP2Ac), a scaffolding (A), and a regulatory (B) subunit. In cultivated potato, six PP2Ac isoforms were identified, named StPP2Ac1, 2a, 2b, 3, 4, and 5. In this study we evaluated the sprouting behavior of potato tubers overexpressing the catalytic subunit 2b (StPP2Ac2b-OE). The onset of sprouting and initial sprout elongation is significantly delayed in StPP2Ac2b-OE tubers; however, sprout growth is accelerated during the late stages of development, due to a high degree of branching. StPP2Ac2b-OE tubers also exhibit a pronounced loss of apical dominance. These developmental characteristics are accompanied by changes in carbohydrate metabolism and response to gibberellic acid, and a differential balance between abscisic acid, gibberellic acid, cytokinins, and auxin. Overexpression of StPP2Ac2b alters the source–sink balance, increasing the source capacity of the tuber, and the sink strength of the sprout to support its accelerated growth.
Astrochemical model to study the abundances of branched carbon-chain molecules in a hot molecular core with realistic binding energies
Authors: Srivastav Satyam , Sil Milan , Gorai Prasanta , Pathak Amit , Sivaraman Bhalamurugan , Das Ankan 
Published: August 2022

ABSTRACT
Straight-chain (normal-propyl cyanide, $\rm {n-C_3H_7CN}$) and branched-chain (iso-propyl cyanide, $\rm {i-C_3H_7CN}$) alkyl cyanides are recently identified in the massive star-forming regions (Sgr B2(N) and Orion). These branched-chain molecules indicate that the key amino acids (side-chain structures) may also be present in a similar region. The process by which this branching could propagate towards the higher order (butyl cyanide, $\rm {C_4H_9CN}$) is an active field of research. Since the grain catalysis process could have formed a major portion of these species, considering a realistic set of binding energies are indeed essential. We employ quantum chemical calculations to estimate the binding energy of these species considering water as a substrate because water is the principal constituent of this interstellar ice. We find significantly lower binding energy values for these species than were previously used. It is noticed that the use of realistic binding energy values can significantly change the abundance of these species. The branching is more favourable for the higher order alkyl cyanides with the new binding energies. With the inclusion of our new binding energy values and one essential destruction reaction ($\rm {i-C_3H_7CN+H \rightarrow CH_3C(CH_3)CN + H_2}$, having an activation barrier of 947 K), abundances of $\rm {t-C_4H_9CN}$ dramatically increased.
Effect of the UV dose on the formation of complex organic molecules in astrophysical ices: irradiation of methanol ices at 20 K and 80 K
Authors: Tenelanda-Osorio Laura I , Bouquet Alexis , Javelle Thomas , Mousis Olivier , Duvernay Fabrice , Danger Grégoire 
Published: August 2022

ABSTRACT
Methanol is a ubiquitous complex organic molecule (COM) in the interstellar medium, thought to be a precursor of larger COMs when it is submitted to different energetic processes, that can trigger chemical reactions in solid and gas phases. Using laboratory experiments, we report the characterization of the evolution of photoproducts generated by the UV irradiation of methanol ice at different UV doses and temperatures (20 and 80 K). We used gas chromatography coupled to mass spectrometry (GC-MS) to analyse the volatile organic compounds (VOCs) recovered during the warming of the photoprocessed methanol ice. We identified 21 molecules (with up to five carbon atoms, including alcohols, aldehydes, ketones, ester, and ethers) and followed their abundance as a function of the UV fluence and ice temperatures. With increasing UV fluence, an increase in the production of heavier COMs is observed, while species with 1 or 2 carbon atoms are depleted or do not increase. Species within a same chemical family show the same pattern of evolution, with heavier molecules present in smaller quantities. Ketones and esters are the chemical families that lead to more complex molecules and start forming at the earliest stages of irradiation. Their formation pathways are driven by radical recombinations with CO as the main building blocks. Aldehydes are formed before their alcohol counterparts, implying they do not form through alcohol dehydrogenation, but via radical recombination around HCO. Ethers seem to be the precursors of a large set of COMs, and alcohols present a steady profile throughout irradiation.
Constraining IGM enrichment and metallicity with the C iv forest correlation function
Authors: Tie Suk Sien , Hennawi Joseph F , Kakiichi Koki , Bosman Sarah E I 
Published: August 2022

ABSTRACT
The distribution and abundance of metals in the diffuse intergalactic medium (IGM) have implications for galaxy formation and evolution models, and has been argued to be sensitive to the Universe’s reionization history. However, reduced sensitivity in the near-IR implies that probing IGM metals at z &gt; 4 is currently out of reach with the traditional method of detecting individual absorbers. We present a new technique based on clustering analysis that enables the detection of these weak IGM absorbers. We investigate the two-point correlation function (2PCF) of the ${\rm C\, {\small IV}}$ forest as a probe of IGM metallicity and enrichment topology by simulating the z = 4.5 IGM with models of inhomogeneous metal distributions. The 2PCF of the ${\rm C\, {\small IV}}$ forest demonstrates a clear peak at a characteristic separation corresponding to the doublet separation of the ${\rm C\, {\small IV}}$ line.The peak amplitude scales quadratically with metallicity, while enrichment topology affects both the shape and amplitude of the 2PCF. For models consistent with the distribution of metals at z ∼ 3, we find that we can constrain [C/H] to within 0.2 dex, log$\, M_{\rm {min}}$ to within 0.4 dex, and R to within 15 per cent. We show that CGM absorbers can be reliably identified and masked, thus recovering the underlying IGM signal. The auto-correlation of the metal-line forest presents a compelling avenue to constrain the IGM metallicity and enrichment topology with high precision at z &gt; 4, thereby pushing such measurements into the Epoch of Reionization.
Evaluating the prevalence of spurious correlations in pulsar timing array data sets
Authors: Zic Andrew , Hobbs George , Shannon R M , Reardon Daniel , Goncharov Boris , Bhat N D Ramesh , Cameron Andrew , Dai Shi , Dawson J R , Kerr Matthew , Manchester R N , Mandow Rami , Marshman Tommy , Russell Christopher J , Thyagarajan Nithyanandan , Zhu X-J 
Published: August 2022

ABSTRACTPulsar timing array collaborations have recently reported evidence for a noise process with a common spectrum among the millisecond pulsars in the arrays. The spectral properties of this common-noise process are consistent with expectations for an isotropic gravitational-wave background (GWB) from inspiralling supermassive black hole binaries. However, recent simulation analyses based on Parkes Pulsar Timing Array data indicate that such a detection may arise spuriously. In this paper, we use simulated pulsar timing array data sets to further test the robustness of the inference methods for spectral and spatial correlations from a GWB. Expanding on our previous results, we find strong support (Bayes factors exceeding 105) for the presence of a common-spectrum noise process in data sets where no common process is present, under a wide range of timing noise prescriptions per pulsar. We show that these results are highly sensitive to the choice of Bayesian priors on timing noise parameters, with priors that more closely match the injected distributions of timing noise parameters resulting in diminished support for a common-spectrum noise process. These results emphasize shortcomings in current methods for inferring the presence of a common-spectrum process, and imply that the detection of a common process is not a reliable precursor to detection of the GWB. Future searches for the nanohertz GWB should remain focused on detecting spatial correlations, and make use of more tailored specifications for a common-spectrum noise process.
Spectral and timing analysis of Be/X-ray binary EXO 2030+375 during its giant 2021 outburst
Authors: Tamang Ruchi , Ghising Manoj , Tobrej Mohammed , Rai Binay , Paul Bikash Chandra 
Published: August 2022

ABSTRACT
We report the X-ray spectral and timing analysis of the high mass X-ray binary EXO 2030+375 during the 2021 type II outburst. We have incorporated NuSTAR, NICER, Swift/BAT, and Fermi/GBM observations to carry out a comprehensive analysis of the source. Pulse profiles in different energy ranges and time intervals have been generated and analysed. We have performed a brief comparison of the observations amidst the peak outburst condition and also during the decaying state of the outburst. Pulse profiles are found to evolve with time and energy. An iron emission line at (6–7) keV is observed in the X-ray continuum. Distinct absorption features were observed in the spectra corresponding to the peak outburst state while such features were not detected during the later decaying phase of the outburst. We have estimated the characteristic spin-up time-scale to be ∽ 60 yr. The continuum flux of the system and the varying luminosities covering the entire outburst period have been used to interpret the characteristics of the source. We have summarized the variability of various parameters along with their underlying physical implications.
Explaining mercury via a single giant impact is highly unlikely
Authors: Franco P , Izidoro A , Winter O C , Torres K S , Amarante A 
Published: August 2022

ABSTRACTThe classical scenario of terrestrial planet formation is characterized by a phase of giant impacts among Moon-to-Mars mass planetary embryos. While the classic model and its adaptations have produced adequate analogues of the outer three terrestrial planets, Mercury’s origin remains elusive. Mercury’s high-core mass fraction compared to the Earth’s is particularly outstanding. Among collisional hypotheses, this feature has been long interpreted as the outcome of an energetic giant impact among two massive protoplanets. Here, we revisit the classical scenario of terrestrial planet formation with focus on the outcome of giant impacts. We have performed a large number of N-body simulations considering different initial distributions of planetary embryos and planetesimals. Our simulations tested the effects of different giant planet configurations, from virtually circular to very eccentric configurations. We compare the giant impacts produced in our simulations with those that are more likely to account for the formation of Mercury and the Moon according to smoothed hydrodynamic simulations. Impact events that could lead to Moon’s formation are observed in all our simulations with up to ∼20 per cent of all giant impacts, consistent with the range of the expected Moon-forming event conditions. On the other hand, Mercury-forming events via a single giant impact are extremely rare, accounting for less than ∼1 per cent of all giant impacts. Our results suggest that producing Mercury as a remnant of a single giant impact that strips out the mantle of a differentiated planetary object with Earth-like iron-silicate ratio is challenging and alternative scenarios may be required (e.g. multiple collisions).
Efficient detection and assembly of non-reference DNA sequences with synthetic long reads
Authors: Meleshko Dmitry , Yang Rui , Marks Patrick , Williams Stephen , Hajirasouliha Iman 
Published: August 2022

Abstract
Recent pan-genome studies have revealed an abundance of DNA sequences in human genomes that are not present in the reference genome. A lion’s share of these non-reference sequences (NRSs) cannot be reliably assembled or placed on the reference genome. Improvements in long-read and synthetic long-read (aka linked-read) technologies have great potential for the characterization of NRSs. While synthetic long reads require less input DNA than long-read datasets, they are algorithmically more challenging to use. Except for computationally expensive whole-genome assembly methods, there is no synthetic long-read method for NRS detection. We propose a novel integrated alignment-based and local assembly-based algorithm, Novel-X, that uses the barcode information encoded in synthetic long reads to improve the detection of such events without a whole-genome de novo assembly. Our evaluations demonstrate that Novel-X finds many non-reference sequences that cannot be found by state-of-the-art short-read methods. We applied Novel-X to a diverse set of 68 samples from the Polaris HiSeq 4000 PGx cohort. Novel-X discovered 16 691 NRS insertions of size &gt; 300 bp (total length 18.2 Mb). Many of them are population specific or may have a functional impact.