bluuebunny/crossref_metadata_2025_split huggingface dataset:
Insights into the role of sialylation in cancer progression and metastasis
Authors: Dobie Christopher , Skropeta Danielle 
Published: November 2020

AbstractUpregulation of sialyltransferases—the enzymes responsible for the addition of sialic acid to growing glycoconjugate chains—and the resultant hypersialylation of up to 40–60% of tumour cell surfaces are established hallmarks of several cancers, including lung, breast, ovarian, pancreatic and prostate cancer. Hypersialylation promotes tumour metastasis by several routes, including enhancing immune evasion and tumour cell survival, and stimulating tumour invasion and migration. The critical role of enzymes that regulate sialic acid in tumour cell growth and metastasis points towards targeting sialylation as a potential new anti-metastatic cancer treatment strategy. Herein, we explore insights into the mechanisms by which hypersialylation plays a role in promoting metastasis, and explore the current state of sialyltransferase inhibitor development.
Understanding the impact of sex and stage differences on melanoma cancer patient survival: a SEER-based study
Authors: Smith Aiden J. , Lambert Paul C. , Rutherford Mark J. 
Published: November 2020

Abstract
Background
This paper investigates the difference in survival of melanoma patients across stage and sex by utilising net survival measures. Metrics are presented at both the individual and population level.

Methods
Flexible parametric models were fitted to estimate life-expectancy metrics to be applied to a group of 104,938 subjects with a melanoma skin cancer diagnosis from 2000 to 2017. Period analysis was used for better predictions for newly diagnosed patients, and missing-stage information was imputed for 9918 patients. Female relative survival was assigned to male subjects to demonstrate the survival discrepancies experienced between sexes.

Results
At the age of 60, males diagnosed at the regional stage lose an average of 4.99 years of life compared to the general population, and females lose 4.79 years, demonstrating the sex variation in expected mortality. In 2017, males contributed 3545 more life years lost than females, and a potential 1931 life years could be preserved if sex differences in survival were eliminated.

Conclusions
This study demonstrates the survival differences across population subgroups as a result of a melanoma cancer diagnosis. Females experience better prognosis across age and stage at diagnosis; however, further investigation is necessary to better understand the mechanisms behind this difference.
Heparan sulfate assists SARS-CoV-2 in cell entry and can be targeted by approved drugs in vitro
Authors: Zhang Qi , Chen Catherine Zhengzheng , Swaroop Manju , Xu Miao , Wang Lihui , Lee Juhyung , Wang Amy Qiu , Pradhan Manisha , Hagen Natalie , Chen Lu , Shen Min , Luo Zhiji , Xu Xin , Xu Yue , Huang Wenwei , Zheng Wei , Ye Yihong 
Published: November 2020

AbstractThe cell entry of SARS-CoV-2 has emerged as an attractive drug repurposing target for COVID-19. Here we combine genetics and chemical perturbation to demonstrate that ACE2-mediated entry of SARS-Cov and CoV-2 requires the cell surface heparan sulfate (HS) as an assisting cofactor: ablation of genes involved in HS biosynthesis or incubating cells with a HS mimetic both inhibit Spike-mediated viral entry. We show that heparin/HS binds to Spike directly, and facilitates the attachment of Spike-bearing viral particles to the cell surface to promote viral entry. We screened approved drugs and identified two classes of inhibitors that act via distinct mechanisms to target this entry pathway. Among the drugs characterized, Mitoxantrone is a potent HS inhibitor, while Sunitinib and BNTX disrupt the actin network to indirectly abrogate HS-assisted viral entry. We further show that drugs of the two classes can be combined to generate a synergized activity against SARS-CoV-2-induced cytopathic effect. Altogether, our study establishes HS as an attachment factor that assists SARS coronavirus cell entry and reveals drugs capable of targeting this important step in the viral life cycle.
Systematic elucidation of neuron-astrocyte interaction in models of amyotrophic lateral sclerosis using multi-modal integrated bioinformatics workflow
Authors: Mishra Vartika , Re Diane B. , Le Verche Virginia , Alvarez Mariano J. , Vasciaveo Alessandro , Jacquier Arnaud , Doulias Paschalis-Tomas , Greco Todd M. , Nizzardo Monica , Papadimitriou Dimitra , Nagata Tetsuya , Rinchetti Paola , Perez-Torres Eduardo J. , Politi Kristin A. , Ikiz Burcin , Clare Kevin , Than Manuel E. , Corti Stefania , Ischiropoulos Harry , Lotti Francesco , Califano Andrea , Przedborski Serge 
Published: November 2020

AbstractCell-to-cell communications are critical determinants of pathophysiological phenotypes, but methodologies for their systematic elucidation are lacking. Herein, we propose an approach for the Systematic Elucidation and Assessment of Regulatory Cell-to-cell Interaction Networks (SEARCHIN) to identify ligand-mediated interactions between distinct cellular compartments. To test this approach, we selected a model of amyotrophic lateral sclerosis (ALS), in which astrocytes expressing mutant superoxide dismutase-1 (mutSOD1) kill wild-type motor neurons (MNs) by an unknown mechanism. Our integrative analysis that combines proteomics and regulatory network analysis infers the interaction between astrocyte-released amyloid precursor protein (APP) and death receptor-6 (DR6) on MNs as the top predicted ligand-receptor pair. The inferred deleterious role of APP and DR6 is confirmed in vitro in models of ALS. Moreover, the DR6 knockdown in MNs of transgenic mutSOD1 mice attenuates the ALS-like phenotype. Our results support the usefulness of integrative, systems biology approach to gain insights into complex neurobiological disease processes as in ALS and posit that the proposed methodology is not restricted to this biological context and could be used in a variety of other non-cell-autonomous communication mechanisms.
State-of-the-art augmented NLP transformer models for direct and single-step retrosynthesis
Authors: Tetko Igor V. , Karpov Pavel , Van Deursen Ruud , Godin Guillaume 
Published: November 2020

AbstractWe investigated the effect of different training scenarios on predicting the (retro)synthesis of chemical compounds using text-like representation of chemical reactions (SMILES) and Natural Language Processing (NLP) neural network Transformer architecture. We showed that data augmentation, which is a powerful method used in image processing, eliminated the effect of data memorization by neural networks and improved their performance for prediction of new sequences. This effect was observed when augmentation was used simultaneously for input and the target data simultaneously. The top-5 accuracy was 84.8% for the prediction of the largest fragment (thus identifying principal transformation for classical retro-synthesis) for the USPTO-50k test dataset, and was achieved by a combination of SMILES augmentation and a beam search algorithm. The same approach provided significantly better results for the prediction of direct reactions from the single-step USPTO-MIT test set. Our model achieved 90.6% top-1 and 96.1% top-5 accuracy for its challenging mixed set and 97% top-5 accuracy for the USPTO-MIT separated set. It also significantly improved results for USPTO-full set single-step retrosynthesis for both top-1 and top-10 accuracies. The appearance frequency of the most abundantly generated SMILES was well correlated with the prediction outcome and can be used as a measure of the quality of reaction prediction.
Introducing Biomedisa as an open-source online platform for biomedical image segmentation
Authors: Lösel Philipp D. , van de Kamp Thomas , Jayme Alejandra , Ershov Alexey , Faragó Tomáš , Pichler Olaf , Tan Jerome Nicholas , Aadepu Narendar , Bremer Sabine , Chilingaryan Suren A. , Heethoff Michael , Kopmann Andreas , Odar Janes , Schmelzle Sebastian , Zuber Marcus , Wittbrodt Joachim , Baumbach Tilo , Heuveline Vincent 
Published: November 2020

AbstractWe present Biomedisa, a free and easy-to-use open-source online platform developed for semi-automatic segmentation of large volumetric images. The segmentation is based on a smart interpolation of sparsely pre-segmented slices taking into account the complete underlying image data. Biomedisa is particularly valuable when little a priori knowledge is available, e.g. for the dense annotation of the training data for a deep neural network. The platform is accessible through a web browser and requires no complex and tedious configuration of software and model parameters, thus addressing the needs of scientists without substantial computational expertise. We demonstrate that Biomedisa can drastically reduce both the time and human effort required to segment large images. It achieves a significant improvement over the conventional approach of densely pre-segmented slices with subsequent morphological interpolation as well as compared to segmentation tools that also consider the underlying image data. Biomedisa can be used for different 3D imaging modalities and various biomedical applications.
The persistence potential of transferable plasmids
Authors: Wang Teng , You Lingchong 
Published: November 2020

AbstractConjugative plasmids can mediate the spread and maintenance of diverse traits and functions in microbial communities. This role depends on the plasmid’s ability to persist in a population. However, for a community consisting of multiple populations transferring multiple plasmids, the conditions underlying plasmid persistence are poorly understood. Here, we describe a plasmid-centric framework that makes it computationally feasible to analyze gene flow in complex communities. Using this framework, we derive the ‘persistence potential’: a general, heuristic metric that predicts the persistence and abundance of any plasmids. We validate the metric with engineered microbial consortia transferring mobilizable plasmids and with quantitative data available in the literature. We believe that our framework and the resulting metric will facilitate a quantitative understanding of natural microbial communities and the engineering of microbial consortia.
99TcO4− removal from legacy defense nuclear waste by an alkaline-stable 2D cationic metal organic framework
Authors: Shen Nannan , Yang Zaixing , Liu Shengtang , Dai Xing , Xiao Chengliang , Taylor-Pashow Kathryn , Li Dien , Yang Chuang , Li Jie , Zhang Yugang , Zhang Mingxing , Zhou Ruhong , Chai Zhifang , Wang Shuao 
Published: November 2020

AbstractRemoval of 99TcO4− from legacy defense nuclear tank waste at Savannah River Site is highly desirable for the purpose of nuclear safety and environmental protection, but currently not achievable given the extreme conditions including high alkalinity, high ionic strength, and strong radiation field. Herein, we present a potential solution to this long-term issue by developing a two-dimensional cationic metal organic framework SCU-103, showing ultrahigh stability in alkaline aqueous media and great resistance to both β and γ radiation. More importantly, it is very effective for 99TcO4− separation from aqueous media as demonstrated by fast exchange kinetics, high sorption capacity, and superior selectivity, leading to the successful removal of 99TcO4− from actual Savannah River Site high level tank waste for the first time, to the best of our knowledge. In addition, the uptake mechanism is comprehensively elucidated by molecular dynamics simulation and density functional theory calculation, showing a unique chemical recognition of anions with low charge density.
Oiling-out effect improves the efficiency of extracting aroma compounds from edible oil
Authors: Suzuki Daisuke , Sato Yuko , Kamasaka Hiroshi , Kuriki Takashi , Tamura Hirotoshi 
Published: November 2020

AbstractVolatile compounds in foods are a significant factor that affects food intake and preference. However, volatile components in edible oils are poorly understood due to a strong matrix effect. In this study, we developed a method of extracting volatile compounds from extra virgin coconut oil (EVCO) by means of oiling-out assisted liquid-liquid extraction (OA-LLE). Consequently, 44 aroma compounds were isolated and identified from only 5 g of EVCO. Various aroma compounds were detected in addition to δ-lactones. The ratio of the natural abundance of the enantiomers of δ-lactones in EVCO was also revealed. Compared with the conventional methods of solvent assisted flavor evaporation (SAFE) and head-space solid-phase micro extraction (HS-SPME), OA-LLE was able to isolate a wide range and large number of volatile compounds from EVCO without leaving oil residues. Therefore, isolating aroma compounds from edible oil based on the oiling-out effect should provide an innovative extraction method.
S-band hybrid amplifiers based on hydrogenated diamond FETs
Authors: Ciccognani Walter , Colangeli Sergio , Verona Claudio , Di Pietrantonio Fabio , Cannatà Domenico , Benetti Massimiliano , Camarchia Vittorio , Pirola Marco , Longhi Patrick E. , Verona Rinati Gianluca , Marinelli Marco , Limiti Ernesto 
Published: November 2020

AbstractThe first realizations of S-band hybrid amplifiers based on hydrogenated-diamond (H-diamond) FETs are reported. As test vehicles of the adopted H-diamond technology at microwave frequencies, two designs are proposed: one, oriented to low-noise amplification, the other, oriented to high-power operation. The two amplifying stages are so devised as to be cascaded into a two-stage amplifier. The activities performed, from the technological steps to characterization, modelling, design and realization are illustrated. Measured performance demonstrates, for the low-noise stage, a noise figure between 7 and 8 dB in the 2–2.5 GHz bandwidth, associated with a transducer gain between 5 and 8 dB. The OIP3 at 2 GHz is 21 dBm. As to the power-oriented stage, its transducer gain is 5–6 dB in the 2–2.5 GHz bandwidth. The 1-dB output compression point at 2 GHz is 20 dBm whereas the OIP3 is 33 dBm. Cascading the measured S-parameters of the two stages yields a transducer gain of 15 ± 1.2 dB in the 2–3 GHz bandwidth.
A versatile toolbox for semi-automatic cell-by-cell object-based colocalization analysis
Authors: Lunde Anders , Glover Joel C. 
Published: November 2020

AbstractDifferential fluorescence labeling and multi-fluorescence imaging followed by colocalization analysis is commonly used to investigate cellular heterogeneity in situ. This is particularly important when investigating the biology of tissues with diverse cell types. Object-based colocalization analysis (OBCA) tools can employ automatic approaches, which are sensitive to errors in cell segmentation, or manual approaches, which can be impractical and tedious. Here, we present a novel set of tools for OBCA using a semi-automatic approach, consisting of two ImageJ plugins, a Microsoft Excel macro, and a MATLAB script. One ImageJ plugin enables customizable processing of multichannel 3D images for enhanced visualization of features relevant to OBCA, and another enables semi-automatic colocalization quantification. The Excel macro and the MATLAB script enable data organization and 3D visualization of object data across image series. The tools are well suited for experiments involving complex and large image data sets, and can be used in combination or as individual components, allowing flexible, efficient and accurate OBCA. Here we demonstrate their utility in immunohistochemical analyses of the developing central nervous system, which is characterized by complexity in the number and distribution of cell types, and by high cell packing densities, which can both create challenging situations for OBCA.
Phenotypic, genotypic and biochemical changes during pyrethroid resistance selection in Anopheles gambiae mosquitoes
Authors: Machani Maxwell G. , Ochomo Eric , Zhong Daibin , Zhou Guofa , Wang Xiaoming , Githeko Andrew K. , Yan Guiyun , Afrane Yaw A. 
Published: November 2020

AbstractThe directional selection for insecticide resistance due to indiscriminate use of insecticides in public health and agricultural system favors an increase in the frequency of insecticide-resistant alleles in the natural populations. Similarly, removal of selection pressure generally leads to decay in resistance. Past investigations on the emergence of insecticide resistance in mosquitoes mostly relied on field survey of resistance in vector populations that typically had a complex history of exposure to various public health and agricultural pest control insecticides in nature, and thus the effect of specific insecticides on rate of resistance emergency or resistance decay rate is not known. This study examined the phenotypic, genotypic, and biochemical changes that had occurred during the process of selection for pyrethroid resistance in Anopheles gambiae, the most important malaria vector in Africa. In parallel, we also examined these changes in resistant populations when there is no selection pressure applied. Through repeated deltamethrin selection in adult mosquitoes from a field population collected in western Kenya for 12 generations, we obtained three independent and highly pyrethroid-resistant An. gambiae populations. Three susceptible populations from the same parental population were generated by removing selection pressure. These two lines of mosquito populations differed significantly in monooxygenase and beta-esterase activities, but not in Vgsc gene mutation frequency, suggesting metabolic detoxification mechanism plays a major role in generating moderate-intensity resistance or high-intensity resistance. Pre-exposure to the synergist piperonyl butoxide restored the susceptibility to insecticide among the highly resistant mosquitoes, confirming the role of monooxygenases in pyrethroid resistance. The rate of resistance decay to become fully susceptible from moderate-intensity resistance took 15 generations, supporting at least 2-years interval is needed when the rotational use of insecticides with different modes of action is considered for resistance management.
Sweat and saliva cortisol response to stress and nutrition factors
Authors: Pearlmutter Paul , DeRose Gia , Samson Cheyenne , Linehan Nicholas , Cen Yuqiao , Begdache Lina , Won Daehan , Koh Ahyeon 
Published: November 2020

AbstractCortisol is a biomarker for stress monitoring; however, the biomedical and clinical relevance is still controversial due to the complexity of cortisol secretion mechanisms and their circadian cycles as well as environmental factors that affect physiological cortisol level, which include individual mood and dietary intake. To further investigate this multifaceted relationship, a human pilot study examined cortisol concentration in sweat and saliva samples collected from 48 college-aged participants during aerobic exercise sessions along with mental distress and nutrition surveys. Enzyme-linked immunosorbent assays determined highly significant differences between apocrine-dominant sweat (AP), saliva before exercise (SBE), and saliva after exercise (SAE) cortisol concentration (AP-SBE: p = 0.0017, AP-SAE: p = 0.0102). A significantly greater AP cortisol concentration was detected in males compared to females (p = 0.0559), and significant SAE cortisol concentration differences were also recorded between recreational athletes and non-athletes (p = 0.044). However, Kessler 10 Psychological Distress Scale (K10) scores, an examination administered to deduce overall wellness, provided no significant differences between males and females or athletes and non-athletes in distress levels, which statistically signifies a direct relationship to cortisol was not present. For further analysis, dietary intake from all participants was considered to investigate whether a multiplexed association was prevalent between nutrition, mood, and cortisol release. Significant positive correlations between AP cortisol, SAE cortisol, K10 scores, and fat intake among female participants and athletes were discovered. The various machine learning algorithms utilized the extensive connections between dietary intake, overall well-being, sex factors, athletic activity, and cortisol concentrations in various biofluids to predict K10 scores. Indeed, the understanding of physiochemical stress response and the associations between studied factors can advance algorithm developments for cortisol biosensing systems to mitigate stress-based illnesses and improve an individual’s quality of life.
A density-based threshold model for evaluating the separation of particles in heterogeneous mixtures with curvilinear microfluidic channels
Authors: Chen Chun Kwan , Khoo Bee Luan 
Published: November 2020

AbstractParticle separation techniques play an important role in biomedical research. Inertial focusing based microfluidics using nonlinear channels is one of the promising label-free technologies for biological applications. The particle separation is achieved as a result of the combination of inertial lift force (FL) and Dean drag force (FD). Although the mathematical expressions of FL and FD have been well derived in prior studies, they are still complicated, which limits their popularity in practice. Recent studies modified these expressions through experiments and proposed a threshold model, which assumes that only particles larger than the threshold will be well focused. Although this threshold model has been used in recent studies, two varying versions of the threshold model (TM1 and TM2) prevents standardisation in practice. In addition, both models were developed with regular low-density particles and may not be applicable to samples with higher density or samples with irregular shapes. Here, we evaluated the threshold models with samples of different densities. Based on these evaluations, we derived a modified model (TM4), which additionally considers the factor of particle density to improve the accuracy of existing models. Our results demonstrated that TM4 could more reliably predict the sorting efficiency of samples within a wider density range.
Optimization of membrane dispersion ethanol precipitation process with a set of temperature control improved equipment
Authors: Pan Jingjing , Tai Yanni , Qu Haibin , Gong Xingchu 
Published: November 2020

AbstractEthanol precipitation is an important separation and purification process in the traditional Chinese medicines (TCMs) industry. In the present study, a membrane dispersion micromixer was applied to achieve good mixing for the ethanol precipitation process of Astragali radix concentrate. New experimental apparatus was set up to rapidly lower the temperature of ethanol solution before mixing with the concentrate. Ethanol precipitation process was optimized according to Quality by design concept. To identify critical material attributes (CMAs), ten batches of Astragali radix were used to prepare concentrates. Calycosin-7-O-β-D-glucoside content, the sucrose content, and the electrical conductivity were found to be CMAs after the correlation analysis and stepwise regression modelling. Definitive screening design was used to investigate the relationships among critical process parameters, CMAs, and process critical quality attributes (CQAs). Quadratic models were developed and design space was calculated according to the probability of attaining process CQA standards. A material quality control strategy was proposed. High quality and low quality Astragali radix concentrates can be discriminated by the inequalities. Low quality Astragali radix concentrates should not be released for ethanol precipitation process directly. Verification experiment results indicated accurate models and reliable design space. The temperature control method and control strategy are promising for ethanol precipitation process of other TCMs or foods.