bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single-cell transcriptomics and surface epitope detection in human brain epileptic lesions identifies pro-inflammatory signaling
Authors: Kumar Pavanish , Lim Amanda , Hazirah Sharifah Nur , Chua Camillus Jian Hui , Ngoh Adeline , Poh Su Li , Yeo Tong Hong , Lim Jocelyn , Ling Simon , Sutamam Nursyuhadah Binte , Petretto Enrico , Low David Chyi Yeu , Zeng Li , Tan Eng-King , Arkachaisri Thaschawee , Yeo Joo Guan , Ginhoux Florent , Chan Derrick , Albani Salvatore 
Published: June 2022

AbstractEpileptogenic triggers are multifactorial and not well understood. Here we aimed to address the hypothesis that inappropriate pro-inflammatory mechanisms contribute to the pathogenesis of refractory epilepsy (non-responsiveness to antiepileptic drugs) in human patients. We used single-cell cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to reveal the immunotranscriptome of surgically resected epileptic lesion tissues. Our approach uncovered a pro-inflammatory microenvironment, including extensive activation of microglia and infiltration of other pro-inflammatory immune cells. These findings were supported by ligand–receptor (LR) interactome analysis, which demonstrated potential mechanisms of infiltration and evidence of direct physical interactions between microglia and T cells. Together, these data provide insight into the immune microenvironment in epileptic tissue, which may aid the development of new therapeutics.
Global hydro-environmental lake characteristics at high spatial resolution
Authors: Lehner Bernhard , Messager Mathis L. , Korver Maartje C. , Linke Simon 
Published: June 2022

AbstractHere we introduce the LakeATLAS dataset, which provides a broad range of hydro-environmental characteristics for more than 1.4 million lakes and reservoirs globally with an area of at least 10 ha. LakeATLAS forms part of the larger HydroATLAS data repository and expands the existing datasets of sub-basin and river reach descriptors by adding equivalent information for lakes and reservoirs in a compatible structure. Matching its HydroATLAS counterparts, version 1.0 of LakeATLAS contains data for 56 variables, partitioned into 281 individual attributes and organized in six categories: hydrology; physiography; climate; land cover & use; soils & geology; and anthropogenic influences. LakeATLAS derives these attributes by processing and reformatting original data from well-established global digital maps at 15 arc-second (~500 m) grid cell resolution and assigns the information spatially to each lake by aggregating it within the lake, in a 3-km vicinity buffer around the lake, and/or within the entire upstream drainage area of the lake. The standardized format of LakeATLAS ensures versatile applicability in hydro-ecological assessments from regional to global scales.
Modelling of life cycle cost of conventional and alternative vehicles
Authors: Furch Jan , Konečný Vlastimil , Krobot Zdeněk 
Published: June 2022

AbstractOver the past decade, the passenger transport segment has undergone significant changes, particularly in the way vehicles are propelled. These changes have been influenced by the global drive to reduce the environmental burden associated with the operation of vehicles. Although these trends are primarily focused on the environmental aspects of vehicle operation, the economic aspects inevitably associated with the operation of each vehicle are also changing. This article deals with the calculation of life cycle costs, or the return on investment for vehicles with alternative drives compared to conventional drives. In order to obtain objective outputs, a mathematical model for the calculation of the life cycle costs of passenger vehicles has been developed and applied to these vehicles. The presented mathematical model expresses the acquisition costs and mainly the ownership costs for operation and maintenance. Finally, a comparison of the whole life cycle costs of selected vehicles with different powertrains was made. The following powertrains are compared in this paper, i.e. petrol engine, diesel engine, petrol and CNG engine, mild hybrid engine, plug-in hybrid engine and electric motor. The presented findings and input values for the calculations of the individual cost components reflect the current state in terms of economic demands. Due to the high rate of development and improvement of alternative propulsion modes, especially pure electric propulsion technologies, it can be assumed that the life cycle costs will follow a decreasing trend.
Evaluating CO2 breakthrough in a shaly caprock material: a multi-scale experimental approach
Authors: Stavropoulou Eleni , Laloui Lyesse 
Published: June 2022

AbstractThe potential of underground CO2 storage relies on the sealing efficiency of an overlaying caprock that acts as a geological barrier. Shales are considered as potential caprock formations thanks to their favourable hydro-mechanical properties. In this work the sealing capacity of Opalinus Clay shale to CO2 injection is studied by means of capillary entry-pressure and volumetric response. The overall objective of this work is to contribute to the safe design of a CO2 injection strategy by providing a better understanding of the geomechanical response of the caprock material to CO2 injection and eventual breakthrough at different scales. This is achieved by relating lab-measured hydro-mechanical properties of the studying caprock material (porosity, permeability, volumetric response) to field-related parameters (effective stress, injection pressure). A number of CO2 breakthrough tests is performed in Opalinus Clay samples under two different scales, meso and micro. At the meso-scale, CO2 injection is performed in oedometric conditions under different levels of axial effective stress in both gaseous or liquid phase. In parallel, the material’s transport properties in terms of water permeability are assessed before CO2 injection at each corresponding level of effective stress. The impact of CO2 phase and open porosity on the material’s CO2 entry pressure are demonstrated. The correlation between measured entry pressure and absolute permeability is discussed. A second testing campaign at a smaller scale is presented where CO2 breakthrough is for the first time identified with in-situ X-ray tomography. CO2 injection is performed under isotropic conditions on an Opalinus Clay micro-sample (micro-scale), and CO2 breakthrough is identified through quantitative image analysis based on the measured localised volumetric response of the material. This innovative methodology provides important insight into the anisotropic response of this complex material that is indispensable for its representative modelling in the context of safe geological CO2 storage.
Clinical features, electroencephalogram, and biomarkers in pediatric sepsis-associated encephalopathy
Authors: de Araújo Bruno Espírito Santo , da Silva Fontana Rosiane , de Magalhães-Barbosa Maria Clara , Lima-Setta Fernanda , Paravidino Vitor Barreto , Riveiro Paula Marins , Pulcheri Lucas Berbert , dos Santos Salú Margarida , Genuíno-Oliveira Mariana Barros , Robaina Jaqueline Rodrigues , da Cunha Antonio José Ledo Alves , Cruz Fernanda Ferreira , Rocco Patricia Rieken Macedo , Bozza Fernando Augusto , de Castro-Faria-Neto Hugo Caire , Prata-Barbosa Arnaldo 
Published: June 2022

AbstractTo date, no specific diagnostic criteria for sepsis-associated encephalopathy (SAE) have been established. We studied 33 pediatric patients with sepsis prospectively and evaluated the level of consciousness, the presence of delirium, electroencephalographic (EEG) findings, and plasma levels of neuron-specific enolase and S100-calcium-binding protein-B. A presumptive diagnosis of SAE was primarily considered in the presence of a decreased level of consciousness and/or delirium (clinical criteria), but specific EEG abnormalities were also considered (EEG criteria). The time course of the biomarkers was compared between groups with and without clinical or EEG criteria. The Functional Status Scale (FSS) was assessed at admission, discharge, and 3–6 months post-discharge. Clinical criteria were identified in 75.8% of patients, EEG criteria in 26.9%, both in 23.1%, and none in 23.1%. Biomarkers did not differ between groups. Three patients had an abnormal FSS at discharge, but no one on follow-up. A definitive diagnostic pattern for SAE remained unclear. Clinical criteria should be the basis for diagnosis, but sedation may be a significant confounder, also affecting EEG interpretation. The role of biomarkers requires a better definition. The diagnosis of SAE in pediatric patients remains a major challenge. New consensual diagnostic definitions and mainly prognostic studies are needed.
Performance of chlorophyll a fluorescence parameters in Lemna minor under heavy metal stress induced by various concentration of copper
Authors: Singh Hanwant , Kumar Deepak , Soni Vineet 
Published: June 2022

AbstractThe objective of the present investigation was to understand the efficacy of chlorophyll fluorescence analysis and to identify the specific photosynthetic parameters for early and rapid detection of Cu-induced HM-stress in plants. Aquatic angiospermLemna minorwas exposed to various concentrations (0–40 µM) of Cu. We observed that the FV/FO(Efficiency of the water-splitting complex on the donor side of PSII), quantum yield for electron transport, and quantum yield of primary photochemistry were decreased however, dissipated quantum yield was increased with Cu concentration. ABS/CSM, TRO/CSM, ETO/CSMand maximum quantum yield were displayed the dose–response relationship under Cu stress. Performance indexes were increased initially due to the beneficial effects of Cu at lower concentration while decreased significantly (p ≤ 0.05) at highest concentration of Cu. The outcomes of the present research revealed that the ChlF analysis is very sensitive tool that can be used to determine the toxicity of heavy metals in plants.
Evaluation of anticancer effects of carboplatin–gelatin nanoparticles in different sizes synthesized with newly self-assembly method by exposure to IR light
Authors: Danışman-Kalındemirtaş Ferdane , Kariper İshak Afşin , Erdemir Gökçe , Sert Esra , Erdem-Kuruca Serap 
Published: June 2022

AbstractCarboplatin (CP), a platinum analog, is one of the most widely used chemotherapeutic agents in the treatment of colorectal cancer. Although platinum-based drugs are quite effective in anticancer treatments, their use in a wide spectrum and effective treatment possibilities are limited due to their systemic side effects and drug resistance development. In recent years, studies have focused on increasing the therapeutic efficacy of platinum-based drugs with drug delivery systems. Gelatin, a protein, obtained by the hydrolysis of collagen, is a biocompatible and biodegradable material that can be used in nano drug delivery systems. In this study, CP-loaded gelatin-based NPs (CP-NPs) were exposed to IR light in different temperatures at 30, 35, 40, 45, and 50 °C and characterized by FESEM-EDX, FTIR, UV–Vis, DLS. Accordingly, we synthesized gelatin-based CP-NPs of different sizes between 10–290 nm by exposure to IR. We found that CP-NPs-50, 16 nm nano-sized, obtained at 50 °C had the most cytotoxicity and was 2.2 times more effective than the free drug in HCT 116 colon cancer cells. Moreover, we showed that the cytotoxicity of CP-NPs-50 in normal HUVEC cells was lower. Additionally, we demonstrated that CP-NPs enhanced apoptotic activity while not developing MDR1-related resistance in colon cancer cells. In this study, for the first time drug loaded gelatin-based nanoparticles were synthesized in different sizes with a newly self-assembly method by exposing them to infrared light at different temperatures and their anticancer effects were evaluated subsequently.
Development of low glycemic index instant Phirni (pudding) mix-its visco-thermal, morphological and rheological characterization
Authors: Naseer Bazila , Naik Haroon Rashid , Hussain Syed Zameer , Qadri Tahiya , Dar Basharat Nabi , Amin Tawheed , Reshi Monica , Shafi Fouzia , Fatima Tabasum 
Published: June 2022

AbstractHigh amylose rice (HAR) and carboxymethyl cellulose (CMC) are the preferred choices for enhancement of resistant starch content and lowering of glycemic index in dairy desserts. The effects of different levels of skimmed milk powder (SMP): HAR flour (45:55 to 75:25) and CMC (0.1 to 1%) were investigated on physical characteristics of dry-mix and on texture profile parameters, resistant starch (RS), predicted glycemic index (pGI), glycemic load (GL) and overall acceptability of phirni (a traditional milk pudding). Design expert predicted SMP (70): HAR (30) and CMC (0.8%) as optimum levels for reducing the pGI and maximizing the RS content and other quality characteristics in phirni. RS content of phirni (4.38%) prepared from optimized dry-mix (ODM) was higher while pGI (48.12) and GL (7.50) were lower as compared to phirni prepared from market dry-mix (MDM). The visco-thermal properties of ODM and MDM also showed significant variations. Storage modulus (Gʹ) and loss modulus (Gʹʹ) indicated that ODM phirni was less solid than MDM phirni. Scanning electron micrographs showed fused structures in ODM, while coarse sheet like structures were observed across the surface of MDM. Thus, ODM can be a promising substitute for the available milk desserts for diabetic patients.
Cell graph neural networks enable the precise prediction of patient survival in gastric cancer
Authors: Wang Yanan , Wang Yu Guang , Hu Changyuan , Li Ming , Fan Yanan , Otter Nina , Sam Ikuan , Gou Hongquan , Hu Yiqun , Kwok Terry , Zalcberg John , Boussioutas Alex , Daly Roger J. , Montúfar Guido , Liò Pietro , Xu Dakang , Webb Geoffrey I. , Song Jiangning 
Published: June 2022

AbstractGastric cancer is one of the deadliest cancers worldwide. An accurate prognosis is essential for effective clinical assessment and treatment. Spatial patterns in the tumor microenvironment (TME) are conceptually indicative of the staging and progression of gastric cancer patients. Using spatial patterns of the TME by integrating and transforming the multiplexed immunohistochemistry (mIHC) images as Cell-Graphs, we propose a graph neural network-based approach, termed Cell−GraphSignatureorCGSignature, powered by artificial intelligence, for the digital staging of TME and precise prediction of patient survival in gastric cancer. In this study, patient survival prediction is formulated as either a binary (short-term and long-term) or ternary (short-term, medium-term, and long-term) classification task. Extensive benchmarking experiments demonstrate that the CGSignature achieves outstanding model performance, with Area Under the Receiver Operating Characteristic curve of 0.960 ± 0.01, and 0.771 ± 0.024 to 0.904 ± 0.012 for the binary- and ternary-classification, respectively. Moreover, Kaplan–Meier survival analysis indicates that the “digital grade” cancer staging produced by CGSignature provides a remarkable capability in discriminating both binary and ternary classes with statistical significance (P value < 0.0001), significantly outperforming the AJCC 8th edition Tumor Node Metastasis staging system. Using Cell-Graphs extracted from mIHC images, CGSignature improves the assessment of the link between the TME spatial patterns and patient prognosis. Our study suggests the feasibility and benefits of such an artificial intelligence-powered digital staging system in diagnostic pathology and precision oncology.
The pro-inflammatory effect of Staphylokinase contributes to community-associated Staphylococcus aureus pneumonia
Authors: Wang Yanan , Zhao Na , Jian Ying , Liu Yao , Zhao Lin , He Lei , Liu Qian , Li Min 
Published: June 2022

AbstractPneumonia caused by community-associated Staphylococcus aureus (CA-SA) has high morbidity and mortality, but its pathogenic mechanism remains to be further investigated. Herein, we identify that staphylokinase (SAK) is significantly induced in CA-SA and inhibits biofilm formation in a plasminogen-dependent manner. Importantly, SAK can enhance CA-SA-mediated pneumonia in both wild-type and cathelicidins-related antimicrobial peptide knockout (CRAMP−/−) mice, suggesting that SAK exacerbates pneumonia in a CRAMP-independent manner. Mechanistically, SAK induces pro-inflammatory effects, especially in the priming step of NLRP3 inflammasome activation. Moreover, we demonstrate that SAK can increase K+ efflux, production of reactive oxygen species production, and activation of NF-κB signaling. Furthermore, the NLRP3 inflammasome inhibitor can counteract the effective of SAK induced CA-SA lung infection in mice. Taken together, we speculate that SAK exacerbates CA-SA-induced pneumonia by promoting NLRP3 inflammasome activation, providing new insights into the pathogenesis of highly virulent CA-SA and emphasizes the importance of controlling inflammation in acute pneumonia.
A systematic review of the definitions and interpretations in scientific literature of ‘less but better’ meat in high-income settings
Authors: Resare Sahlin Kajsa , Trewern Joanna 
Published: June 2022

Abstract‘Less but better’ is a pragmatic approach to tackling the sustainability challenges of meat consumption and production. Definitions of ‘less’ and ‘better’ lack clarity. Here we explore interpretations of these concepts, finding increasing use of ‘less but better’ in the literature from Western, high-income settings. Despite discrepancies among interpretations of ‘less’ meat, existing quantifications indicate that significant reduction is needed to achieve desirable food system outcomes. Interpretations of ‘better’ meat incorporate the delivery of environmental sustainability, improved animal welfare and better health or nutrition, but lack clear principles and omit many sustainability themes. Practices and outcomes are seldom linked, and diverging narratives on interactions between ‘less’ and ‘better’ exist. A shared vision of livestock systems with improved sustainability across multiple indicators is needed to establish principles for ‘less but better’ in order for decision-making to deliver desired outcomes.
Interacting partners of Brassica juncea regulator of G-protein signaling protein suggest its role in cell wall metabolism and cellular signaling
Authors: Kumar Roshan , Bisht Naveen C. 
Published: June 2022

Abstract
Heterotrimeric G-proteins interact with various upstream and downstream effectors to regulate various aspects of plant growth and development. G-protein effectors have been recently reported in Arabidopsis thaliana; however, less information is available from polyploid crop species having complex networks of G-protein components. Regulator of G-protein signaling (RGS) is a well-characterized GTPase accelerating protein, which plays an important role in the regulation of the G-protein cycle in plants. In the present study, four homologs encoding RGS proteins were isolated from the allotetraploid Brassica juncea, a globally important oilseed, vegetable, and condiment crop. The B. juncea RGS proteins were grouped into distinct BjuRGS1 and BjuRGS2 orthologous clades, and the expression of BjuRGS1 homologs was predominantly higher than BjuRGS2 homologs across the tested tissue types of B. juncea. Utilizing B. juncea Y2H library screening, a total of 30 nonredundant interacting proteins with the RGS-domain of the highly expressed BjuA.RGS1 was identified. Gene ontology analysis indicated that these effectors exerted various molecular, cellular, and physiological functions. Many of them were known to regulate cell wall metabolism (BjuEXP6, Bju-α-MAN, BjuPGU4, BjuRMS3) and phosphorylation-mediated cell signaling (BjuMEK4, BjuDGK3, and BjuKinase). Furthermore, transcript analysis indicated that the identified interacting proteins have a coexpression pattern with the BjuRGS homologs. These findings increase our knowledge about the novel targets of G-protein components from a globally cultivated Brassica crop and provide an important resource for developing a plant G-protein interactome network.
EFR3 and phosphatidylinositol 4-kinase IIIα regulate insulin-stimulated glucose transport and GLUT4 dispersal in 3T3-L1 adipocytes
Authors: Koester Anna M. , Geiser Angéline , Laidlaw Kamilla M.E. , Morris Silke , Cutiongco Marie F.A. , Stirrat Laura , Gadegaard Nikolaj , Boles Eckhard , Black Hannah L. , Bryant Nia J. , Gould Gwyn W. 
Published: June 2022

AbstractInsulin stimulates glucose transport in muscle and adipocytes. This is achieved by regulated delivery of intracellular glucose transporter (GLUT4)-containing vesicles to the plasma membrane where they dock and fuse, resulting in increased cell surface GLUT4 levels. Recent work identified a potential further regulatory step, in which insulin increases the dispersal of GLUT4 in the plasma membrane away from the sites of vesicle fusion. EFR3 is a scaffold protein that facilitates localization of phosphatidylinositol 4-kinase type IIIα to the cell surface. Here we show that knockdown of EFR3 or phosphatidylinositol 4-kinase type IIIα impairs insulin-stimulated glucose transport in adipocytes. Using direct stochastic reconstruction microscopy, we also show that EFR3 knockdown impairs insulin stimulated GLUT4 dispersal in the plasma membrane. We propose that EFR3 plays a previously unidentified role in controlling insulin-stimulated glucose transport by facilitating dispersal of GLUT4 within the plasma membrane.
Tuning of renewable energy bids based on energy risk management: Enhanced microgrids with pareto‐optimal profits for the utility and prosumers
Authors: Mohan Vivek , Antonis Anjula Mary , M. Jisma , Krishnakumar Nila , Bu Siqi 
Published: June 2022

AbstractThe increasing penetration of renewable energy sources (RES) and electric vehicles (EVs) demands the building of a microgrid energy portfolio that is cost‐effective and robust against generation uncertainties (energy risk). Energy risk may trigger financial risk in the local energy market, depending on bid values, cost of generation and price of upstream grid power. In this study, a microgrid energy portfolio is built based on adjustments to both the financial and energy risks. These risks are managed in two ways: (1) by pre‐tuning and prioritizing the bid prices for wind and solar energy sources based on their relative levels of energy risk as quantified through a conditional value‐at‐risk (CVaR) approach; and (2) by co‐optimizing the conflicting profits of the utility and prosumers using non‐dominated sorting particle swarm optimization (NSPSO) to obtain a risk‐adjusted Pareto‐optimal energy mix. Thus, the utility predicts the net power balancing cost from the scheduling time horizon, thereby moderating the adverse effect that the uncertainties in renewable energy could have on the collective welfare. The proposed method is tested on a grid‐connected CIGRE low‐voltage (LV) benchmark microgrid with solar and wind sources, microturbines, and EVs. The results demonstrate that the obtained portfolio is realistic, welfare‐optimized and cost‐efficient.