bluuebunny/crossref_metadata_2025 huggingface dataset:
An Optimization Study on the Hull Form and Stern Appendage for Improving Resistance Performance of a Coastal Fishing Vessel
Authors: Yu Jin-Won , Lee Min-Kyung , Kim Yang-Ik , Suh Sung-Bu , Lee Inwon
Published: July 2021

In response to the increasing number of free trade agreements (FTA) and the Trans-Pacific Partnership (TTP), it is necessary to develop next-generation fishing vessels for the littoral sea of the Republic of Korea. The main objectives of such fishing vessels are to enhance the comfort of the crew and to improve fuel efficiency under the newly established principal dimension. This paper employs the hull form variation method to obtain a series of forebody hull forms of the 19 gross tonnage class of a coastal composite fishing vessel. Chine breadth modification has been used for hull form variations. The objective function is the minimum value of wavemaking resistance. A parametric study was conducted to observe the effects of design parameters on the objective functions, and hull-form optimization was performed. In addition to the hull-form optimization, the effect of the stern flap was investigated in terms of both resistance and operational performances.
Evaluation of the Level and Readiness of Internal Logistics for Industry 4.0 in Industrial Companies
Authors: Zoubek Michal , Simon Michal
Published: July 2021

Industry 4.0 integrates modern technologies into independently functioning units and fundamentally changes established production and non-production processes. Industry 4.0 is also used in the field of logistics with the introduction of automation, robotics or modern warehouse systems with a key element of digitisation. Development based on these principles presents huge challenges for the logistics sector as well as opportunities for further growth. Because the field of logistics is very large, it is important to be more specific. Internal logistics is a very important part of production processes; areas such as storage and supply of production lines with input materials are some of the key processes in a company. The implementation of Industry 4.0 principles is specific and, for many companies, demanding technologically, organisationally and financially. Therefore, companies must know their current level of logistics processes and evaluate the readiness of these elements for automation and digitisation. The company’s management should create a strategy which evaluates internal logistics processes for Industry 4.0. Company readiness will be evaluated on the basis of the tools (methodology) presented in the article. An objective assessment with a multi-level system is needed, and therefore internal logistics is structured into sub-areas. The implementation of this innovative method of evaluation in the industrial environment and a description of the tool development process will also be presented. As these are extensive issues, the initial sections cover the theoretical background of the topics that justify the need and novelty of this tool.
A Study on Learning Parameters in Application of Radial Basis Function Neural Network Model to Rotor Blade Design Approximation
Authors: Song Chang-Yong
Published: July 2021

Meta-model sre generally applied to approximate multi-objective optimization, reliability analysis, reliability based design optimization, etc., not only in order to improve the efficiencies of numerical calculation and convergence, but also to facilitate the analysis of design sensitivity. The radial basis function neural network (RBFNN) is the meta-model employing hidden layer of radial units and output layer of linear units, and characterized by relatively fast training, generalization and compact type of networks. It is important to minimize some scattered noisy data to approximate the design space to prevent local minima in the gradient based optimization or the reliability analysis using the RBFNN. Since the noisy data must be smoothed out in order for the RBFNN to be applied as the meta-model to any actual structural design problem, the smoothing parameter must be properly determined. This study aims to identify the effect of various learning parameters including the spline smoothing parameter on the RBFNN performance regarding the design approximation. An actual rotor blade design problem was considered to investigate the characteristics of RBFNN approximation with respect to the range of spline smoothing parameter, the number of training data, and the number of hidden layers. In the RBFNN approximation of the rotor blade design, design sensitivity characteristics such as main effects were also evaluated including the performance analysis according to the variation of learning parameters. From the evaluation results of learning parameters in the rotor blade design, it was found that the number of training data had larger influence on the RBFNN meta-model accuracy than the spline smoothing parameter while the number of hidden layers had little effect on the performances of RBFNN meta-model.
Baseline Air Monitoring of Fine Particulate Matter and Trace Elements in Ontario’s Far North, Canada
Authors: Su Yushan , Sofowote Uwayemi , Munoz Anthony , Noble Michael , Charron Chris , Todd Aaron , Celo Valbona , Dabek-Zlotorzynska Ewa , Kryukova Alla , Switzer Teresa
Published: July 2021

Large mineral deposits have been discovered in Ontario’s Far North and are being considered for further development. Particulate matter and trace elements can be emitted from potential mining activities and these air pollutants are associated with health risks and harmful to the sensitive ecosystem. An air monitoring station, powered by solar panels and a wind turbine, was established in this near-pristine area to monitor baseline levels of fine particulate matter (PM2.5) and trace elements downwind of a proposed mine site. Levels of PM2.5 and trace elements observed from 2015 to 2018 were much lower than measurements observed in southern Ontario, suggesting minimal influence of primary emissions in the study area. One episodic PM2.5 event in July 2015 was attributable to wildfire emissions in northern Ontario. Only 8 out of the 31 target elements were detected in 25% or more of the samples. Good correlations among As, Se, Pb, and Sb, between Mn and Fe, as well as between Ce and La indicated they originated from long-range atmospheric transport from the south. Ontario’s Ambient Air Quality Criteria were not exceeded for any target air pollutants. Four years of air measurements filled the data gap of baseline information in this near-pristine study area and can be used to assess impacts of potential mining activities in the future. Field operations during this study period indicated that the battery-powered air instruments and meteorological sensors worked well in the harsh environment of Ontario’s Far North even in cold winter months. The field experiences gained in this study can be applied to future air monitoring activities in harsh environments where no direct power supply is available and site access is limited.
Study on Hand–Eye Cordination Area with Bare-Hand Click Interaction in Virtual Reality
Authors: Zhou Xiaozhou , Jin Yu , Jia Lesong , Xue Chengqi
Published: July 2021

In virtual reality, users’ input and output interactions are carried out in a three-dimensional space, and bare-hand click interaction is one of the most common interaction methods. Apart from the limitations of the device, the movements of bare-hand click interaction in virtual reality involve head, eye, and hand movements. Consequently, clicking performance varies among locations in the binocular field of view. In this study, we explored the optimal interaction area of hand–eye coordination within the binocular field of view in a 3D virtual environment (VE), and implemented a bare-hand click experiment in a VE combining click performance data, namely, click accuracy and click duration, following a gradient descent method. The experimental results show that click performance is significantly influenced by the area where the target is located. The performance data and subjective preferences for clicks show a high degree of consistency. Combining reaction time and click accuracy, the optimal operating area for bare-hand clicking in virtual reality is from 20° to the left to 30° to the right horizontally and from 15° in the upward direction to 20° in the downward direction vertically. The results of this study have implications for guidelines and applications for bare-hand click interaction interface designs in the proximal space of virtual reality.
Life-On-Hold: Lanthanoids Rapidly Induce a Reversible Ametabolic State in Mammalian Cells
Authors: Subbot Anastasia , Kondratieva Sabina , Novikov Ivan , Gogoleva Natalia , Kozlova Olga , Chebotar Igor , Gazizova Guzel , Ryabova Anastasia , Vorontsova Maria , Kikawada Takahiro , Shagimardanova Elena , Gusev Oleg
Published: July 2021

Until now, the ability to reversibly halt cellular processes has been limited to cryopreservation and several forms of anabiosis observed in living organisms. In this paper we show that incubation of living cells with a solution containing ~50 mM neodymium induces a rapid shutdown of intracellular organelle movement and all other evidence of active metabolism. We have named this state REEbernation (derived from the terms REE (rare earth elements) and hibernation) and found that the process involves a rapid replacement of calcium with neodymium in membranes and organelles of a cell, allowing it to maintain its shape and membrane integrity under extreme conditions, such as low pressure. Furthermore, phosphate exchange is blocked as a result of non-dissolvable neodymium salts formation, which “discharged” the cell. We further showed that REEbernation is characterized by an immediate cessation of transcriptional activity in observed cells, providing an intriguing opportunity to study a snapshot of gene expression at a given time point. Finally, we found that the REEbernation state is reversible, and we could restore the metabolism and proliferation capacity of the cells. The REEbernation, in addition to being an attractive model to further investigate the basic mechanisms of cell metabolism control, also provides a new method to reversibly place a cell into “on-hold” mode, opening opportunities to develop protocols for biological samples fixation with a minimum effect on the omics profile for biomedical needs.
Human Trisomic iPSCs from Down Syndrome Fibroblasts Manifest Mitochondrial Alterations Early during Neuronal Differentiation
Authors: Mollo Nunzia , Esposito Matteo , Aurilia Miriam , Scognamiglio Roberta , Accarino Rossella , Bonfiglio Ferdinando , Cicatiello Rita , Charalambous Maria , Procaccini Claudio , Micillo Teresa , Genesio Rita , Calì Gaetano , Secondo Agnese , Paladino Simona , Matarese Giuseppe , Vita Gabriella De , Conti Anna , Nitsch Lucio , Izzo Antonella
Published: July 2021

Background: The presence of mitochondrial alterations in Down syndrome suggests that it might affect neuronal differentiation. We established a model of trisomic iPSCs, differentiating into neural precursor cells (NPCs) to monitor the occurrence of differentiation defects and mitochondrial dysfunction. Methods: Isogenic trisomic and euploid iPSCs were differentiated into NPCs in monolayer cultures using the dual-SMAD inhibition protocol. Expression of pluripotency and neural differentiation genes was assessed by qRT-PCR and immunofluorescence. Meta-analysis of expression data was performed on iPSCs. Mitochondrial Ca2+, reactive oxygen species (ROS) and ATP production were investigated using fluorescent probes. Oxygen consumption rate (OCR) was determined by Seahorse Analyzer. Results: NPCs at day 7 of induction uniformly expressed the differentiation markers PAX6, SOX2 and NESTIN but not the stemness marker OCT4. At day 21, trisomic NPCs expressed higher levels of typical glial differentiation genes. Expression profiles indicated that mitochondrial genes were dysregulated in trisomic iPSCs. Trisomic NPCs showed altered mitochondrial Ca2+, reduced OCR and ATP synthesis, and elevated ROS production. Conclusions: Human trisomic iPSCs can be rapidly and efficiently differentiated into NPC monolayers. The trisomic NPCs obtained exhibit greater glial-like differentiation potential than their euploid counterparts and manifest mitochondrial dysfunction as early as day 7 of neuronal differentiation.
On the Role of Paraoxonase-1 and Chemokine Ligand 2 (C-C motif) in Metabolic Alterations Linked to Inflammation and Disease. A 2021 Update
Authors: Camps Jordi , Castañé Helena , Rodríguez-Tomàs Elisabet , Baiges-Gaya Gerard , Hernández-Aguilera Anna , Arenas Meritxell , Iftimie Simona , Joven Jorge
Published: July 2021

Infectious and many non-infectious diseases share common molecular mechanisms. Among them, oxidative stress and the subsequent inflammatory reaction are of particular note. Metabolic disorders induced by external agents, be they bacterial or viral pathogens, excessive calorie intake, poor-quality nutrients, or environmental factors produce an imbalance between the production of free radicals and endogenous antioxidant systems; the consequence being the oxidation of lipids, proteins, and nucleic acids. Oxidation and inflammation are closely related, and whether oxidative stress and inflammation represent the causes or consequences of cellular pathology, both produce metabolic alterations that influence the pathogenesis of the disease. In this review, we highlight two key molecules in the regulation of these processes: Paraoxonase-1 (PON1) and chemokine (C-C motif) ligand 2 (CCL2). PON1 is an enzyme bound to high-density lipoproteins. It breaks down lipid peroxides in lipoproteins and cells, participates in the protection conferred by HDL against different infectious agents, and is considered part of the innate immune system. With PON1 deficiency, CCL2 production increases, inducing migration and infiltration of immune cells in target tissues and disturbing normal metabolic function. This disruption involves pathways controlling cellular homeostasis as well as metabolically-driven chronic inflammatory states. Hence, an understanding of these relationships would help improve treatments and, as well, identify new therapeutic targets.
Battle Royale: Innate Recognition of Poxviruses and Viral Immune Evasion
Authors: Yu Huibin , Bruneau Ryan C. , Brennan Greg , Rothenburg Stefan
Published: July 2021

Host pattern recognition receptors (PRRs) sense pathogen-associated molecular patterns (PAMPs), which are molecular signatures shared by different pathogens. Recognition of PAMPs by PRRs initiate innate immune responses via diverse signaling pathways. Over recent decades, advances in our knowledge of innate immune sensing have enhanced our understanding of the host immune response to poxviruses. Multiple PRR families have been implicated in poxvirus detection, mediating the initiation of signaling cascades, activation of transcription factors, and, ultimately, the expression of antiviral effectors. To counteract the host immune defense, poxviruses have evolved a variety of immunomodulators that have diverse strategies to disrupt or circumvent host antiviral responses triggered by PRRs. These interactions influence the outcomes of poxvirus infections. This review focuses on our current knowledge of the roles of PRRs in the recognition of poxviruses, their elicited antiviral effector functions, and how poxviral immunomodulators antagonize PRR-mediated host immune responses.
Influence of Fiber Shape and Volume Content on the Performance of Reactive Powder Concrete (RPC)
Authors: Wang Chuanlin , Xue Guojie , Zhao Xianbo
Published: July 2021

This research studied the influence of three types of open (short-straight, long-straight, semicircular) and three different shapes of closed steel fibers (triangular, rectangular, circular) with different fiber contents by volume (0, 0.5%, 1%, 1.5%, and 2%) on the working and mechanical performance of reactive powder concrete (RPC). The results indicated that (1) the number of steel fibers and the enclosed area formed by closed steel fibers would remarkably impact the performance of RPC; (2) the semicircular fiber improves RPC’s strength the most among the three open shapes; (3) the short-straight fiber works more effectively than the closed steel fibers; (4) the circular fiber works the most efficiently in improving RPC’s mechanical performance while the triangular ones have the least effect among the three closed steel fibers; (5) both the closed and open steel fibers improve their compressive strength more than their flexural strength; (6) the closed steel fiber works more efficiently in improving the flexural strength but less efficiently in improving the compressive strength; (7) the open steel fibers enhance the mechanical performance of RPC via their anchoring performance while the closed steel fibers work by confining the concrete; (8) the hybrid utilization of steel fibers improves RPC’s mechanical performance to a higher level via combing the advantages of open and closed steel fibers.
Deep Learning-Based Stage-Wise Risk Stratification for Early Lung Adenocarcinoma in CT Images: A Multi-Center Study
Authors: Gong Jing , Liu Jiyu , Li Haiming , Zhu Hui , Wang Tingting , Hu Tingdan , Li Menglei , Xia Xianwu , Hu Xianfang , Peng Weijun , Wang Shengping , Tong Tong , Gu Yajia
Published: July 2021

This study aims to develop a deep neural network (DNN)-based two-stage risk stratification model for early lung adenocarcinomas in CT images, and investigate the performance compared with practicing radiologists. A total of 2393 GGNs were retrospectively collected from 2105 patients in four centers. All the pathologic results of GGNs were obtained from surgically resected specimens. A two-stage deep neural network was developed based on the 3D residual network and atrous convolution module to diagnose benign and malignant GGNs (Task1) and classify between invasive adenocarcinoma (IA) and non-IA for these malignant GGNs (Task2). A multi-reader multi-case observer study with six board-certified radiologists’ (average experience 11 years, range 2–28 years) participation was conducted to evaluate the model capability. DNN yielded area under the receiver operating characteristic curve (AUC) values of 0.76 ± 0.03 (95% confidence interval (CI): (0.69, 0.82)) and 0.96 ± 0.02 (95% CI: (0.92, 0.98)) for Task1 and Task2, which were equivalent to or higher than radiologists in the senior group with average AUC values of 0.76 and 0.95, respectively (p > 0.05). With the CT image slice thickness increasing from 1.15 mm ± 0.36 to 1.73 mm ± 0.64, DNN performance decreased 0.08 and 0.22 for the two tasks. The results demonstrated (1) a positive trend between the diagnostic performance and radiologist’s experience, (2) the DNN yielded equivalent or even higher performance in comparison with senior radiologists, and (3) low image resolution decreased model performance in predicting the risks of GGNs. Once tested prospectively in clinical practice, the DNN could have the potential to assist doctors in precision diagnosis and treatment of early lung adenocarcinoma.
DeepRePath: Identifying the Prognostic Features of Early-Stage Lung Adenocarcinoma Using Multi-Scale Pathology Images and Deep Convolutional Neural Networks
Authors: Shim Won Sang , Yim Kwangil , Kim Tae-Jung , Sung Yeoun Eun , Lee Gyeongyun , Hong Ji Hyung , Chun Sang Hoon , Kim Seoree , An Ho Jung , Na Sae Jung , Kim Jae Jun , Moon Mi Hyoung , Moon Seok Whan , Park Sungsoo , Hong Soon Auck , Ko Yoon Ho
Published: July 2021

The prognosis of patients with lung adenocarcinoma (LUAD), especially early-stage LUAD, is dependent on clinicopathological features. However, its predictive utility is limited. In this study, we developed and trained a DeepRePath model based on a deep convolutional neural network (CNN) using multi-scale pathology images to predict the prognosis of patients with early-stage LUAD. DeepRePath was pre-trained with 1067 hematoxylin and eosin-stained whole-slide images of LUAD from the Cancer Genome Atlas. DeepRePath was further trained and validated using two separate CNNs and multi-scale pathology images of 393 resected lung cancer specimens from patients with stage I and II LUAD. Of the 393 patients, 95 patients developed recurrence after surgical resection. The DeepRePath model showed average area under the curve (AUC) scores of 0.77 and 0.76 in cohort I and cohort II (external validation set), respectively. Owing to low performance, DeepRePath cannot be used as an automated tool in a clinical setting. When gradient-weighted class activation mapping was used, DeepRePath indicated the association between atypical nuclei, discohesive tumor cells, and tumor necrosis in pathology images showing recurrence. Despite the limitations associated with a relatively small number of patients, the DeepRePath model based on CNNs with transfer learning could predict recurrence after the curative resection of early-stage LUAD using multi-scale pathology images.
PD-1 and beyond to Activate T Cells in Cutaneous Squamous Cell Cancers: The Case for 4-1BB and VISTA Antibodies in Combination Therapy
Authors: Wright Quentin , Gonzalez Cruz Jazmina L. , Wells James W. , Leggatt Graham R.
Published: July 2021

Non-melanoma skin cancers (NMSC) have a higher incidence than all other cancers combined with cutaneous squamous cell carcinoma (cSCC), capable of metastasis, representing approximately 20% of NMSCs. Given the accessibility of the skin, surgery is frequently employed to treat localized disease, although certain localities, the delineation of clear margins, frequency and recurrence of tumors can make these cancers inoperable in a subset of patients. Other treatment modalities, including cryotherapy, are commonly used for individual lesions, with varying success. Immunotherapy, particularly with checkpoint antibodies, is increasingly a promising therapeutic approach in many cancers, offering the potential advantage of immune memory for protection against lesion recurrence. This review addresses a role for PD-1, 4-1BB and VISTA checkpoint antibodies as monotherapies, or in combination as a therapeutic treatment for both early and late-stage cSCC.
Mitochondrial Metabolism in Carcinogenesis and Cancer Therapy
Authors: Moindjie Hadia , Rodrigues-Ferreira Sylvie , Nahmias Clara
Published: July 2021

Carcinogenesis is a multi-step process that refers to transformation of a normal cell into a tumoral neoplastic cell. The mechanisms that promote tumor initiation, promotion and progression are varied, complex and remain to be understood. Studies have highlighted the involvement of oncogenic mutations, genomic instability and epigenetic alterations as well as metabolic reprogramming, in different processes of oncogenesis. However, the underlying mechanisms still have to be clarified. Mitochondria are central organelles at the crossroad of various energetic metabolisms. In addition to their pivotal roles in bioenergetic metabolism, they control redox homeostasis, biosynthesis of macromolecules and apoptotic signals, all of which are linked to carcinogenesis. In the present review, we discuss how mitochondria contribute to the initiation of carcinogenesis through gene mutations and production of oncometabolites, and how they promote tumor progression through the control of metabolic reprogramming and mitochondrial dynamics. Finally, we present mitochondrial metabolism as a promising target for the development of novel therapeutic strategies.
The Ability of Metabolomics to Discriminate Non-Small-Cell Lung Cancer Subtypes Depends on the Stage of the Disease and the Type of Material Studied
Authors: Kowalczyk Tomasz , Kisluk Joanna , Pietrowska Karolina , Godzien Joanna , Kozlowski Miroslaw , Reszeć Joanna , Sierko Ewa , Naumnik Wojciech , Mróz Robert , Moniuszko Marcin , Kretowski Adam , Niklinski Jacek , Ciborowski Michal
Published: July 2021

Identification of the NSCLC subtype at an early stage is still quite sophisticated. Metabolomics analysis of tissue and plasma of NSCLC patients may indicate new, and yet unknown, metabolic pathways active in the NSCLC. Our research characterized the metabolomics profile of tissue and plasma of patients with early and advanced NSCLC stage. Samples were subjected to thorough metabolomics analyses using liquid chromatography-mass spectrometry (LC-MS) technique. Tissue and/or plasma samples from 137 NSCLC patients were analyzed. Based on the early stage tissue analysis, more than 200 metabolites differentiating adenocarcinoma (ADC) and squamous cell lung carcinoma (SCC) subtypes as well as normal tissue, were identified. Most of the identified metabolites were amino acids, fatty acids, carnitines, lysoglycerophospholipids, sphingomyelins, plasmalogens and glycerophospholipids. Moreover, metabolites related to N-acyl ethanolamine (NAE) biosynthesis, namely glycerophospho (N-acyl) ethanolamines (GP-NAE), which discriminated early-stage SCC from ADC, have also been identified. On the other hand, the analysis of plasma of chronic obstructive pulmonary disease (COPD) and NSCLC patients allowed exclusion of the metabolites related to the inflammatory state in lungs and the identification of compounds (lysoglycerophospholipids, glycerophospholipids and sphingomyelins) truly characteristic to cancer. Our results, among already known, showed novel, thus far not described, metabolites discriminating NSCLC subtypes, especially in the early stage of cancer. Moreover, the presented results also indicated the activity of new metabolic pathways in NSCLC. Further investigations on the role of NAE biosynthesis pathways in the early stage of NSCLC may reveal new prognostic and diagnostic targets.
Artificial Intelligence Compared to Radiologists for the Initial Diagnosis of Prostate Cancer on Magnetic Resonance Imaging: A Systematic Review and Recommendations for Future Studies
Authors: Syer Tom , Mehta Pritesh , Antonelli Michela , Mallett Sue , Atkinson David , Ourselin Sébastien , Punwani Shonit
Published: July 2021

Computer-aided diagnosis (CAD) of prostate cancer on multiparametric magnetic resonance imaging (mpMRI), using artificial intelligence (AI), may reduce missed cancers and unnecessary biopsies, increase inter-observer agreement between radiologists, and alleviate pressures caused by rising case incidence and a shortage of specialist radiologists to read prostate mpMRI. However, well-designed evaluation studies are required to prove efficacy above current clinical practice. A systematic search of the MEDLINE, EMBASE, and arXiv electronic databases was conducted for studies that compared CAD for prostate cancer detection or classification on MRI against radiologist interpretation and a histopathological reference standard, in treatment-naïve men with a clinical suspicion of prostate cancer. Twenty-seven studies were included in the final analysis. Due to substantial heterogeneities in the included studies, a narrative synthesis is presented. Several studies reported superior diagnostic accuracy for CAD over radiologist interpretation on small, internal patient datasets, though this was not observed in the few studies that performed evaluation using external patient data. Our review found insufficient evidence to suggest the clinical deployment of artificial intelligence algorithms at present. Further work is needed to develop and enforce methodological standards, promote access to large diverse datasets, and conduct prospective evaluations before clinical adoption can be considered.
ADAM9-Responsive Mesoporous Silica Nanoparticles for Targeted Drug Delivery in Pancreatic Cancer
Authors: Slapak Etienne J. , Kong Lily , el Mandili Mouad , Nieuwland Rienk , Kros Alexander , Bijlsma Maarten F. , Spek C. Arnold
Published: July 2021

Pancreatic ductal adenocarcinoma (PDAC) has the worst survival rate of all cancers. This poor prognosis results from the lack of efficient systemic treatment regimens, demanding high-dose chemotherapy that causes severe side effects. To overcome dose-dependent toxicities, we explored the efficacy of targeted drug delivery using a protease-dependent drug-release system. To this end, we developed a PDAC-specific drug delivery system based on mesoporous silica nanoparticles (MSN) functionalized with an avidin–biotin gatekeeper system containing a protease linker that is specifically cleaved by tumor cells. Bioinformatic analysis identified ADAM9 as a PDAC-enriched protease, and PDAC cell-derived conditioned medium efficiently cleaved protease linkers containing ADAM9 substrates. Cleavage was PDAC specific as conditioned medium from leukocytes was unable to cleave the ADAM9 substrate. Protease linker-functionalized MSNs were efficiently capped with avidin, and cap removal was confirmed to occur in the presence of PDAC cell-derived ADAM9. Subsequent treatment of PDAC cells in vitro with paclitaxel-loaded MSNs indeed showed high cytotoxicity, whereas no cell death was observed in white blood cell-derived cell lines, confirming efficacy of the nanoparticle-mediated drug delivery system. Taken together, this research introduces a novel ADAM9-responsive, protease-dependent, drug delivery system for PDAC as a promising tool to reduce the cytotoxicity of systemic chemotherapy.
Effect of Preparation Methods on the Performance of Pt/TiO2 Catalysts for the Catalytic Oxidation of Carbon Monoxide in Simulated Sintering Flue Gas
Authors: Cai Jianyu , Yu Zehui , Li Jian
Published: July 2021

A series of Pt/TiO2 catalysts were prepared by the impregnation (IM), dry ball mill (DB), or wet ball mill (WB) methods, and their catalytic activity for the oxidation of CO was evaluated. The structure and redox properties of the catalysts were investigated by N2 desorption, XRD, SEM, TEM, XPS, H2-TPR, SO2-TPD, and CO chemisorption analysis. It was determined that the preparation method affects the physical structure of the catalyst and the particle size and dispersion of Pt on the catalyst surface. The catalyst prepared by the impregnation method had a more suitable physical structure than the other catalysts, with a smaller particle size, a higher dispersion of Pt on the surface, and the lowest strength of SO2 adsorption. Pt/TiO2(IM) catalysts presented the best catalytic activity for the oxidation of CO in simulated sintering flue gas at 140 °C, as well as better sulfur and water resistance with simulated sintering flue gas containing 50 ppm of SO2 and 15% water vapor.
Improving the Conversion of Biomass in Catalytic Pyrolysis via Intensification of Biomass—Catalyst Contact by Co-Pressing
Authors: Muhammad Ishaka , Manos George
Published: July 2021

Biomass pyrolysis is a promising technology for fuel and chemical production from an abundant renewable source. It takes place usually in two stages; non-catalytic pyrolysis with further catalytic upgrading of the formed pyrolysis oil. The direct catalytic pyrolysis of biomass reduces the pyrolysis temperature, increase the yield to target products and improves their quality. However, in such one-stage process the contact between biomass and solid catalyst particles is poor leading to an excessively high degree of pure thermal pyrolysis reactions. The aim of this study was to enhance the catalyst-biomass contact via co-pressing of biomass and catalyst particles as a pre-treatment method. Catalytic pyrolysis of biomass components with HY and USY zeolites was studied using thermogravimetric analysis (TGA), as well as experiments in a pyrolysis reactor. The liquid and coke yields were characterized using gas chromatography, and TGA respectively. The TGA results showed that the degradation of the co-pressed cellulose occurred at lower temperatures compared to the pure thermal degradation, as well as catalytic degradation of non-pretreated cellulose. All biomass components produced better results using the co-pressing method, where the liquid yields increased while coke/char yields decreased. Bio-oil from catalytic pyrolysis of cellulose with HY catalyst mainly produced heavier fractions, while in the presence of USY catalyst medium fraction was mainly produced within the gasoline range. For hemicellulose catalytic pyrolysis, the catalysts had similar effects in enhancing the lighter fraction, but specifically, HY showed higher selectivity to middle fraction while USY has produced higher percentage of lighter fraction. Using with both catalysts, co-pressing had the best effect of eliminating the heavier fraction and improving the gasoline range fraction. Spent catalyst from co-pressed sample had lower concentrations of coke/char components due to the shorter residence times of volatiles, which suppresses the occurrence of secondary reactions leading to coke/char formations.
Green Synthesis of Flower-Shaped Copper Oxide and Nickel Oxide Nanoparticles via Capparis decidua Leaf Extract for Synergic Adsorption-Photocatalytic Degradation of Pesticides
Authors: Iqbal Amna , Haq Atta ul , Cerrón-Calle Gabriel Antonio , Naqvi Syed Ali Raza , Westerhoff Paul , Garcia-Segura Sergi
Published: July 2021

Green manufacturing of catalysts enables sustainable advanced oxidation processes and water treatment processes for removing trace contaminants such as pesticides. An environmentally friendly biosynthesis process produced high-surface-area CuO and NiO nanocatalysts using phytochemicals in the Capparis decidua leaf extract, which served as a reductant and influenced catalyst shape. Capparis decidua is a bushy shrub, widely distributed in dry and arid regions of Africa, Pakistan, India, Egypt, Jordan, Sudan, Saudi Arabia. The synthesized CuO and NiO nanoparticles were characterized by UV-vis spectroscopy (UV-vis), field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDS), Fourier transform infrared spectroscopy (FT-IR), and X-ray diffraction (XRD) and thermo-gravimetric analysis/differential thermal analysis (TGA/DTA). The produced nanoparticles were spherical and flower-like in shape and have a characteristic face-centered cubic structure of CuO and NiO. Biosynthesized catalysts were photoactive and degraded recalcitrant pesticide Lambda-cyhalothrin (L-CHT). Photocatalytic degradation of L-CHT was affected by the initial L-CHT concentration, solution pH levels between 5 and 9, and photocatalyst concentration. The L-CHT removal percentage attained by CuO photocatalyst (~99%) was higher than for NiO photocatalyst (~89%). The degradation of L-CHT follows a pseudo-first-order kinetic model, and the apparent rate constant (kapp) decreased from 0.033 min−1 for CuO to 0.0084 min−1 for NiO photocatalyst. The novel flower-shaped nanoparticles demonstrated high stability in water and recyclability for removing L-CHT pesticide contamination in water.
Infusion of Phagocytic Macrophages Overexpressing CPT1a Ameliorates Kidney Fibrosis in the UUO Model
Authors: Calle Priscila , Játiva Soraya , Torrico Selene , Muñoz Angeles , García Miriam , Sola Anna , Serra Dolors , Mera Paula , Herrero Laura , Hotter Georgina
Published: July 2021

Phagocytosis is an inherent function of tissue macrophages for the removal of apoptotic cells and cellular debris during acute and chronic injury; however, the dynamics of this event during fibrosis development is unknown. We aim to prove that during the development of kidney fibrosis in the unilateral ureteral obstruction (UUO) model, there are some populations of macrophage with a reduced ability to phagocytose, and whether the infusion of a population of phagocytic macrophages could reduce fibrosis in the murine model UUO. For this purpose, we have identified the macrophage populations during the development of fibrosis and have characterized their phagocytic ability and their expression of CPT1a. Furthermore, we have evaluated the therapeutic effect of macrophages overexpressing CPT1a with high phagocytic skills. We evidenced that the macrophage population which exhibits high phagocytic ability (F4/80low-CD11b) in fibrotic animals decreases during the progression of fibrosis while the macrophage population with lower phagocytic ability (F4/80high-CD11b) in fibrotic conditions, conversely, increases and CPT1a macrophage cell therapy with a strengthening phagocytic ability is associated with a therapeutic effect on kidney fibrosis. We have developed a therapeutic approach to reduce fibrosis in the UUO model by enrichment of the kidney resident macrophage population with a higher proportion of exogenous phagocytic macrophages overexpressing CPT1a.
Prospects and Challenges for T Cell-Based Therapies of HCC
Authors: Woller Norman , Engelskircher Sophie Anna , Wirth Thomas , Wedemeyer Heiner
Published: July 2021

The scope of therapeutic options for the treatment of hepatocellular carcinoma (HCC) has recently been expanded by immunotherapeutic regimens. T cell-based therapies, especially in combination with other treatments have achieved far better outcomes compared to conventional treatments alone. However, there is an emerging body of evidence that eliciting T cell responses in immunotherapeutic approaches is insufficient for favorable outcomes. Immune responses in HCC are frequently attenuated in the tumor microenvironment (TME) or may even support tumor progress. Hence, therapies with immune checkpoint inhibitors or adoptive cell therapies appear to necessitate additional modification of the TME to unlock their full potential. In this review, we focus on immunotherapeutic strategies, underlying molecular mechanisms of CD8 T cell immunity, and causes of treatment failure in HCC of viral and non-viral origin. Furthermore, we provide an overview of TME features in underlying etiologies of HCC patients that mediate therapy resistance to checkpoint inhibition and discuss strategies from the literature concerning current approaches to these challenges.
CRISPR/Cas13-Based Approaches for Ultrasensitive and Specific Detection of microRNAs
Authors: Granados-Riveron Javier T. , Aquino-Jarquin Guillermo
Published: July 2021

MicroRNAs (miRNAs) have a prominent role in virtually every aspect of cell biology. Due to the small size of mature miRNAs, the high degree of similarity between miRNA family members, and the low abundance of miRNAs in body fluids, miRNA expression profiling is technically challenging. Biosensors based on electrochemical detection for nucleic acids are a novel category of inexpensive and very sensitive diagnostic tools. On the other hand, after recognizing the target sequence, specific CRISPR-associated proteins, including orthologues of Cas12, Cas13, and Cas14, exhibit collateral nonspecific catalytic activities that can be employed for specific and ultrasensitive nucleic acid detection from clinically relevant samples. Recently, several platforms have been developed, connecting the benefits of enzyme-assisted signal amplification and enzyme-free amplification biosensing technologies with CRISPR-based approaches for miRNA detection. Together, they provide high sensitivity, precision, and fewer limitations in diagnosis through efficient sensors at a low cost and a simple miniaturized readout. This review provides an overview of several CRISPR-based biosensing platforms that have been developed and successfully applied for ultrasensitive and specific miRNA detection.
Numerical Simulations of Red-Blood Cells in Fluid Flow: A Discrete Multiphysics Study
Authors: Rahmat Amin , Kuchel Philip , Barigou Mostafa , Alexiadis Alessio
Published: July 2021

In this paper, we present a methodological study of modelling red blood cells (RBCs) in shear-induced flows based on the discrete multiphysics (DMP) approach. The DMP is an alternative approach from traditional multiphysics based on meshless particle-based methods. The proposed technique has been successful in modelling multiphysics and multi-phase problems with large interfacial deformations such as those in biological systems. In this study, we present the proposed method and introduce an accurate geometrical representation of the RBC. The results were validated against available data in the literature. We further illustrate that the proposed method is capable of modelling the rupture of the RBC membrane with minimum computational difficulty.
Data-Driven Analysis of Forest–Climate Interactions in the Conterminous United States
Authors: Rumyantseva Olga , Strigul Nikolay
Published: July 2021

A predictive understanding of interactions between vegetation and climate has been a grand challenge in terrestrial ecology for over 200 years. Developed in recent decades, continental-scale monitoring of climate and forest dynamics enables quantitative examination of vegetation–climate relationships through a data-driven paradigm. Here, we apply a data-intensive approach to investigate forest–climate interactions across the conterminous USA. We apply multivariate statistical methods (stepwise regression, principal component analysis) including machine learning to infer significant climatic drivers of standing forest basal area. We focus our analysis on the ecoregional scale. For most ecoregions analyzed, both stepwise regression and random forests indicate that factors related to precipitation are the most significant predictors of forest basal area. In almost half of US ecoregions, precipitation of the coldest quarter is the single most important driver of basal area. The demonstrated data-driven approach may be used to inform forest-climate envelope modeling and the forecasting of large-scale forest dynamics under climate change scenarios. These results have important implications for climate, biodiversity, industrial forestry, and indigenous communities in a changing world.
Left Ventricular Assist Device Implantation in a Thrombosed Apical Aneurysm
Authors: Masarone Daniele , Melillo Enrico , Gravino Rita , Vastarella Rossella , Caiazzo Angelo , Ursomando Fabio , Pacileo Giuseppe , Petraio Andrea
Published: July 2021

Left ventricular assist device implantation is a challenging procedure in the presence of a giant thrombosed aneurysm, and no standard surgical techniques are currently recommended in this setting. In this case, we report the successful implantation of a left ventricular assist device (HeartMate III) in a patient with a massive thrombosed apical aneurysm. The patient presented with extended antero-apical necrosis as a result of a delay in hospital admission for acute coronary syndrome due to the patient’s concerns about the COVID-19 pandemic outbreak.
Influence of Detonation-Spraying Parameters on the Phase Composition and Tribological Properties of Al2O3 Coatings
Authors: Kantay Nurgamit , Rakhadilov Bauyrzhan , Kurbanbekov Sherzod , Yeskermessov Didar , Yerbolatova Gulnara , Apsezhanova Akbota
Published: July 2021

Al2O3 coatings were applied on the surface of 12Ch18N10T steel by the detonation method at different degrees of filling of the detonation gun. The aim was to study the influence of technological parameters on the formation of the coating’s structure, phase composition and tribological characteristics. The degree of filling the gun with a gas mixture (C2H2/O2) varied from 53% to 68%. X-ray diffraction study showed that the content of α-Al2O3 increases depending on the degree of filling. The results showed that the hardness increases with an increase in the α-Al2O3 phase. When the gun is 53% filled with gas, the Al2O3-based coating has the hardness of 20.56 GPa compared to 58%, 63% and 68% fillings. Tribology tests have shown that the wear rate and friction coefficient of the coating is highly dependent on the degree of filling of the gun.
Electrohydrodynamic Instabilities in Free Emulsion Films
Authors: Mostowfi Farshid , Tchoukov Plamen , Panchev Nikolay , Dabros Tadeusz , Czarnecki Jan
Published: July 2021

Electrohydrodynamic instabilities were induced in thin water-in-oil emulsion films by application of external DC electric field. The dominant wavelengths of instabilities were measured for constant electric fields of various strengths. The dominant wavelengths agreed reasonably well with theoretical predictions based on a linear stability model. The linear stability model used in this study took into account experimentally measured repulsive disjoining pressure and calculated Maxwell stress. The observation of such instabilities can help to understand the rupture mechanism of emulsion films under the influence of electric field.
Convenient Access to Functionalized Non-Symmetrical Atropisomeric 4,4′-Bipyridines
Authors: Aubert Emmanuel , Wenger Emmanuel , Peluso Paola , Mamane Victor
Published: July 2021

Non-symmetrical chiral 4,4′-bipyridines have recently found interest in organocatalysis and medicinal chemistry. In this regard, the development of efficient methods for their synthesis is highly desirable. Herein, a series of non-symmetrical atropisomeric polyhalogenated 4,4′-bipyridines were prepared and further functionalized by using cross-coupling reactions. The desymmetrization step is based on the N-oxidation of one of the two pyridine rings of the 4,4′-bipyridine skeleton. The main advantage of this methodology is the possible post-functionalization of the pyridine N-oxide, allowing selective introduction of chlorine, bromine or cyano groups in 2- and 2′-postions of the chiral atropisomeric 4,4′-bipyridines. The crystal packing in the solid state of some newly prepared derivatives was analyzed and revealed the importance of halogen bonds in intermolecular interactions.
Improvement and Assessment of a Blind Image Deblurring Algorithm Based on Independent Component Analysis
Authors: Fiori Simone
Published: July 2021

The aim of the present paper is to improve an existing blind image deblurring algorithm, based on an independent component learning paradigm, by manifold calculus. The original technique is based on an independent component analysis algorithm applied to a set of pseudo-images obtained by Gabor-filtering a blurred image and is based on an adapt-and-project paradigm. A comparison between the original technique and the improved method shows that independent component learning on the unit hypersphere by a Riemannian-gradient algorithm outperforms the adapt-and-project strategy. A comprehensive set of numerical tests evidenced the strengths and weaknesses of the discussed deblurring technique.
Prototyping a Smart Contract Based Public Procurement to Fight Corruption
Authors: Weingärtner Tim , Batista Danielle , Köchli Sandro , Voutat Gilles
Published: July 2021

Corruption in public procurement is a worldwide appearance that causes immense financial and reputational damages. Especially in developing countries, corruption is a widespread issue due to secrecy and lack of transparency. An important instrument for transparency and accountability assurance is the record which is managed and controlled by recordkeeping systems. Blockchain technology and more precisely blockchain-based smart contracts are emerging technological tools that can be used as recordkeeping systems and a tool to mitigate some of the fraud involving public procurement records. Immutability, transparency, distribution and automation are some of the features of smart contracts already implemented in several applications to avoid malicious human interference. In this paper, we discuss some of the frauds in public procurement, and we propose smart contracts to automatize different stages of the public procurement procedure attempting to fix their biggest current weaknesses. The processes we have focused on include the bidding process, supplier habilitation and delivery verification. In the three subprocesses, common irregularities include human fallibility, improper information disclosure and hidden agreements which concern not only governments but also civil society. To show the feasibility and usability of our proposal, we have implemented a prototype that demonstrates the process using sample data.