bluuebunny/crossref_metadata_2025 huggingface dataset:
AE-CGAN Model based High Performance Network Intrusion Detection System
Authors: Lee JooHwa , Park KeeHyun
Published: October 2019

In this paper, a high-performance network intrusion detection system based on deep learning is proposed for situations in which there are significant imbalances between normal and abnormal traffic. Based on the unsupervised learning models autoencoder (AE) and the generative adversarial networks (GAN) model during deep learning, the study aim is to solve the imbalance of data and intrusion detection of high performance. The AE-CGAN (autoencoder-conditional GAN) model is proposed to improve the performance of intrusion detection. This model oversamples rare classes based on the GAN model in order to solve the performance degradation caused by data imbalance after processing the characteristics of the data to a lower level using the autoencoder model. To measure the performance of the AE-CGAN model, data is classified using random forest (RF), a typical machine learning classification algorithm. In this experiment, we used the canadian institute for cybersecurity intrusion detection system (CICIDS)2017 dataset, the latest public dataset of network intrusion detection system (NIDS), and compared the three models to confirm efficacy of the proposed model. We compared the performance of three types of models. These included single-RF, a classification model using only a classification algorithm, AE-RF which is processed by classifying data features, and the AE-CGAN model which is classified after solving the data feature processing and data imbalance. Experimental results showed that the performance of the AE-CGAN model proposed in this paper was the highest. In particular, when the data were unbalanced, the performances of recall and F1 score, which are more accurate performance indicators, were 93.29% and 95.38%, respectively. The AE-CGAN model showed much better performance.
Evaluating Seismic Soil Liquefaction Potential Using Bayesian Belief Network and C4.5 Decision Tree Approaches
Authors: Ahmad Mahmood , Tang Xiao-Wei , Qiu Jiang-Nan , Ahmad Feezan
Published: October 2019

Liquefaction is considered a damaging phenomenon of earthquakes and a major cause of concern in civil engineering. Therefore, its predictory assessment is an essential task for geotechnical experts. This paper investigates the performance of Bayesian belief network (BBN) and C4.5 decision tree (DT) models to evaluate seismic soil liquefaction potential based on the updated and relatively large cone penetration test (CPT) dataset (which includes 251 case histories), comparing them to a simplified procedure and an evolutionary-based approach. The BBN model was developed using the K2 machine learning algorithm and domain knowledge (DK) with data fusion methodology, while the DT model was created using a C4.5 algorithm. This study shows that the BBN model is preferred over the others for evaluation of seismic soil liquefaction potential. Owing to its overall performance, simplicity in practice, data-driven characteristics, and ability to map interactions between variables, the use of a BBN model in assessing seismic soil liquefaction is quite promising. The results of a sensitivity analysis show that ‘equivalent clean sand penetration resistance’ is the most significant factor affecting liquefaction potential. This study also interprets the probabilistic reasoning of the robust BBN model and most probable explanation (MPE) of seismic soil liquefied sites, based on an engineering point of view.
Melanoma Growth Analysis in Blood Serum and Tissue Using Xenograft Model with Response to Cold Atmospheric Plasma Activated Medium
Authors: Adhikari Manish , Adhikari Bhawana , Kaushik Neha , Lee Su-Jae , Kaushik Nagendra Kumar , Choi Eun Ha
Published: October 2019

Background: Cold atmospheric plasma (CAP) proposed as a novel therapeutic tool for the various kinds of cancer treatment. Cold atmospheric Plasma-Activated Media (PAM) has exhibited its promising application in plasma medicine for the treatment of cancer. Methods: We investigated the role of PAM on the human melanoma cancer G-361 cells xenograft in vivo by estimating the biochemical and gene expression of apoptotic genes. Results: Reactive oxygen and nitrogen species (RONS) generated by PAM could significantly decrease the tumor volume (40%) and tumor weight (26%) when administered intradermally (i.d.) into the melanoma region continuously for three days. Biochemical studies in blood serum along with excised melanoma samples revealed an increase in protein carbonylation and MDA content as compared to the control, while LDH and L-DOPA in serum and melanoma tissues were decreased significantly in PAM treated group. PAM generated RONS increased apoptotic genes like Bcl-2, Bax, Parp, Casp8, and P53 in melanoma tissue. Immunohistochemistry data confirms that PAM treatment increased apoptosis at the tissue level. Conclusions: These results suggested that RONS present in PAM inhibit the induction of xenograft melanoma cancer cells through the induction of apoptosis and upregulating of various biochemical parameters within blood serum and melanoma.
Improving Electric Energy Consumption Prediction Using CNN and Bi-LSTM
Authors: Le Tuong , Vo Minh , Vo Bay , Hwang Eenjun , Rho Seungmin , Baik Sung
Published: October 2019

The electric energy consumption prediction (EECP) is an essential and complex task in intelligent power management system. EECP plays a significant role in drawing up a national energy development policy. Therefore, this study proposes an Electric Energy Consumption Prediction model utilizing the combination of Convolutional Neural Network (CNN) and Bi-directional Long Short-Term Memory (Bi-LSTM) that is named EECP-CBL model to predict electric energy consumption. In this framework, two CNNs in the first module extract the important information from several variables in the individual household electric power consumption (IHEPC) dataset. Then, Bi-LSTM module with two Bi-LSTM layers uses the above information as well as the trends of time series in two directions including the forward and backward states to make predictions. The obtained values in the Bi-LSTM module will be passed to the last module that consists of two fully connected layers for finally predicting the electric energy consumption in the future. The experiments were conducted to compare the prediction performances of the proposed model and the state-of-the-art models for the IHEPC dataset with several variants. The experimental results indicate that EECP-CBL framework outperforms the state-of-the-art approaches in terms of several performance metrics for electric energy consumption prediction on several variations of IHEPC dataset in real-time, short-term, medium-term and long-term timespans.
Tailorable and Broadband On-Chip Optical Power Splitter
Authors: Kim Hyeongpin , Shin Heedeuk
Published: October 2019

An on-chip optical power splitter is a key component of photonic signal processing and quantum integrated circuits and requires compactness, wideband, low insertion loss, and variable splitting ratio. However, designing an on-chip splitter with both customizable splitting ratio and wavelength independence is a big challenge. Here, we propose a tailorable and broadband optical power splitter over 100 nm with low insertion loss less than 0.3%, as well as a compact footprint, based on 1×2 interleaved tapered waveguides. The proposed scheme can design the output power ratio of transverse electric modes, lithographically, and a selection equation of a power splitting ratio is extracted to obtain the desired power ratio. Our splitter scheme is close to an impeccable on-chip optical power splitter for classical and quantum integrated photonic circuits.
Recommendation Agent Adoption: How Recommendation Presentation Influences Employees’ Perceptions, Behaviors, and Decision Quality
Authors: Bigras Émilie , Léger Pierre-Majorique , Sénécal Sylvain
Published: October 2019

The purpose of this paper is to report the results of a laboratory experiment that investigated how assortment planners’ perceptions, usage behavior, and decision quality are influenced by the way recommendations of an artificial intelligence (AI)-based recommendation agent (RA) are presented. A within-subject laboratory experiment was conducted with twenty subjects. Participants perceptions and usage behavior toward an RA while making decisions were assessed using validated measurement scales and eye-tracking technology. The results of this study show the importance of a transparent RA demanding less cognitive effort to understand and access the explanations of a transparent RA on assortment planners’ perceptions (i.e., source credibility, sense of control, decision quality, and satisfaction), usage behavior, and decision quality. Results from this study suggest that designing RAs with more transparency for the users bring perceptual and attitudinal benefits that influence both the adoption and continuous use of those systems by employees. This study contributes to filling the literature gap on RAs in organizational contexts, thus advancing knowledge in the human–computer interaction literature. The findings of this study provide guidelines for RA developers and user experience (UX) designers on how to best create and present an AI-based RA to employees.
Expert Finding Systems: A Systematic Review
Authors: Husain Omayma , Salim Naomie , Alias Rose Alinda , Abdelsalam Samah , Hassan Alzubair
Published: October 2019

The data overload problem and the specific nature of the experts’ knowledge can hinder many users from finding experts with the expertise they required. There are several expert finding systems, which aim to solve the data overload problem and often recommend experts who can fulfil the users’ information needs. This study conducted a Systematic Literature Review on the state-of-the-art expert finding systems and expertise seeking studies published between 2010 and 2019. We used a systematic process to select ninety-six articles, consisting of 57 journals, 34 conference proceedings, three book chapters, and one thesis. This study analyses the domains of expert finding systems, expertise sources, methods, and datasets. It also discusses the differences between expertise retrieval and seeking. Moreover, it identifies the contextual factors that have been combined into expert finding systems. Finally, it identifies five gaps in expert finding systems for future research. This review indicated that ≈65% of expert finding systems are used in the academic domain. This review forms a basis for future expert finding systems research.
Space Charge Accumulation and Decay in Dielectric Materials with Dual Discrete Traps
Authors: Xing Zhaoliang , Zhang Chong , Cui Haozhe , Hai Yali , Wu Qingzhou , Min Daomin
Published: October 2019

Charge trapping and de-trapping properties can affect space charge accumulation and electric field distortion behavior in polymers. Dielectric materials may contain different types of traps with different energy distributions, and it is of interest to investigate the charge trapping/de-trapping dynamic processes in dielectric materials containing multiple discrete trap centers. In the present work, we analyze the charge trapping/de-trapping dynamics in materials with two discrete traps in two cases where charges are injected continuously or only for a very short period. The time dependent trapped charge densities are obtained by the integration of parts in the case of continuous charge injection. In the case of instantaneous charge injection, we simplify the charge trapping/de-trapping equations and obtain the analytical solutions of trapped charge densities, quasi-free charge density, and effective carrier mobility. The analytical solutions are in good agreement with the numerical results. Then, the space charge dynamics in dielectric materials with two discrete trapping centers are studied by the bipolar charge transport (BCT) model, consisting of charge injection, charge migration, charge trapping, de-trapping, and recombination processes. The BCT outputs show the time evolution of spatial distributions of space charge densities. Moreover, we also achieve the charge densities at the same position in the sample as a function of time by the BCT model. It is found that the DC poling duration can affect the energy distribution of accumulated space charges. In addition, it is found that the coupling dynamic processes will establish a dynamic equilibrium rather than a thermodynamic equilibrium in the dielectric materials.
Selective Finite Memory Structure Filtering Using the Chi-Square Test Statistic for Temporarily Uncertain Systems
Authors: Kim Pyung Soo
Published: October 2019

In this paper, a finite memory structure (FMS) filtering with two kinds of measurement windows is proposed using the chi-square test statistic to cover nominal systems as well as temporarily uncertain systems. First, the simple matrix form for the FMS filter is developed from the conditional density of the current state given finite past measurements. Then, one of the two FMS filters, the primary FMS filter or the secondary FMS filter, with different measurement windows is operated selectively according to the presence or absence of uncertainty, to obtain a valid estimate. The primary FMS filter is selected for the nominal system and the secondary FMS filter is selected for the temporarily uncertain system, respectively. A declaration rule is defined to indicate the presence or absence of uncertainty, operate the suitable one from two filters, and then obtain the valid filtered estimate. A test variable for the declaration rule is developed using a chi-square test statistic from the estimation error and compared to a precomputed threshold. In order to verify the proposed selective FMS filtering and compare with the existing FMS filter and the infinite memory structure (IMS) filter, computer simulations are performed for a selection of dynamic systems including a F404 gas turbine aircraft engine and an electric motor. Simulation results confirm that the proposed selective FMS filtering works well for nominal systems as well as temporarily uncertain systems. In addition, the proposed selective FMS filtering is shown to be remarkably better than the IMS filtering for the temporarily uncertain system.
Effects of Diverging Nozzle Downstream on Flow Field Parameters of Rotating Detonation Combustor
Authors: Sun Chengwen , Zheng Hongtao , Li Zhiming , Zhao Ningbo , Qi Lei , Guo Hongbo
Published: October 2019

In this study, three-dimensional numerical studies have been performed to investigate the performance of a rotating detonation combustor with a diverging nozzle downstream. The effects of a diverging nozzle on the formation and propagation process of a detonation wave and typical flow field parameters in a rotating detonation combustor are mainly discussed. The results indicate that the diverging nozzle downstream is an important factor affecting the performance and design of a rotating detonation combustor. The diverging nozzle does not affect the formation and propagation process of the rotating detonation wave, while the time of two key wave collisions are delayed during the formation process of the detonation wave. With increases of the diverging angle, the rotating detonation combustor with the diverging nozzle can still maintain a certain pressure gain performance. Both the diverging nozzle and diverging angle have great influence on the flow field parameters of the rotating detonation combustor, including reducing the high pressure and temperature load, making the distribution of the outlet parameters uniform, and changing the local supersonic flow at the outlet. Among them, the outlet static pressure is reduced by up to 88.32%, and the outlet static temperature is reduced by up to 32.12%. This evidently improves the working environment of the combustor while reducing the thermodynamic and aerodynamic loads at the outlet. In particular, the diverging nozzle does not affect the supersonic characteristics of the outlet airflow, and on this basis, the Mach number becomes coincident and enhanced.
Optimal Estimation of Parameters Encoded in Quantum Coherent State Quadratures
Authors: Arnhem Matthieu , Karpov Evgueni , Cerf Nicolas J.
Published: October 2019

In the context of multiparameter quantum estimation theory, we investigate the construction of linear schemes in order to infer two classical parameters that are encoded in the quadratures of two quantum coherent states. The optimality of the scheme built on two phase-conjugate coherent states is proven with the saturation of the quantum Cramér–Rao bound under some global energy constraint. In a more general setting, we consider and analyze a variety of n-mode schemes that can be used to encode n classical parameters into n quantum coherent states and then estimate all parameters optimally and simultaneously.
Determination of the Optimal State of Dough Fermentation in Bread Production by Using Optical Sensors and Deep Learning
Authors: Giefer Lino Antoni , Lütjen Michael , Rohde Ann-Kathrin , Freitag Michael
Published: October 2019

Dough fermentation plays an essential role in the bread production process, and its success is critical to producing high-quality products. In Germany, the number of stores per bakery chain has increased within the last years as well as the trend to finish the bakery products local at the stores. There is an unsatisfied demand for skilled workers, which leads to an increasing number of untrained and inexperienced employees at the stores. This paper proposes a method for the automatic monitoring of the fermentation process based on optical techniques. By using a combination of machine learning and superellipsoid model fitting, we have developed an instance segmentation and parameter estimation method for dough objects that are positioned inside a fermentation chamber. In our method we measure the given topography at discrete points in time using a movable laser sensor system that is located at the back of the fermentation chamber. By applying the superellipsoid model fitting method, we estimated the volume of each object and achieved results with a deviation of approximately 10% on average. Thereby, the volume gradient is monitored continuously and represents the progress of the fermentation state. Exploratory tests show the reliability and the potential of our method, which is particularly suitable for local stores but also for high volume production in bakery plants.
Employing the Method of Characteristics to Obtain the Solution of Spectral Evolution of Turbulent Kinetic Energy Density Equation in an Isotropic Flow
Authors: Paveglio Szinvelski Charles Rogério , Buligon Lidiane , Annes Degrazia Gervásio , Tirabassi Tiziano , Costa Acevedo Otavio , Roberti Débora Regina
Published: October 2019

This study aims to review the physical theory and parametrizations associated to Turbulent Kinetic Energy Density Function (STKE). The bibliographic references bring a broad view of the physical problem, mathematical techniques and modeling of turbulent kinetic energy dynamics in the convective boundary layer. A simplified model based on the dynamical equation for the STKE, in an isotropic and homogeneous turbulent flow regime, is done by formulating and considering the isotropic inertial energy transfer and viscous dissipation terms. This model is described by the Cauchy Problem and solved employing the Method of Characteristics. Therefore, a discussion on Linear First Order Partial Differential Equation, its existence, and uniqueness of solution has been presented. The spectral function solution obtained from its associated characteristic curves and initial condition (Method of Characteristics) reproduces the main features of a modeled physical system. In addition, this modeling allows us to obtain the scaling parameters, which are frequently employed in parameterizations for turbulent dispersion.
Boltzmann-Based Empirical Model to Calculate Volume Loss during Spirit Ageing
Authors: del Toro del Toro Noemí , Fong Casas Fredy , Ayan Rial Julio , Caridad Portuondo González Maria , Crespo Sariol Harold , Navarro Campa José , Yperman Jan , Vandamme Dries , Carleer Robert
Published: October 2019

The Boltzmann equation is applied to fit data of volume loss for evaporation (in %) during spirit ageing in northern white oak (Quercus Alba) standard barrels of 205 L (+/− 10 L) using a temperature and humidity controlled cellar. The Boltzmann equation satisfactory fitted to the experimental data of the volume loss against temperature at constant humidity. Two parameters of the Boltzmann equation showed a linear dependency on the relative humidity of the air, while the other two parameters exhibited a constant value independently of the air humidity. The found empirical mathematical model can be used to calculate the volume loss for evaporation of spirits (40% v/v of ethanol) during ageing in terms of relative humidity (range: 40%–95%) and temperature (range: 10–30 °C) with significant accuracy.
Polarization Induced Electro-Functionalization of Pore Walls: A Contactless Technology
Authors: Bouchet-Spinelli Aurélie , Descamps Emeline , Liu Jie , Ismail Abdulghani , Pham Pascale , Chatelain François , Leïchlé Thierry , Leroy Loïc , Marche Patrice Noël , Raillon Camille , Roget André , Roupioz Yoann , Sojic Neso , Buhot Arnaud , Haguet Vincent , Livache Thierry , Mailley Pascal
Published: October 2019

This review summarizes recent advances in micro- and nanopore technologies with a focus on the functionalization of pores using a promising method named contactless electro-functionalization (CLEF). CLEF enables the localized grafting of electroactive entities onto the inner wall of a micro- or nano-sized pore in a solid-state silicon/silicon oxide membrane. A voltage or electrical current applied across the pore induces the surface functionalization by electroactive entities exclusively on the inside pore wall, which is a significant improvement over existing methods. CLEF’s mechanism is based on the polarization of a sandwich-like silicon/silicon oxide membrane, creating electronic pathways between the core silicon and the electrolyte. Correlation between numerical simulations and experiments have validated this hypothesis. CLEF-induced micro- and nanopores functionalized with antibodies or oligonucleotides were successfully used for the detection and identification of cells and are promising sensitive biosensors. This technology could soon be successfully applied to planar configurations of pores, such as restrictions in microfluidic channels.
High Serum Caspase-Cleaved Cytokeratin-18 Levels and Mortality of Traumatic Brain Injury Patients
Authors: Lorente Leonardo , Martín María M. , González-Rivero Agustín F. , Pérez-Cejas Antonia , Argueso Mónica , Ramos Luis , Solé-Violán Jordi , Cáceres Juan J. , Jiménez Alejandro , García-Marín Victor
Published: October 2019

Objective: Apoptosis increases in traumatic brain injury (TBI). Caspase-cleaved cytokeratin (CCCK)-18 in blood during apoptosis could appear. At the time of admission due to TBI, higher blood CCCK-18 levels were found in non-surviving than in surviving patients. Therefore, the objective of our study was to analyze whether serum CCCK-18 levels determined during the first week after TBI could predict early mortality (at 30 days). Methods: Severe TBI patients were included (considering severe when Glasgow Coma Scale < 9) in this observational and multicentre study. Serum CCCK-18 levels were determined at day 1 of TBI, and at days 4 and 8 after TBI. Results: Serum CCCK-18 levels at day 1 of TBI, and in the days 4 and 8 after TBI were higher (p < 0.001) in non-surviving than in surviving patients (34 and 90 patients, respectively) and could predict early mortality (p < 0.001 in the area under the curve). Conclusions: The new findings from our study were that serum CCCK-18 levels at any moment of the first week of TBI were higher in non-surviving patients and were able to predict early mortality.
The PAK1-Stat3 Signaling Pathway Activates IL-6 Gene Transcription and Human Breast Cancer Stem Cell Formation
Authors: Kim Ji-Hyang , Choi Hack Sun , Kim Su-Lim , Lee Dong-Sun
Published: October 2019

Cancer stem cells (CSCs) have unique properties, including self-renewal, differentiation, and chemoresistance. In this study, we found that p21-activated kinase (PAK1) inhibitor (Group I, PAK inhibitor, IPA-3) and inactivator (ivermectin) treatments inhibit cell proliferation and that tumor growth of PAK1-knockout cells in a mouse model is significantly reduced. IPA-3 and ivermectin inhibit CSC formation. PAK1 physically interacts with Janus Kinase 2 (JAK2), and JAK2 inhibitor (TG101209) treatment inhibits mammosphere formation and reduces the nuclear PAK1 protein level. PAK1 interacts with signal transducer and activator of transcription 3 (Stat3), and PAK1 and Stat3 colocalize in the nucleus. We show through electrophoretic mobility shift assay (EMSA), chromatin immunoprecipitation (ChIP), and reporter assays that the PAK1/Stat3 complex binds to the IL-6 promoter and regulates the transcription of the IL-6 gene. Inhibition of PAK1 and JAK2 in mammospheres reduces the nuclear pStat3 and extracellular IL-6 levels. PAK1 inactivation inhibits CSC formation by decreasing pStat3 and extracellular IL-6 levels. Our results reveal that JAK2/PAK1 dysregulation inhibits the Stat3 signaling pathway and CSC formation, the PAK1/Stat3 complex regulates IL-6 gene expression, PAK1/Stat3 signaling regulates CSC formation, and PAK1 may be an important target for treating breast cancer.
99mTc-A1 as a Novel Imaging Agent Targeting Mesothelin-Expressing Pancreatic Ductal Adenocarcinoma
Authors: Montemagno Christopher , Cassim Shamir , Trichanh Dimitry , Savary Clara , Pouyssegur Jacques , Pagès Gilles , Fagret Daniel , Broisat Alexis , Ghezzi Catherine
Published: October 2019

Mesothelin is a membrane-associated protein overexpressed in pancreatic ductal adenocarcinoma (PDAC). Some mesothelin-targeted therapies are in clinical development but the identification of patients eligible for such therapies is still challenging. The objective of this study was to perform the imaging of mesothelin in mice models of PDAC with a technetium-labeled anti-mesothelin single-domain antibody (99mTc-A1). Methods: The Cancer Genomic Atlas (TCGA) database was used to determine the prognostic role of mesothelin in PDAC. 99mTc-A1 was evaluated both in vitro in PDAC cells (SW1990 and AsPC-1) and in vivo in an experimental model of mesothelin-expressing PDAC (AsPC-1) in mice. Results: TCGA analysis showed that PDAC patients with high mesothelin expression had a shorter overall survival (P = 0.00066). The binding of 99mTc-A1 was 2.1-fold greater in high-mesothelin-expressing AsPC-1 cells when compared to moderate-mesothelin-expressing SW1990 cells (p < 0.05). In vivo, the 99mTc-A1 uptake was 3.5-fold higher in AsPC-1-derived tumors as compared to a technetium-labeled irrelevant antibody (99mTc-Ctl) (p < 0.01). Conclusions: 99mTc-A1 accurately allows imaging of mesothelin-expressing experimental PDAC tumors. Our experiments paved the way for the development of a companion test for mesothelin-targeted therapies.
17β-Estradiol Activates HSF1 via MAPK Signaling in ERα-Positive Breast Cancer Cells
Authors: Vydra Natalia , Janus Patryk , Toma-Jonik Agnieszka , Stokowy Tomasz , Mrowiec Katarzyna , Korfanty Joanna , Długajczyk Anna , Wojtaś Bartosz , Gielniewski Bartłomiej , Widłak Wiesława
Published: October 2019

Heat Shock Factor 1 (HSF1) is a key regulator of gene expression during acute environmental stress that enables the cell survival, which is also involved in different cancer-related processes. A high level of HSF1 in estrogen receptor (ER)-positive breast cancer patients correlated with a worse prognosis. Here we demonstrated that 17β-estradiol (E2), as well as xenoestrogen bisphenol A and ERα agonist propyl pyrazole triol, led to HSF1 phosphorylation on S326 in ERα positive but not in ERα-negative mammary breast cancer cells. Furthermore, we showed that MAPK signaling (via MEK1/2) but not mTOR signaling was involved in E2/ERα-dependent activation of HSF1. E2­activated HSF1 was transcriptionally potent and several genes essential for breast cancer cells growth and/or ERα action, including HSPB8, LHX4, PRKCE, WWC1, and GREB1, were activated by E2 in a HSF1-dependent manner. Our findings suggest a hypothetical positive feedback loop between E2/ERα and HSF1 signaling, which may support the growth of estrogen-dependent tumors.
Expression of Irisin/FNDC5 in Cancer Cells and Stromal Fibroblasts of Non-Small Cell Lung Cancer
Authors: Nowinska Katarzyna , Jablonska Karolina , Pawelczyk Konrad , Piotrowska Aleksandra , Partynska Aleksandra , Gomulkiewicz Agnieszka , Ciesielska Urszula , Katnik Ewa , Grzegrzolka Jedrzej , Glatzel-Plucinska Natalia , Ratajczak-Wielgomas Katarzyna , Podhorska-Okolow Marzenna , Dziegiel Piotr
Published: October 2019

Background: Recent in vitro studies have indicated that irisin inhibits proliferation, migration and epithelial-mesenchymal transition. Irisin expression has not been studied in tumour tissues of non-small cell lung cancer (NSCLC) patients yet. The aim of the study was to determine the irisin expression in NSCLCs in comparison to the clinicopathological factors and expression of TTF-1, p63 and Ki-67. Material and methods: Tissue microarrays with 729 NSCLC and 140 non-malignant lung tissue (NMLT) were used to perform immunohistochemical reactions. Laser Capture Microdissection (LCM) was used to collect cancer and stromal cells from NSCLCs. FNDC5 expression was tested for LCM samples, 75 NSCLCs and 25 NMLTs with the RT-PCR technique. Western-blot, immunofluorescence reaction and RT-PCR assays were performed on lung cancer cell lines. Results: Irisin expression was observed in NSCLC cancer cells and stromal fibroblasts. In cancer cells, irisin expression was decreased in higher grades (G) of malignancy, tumour size (T) and according to lymph node metastasis. In stromal cells, irisin expression was increased in higher G and advanced T. A shorter overall survival was observed in patients with higher irisin expression in NSCLC stromal cells. Conclusions: Irisin expression in stromal fibroblasts may influence cancer cell proliferation and may be a prognostic factor for survival in NSCLC.
Enantioselective Mannich Reaction Promoted by Chiral Phosphinoyl-Aziridines
Authors: Buchcic Aleksandra , Zawisza Anna , Leśniak Stanisław , Adamczyk Justyna , Pieczonka Adam Marek , Rachwalski Michał
Published: October 2019

In this study, a set of enantiomerically pure aziridines bearing a phosphine oxide moiety were prepared in high yields and tested as chiral catalysts in the direct asymmetric Mannich reaction of hydroxyacetone, an amine (p-anisidine), and various aromatic aldehydes. The appropriate Mannich adducts were formed in chemical yields from moderate to good with a high level of enantio- and diastereoselectivity. The best results were obtained using the catalysts bearing a free NH-aziridine subunit.
Ga/HZSM-5 Catalysed Acetic Acid Ketonisation for Upgrading of Biomass Pyrolysis Vapours
Authors: Jahangiri Hessam , Osatiashtiani Amin , Ouadi Miloud , Hornung Andreas , Lee Adam F. , Wilson Karen
Published: October 2019

Pyrolysis bio-oils contain significant amounts of carboxylic acids which limit their utility as biofuels. Ketonisation of carboxylic acids within biomass pyrolysis vapours is a potential route to upgrade the energy content and stability of the resulting bio-oil condensate, but requires active, selective and coke-resistant solid acid catalysts. Here we explore the vapour phase ketonisation of acetic acid over Ga-doped HZSM-5. Weak Lewis acid sites were identified as the active species responsible for acetic acid ketonisation to acetone at 350 °C and 400 °C. Turnover frequencies were proportional to Ga loading, reaching ~6 min−1 at 400 °C for 10Ga/HZSM-5. Selectivity to the desired acetone product correlated with the weak:strong acid site ratio, being favoured over weak Lewis acid sites and reaching 30% for 10Ga/HZSM-5. Strong Brønsted acidity promoted competing unselective reactions and carbon laydown. 10Ga/HZSM-5 exhibited good stability for over 5 h on-stream acetic acid ketonisation.
The Glucocorticoid Receptor in Cardiovascular Health and Disease
Authors: Liu Bing , Zhang Tie-Ning , Knight Jessica K. , Goodwin Julie E.
Published: October 2019

The glucocorticoid receptor is a member of the nuclear receptor family that controls many distinct gene networks, governing various aspects of development, metabolism, inflammation, and the stress response, as well as other key biological processes in the cardiovascular system. Recently, research in both animal models and humans has begun to unravel the profound complexity of glucocorticoid signaling and convincingly demonstrates that the glucocorticoid receptor has direct effects on the heart and vessels in vivo and in vitro. This research has contributed directly to improving therapeutic strategies in human disease. The glucocorticoid receptor is activated either by the endogenous steroid hormone cortisol or by exogenous glucocorticoids and acts within the cardiovascular system via both genomic and non-genomic pathways. Polymorphisms of the glucocorticoid receptor are also reported to influence the progress and prognosis of cardiovascular disease. In this review, we provide an update on glucocorticoid signaling and highlight the critical role of this signaling in both physiological and pathological conditions of the cardiovascular system. With increasing in-depth understanding of glucocorticoid signaling, the future is promising for the development of targeted glucocorticoid treatments and improved clinical outcomes.
The cGAS Paradox: Contrasting Roles for cGAS-STING Pathway in Chromosomal Instability
Authors: Hong Christy , Tijhuis Andrea E. , Foijer Floris
Published: October 2019

Chromosomal instability (CIN) is an intricate phenomenon that is often found in human cancer, characterized by persisting errors in chromosome segregation. This ongoing chromosome mis-segregation results in structural and numerical chromosomal abnormalities that have been widely described to promote tumor evolution. In addition to being a driver of tumor evolution, recent evidence demonstrates CIN to be the central node of the crosstalk between a tumor and its surrounding microenvironment, as mediated by the cGAS-STING pathway. The role that cGAS-STING signaling exerts on CIN tumors is both complex and paradoxical. On one hand, the cGAS-STING axis promotes the clearance of CIN tumors through recruitment of immune cells, thus suppressing tumor progression. On the other hand, the cGAS-STING pathway has been described to be the major regulator in the promotion of metastasis of CIN tumors. Here, we review this dual role of the cGAS-STING pathway in the context of chromosomal instability and discuss the potential therapeutic implications of cGAS-STING signaling for targeting CIN tumors.
Systemic Metabolomic Profiling of Acute Myeloid Leukemia Patients before and During Disease-Stabilizing Treatment Based on All-Trans Retinoic Acid, Valproic Acid, and Low-Dose Chemotherapy
Authors: Grønningsæter Ida Sofie , Fredly Hanne Kristin , Gjertsen Bjørn Tore , Hatfield Kimberley Joanne , Bruserud Øystein
Published: October 2019

Acute myeloid leukemia (AML) is an aggressive malignancy, and many elderly/unfit patients cannot receive intensive and potentially curative therapy. These patients receive low-toxicity disease-stabilizing treatment. The combination of all-trans retinoic acid (ATRA) and the histone deacetylase inhibitor valproic acid can stabilize the disease for a subset of such patients. We performed untargeted serum metabolomic profiling for 44 AML patients receiving treatment based on ATRA and valproic acid combined with low-dose cytotoxic drugs (cytarabine, hydroxyurea, 6-mercaptopurin) which identified 886 metabolites. When comparing pretreatment samples from responders and non-responders, metabolites mainly belonging to amino acid and lipid (i.e., fatty acid) pathways were altered. Furthermore, patients with rapidly progressive disease showed an extensively altered lipid metabolism. Both ATRA and valproic acid monotherapy also altered the amino acid and lipid metabolite profiles; however, these changes were only highly significant for valproic acid treatment. Twenty-three metabolites were significantly altered by seven-day valproic acid treatment (p < 0.05, q < 0.05), where the majority of altered metabolites belonged to lipid (especially fatty acid metabolism) and amino acid pathways, including several carnitines. These metabolomic effects, and especially the effects on lipid metabolism, may be important for the antileukemic and epigenetic effects of this treatment.
Emerging Approaches to Investigate the Influence of Transition Metals in the Proteinopathies
Authors: Lermyte Frederik , Everett James , Brooks Jake , Bellingeri Francesca , Billimoria Kharmen , Sadler Peter J. , O’Connor Peter B. , Telling Neil D. , Collingwood Joanna F.
Published: October 2019

Transition metals have essential roles in brain structure and function, and are associated with pathological processes in neurodegenerative disorders classed as proteinopathies. Synchrotron X-ray techniques, coupled with ultrahigh-resolution mass spectrometry, have been applied to study iron and copper interactions with amyloid β (1–42) or α-synuclein. Ex vivo tissue and in vitro systems were investigated, showing the capability to identify metal oxidation states, probe local chemical environments, and localize metal-peptide binding sites. Synchrotron experiments showed that the chemical reduction of ferric (Fe3+) iron and cupric (Cu2+) copper can occur in vitro after incubating each metal in the presence of Aβ for one week, and to a lesser extent for ferric iron incubated with α-syn. Nanoscale chemical speciation mapping of Aβ-Fe complexes revealed a spatial heterogeneity in chemical reduction of iron within individual aggregates. Mass spectrometry allowed the determination of the highest-affinity binding region in all four metal-biomolecule complexes. Iron and copper were coordinated by the same N-terminal region of Aβ, likely through histidine residues. Fe3+ bound to a C-terminal region of α-syn, rich in aspartic and glutamic acid residues, and Cu2+ to the N-terminal region of α-syn. Elucidating the biochemistry of these metal-biomolecule complexes and identifying drivers of chemical reduction processes for which there is evidence ex-vivo, are critical to the advanced understanding of disease aetiology.
C9orf72 Proteins Regulate Autophagy and Undergo Autophagosomal or Proteasomal Degradation in a Cell Type-Dependent Manner
Authors: Leskelä Stina , Huber Nadine , Rostalski Hannah , Natunen Teemu , Remes Anne M. , Takalo Mari , Hiltunen Mikko , Haapasalo Annakaisa
Published: October 2019

Dysfunctional autophagy or ubiquitin-proteasome system (UPS) are suggested to underlie abnormal protein aggregation in neurodegenerative diseases. Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS)-associated C9orf72 is implicated in autophagy, but whether it activates or inhibits autophagy is partially controversial. Here, we utilized knockdown or overexpression of C9orf72 in mouse N2a neuroblastoma cells or cultured neurons to elucidate the potential role of C9orf72 proteins in autophagy and UPS. Induction of autophagy in C9orf72 knockdown N2a cells led to decreased LC3BI to LC3BII conversion, p62 degradation, and formation of LC3-containing autophagosomes, suggesting compromised autophagy. Proteasomal activity was slightly decreased. No changes in autophagy nor proteasomal activity in C9orf72-overexpressing N2a cells were observed. However, in these cells, autophagy induction by serum starvation or rapamycin led to significantly decreased C9orf72 levels. The decreased levels of C9orf72 in serum-starved N2a cells were restored by the proteasomal inhibitor lactacystin, but not by the autophagy inhibitor bafilomycin A1 (BafA1) treatment. These data suggest that C9orf72 undergoes proteasomal degradation in N2a cells during autophagy. Lactacystin significantly elevated C9orf72 levels in N2a cells and neurons, further suggesting UPS-mediated regulation. In rapamycin and BafA1-treated neurons, C9orf72 levels were significantly increased. Altogether, these findings corroborate the previously suggested regulatory role for C9orf72 in autophagy and suggest cell type-dependent regulation of C9orf72 levels via UPS and/or autophagy.
Contextual Regulation of TGF-β Signaling in Liver Cancer
Authors: Tu Shuo , Huang Wei , Huang Chunhong , Luo Zhijun , Yan Xiaohua
Published: October 2019

Primary liver cancer is one of the leading causes for cancer-related death worldwide. Transforming growth factor beta (TGF-β) is a pleiotropic cytokine that signals through membrane receptors and intracellular Smad proteins, which enter the nucleus upon receptor activation and act as transcription factors. TGF-β inhibits liver tumorigenesis in the early stage by inducing cytostasis and apoptosis, but promotes malignant progression in more advanced stages by enhancing cancer cell survival, EMT, migration, invasion and finally metastasis. Understanding the molecular mechanisms underpinning the multi-faceted roles of TGF-β in liver cancer has become a persistent pursuit during the last two decades. Contextual regulation fine-tunes the robustness, duration and plasticity of TGF-β signaling, yielding versatile albeit specific responses. This involves multiple feedback and feed-forward regulatory loops and also the interplay between Smad signaling and non-Smad pathways. This review summarizes the known regulatory mechanisms of TGF-β signaling in liver cancer, and how they channel, skew and even switch the actions of TGF-β during cancer progression.
From OPC to Oligodendrocyte: An Epigenetic Journey
Authors: Tiane Assia , Schepers Melissa , Rombaut Ben , Hupperts Raymond , Prickaerts Jos , Hellings Niels , van den Hove Daniel , Vanmierlo Tim
Published: October 2019

Oligodendrocytes provide metabolic and functional support to neuronal cells, rendering them key players in the functioning of the central nervous system. Oligodendrocytes need to be newly formed from a pool of oligodendrocyte precursor cells (OPCs). The differentiation of OPCs into mature and myelinating cells is a multistep process, tightly controlled by spatiotemporal activation and repression of specific growth and transcription factors. While oligodendrocyte turnover is rather slow under physiological conditions, a disruption in this balanced differentiation process, for example in case of a differentiation block, could have devastating consequences during ageing and in pathological conditions, such as multiple sclerosis. Over the recent years, increasing evidence has shown that epigenetic mechanisms, such as DNA methylation, histone modifications, and microRNAs, are major contributors to OPC differentiation. In this review, we discuss how these epigenetic mechanisms orchestrate and influence oligodendrocyte maturation. These insights are a crucial starting point for studies that aim to identify the contribution of epigenetics in demyelinating diseases and may thus provide new therapeutic targets to induce myelin repair in the long run.
Cell Cycle Arrest by Supraoptimal Temperature in the Alga Chlamydomonas reinhardtii
Authors: Zachleder Vilém , Ivanov Ivan , Vítová Milada , Bišová Kateřina
Published: October 2019

Temperature is one of the key factors affecting growth and division of algal cells. High temperature inhibits the cell cycle in Chlamydomonas reinhardtii. At 39 °C, nuclear and cellular divisions in synchronized cultures were blocked completely, while DNA replication was partly affected. In contrast, growth (cell volume, dry matter, total protein, and RNA) remained unaffected, and starch accumulated at very high levels. The cell cycle arrest could be removed by transfer to 30 °C, but a full recovery occurred only in cultures cultivated up to 14 h at 39 °C. Thereafter, individual cell cycle processes began to be affected in sequence; daughter cell release, cell division, and DNA replication. Cell cycle arrest was accompanied by high mitotic cyclin-dependent kinase activity that decreased after completion of nuclear and cellular division following transfer to 30 °C. Cell cycle arrest was, therefore, not caused by a lack of cyclin-dependent kinase activity but rather a blockage in downstream processes.
Graphene–Gold Nanostructures Hybrid Composites Screen-Printed Electrode for the Sensitive Electrochemical Detection of Vancomycin
Authors: Blidar Adrian , Feier Bogdan , Pusta Alexandra , Drăgan Ana-Maria , Cristea Cecilia
Published: October 2019

The most important and well-known glycopeptide antibiotic, vancomycin (VAN), is used for the treatment of severe bacterial infections like methicillin-resistant staphylococcal infections and endocarditis caused by enterococci and sepsis. Taking into account the problem of the development of antibiotic resistance as well as its toxicity, both correlated with the VAN concentration (CVAN) in biological samples, there is need for better and more accessible quantification methods for this antibiotic. Considering all of the above, herein, we present a simple electrochemical method for VAN sensing based on a hybrid graphene-gold nanostructure nanocomposite electrode, which allows double detection directly in the oxidation domain and also indirectly, in reduction, using the electro-active gold nanostructures as a probe to monitor the current changing due to the interaction between gold and VAN. The developed method was able to successfully detect VAN in the linear range of 1–100 µM with a limit of detection (LOD) of 0.29 µM for the direct approach and 0.5 µM for the indirect one. The selectivity of the method was tested in the presence of other antibiotics and drugs. This method was successfully applied for the detection of VAN from human serum samples.
Fingerprint Blurring on a Hierarchical Nanoporous Layer Glass
Authors: Tabata Erika , Ito Takumi , Ushioda Yuki , Fujima Takuya
Published: October 2019

A fingerprint blurring phenomenon on a hierarchical nanoporous layer (HNL) glass has been discovered and experimentally investigated. The HNL glass was prepared by a simple one-pot etching as reported by the authors. IR absorption spectra and water contact angle revealed that the blurring does not come from a chemical decomposition but a transportation of the fingerprint components, and the capillary action drives the transportation, not the thermal diffusion. The fine pores in the HNL was indicated to develop the strong capillary force to blur the fingerprint. The fingerprint blurring phenomenon on the HNL can be a candidate for the third anti-fingerprint methodology after the popular ones of low frictional surfaces and anti-glare surfaces.
Nanoengineered Antibacterial Coatings and Materials: A Perspective
Authors: Vasilev Krasimir
Published: October 2019

This feature article begins by outlining the problem of infection and its implication on healthcare. The initial introductory section is followed by a description of the four distinct classes of antibacterial coatings and materials, i.e., bacteria repealing, contact killing, releasing and responsive, that were developed over the years by our team and others. Specific examples of each individual class of antibacterial materials and a discussion on the pros and cons of each strategy are provided. The article contains a dedicated section focused on silver nanoparticle based coatings and materials, which have attracted tremendous interest from the scientific and medical communities. The article concludes with the author’s view regarding the future of the field.