bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of Two Nrf2 Activators, Bardoxolone Methyl and Omaveloxolone, on Retinal Ganglion Cell Survival during Ischemic Optic Neuropathy
Authors: Chien Jia-Ying , Chou Yu-Yau , Ciou Jhih-Wei , Liu Fang-Yun , Huang Shun-Ping
Published: September 2021

Nonarteritic anterior ischemic optic neuropathy (NAION) is one of the most common acute optic neuropathies that affect the over 55-year-old population. NAION causes the loss of visual function, and it has no safe and effective therapy. Bardoxolone methyl (methyl 2-cyano-3,12-dioxooleana-1,9(11)-dien-28-oate; CDDO-Me; RTA 402) is a semisynthetic triterpenoid with effects against antioxidative stress and inflammation in neurodegeneration and kidney disease that activates the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway. Moreover, RTA 402 is an FDA-approved compound for the treatment of solid tumors, lymphoid malignancies, melanoma, and chronic kidney disease. Omaveloxolone (RTA 408) is an activator of Nrf2 and an inhibitor of NFκB, possessing antioxidative and anti-inflammatory activities in mitochondrial bioenergetics. RTA 408 is also under clinical investigation for Friedreich ataxia (FA). In this study, a rodent anterior ischemic optic neuropathy (rAION) model induced by photothrombosis was used to examine the therapeutic effects of RTA 402 and RTA 408. Treatment with RTA402 results in antiapoptotic, antioxidative stress, anti-inflammatory, and myelin-preserving effects on retinal ganglion cell (RGC) survival and visual function via regulation of NQO1 and HO-1, reduced IL-6 and Iba1 expression in macrophages, and promoted microglial expression of TGF-β and Ym1 + 2 in the retina and optic nerve. However, these effects were not observed after RTA 408 treatment. Our results provide explicit evidence that RTA 402 modulates the Nrf2 and NFκB signaling pathways to protect RGCs from apoptosis and maintain the visual function in an rAION model. These findings indicate that RTA 402 may a potential therapeutic agent for ischemic optic neuropathy.
Kinetic Studies of Antioxidant Properties of Ovothiol A
Authors: Osik Nataliya A. , Zelentsova Ekaterina A. , Tsentalovich Yuri P.
Published: September 2021

Ovothiol A (OSH) is one of the strongest natural antioxidants. So far, its presence was found in tissues of marine invertebrates, algae and fish. Due to very low pKa value of the SH group, under physiological conditions, this compound is almost entirely present in chemically active thiolate form and reacts with ROS and radicals significantly faster than other natural thiols. In biological systems, OSH acts in tandem with glutathione GSH, with OSH neutralizing oxidants and GSH maintaining ovothiol in the reduced state. In the present work, we report the rate constants of OSH oxidation by H2O2 and of reduction of oxidized ovothiol OSSO by GSH and we estimate the Arrhenius parameters for these rate constants. The absorption spectra of reaction intermediates, adduct OSSG and sulfenic acid OSOH, were obtained. We also found that OSH effectively quenches the triplet state of kynurenic acid with an almost diffusion-controlled rate constant. This finding indicates that OSH may serve as a good photoprotector to inhibit the deleterious effect of solar UV irradiation; this assumption explains the high concentrations of OSH in the fish lens. The unique antioxidant and photoprotecting properties of OSH open promising perspectives for its use in the treatment of human diseases.
Probabilistic Moment Capacity Models of Reinforced Concrete Slab Members for Underground Box Culverts
Authors: Kim Sang-Hyo , Boldoo Tuguldur , Kim Dae-Yoon , Chu Inyeop , Woo Sang-Kyun
Published: September 2021

This study was performed to evaluate the probabilistic characteristics of the flexural strength of reinforced concrete (RC) flexural members adopted for underground box culverts. These probabilistic models were developed to be adopted for the development of limit state load combination formats for underground RC box culverts. The probabilistic models of uncertainties inherent in the basic design variables were developed to evaluate flexural strength using field material test data as well as field survey data collected from various domestic construction sites of underground box culverts in Korea. The basic design variables include concrete strength, steel rebar strength, and section dimensions, such as slab thickness and rebar locations. Some design variables are assumed to have inherent construction error characteristics, which may be different from those inherent in the RC members for buildings and bridges. The bias models on flexural strength were evaluated based on the experimental results of four-point flexural tests on one-way RC slabs, which were fabricated following the general practice adopted in the local underground box culvert construction process. Based on the probabilistic models of basic design variables, as well as the bias models of flexural strength, Monte Carlo simulations were performed to examine the probabilistic characteristics of both ultimate flexural strength and yield moment strength of RC slab members. Some sensitivity analyses were performed to confirm the soundness of various probability models and the assumptions adopted in the development procedure. The proposed procedure may be applied to develop probabilistic resistance models for structural members, in which the construction error characteristics are assumed to be different from other practices.
Reality Check: Experimental Studies on Microplastics Lack Realism
Authors: Weis Judith S. , Palmquist Karl H.
Published: September 2021

Environmental microplastics are gaining interest due to their ubiquity and the threat they pose to environmental and human health. Critical studies have revealed the abundance of microplastics in nature, while others have tested the impacts of these small plastics on organismal health in the laboratory. Yet, there is often a mismatch between these two areas of research, resulting in major discrepancies and an inability to interpret certain findings. Here, we focus on several main lines of inquiry. First, even though the majority of environmental microplastics are plastic microfibers from textiles, laboratory studies still largely use spherical microbeads. There are also inconsistencies between the measurements of microplastics in the environment as compared to the concentrations that tend to be used in experimental studies. Likewise, the period of exposure occurring in experimental studies and in the environment are vastly different. Lastly, although experimental studies often focus on a particular subset of toxic chemicals present on microplastics, textile microfibers carry other dyes and chemicals that are understudied. They also cause types of physical damage not associated with microspheres. This review will analyze the literature pertaining to these mismatches, focusing on aquatic organisms and model systems, and seek to inform a path forward for this burgeoning area of research.
Soft Computing Paradigms to Find the Numerical Solutions of a Nonlinear Influenza Disease Model
Authors: Sabir Zulqurnain , Ag Ibrahim Ag Asri , Raja Muhammad Asif Zahoor , Nisar Kashif , Umar Muhammad , Rodrigues Joel J. P. C. , Mahmoud Samy R.
Published: September 2021

The aim of this work is to present the numerical results of the influenza disease nonlinear system using the feed forward artificial neural networks (ANNs) along with the optimization of the combination of global and local search schemes. The genetic algorithm (GA) and active-set method (ASM), i.e., GA-ASM, are implemented as global and local search schemes. The mathematical nonlinear influenza disease system is dependent of four classes, susceptible S(u), infected I(u), recovered R(u) and cross-immune individuals C(u). For the solutions of these classes based on influenza disease system, the design of an objective function is presented using these differential system equations and its corresponding initial conditions. The optimization of this objective function is using the hybrid computing combination of GA-ASM for solving all classes of the influenza disease nonlinear system. The obtained numerical results will be compared by the Adams numerical results to check the authenticity of the designed ANN-GA-ASM. In addition, the designed approach through statistical based operators shows the consistency and stability for solving the influenza disease nonlinear system.
Targeting Antigen-Presenting Cells in Multiple Sclerosis Treatment
Authors: Szpakowski Piotr , Ksiazek-Winiarek Dominika , Glabinski Andrzej
Published: September 2021

Multiple sclerosis (MS) is common neurological disease of the central nervous system (CNS) affecting mostly young adults. Despite decades of studies, its etiology and pathogenesis are not fully unraveled and treatment is still insufficient. The vast majority of studies suggest that the immune system plays a major role in MS development. This is also supported by the effectiveness of currently available MS treatments that target immunocompetent cells. In this review, the role of antigen-presenting cells (APC) in MS development as well as the novel therapeutic options targeting those cells in MS are presented. It is known that in MS, peripheral self-antigen-specific immune cells are activated during antigen presentation process and they enter the CNS through the disrupted blood–brain barrier (BBB). Myelin-reactive CD4+ T-cells can be activated by dendritic cells, infiltrating macrophages, microglia cells, or B-cells, which all express MHC class II molecules. There are also suggestions that brain endothelial cells may act as non-professional APCs and present myelin-specific antigens with MHC class II. Similarly, astrocytes, the major glial cells in the CNS, were shown to act as non-professional APCs presenting myelin antigens to autoreactive T-cells. Several currently available MS drugs such as natalizumab, fingolimod, alemtuzumab, and ocrelizumab may modulate antigen presentation in MS. Another way to use this mechanism in MS treatment may be the usage of specific tolerogenic dendritic cells or the induction of tolerance to myelin antigens by peptide vaccines.
Multiservice Loss Models in Single or Multi-Cluster C-RAN Supporting Quasi-Random Traffic
Authors: Chousainov Iskanter-Alexandros , Moscholios Ioannis , Sarigiannidis Panagiotis , Logothetis Michael
Published: September 2021

In this paper, a cloud radio access network (C-RAN) is considered where the baseband units form a pool of computational resource units and are separated from the remote radio heads (RRHs). Based on their radio capacity, the RRHs may form one or many clusters: a single cluster when all RRHs have the same capacity and multi-clusters where RRHs of the same radio capacity are grouped in the same cluster. Each RRH services the so-called multiservice traffic, i.e., calls from many service classes with various radio and computational resource requirements. Calls arrive in the RRHs according to a quasi-random process. This means that new calls are generated by a finite number of mobile users. Arriving calls require simultaneously computational and radio resource units in order to be accepted in the system, i.e., in the serving RRH. If their requirements are met, then these calls are served in the (serving) RRH for a service time which is generally distributed. Otherwise, call blocking occurs. We start with the single-cluster C-RAN and model it as a multiservice loss system, prove that the model has a product form solution, and determine time congestion probabilities via a convolution algorithm whose accuracy is validated with the aid of simulation. Furthermore, the previous model is generalized to include the more complex case of more than one clusters.
Investigation of Dispersion, Interfacial Adhesion of Isotropic and Anisotropic Filler in Polymer Composite
Authors: Samal Sneha , Blanco Ignazio
Published: September 2021

The movement of isotropic and anisotropic particles of iron and graphite within the polymer matrix was predicted and examined by the COMSOL simulation method. The interfacial adhesion of filler particles within the matrix was investigated under surface features observation. Carbonyl Iron (CI) particles, considered to be regular with a uniform size of (1–5 µm), were mixed with irregular particles of graphite (20–150 µm) with 30 V% in quantity in a silicone rubber matrix. The particle–matrix and particle–particle interactions were analyzed from the inner surface features. The drag of non-spherical particles and particle Reynolds numbers (Rep) were taken into consideration in point force models for both the Stokes (Rep ≪ 1) and Newton regime for particle shape. Newton regime is based on the aspect ratio for particles with regular and irregular shapes. The boundary area of the irregular particles holds like an anchor inside the polymer matrix for strong adhesion; however, regular particles have partial attachment due to the gravitational pull of attraction from the bottom contact points. However, uniform distribution of isotropic particles has been observed in comparison to the anisotropic particles within the polymer matrix.
Artificial Intelligence Marketing (AIM) for Enhancing Customer Relationships
Authors: Yau Kok-Lim Alvin , Saad Norizan Mat , Chong Yung-Wey
Published: September 2021

Based on the literature, we present an artificial intelligence marketing (AIM) framework that enables autonomous machines to receive big data and information, use artificial intelligence (AI) to create knowledge, and then disseminate and apply the knowledge to enhance customer relationships in a knowledge-based environment. To develop the AIM framework, we bring together and curate a wide range of relevant literatures including real-life examples and cases, and then understand how these literatures contribute to the framework in this research topic. We explain the AIM framework from the interdisciplinary perspective, which is an important role of both the artificial intelligence and marketing academia. The AIM framework includes three main components, including the pre-processor, the main processor, and the memory storage. The main processor, which is the key component, uses AI to process structured data processed by pre-processor in order to make real-time decisions and reasonings. The AI approach is characterized by its hypothetical abilities, learning paradigms, and operation modes with human. The strategic use of the developed AIM framework based on the literature to enhance customer relationships, including customer trust, satisfaction, commitment, engagement, and loyalty, is presented. Finally, future potential investigations are presented to drive forward this interdisciplinary research topic.
Efficacy and Toxicity of VarroMed® Used for Controlling Varroa destructor Infestation in Different Seasons and Geographical Areas
Authors: Smodiš Škerl Maja Ivana , Rivera-Gomis Jorge , Tlak Gajger Ivana , Bubnič Jernej , Talakić Gabriela , Formato Giovanni , Baggio Alessandra , Mutinelli Franco , Tollenaers Wim , Laget Dries , Malagnini Valeria , Zanotelli Livia , Pietropaoli Marco
Published: September 2021

VarroMed® is a soft acaricide registered for honey bees on the European Union market since 2017 for Varroa control. Researchers involved were partners of different countries of the Varroa control task force of the COLOSS Association. Our goal was to evaluate performances (acaricide efficacy and toxic effects on honey bees) of VarroMed® in different climatic conditions. Our results in the tested apiaries showed an efficacy ranging from 71.2 to 89.3% in summer/autumn, and from 71.8 to 95.6% in winter. No toxic effects on bees were observed, except in one apiary, where severe cold climatic conditions played a crucial role. The treatment could be efficiently applied in broodright as well as in broodless colonies. Integrated pest management (IPM) recommendations for beekeepers are provided in order to apply the best Varroa control protocol.
2D Solid-State HETCOR 1H-13C NMR Experiments with Variable Cross Polarization Times as a Tool for a Better Understanding of the Chemistry of Cellulose-Based Pyrochars—A Tutorial
Authors: Knicker Heike , Velasco-Molina Marta , Knicker Michael
Published: September 2021

The chemistry and nature of biochars are still far from being well understood. In the present work, solid-state 2D HETCOR 1H-13C NMR spectroscopy is introduced for an improved characterization of the aromatic network in biochars. To that end, a pyrochar obtained from the pyrolysis of cellulose at 350 °C for 1 h was used as an example. Variation of the contact time during cross polarization from 50 µs, to 200 µs and 1000 µs gave information about the protonation degree of the different C groups and their interactions. We demonstrated that carbohydrates did not survive the used pyrolysis conditions. Therefore, O-alkyl C was assigned to ethers. Phenols were not identified to a higher extent suggesting that furan and benzofuran-type units determine the O-functionality of the aromatic domains. The latter are directly connected to alkyl chains. Those features are expected to affect chemical but also physical properties of the biochar. Based on our results, we developed a new concept describing the nature of the aromatic network in the studied cellulose-based pyrochars. The latter contrasts common views about the chemical nature of biochar, possibly because pyrolysis temperatures > 350 °C are required for achieving advanced condensation of the aromatic domains.
Hybrid Representation of Sensor Data for the Classification of Driving Behaviour
Authors: Savelonas Michalis , Vernikos Ioannis , Mantzekis Dimitris , Spyrou Evaggelos , Tsakiri Athanasia , Karkanis Stavros
Published: September 2021

Monitoring driving behaviour is important in controlling driving risk, fuel consumption, and CO2 emissions. Recent advances in machine learning, which include several variants of convolutional neural networks (CNNs), and recurrent neural networks (RNNs), such as long short-term memory (LSTM) and gated recurrent unit (GRU) networks, could be valuable for the development of objective and efficient computational tools in this direction. The main idea in this work is to complement data-driven classification of driving behaviour with rules derived from domain knowledge. In this light, we present a hybrid representation approach, which employs NN-based time-series encoding and rule-guided event detection. Histograms derived from the output of these two components are concatenated, normalized, and used to train a standard support vector machine (SVM). For the NN-based component, CNN-based, LSTM-based, and GRU-based variants are investigated. The CNN-based variant uses image-like representations of sensor measurements, whereas the RNN-based variants (LSTM and GRU) directly process sensor measurements in the form of time-series. Experimental evaluation on three datasets leads to the conclusion that the proposed approach outperforms a state-of-the-art camera-based approaches in distinguishing between normal and aggressive driving behaviour without using data derived from a camera. Moreover, it is demonstrated that both NN-guided time-series encoding and rule-guided event detection contribute to overall classification accuracy.
Automatic Hate Speech Detection in English-Odia Code Mixed Social Media Data Using Machine Learning Techniques
Authors: Mohapatra Sudhir Kumar , Prasad Srinivas , Bebarta Dwiti Krishna , Das Tapan Kumar , Srinivasan Kathiravan , Hu Yuh-Chung
Published: September 2021

Hate speech on social media may spread quickly through online users and subsequently, may even escalate into local vile violence and heinous crimes. This paper proposes a hate speech detection model by means of machine learning and text mining feature extraction techniques. In this study, the authors collected the hate speech of English-Odia code mixed data from a Facebook public page and manually organized them into three classes. In order to build binary and ternary datasets, the data are further converted into binary classes. The modeling of hate speech employs the combination of a machine learning algorithm and features extraction. Support vector machine (SVM), naïve Bayes (NB) and random forest (RF) models were trained using the whole dataset, with the extracted feature based on word unigram, bigram, trigram, combined n-grams, term frequency-inverse document frequency (TF-IDF), combined n-grams weighted by TF-IDF and word2vec for both the datasets. Using the two datasets, we developed two kinds of models with each feature—binary models and ternary models. The models based on SVM with word2vec achieved better performance than the NB and RF models for both the binary and ternary categories. The result reveals that the ternary models achieved less confusion between hate and non-hate speech than the binary models.
Driving Factors of Energy Consumption in the Developed Regions of Developing Countries: A Case of Zhejiang Province, China
Authors: Qing Ganghua , Luo Yifan , Huang Weiwei , Wang Wanjue , Yue Zijing , Wang Jie , Li Qingyi , Jiang Shuhan , Sun Shien
Published: September 2021

Regional energy development and approaches are significant for China’s overall economic and social development. The GDP in Zhejiang province surpassed 6 trillion yuan in 2019, and its energy consumption reached 200 million tons of standard coal (tce), both of which are at the forefront of China. In order to explore the main factors of the increase in energy consumption in Zhejiang and provide essential references for energy saving and other provinces, this paper analyzes the total energy consumption and industrial sectors on the basis of the logarithmic mean divisia index (LMDI) model. Study results show that the economy’s scale is the most crucial factor affecting Zhejiang’s energy consumption, with a significant growth effect. In 2015, the scale effect increased energy consumption to the highest value of 14 million tce and then reduced it to 13 million tce in 2019. The impact of the population on energy consumption increased by 10 million tce from 2010 to 2019. Energy intensity reduces energy consumption by between 0.05 and 0.15 billion tce per year, which is the main factor in reducing energy consumption. The energy structure generally plays a weak positive role due to the different energy types. The decomposition of the energy consumption per unit of value added in the industrial sector showed that the intensity and structural effect primarily reduce energy consumption, for example, the metal smelting and rolling, textile printing and paper, electric power, heating, and other industries. According to the results, enterprises should enhance the intelligence and efficiency of dispatch management and emergency responses. Zhejiang should also accelerate an international oil and gas trading center and resource allocation base to reach its carbon-neutrality goal.
Chaotic Dynamics by Some Quadratic Jerk Systems
Authors: Liu Mei , Sang Bo , Wang Ning , Ahmad Irfan
Published: September 2021

This paper is about the dynamical evolution of a family of chaotic jerk systems, which have different attractors for varying values of parameter a. By using Hopf bifurcation analysis, bifurcation diagrams, Lyapunov exponents, and cross sections, both self-excited and hidden attractors are explored. The self-exited chaotic attractors are found via a supercritical Hopf bifurcation and period-doubling cascades to chaos. The hidden chaotic attractors (related to a subcritical Hopf bifurcation, and with a unique stable equilibrium) are also found via period-doubling cascades to chaos. A circuit implementation is presented for the hidden chaotic attractor. The methods used in this paper will help understand and predict the chaotic dynamics of quadratic jerk systems.
Mathematical Modeling and Forecasting of COVID-19 in Saudi Arabia under Fractal-Fractional Derivative in Caputo Sense with Power-Law
Authors: Jeelani Mdi Begum , Alnahdi Abeer S. , Abdo Mohammed S. , Abdulwasaa Mansour A. , Shah Kamal , Wahash Hanan A.
Published: September 2021

This manuscript is devoted to investigating a fractional-order mathematical model of COVID-19. The corresponding derivative is taken in Caputo sense with power-law of fractional order μ and fractal dimension χ. We give some detailed analysis on the existence and uniqueness of the solution to the proposed problem. Furthermore, some results regarding basic reproduction number and stability are given. For the proposed theoretical analysis, we use fixed point theory while for numerical analysis fractional Adams–Bashforth iterative techniques are utilized. Using our numerical scheme is verified by using some real values of the parameters to plot the approximate solution to the considered model. Graphical presentations corresponding to different values of fractional order and fractal dimensions are given. Moreover, we provide some information regarding the real data of Saudi Arabia from 1 March 2020 till 22 April 2021, then calculated the fatality rates by utilizing the SPSS, Eviews and Expert Modeler procedure. We also built forecasts of infection for the period 23 April 2021 to 30 May 2021, with 95% confidence.
Temperatures Outside the Optimal Range for Helicobacter pylori Increase Its Harboring within Candida Yeast Cells
Authors: Sánchez-Alonzo Kimberly , Arellano-Arriagada Luciano , Castro-Seriche Susana , Parra-Sepúlveda Cristian , Bernasconi Humberto , Benavidez-Hernández Héctor , Campos Víctor L. , Sáez Katia , Smith Carlos T. , García-Cancino Apolinaria
Published: September 2021

Helicobacter pylori is capable of entering into yeast, but the factors driving this endosymbiosis remain unknown. This work aimed to determine if temperatures outside the optimal range for H. pylori increase its harboring within Candida. H. pylori strains were co-cultured with Candida strains in Brucella broth supplemented with 5% fetal bovine serum and incubated at 4, 25, 37 or 40 °C. After co-culturing, yeasts containing bacteria-like bodies (Y-BLBs) were observed by optical microscopy, and the bacterium were identified as H. pylori by FISH. The H. pylori 16S rRNA gene was amplified from the total DNA of Y-BLBs. The viability of intra-yeast H. pylori cells was confirmed using a viability assay. All H. pylori strains were capable of entering into all Candida strains assayed. The higher percentages of Y-BLBs are obtained at 40 °C with any of the Candida strains. H pylori also increased its harboring within yeast in co-cultures incubated at 25 °C when compared to those incubated at 37 °C. In conclusion, although H. pylori grew significantly at 40 °C, this temperature increased its harboring within Candida. The endosymbiosis between both microorganisms is strain-dependent and permits bacterial cells to remain viable under the stressing environmental conditions assayed.
Clinical Significance of the Head-Up Tilt Test in Improving Prognosis in Patients with Possible Neurally Mediated Syncope
Authors: Ayabe Kengo , Komiyama Tomoyoshi , Hasegawa Misaki , Sakai Tetsuri , Morise Masahiro , Sakama Susumu , Yagishita Atsuhiko , Amino Mari , Ikari Yuji , Yoshioka Koichiro
Published: September 2021

Syncope is commonly encountered in daily clinical practice. Depending on its etiology (benign or life-threatening conditions or environmental triggers), syncope can be neurally mediated (reflex), cardiac, or orthostatic. Furthermore, neurologic disease can cause symptoms that mimic syncope. However, there is limited research on neurally mediated syncope (NMS), which is considered a benign disorder, and close follow-ups are rarely performed. NMS can cause serious clinical events, including severe trauma and car accidents. The head-up tilt test (HUTT) is the gold standard for diagnosing NMS; however, its clinical significance remains unknown, and its relevance to NMS prognosis requires further research. This retrospective study aimed to assess the clinical significance of the HUTT for NMS. We reviewed the charts of 101 patients who underwent HUTT at Tokai University Hospital in Japan between January 2016 and March 2019. During the HUTT, 72 patients (69.2%) experienced syncope. Patients were followed up for 886.1 ± 457.7 days (interquartile range: 518–1293 days). The syncope recurrence rate was 16.9%; however, no significant difference was observed between the two groups (HUTT positive vs. negative) (13.8% vs. 18.1%, p = 0.772). Four of 29 (13.9%) and two of 72 (2.8%) patients in the negative and positive HUTT groups, respectively, experienced cardiac events (p = 0.019). Negative HUTT results may assist in anticipating unexpected clinical events within a few years. A negative HUTT result may allow us to reconsider the NMS diagnosis based on clinical information. Close outpatient follow-up of patients with negative HUTT results is warranted.
Evaluation of Immune Dysregulation in an Austrian Patient Cohort Suffering from Myalgic Encephalomyelitis/Chronic Fatigue Syndrome
Authors: Lutz Lena , Rohrhofer Johanna , Zehetmayer Sonja , Stingl Michael , Untersmayr Eva
Published: September 2021

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe multi-systemic disease characterized by debilitating fatigue that is not relieved by rest. The causes of the disease are still largely unexplained, and no causative treatment is currently available. Changes in the immune response are considered as fundamental in the development of ME/CFS. Thus, we aimed to evaluate the immunological profile of ME/CFS patients in a retrospective data analysis. As part of the routine workup for ME/CFS patients, a differential blood count, leukocyte subtyping, and quantification of immunoglobulins and IgG subclasses, as well as a complement analysis, was performed. Out of 262 ME/CFS patients, 64.9% had a reduction or deficiency in at least one of the listed immune parameters. In contrast, 26.3% showed signs of immune activation or inflammation. A total of 17.6% of the ME/CFS patients had an unclassified antibody deficiency, with IgG3 and IgG4 subclass deficiencies as the most common phenotypes. Reduced MBL (mannose-binding lectin) levels were found in 32% of ME/CFS patients, and MBL deficiency in 7%. In summary, the present results confirmed the relevance of immune dysfunction in ME/CFS patients underlining the involvement of a dysfunctional immune response in the disease. Thus, immune parameters are relevant disease biomarkers, which might lead to targeted therapeutic approaches in the future.
CDR1 Composition Can Affect Nanobody Recombinant Expression Yields
Authors: Orlando Marco , Fortuna Sara , Oloketuyi Sandra , Bajc Gregor , Goldenzweig Adi , de Marco Ario
Published: September 2021

The isolation of nanobodies from pre-immune libraries by means of biopanning is a straightforward process. Nevertheless, the recovered candidates often require optimization to improve some of their biophysical characteristics. In principle, CDRs are not mutated because they are likely to be part of the antibody paratope, but in this work, we describe a mutagenesis strategy that specifically addresses CDR1. Its sequence was identified as an instability hot spot by the PROSS program, and the available structural information indicated that four CDR1 residues bound directly to the antigen. We therefore modified the loop flexibility with the addition of an extra glycine rather than by mutating single amino acids. This approach significantly increased the nanobody yields but traded-off with moderate affinity loss. Accurate modeling coupled with atomistic molecular dynamics simulations enabled the modifications induced by the glycine insertion and the rationale behind the engineering design to be described in detail.
Development of High Affinity Calcitonin Analog Fragments Targeting Extracellular Domains of Calcitonin Family Receptors
Authors: Lee Sangmin
Published: September 2021

The calcitonin and amylin receptors (CTR and AMY receptors) are the drug targets for osteoporosis and diabetes treatment, respectively. Salmon calcitonin (sCT) and pramlintide were developed as peptide drugs that activate these receptors. However, next-generation drugs with improved receptor binding profiles are desirable for more effective pharmacotherapy. The extracellular domain (ECD) of CTR was reported as the critical binding site for the C-terminal half of sCT. For the screening of high-affinity sCT analog fragments, purified CTR ECD was used for fluorescence polarization/anisotropy peptide binding assay. When three mutations (N26D, S29P, and P32HYP) were introduced to the sCT(22–32) fragment, sCT(22–32) affinity for the CTR ECD was increased by 21-fold. CTR was reported to form a complex with receptor activity-modifying protein (RAMP), and the CTR:RAMP complexes function as amylin receptors with increased binding for the peptide hormone amylin. All three types of functional AMY receptor ECDs were prepared and tested for the binding of the mutated sCT(22–32). Interestingly, the mutated sCT(22–32) also retained its high affinity for all three types of the AMY receptor ECDs. In summary, the mutated sCT(22–32) showing high affinity for CTR and AMY receptor ECDs could be considered for developing the next-generation peptide agonists.
Association of Lipid Peroxidation Product 4-Hydroxynonenal with Post-Traumatic Stress Disorder
Authors: Perković Matea Nikolac , Milković Lidija , Uzun Suzana , Mimica Ninoslav , Pivac Nela , Waeg Georg , Žarković Neven
Published: September 2021

Repeated activation of the hypothalamic-pituitary-adrenal axis system, sleep disturbances, and other symptoms related to posttraumatic stress disorder (PTSD) elevate reactive oxygen species, increase inflammation, and accelerate cellular aging, leading to neuroprogression and cognitive decline. However, there is no information about possible involvement of 4-hydroxynonenal (4-HNE), the product of lipid peroxidation associated with stress-associated diseases, in the complex etiology of PTSD. Therefore, the aim of this study was to compare the plasma levels of 4-HNE between war veterans with PTSD (n = 62) and age-, sex- and ethnicity- matched healthy control subjects (n = 58) in order to evaluate the potential of HNE-modified proteins as blood-based biomarker of PTSD. The genuine 4-HNE-Enzyme-Linked Immunosorbent Assay (HNE-ELISA), based on monoclonal antibody specific for HNE-histidine (HNE-His) adducts, was used to determine plasma HNE-protein conjugates. Our results revealed significantly elevated levels of 4-HNE in patients with PTSD. Moreover, the accumulation of plasma 4-HNE seems to increase with aging but in a negative correlation with BMI, showing specific pattern of change for individuals diagnosed with PTSD. These findings suggest that oxidative stress and altered lipid metabolism reflected by increase of 4-HNE might be associated with PTSD. If confirmed with further studies, elevated 4-HNE plasma levels might serve as a potential biomarker of PTSD.
Complementary Effect of Non-Persistent Silver Nano-Architectures and Chlorhexidine on Infected Wound Healing
Authors: Pernakov Mykola , Ermini Maria Laura , Sulaieva Oksana , Cassano Domenico , Santucci Marco , Husak Yevhenia , Korniienko Viktoriia , Giannone Giulia , Yusupova Aziza , Liubchak Iryna , Hristova Maria Teodora , Savchenko Anton , Holubnycha Viktoriia , Voliani Valerio , Pogorielov Maksym
Published: September 2021

Surgical site infection (SSI) substantially contributes each year to patients’ morbidity and mortality, accounting for about 15% of all nosocomial infections. SSI drastically increases the rehab stint and expenses while jeopardizing health outcomes. Besides prevention, the treatment regime relies on an adequate antibiotic therapy. On the other hand, resistant bacterial strains have currently reached up to 34.3% of the total infections, and this percentage grows annually, reducing the efficacy of the common treatment schemes. Thus, new antibacterial strategies are urgently demanded. Here, we demonstrated in rats the effectiveness of non-persistent silver nano-architectures (AgNAs) in infected wound healing together with their synergistic action in combination with chlorhexidine. Besides the in vivo efficacy evaluation, we performed analysis of the bacteriological profile of purulent wound, histological evaluations, and macrophages polarization quantifications to further validate our findings and elucidate the possible mechanisms of AgNAs action on wound healing. These findings open the way for the composition of robust multifunctional nanoplatforms for the translation of safe and efficient topical treatments of SSI.
The Role of WAVE2 Signaling in Cancer
Authors: Rana Priyanka Shailendra , Alkrekshi Akram , Wang Wei , Markovic Vesna , Sossey-Alaoui Khalid
Published: September 2021

The Wiskott–Aldrich syndrome protein (WASP) and WASP family verprolin-homologous protein (WAVE)—WAVE1, WAVE2 and WAVE3 regulate rapid reorganization of cortical actin filaments and have been shown to form a key link between small GTPases and the actin cytoskeleton. Upon receiving upstream signals from Rho-family GTPases, the WASP and WAVE family proteins play a significant role in polymerization of actin cytoskeleton through activation of actin-related protein 2/3 complex (Arp2/3). The Arp2/3 complex, once activated, forms actin-based membrane protrusions essential for cell migration and cancer cell invasion. Thus, by activation of Arp2/3 complex, the WAVE and WASP family proteins, as part of the WAVE regulatory complex (WRC), have been shown to play a critical role in cancer cell invasion and metastasis, drawing significant research interest over recent years. Several studies have highlighted the potential for targeting the genes encoding either part of or a complete protein from the WASP/WAVE family as therapeutic strategies for preventing the invasion and metastasis of cancer cells. WAVE2 is well documented to be associated with the pathogenesis of several human cancers, including lung, liver, pancreatic, prostate, colorectal and breast cancer, as well as other hematologic malignancies. This review focuses mainly on the role of WAVE2 in the development, invasion and metastasis of different types of cancer. This review also summarizes the molecular mechanisms that regulate the activity of WAVE2, as well as those oncogenic pathways that are regulated by WAVE2 to promote the cancer phenotype. Finally, we discuss potential therapeutic strategies that target WAVE2 or the WAVE regulatory complex, aimed at preventing or inhibiting cancer invasion and metastasis.
The Need for New Biomarkers to Assist with Stroke Prevention and Prediction of Post-Stroke Therapy Based on Plasma-Derived Extracellular Vesicles
Authors: Driga Mircea Popescu , Catalin Bogdan , Olaru Denisa Greta , Slowik Agnieszka , Plesnila Nikolaus , Hermann Dirk M. , Popa-Wagner Aurel
Published: September 2021

The risk of having a stroke event doubles each decade after the age of 55. Therefore, it is of great interest to develop neurorestorative therapies of stroke which occurs mostly in elderly people. However, to date, patients at risk for these sequels of stroke are not duly diagnosed and treated due to the lack of reliable biomarkers. Extracellular vesicles (EVs) are lipid bilayer-delimited particles that are shed by the brain cells and are able to cross the blood–brain barrier and enter the blood stream; thus, they may be used to interrogate molecular and cellular events in the brain damaged area. In this review, we summarize the major molecular and cellular responses of astroglia and neurons to cerebral ischemia and assess their impact on post-stroke recovery and rehabilitation. In particular, we ask if EVs secreted by brain cells are responses to cerebral ischemia, and they may shed new light on the interplay between exosomes-mediated interactions between brain cells and the question of how to exploit it in order to predict the individual course of the disease and to introduce specific preventive or therapeutic strategies. Given these findings, we are left with two options: either to (i) transplant neuronal precursors into the damaged cortical area or (ii) to covert abundantly present proliferating astrocytes in the perilesional area into neurons by using recently developed genetic technologies. However, given the complexity of molecular and cellular responses to cerebral ischemia and our limited capabilities to restore brain structure and function, we are left with only one realistic aim: to invest more in prevention.
Insights into Mechanisms of Pheochromocytomas and Paragangliomas Driven by Known or New Genetic Drivers
Authors: Flores Shahida K. , Estrada-Zuniga Cynthia M. , Thallapureddy Keerthi , Armaiz-Peña Gustavo , Dahia Patricia L. M.
Published: September 2021

Pheochromocytomas and paragangliomas are rare tumors of neural crest origin. Their remarkable genetic diversity and high heritability have enabled discoveries of bona fide cancer driver genes with an impact on diagnosis and clinical management and have consistently shed light on new paradigms in cancer. In this review, we explore unique mechanisms of pheochromocytoma and paraganglioma initiation and management by drawing from recent examples involving rare mutations of hypoxia-related genes VHL, EPAS1 and SDHB, and of a poorly known susceptibility gene, TMEM127. These models expand our ability to predict variant pathogenicity, inform new functional domains, recognize environmental-gene connections, and highlight persistent therapeutic challenges for tumors with aggressive behavior.
Efficacy of Combined Therapy with Drug-Eluting Beads-Transcatheter Arterial Chemoembolization Followed by Conventional Transcatheter Arterial Chemoembolization for Unresectable Hepatocellular Carcinoma: A Multi-Center Study
Authors: Morishita Asahiro , Tani Joji , Nomura Takako , Takuma Kei , Nakahara Mai , Oura Kyoko , Tadokoro Tomoko , Fujita Koji , Shi Tingting , Yamana Hiroki , Matsui Takanori , Takata Tadayuki , Sanomura Takayuki , Nishiyama Yoshihiro , Himoto Takashi , Tomonari Tetsu , Moriya Akio , Senoo Tomonori , Takaguchi Koichi , Masaki Tsutomu
Published: September 2021

EB-TACE has recently been performed because of its lower hepatotoxicity compared to cTACE in less advanced HCC. However, local recurrence at the tumor margins is often observed after DEB-TACE. cTACE involves filling the intratumoral sinusoids with lipiodol-containing anticancer drugs and accumulating in the drainage area, which is the first site of HCC recurrence. The aim of this study is to evaluate the therapeutic effect of DEB-TACE followed by cTACE in HCC patients. Between 2014 and 2020, 65 patients with Barcelona clinic liver cancer (BCLC) stage B (intermediate stage) of HCC were enrolled and divided into two groups: one group received DEB-TACE followed by cTACE (cTACE group) and the other group received only DEB-TACE (non-cTACE group). Sixty-five patients were medically followed. The median observation time was 14 ± 13.1 months after the first DEB-TACE and outcomes were analyzed for multiple factors. Results: The complete response rate was significantly higher in the cTACE group than in the non-TACE group. The analysis showed that the only factor that increased the CR rate in the cTACE group was the total tumor number (less than four). The OS rate of CR patients was higher than that of non-CR patients in the cTACE group. Adverse events in the cTACE group included severe thrombocytopenia but only in one of twenty-seven patients. Conclusions: The combined therapy with DEB-TACE followed by cTACE may be a new effective therapeutic strategy for the intermediate stage of HCC patients.
USP44 Promoter Methylation in Plasma Cell-Free DNA in Prostate Cancer
Authors: Londra Dora , Mastoraki Sophia , Bournakis Evangelos , Zavridou Martha , Thanos Anastasios , Rampias Theodoros , Lianidou Evi S.
Published: September 2021

Liquid biopsy provides real-time monitoring of tumor evolution and response to therapy through analysis of circulating tumor cells (CTCs) and plasma-circulating tumor DNA (ctDNA). USP44 is a critical gene which plays an important role in cell proliferation; however, its accurate role in other cellular networks is under research. USP44 promoter methylation has been so far reported in colorectal neoplasia and metastatic breast cancer. In this study, we examined for the first time USP44 promoter methylation in plasma cell-free DNA (cfDNA) of patients with prostate cancer (early stage n = 32, metastatic n = 39) and 10 healthy donors (HD). USP44 promoter methylation was detected in plasma cell-free DNA by a newly developed highly specific and sensitive real-time MSP method. Our findings indicate that USP44 promoter is methylated in plasma cell-free DNA of metastatic prostate cancer patients and that detection of USP44 promoter methylation is significantly associated with overall survival (OS) (p = 0.008). We report for the first time that detection of USP44 promoter methylation in plasma cell free DNA provides significant prognostic information in metastatic prostate cancer.
Extracellular Vesicle-Associated miRNAs and Chemoresistance: A Systematic Review
Authors: Campos America , Sharma Shayna , Obermair Andreas , Salomon Carlos
Published: September 2021

Cancer is a leading public health issue globally, and diagnosis is often associated with poor outcomes and reduced patient survival. One of the major contributors to the fatality resultant of cancer is the development of resistance to chemotherapy, known as chemoresistance. Furthermore, there are limitations in our ability to identify patients that will respond to therapy, versus patients that will develop relapse, and display limited or no response to treatment. This often leads to patients being subjected to multiple futile treatment cycles, and results in a reduction in their quality of life. Therefore, there is an urgent clinical need to develop tools to identify patients at risk of chemoresistance, and recent literature has suggested that small extracellular vesicles, known as exosomes, may be a vital source of information. Extracellular vesicles (EV) are membrane bound vesicles, involved in cell-cell communication, through the transfer of their cargo, which includes proteins, lipids, and miRNAs. A defined exploration strategy was performed in this systematic review in order to provide a compilation of key EV miRNAs which may be predictive of chemoresistance. We searched the PubMed, Science Direct, and Scopus databases using the following keywords: Extracellular vesicles OR exosomes OR EVs AND miRNA AND Chemotherapy OR Chemoresistance OR Cancer Recurrence from 2010 to 2020. We found 31 articles that reported key EV-associated miRNAs involved in cancer recurrence related to chemoresistance. Interestingly, multiple studies of the same tumor type identified different microRNAs, and few studies identified the same ones. Specifically, miR-21, miR-222, and miR-155 displayed roles in response to chemotherapy, and were found to be common in colorectal cancer, ovarian cancer, breast cancer, and diffuse large B cell lymphoma patients (DLBCL). miR-21 and miR-222 were found to favour the development of chemoresistance, whereas miR-155 exhibited a contrasting role, depending on the type of primary tumor. Whilst high levels of miR-155 were found to correlate with chemotherapy resistance in DLBCL, it was found to be predictive of an effective response towards chemotherapy in breast cancer. Thus, further research regarding the roles of these miRNAs would be beneficial in terms of designing novel tools to counteract the progression of cancer in a not-to-distant future.