bluuebunny/crossref_metadata_2025 huggingface dataset:
Vitamin D Deficiency, Excessive Gestational Weight Gain, and Oxidative Stress Predict Small for Gestational Age Newborns Using an Artificial Neural Network Model
Authors: Perichart-Perera Otilia , Avila-Sosa Valeria , Solis-Paredes Juan Mario , Montoya-Estrada Araceli , Reyes-Muñoz Enrique , Rodríguez-Cano Ameyalli M. , González-Leyva Carla P. , Sánchez-Martínez Maribel , Estrada-Gutierrez Guadalupe , Irles Claudine
Published: March 2022

(1) Background: Size at birth is an important early determinant of health later in life. The prevalence of small for gestational age (SGA) newborns is high worldwide and may be associated with maternal nutritional and metabolic factors. Thus, estimation of fetal growth is warranted. (2) Methods: In this work, we developed an artificial neural network (ANN) model based on first-trimester maternal body fat composition, biochemical and oxidative stress biomarkers, and gestational weight gain (GWG) to predict an SGA newborn in pregnancies with or without obesity. A sensibility analysis to classify maternal features was conducted, and a simulator based on the ANN algorithm was constructed to predict the SGA outcome. Several predictions were performed by varying the most critical maternal features attained by the model to obtain different scenarios leading to SGA. (3) Results: The ANN model showed good performance between the actual and simulated data (R2 = 0.938) and an AUROC of 0.8 on an independent dataset. The top-five maternal predictors in the first trimester were protein and lipid oxidation biomarkers (carbonylated proteins and malondialdehyde), GWG, vitamin D, and total antioxidant capacity. Finally, excessive GWG and redox imbalance predicted SGA newborns in the implemented simulator. Significantly, vitamin D deficiency also predicted simulated SGA independently of GWG or redox status. (4) Conclusions: The study provided a computational model for the early prediction of SGA, in addition to a promising simulator that facilitates hypothesis-driven constructions, to be further validated as an application.
Elemental Sulfur Inhibits Yeast Growth via Producing Toxic Sulfide and Causing Disulfide Stress
Authors: Wang Tianqi , Yang Yuqing , Liu Menghui , Liu Honglei , Liu Huaiwei , Xia Yongzhen , Xun Luying
Published: March 2022

Elemental sulfur is a common fungicide, but its inhibition mechanism is unclear. Here, we investigated the effects of elemental sulfur on the single-celled fungus Saccharomyces cerevisiae and showed that the inhibition was due to its function as a strong oxidant. It rapidly entered S. cerevisiae. Inside the cytoplasm, it reacted with glutathione to generate glutathione persulfide that then reacted with another glutathione to produce H2S and glutathione disulfide. H2S reversibly inhibited the oxygen consumption by the mitochondrial electron transport chain, and the accumulation of glutathione disulfide caused disulfide stress and increased reactive oxygen species in S. cerevisiae. Elemental sulfur inhibited the growth of S. cerevisiae; however, it did not kill the yeast for up to 2 h exposure. The combined action of elemental sulfur and hosts’ immune responses may lead to the demise of fungal pathogens.
Squalene Loaded Nanoparticles Effectively Protect Hepatic AML12 Cell Lines against Oxidative and Endoplasmic Reticulum Stress in a TXNDC5-Dependent Way
Authors: Bidooki Seyed Hesamoddin , Alejo Teresa , Sánchez-Marco Javier , Martínez-Beamonte Roberto , Abuobeid Roubi , Burillo Juan Carlos , Lasheras Roberto , Sebastian Victor , Rodríguez-Yoldi María J. , Arruebo Manuel , Osada Jesús
Published: March 2022

Virgin olive oil, the main source of fat in the Mediterranean diet, contains a substantial amount of squalene which possesses natural antioxidant properties. Due to its highly hydrophobic nature, its bioavailability is reduced. In order to increase its delivery and potentiate its actions, squalene has been loaded into PLGA nanoparticles (NPs). The characterization of the resulting nanoparticles was assessed by electron microscopy, dynamic light scattering, zeta potential and high-performance liquid chromatography. Reactive oxygen species (ROS) generation and cell viability assays were carried out in AML12 (alpha mouse liver cell line) and a TXNDC5-deficient AML12 cell line (KO), which was generated by CRISPR/cas9 technology. According to the results, squalene was successfully encapsulated in PLGA NPs, and had rapid and efficient cellular uptake at 30 µM squalene concentration. Squalene reduced ROS in AML12, whereas ROS levels increased in KO cells and improved cell viability in both when subjected to oxidative stress by significant induction of Gpx4. Squalene enhanced cell viability in ER-induced stress by decreasing Ern1 or Eif2ak3 expressions. In conclusion, TXNDC5 shows a crucial role in regulating ER-induced stress through different signaling pathways, and squalene protects mouse hepatocytes from oxidative and endoplasmic reticulum stresses by several molecular mechanisms depending on TXNDC5.
Antioxidant Content and Antioxidant Capacity of the Protein-Rich Powdered Beverages Enriched with Flax Seeds Gum
Authors: Bochnak-Niedźwiecka Justyna , Szymanowska Urszula , Kapusta Ireneusz , Świeca Michał
Published: March 2022

Powdered beverages produced from dried fruit and vegetables are new products whose properties may be tailored by adding efficient nutrients and functional ingredients. The analyses of low-molecular antioxidants and antioxidant properties as well as nutrient content and digestibility were tested in beverages enriched with lentil proteins (AGF) and flaxseed gum (FSG). A replacement of sprouted lentil flour with the AGF deteriorated the phenolic content. As a main source of phenolics and vitamin C, lyophilized parsley leaves and broccoli sprouts were recognized. (There was no clear effect of the FGS.) The highest content of phenolics was determined in the beverages with these additives without the AGS (c.a. 125 μg/g). The AGF significantly improved the ability to quench ABTS radicals and reduce power. The best results were for the beverages without the FSG. (The effect was enhanced by lyophilized fruit and green vegetables.) The lowest chelating power and ability to quench hydroxyl radicals were in the beverages based on the AGF (improvement by the FSG and green vegetables). The tailoring of beverages’ recipes significantly increased protein content and did not affect nutrient digestibility. The modifications allow obtaining the beverages exhibiting multidirectional antioxidant properties, being a source of easily bioaccessible starch and proteins.
Phytochemical Characterization, and Antioxidant and Antimicrobial Properties of Agitated Cultures of Three Rue Species: Ruta chalepensis, Ruta corsica, and Ruta graveolens
Authors: Szewczyk Agnieszka , Marino Andreana , Molinari Jessica , Ekiert Halina , Miceli Natalizia
Published: March 2022

The in vitro cultures of the following three species of the genus Ruta were investigated: R. chalepensis, R. corsica, and R. graveolens. The dynamics of biomass growth and accumulation of secondary metabolites in the 3-, 4-, 5-, 6-, and 7-week growth cycle were analysed. The antioxidant capacity of the methanol extracts obtained from the biomass of the in vitro cultures was also assessed by different in vitro assays: 1,1-diphenyl-2-picrylhydrazil (DPPH), reducing power, and Fe2+ chelating activity assays. Moreover, a preliminary screening of the antimicrobial potential of the extracts was performed. The extracts were phytochemically characterized by high-performance liquid chromatography (HPLC), which highlighted the presence of linear furanocoumarins (bergapten, isoimperatorin, isopimpinellin, psoralen, and xanthotoxin) and furoquinoline alkaloids (γ-fagarine, 7-isopentenyloxy-γ-fagarine, and skimmianine). The dominant group of compounds in all the cultures was coumarins (maximum content 1031.5 mg/100 g DW (dry weight), R. chalepensis, 5-week growth cycle). The results of the antioxidant tests showed that the extracts of the three species had varied antioxidant capacity: in particular, the R. chalepensis extract exhibited the best radical scavenging activity (IC50 = 1.665 ± 0.009 mg/mL), while the R. graveolens extract displayed the highest chelating property (IC50 = 0.671 ± 0.013 mg/mL). Finally, all the extracts showed good activity against Staphylococcus aureus with MIC values of 250 μg/mL for the R. corsica extract and 500 μg/mL for both R. graveolens and R. chalepensis extracts.
Functional Characterization of Serotonin N-Acetyltransferase in Archaeon Thermoplasma volcanium
Authors: Lee Kyungjin , Choi Geun-Hee , Back Kyoungwhan
Published: March 2022

Serotonin N-acetyltransferase is the penultimate enzyme in the melatonin biosynthetic pathway that catalyzes serotonin into N-acetylserotonin. Many SNAT genes have been cloned and characterized from organisms ranging from bacteria to plants and mammals. However, to date, no SNAT gene has been identified from Archaea. In this study, three archaeal SNAT candidate genes were synthesized and expressed in Escherichia coli, and SNAT enzyme activity was measured using their purified recombinant proteins. Two SNAT candidate genes, from Methanoregulaceae (Archaea) and Pyrococcus furiosus, showed no SNAT enzyme activity, whereas a SNAT candidate gene from Thermoplasma volcanium previously named TvArd1 exhibited SNAT enzyme activity. The substrate affinity and the maximum reaction rate of TvSNAT toward serotonin were 621 μM and 416 pmol/min/mg protein, respectively. The highest amine substrate was tyramine, followed by tryptamine, serotonin, and 5-methoxytryptamine, which were similar to those of plant SNAT enzymes. Homologs of TvSNAT were found in many Archaea families. Ectopic overexpression of TvSNAT in rice resulted in increased melatonin content, antioxidant activity, and seed size in conjunction with the enhanced expression of seed size-related gene. This study is the first to report the discovery of SNAT gene in Archaea. Future research avenues include the cloning of TvSNAT orthologs in different phyla, and identification of their regulation and functions related to melatonin biosynthesis in living organisms.
Antioxidants of Fruit Extracts as Antimicrobial Agents against Pathogenic Bacteria
Authors: Suriyaprom Sureeporn , Mosoni Pascale , Leroy Sabine , Kaewkod Thida , Desvaux Mickaël , Tragoolpua Yingmanee
Published: March 2022

Fruit is an essential part of the human diet and is of great interest because of its richness in phytochemicals. Various fruit extracts from citrus, berries and pomegranates have been shown to possess a broad spectrum of medicinal properties. Fruit phytochemicals are of considerable interest because of their antioxidant properties involving different mechanisms of action, which can act against different pathogenic bacteria. The antioxidant capacity of fruit phytochemicals involves different kinds of reactions, such as radical scavenging and chelation or complexation of metal ions. The interaction between fruit phytochemicals and bacteria has different repercussions: it disrupts the cell envelope, disturbs cell–cell communication and gene regulation, and suppresses metabolic and enzymatic activities. Consequently, fruit phytochemicals can directly inhibit bacterial growth or act indirectly by modulating the expression of virulence factors, both of which reduce microbial pathogenicity. The aim of this review was to report our current knowledge on various fruit extracts and their major bioactive compounds, and determine the effectiveness of organic acids, terpenes, polyphenols, and other types of phenolic compounds with antioxidant properties as a source of antimicrobial agents.
Interval Analysis of Vibro-Acoustic Systems by the Enclosing Interval Finite-Element Method
Authors: Xiang Yujia , Shi Zhiyu
Published: March 2022

Traditional interval analysis methods for interior vibro-acoustic system with uncertain-but-bounded parameters are based on interval perturbation theory. However, the solution sets by traditional interval finite-element methods are intrinsically not capable of reflecting the actual bounds of results, due to the non-conservative approximation for neglecting the high-order terms of both Taylor and Neumann series. In order to cope with this problem, this paper introduces the concept of unimodal components from structural mechanics to factorize the uncertainties, and a new enclosing interval-finite element method (enclosing-IFEM) is proposed to predict the uncertain vibro-acoustic response. In the enclosing-IFEM, the global matrix is assembled with the mixed-nodal-element strategy (MNE), which is different from the element-by-element assembly strategy. Thus, the vibro-acoustic coupling equation can be transformed into an iterative enclosure formula, and it avoids conflicts between the Lagrange multiplier matrix and the coupling sub-block matrix. The focus of this research is to reduce the overestimation caused by dependency phenomenon in the result of the enclosing-IFEM, therefore, both Rump’s and Neumaier–Pownuk methods are analyzed in residual convergence. Furthermore, taking the results of the Monte Carlo approach and other interval finite-element methods as the cross-references, both the efficiency and accuracy of the enclosing-IFEM are examined through two numerical validation examples.
A Data Processing Framework for Polar Performance Diagrams
Authors: Dannenberg Valentin , Schüler Robert , Schürmann Achill
Published: March 2022

Polar performance diagrams are commonly used to predict the performance of a sailing vessel under given wind conditions. They are, in particular, an essential part of robotic sailing vessels and a basis for weather routing algorithms. In this paper we introduce a new framework for scientific work with such diagrams, which we make available as an open source Python package. It contains a model for the creation of polar performance diagrams from measurement data and supports different representations of polar performance diagrams for different tasks. The framework also includes several methods for the visualisation of polar performance diagrams, for example for scientific publications. Additionally, the presented framework solves basic tasks for the future development of weather-routing algorithms in a far more general manner than other methods did previously: it provides the calculation of costs of a sailing trip using custom cost functions, suggestions of optimal steering using convex hull calculations and a more flexible calculation of isochrone points, using custom weather models. Altogether, the presented framework allows future researchers to more easily handle polar performance diagrams. The corresponding Python package is compatible with various established file formats.
An Efficient Parallel Framework for the Discrete Element Method Using GPU
Authors: Dong Youkou , Yan Dingtao , Cui Lan
Published: March 2022

The discrete element method (DEM), a discontinuum-based method to simulate the interaction between neighbouring particles of granular materials, suffers from intensive computational workload caused by massive particle numbers, irregular particle shapes, and complicated interaction modes from the meso-scale representation of the macro information. To promote the efficiency of the DEM and enlarge the modelling scales with a higher realism of the particle shapes, parallel computing on the graphics processing unit (GPU) is developed in this paper. The potential data race between the computing cores in the parallelisation is tackled by establishing the contact pair list with a hybrid technique. All the computations in the DEM are made on the GPU cores. Three benchmark cases, a triaxial test of a sand specimen, cone penetration test and granular flow due to a dam break, are used to evaluate the performance of the GPU parallel strategy. Acceleration of the GPU parallel simulations over the conventional CPU sequential counterparts is quantified in terms of speedup. The average speedups with the GPU parallelisation are 84, 73, and 60 for the benchmark cases.
Applications of Environmental Nanotechnologies in Remediation, Wastewater Treatment, Drinking Water Treatment, and Agriculture
Authors: Kuhn Ramona , Bryant Isaac Mbir , Jensch Robert , Böllmann Jörg
Published: March 2022

Today, nanotechnologies (NTs) are well established in both private households and commercial markets. NTs are fully accepted in several sectors, such as medicine and pharmacy, and in industries, such as chemistry, electricity, food production, military, and other commercial branches, due to their unique properties. With regard to the growing demands for environmental resources caused by the still-growing global population, the application of NTs is an extremely important new branch in the environmental sector, delivering several advantages. Our review provides a comprehensive overview of the current developments in environmental remediation, wastewater treatment, drinking water treatment, and agriculture. More specifically, in the section on environmental remediation, we review the application of NTs towards enhanced reductive dechlorination, removal of heavy metals and remediation of oil spills. In the section on wastewater treatment, we highlight developments in the adsorption of heavy metals and persistent substances, advanced photocatalytic degradation of common wastewater pollutants, and improvements in membrane filtration processes. In the section on drinking water treatment, we discuss applications for the enhanced disinfection of pathogens, removal of heavy metals, point-of-use treatments, and the removal of organic matter. In the final section, on agriculture, we provide an overview of precision farming and the current state of the art concerning nanofertilisers, nanopesticides, nanoherbicides, and nano(bio)sensors.
Modeling Atom Interferometry Experiments with Bose–Einstein Condensates in Power-Law Potentials
Authors: Thomas Stephen , Sapp Colson , Henry Charles , Smith Andrew , Sackett Charles A. , Clark Charles W. , Edwards Mark
Published: March 2022

Recent atom interferometry (AI) experiments involving Bose–Einstein condensates (BECs) have been conducted under extreme conditions of volume and interrogation time. Numerical solution of the rotating-frame Gross–Pitaevskii equation (RFGPE), which is the standard mean-field theory applied to these experiments, is impractical due to the excessive computation time and memory required. We present a variational model that provides approximate solutions of the RFGPE for a power-law potential on a practical time scale. This model is well-suited to the design and analysis of AI experiments involving BECs that are split and later recombined to form an interference pattern. We derive the equations of motion of the variational parameters for this model and illustrate how the model can be applied to the sequence of steps in a recent AI experiment where BECs were used to implement a dual-Sagnac atom interferometer rotation sensor. We use this model to investigate the impact of finite-size and interaction effects on the single-Sagnac-interferometer phase shift.
Reinforcement Learning for Collaborative Robots Pick-and-Place Applications: A Case Study
Authors: Gomes Natanael Magno , Martins Felipe Nascimento , Lima José , Wörtche Heinrich
Published: March 2022

The number of applications in which industrial robots share their working environment with people is increasing. Robots appropriate for such applications are equipped with safety systems according to ISO/TS 15066:2016 and are often referred to as collaborative robots (cobots). Due to the nature of human-robot collaboration, the working environment of cobots is subjected to unforeseeable modifications caused by people. Vision systems are often used to increase the adaptability of cobots, but they usually require knowledge of the objects to be manipulated. The application of machine learning techniques can increase the flexibility by enabling the control system of a cobot to continuously learn and adapt to unexpected changes in the working environment. In this paper we address this issue by investigating the use of Reinforcement Learning (RL) to control a cobot to perform pick-and-place tasks. We present the implementation of a control system that can adapt to changes in position and enables a cobot to grasp objects which were not part of the training. Our proposed system uses deep Q-learning to process color and depth images and generates an ϵ-greedy policy to define robot actions. The Q-values are estimated using Convolution Neural Networks (CNNs) based on pre-trained models for feature extraction. To reduce training time, we implement a simulation environment to first train the RL agent, then we apply the resulting system on a real cobot. System performance is compared when using the pre-trained CNN models ResNext, DenseNet, MobileNet, and MNASNet. Simulation and experimental results validate the proposed approach and show that our system reaches a grasping success rate of 89.9% when manipulating a never-seen object operating with the pre-trained CNN model MobileNet.
The Electrochemical Characterization of Nanostructured Bi2Se3 Thin Films in an Aqueous Na Electrolyte
Authors: Meija Raimonds , Lazarenko Vitalijs , Skrastina Anna , Rublova Yelyzaveta , Andzane Jana , Voikiva Vanda , Viksna Arturs , Erts Donats
Published: March 2022

Due to their layered structure and high theoretical capacity, bismuth chalcogenides have been proposed as anodes in organic electrolyte Li- and Na-ion batteries. On the other hand, their electrochemical properties in aqueous systems have not been reported. Here, the electrochemical performance of Bi2Se3 thin films in 1 M NaNO3 aqueous electrolyte is presented. This aqueous Bi2Se3 system was found to have up to two orders of magnitude increased diffusion coefficients, compared to other anode materials in Na electrolyte-based systems, as well as limited anode electrode degradation over 5 CVs and significant changes in the anode after 30 CVs.
A Method for Detecting the Existence of an Over-Discharged Cell in a Lithium-Ion Battery Pack via Measuring Total Harmonic Distortion
Authors: Kim Jonghyeon , Kowal Julia
Published: March 2022

This paper deals with a method to detect the existence of an over-discharged cell in a lithium-ion battery (LIB) pack by measuring the total harmonic distortion (THD) rate in the voltage response. Over-discharge of the LIB cell reduces the available capacity by irreversible chemical reactions, resulting in serious safety risks such as explosions. Even if only one over-discharged cell exists in the battery pack, it accelerates the decomposition of other cells. In general, the measurement of each cell voltage in a battery pack is required to detect one over-discharged cell. This is because if only the voltage of the battery pack is measured, it cannot be distinguished whether the voltage of each cell is uniformly low or one specific weak cell is over-discharged. The proposed method measures the frequency response through the voltage at only two terminals of the battery pack to detect the presence of one over-discharged cell. When the battery cell is discharged beyond a certain level, the system nonlinearity of the battery pack increases, and it can be detected from the increased THD rate of the battery pack. The proposed method is verified by simulation and measurement.
Optimization of LIB Electrolyte and Exploration of Novel Compounds via the Molecular Dynamics Method
Authors: Saitoh Ken-ichi , Takai Yoshihiro , Sato Tomohiro , Takuma Masanori , Takahashi Yoshimasa
Published: March 2022

Due to great interest in the development of electric vehicles and other applications, improving the performances of lithium-ion batteries (LIBs) is crucial. Specifically, components of electrolytes for LIBs should be adequately chosen from hundreds of thousands of candidate compounds. In this study, we aimed to evaluate some physical properties expected for combinations of molecules for electrolytes by microscopic simulations. That is, the viscosity, ionic conductivity, degree of dissociation, diffusion coefficient, and conformation of each molecule were analyzed via molecular dynamics (MD) simulations. We aimed to understand how molecular-sized structures and properties collaboratively affect the behavior of electrolytes. The practical models of molecules we used were ethylene carbonate (EC), fluoroethylene carbonate (FEC), propylene carbonate (PC), butylene carbonate (BC), γ-butyrolactone (GBL), γ-valerolactone (GVL), dimethyl carbonate (DMC), ethyl-methyl carbonate (EMC), diethyl carbonate (DEC), and lithium hexafluorophosphate (LiPF6). Many molecular systems of electrolytes were simulated, in which one molar LiPF6 was mixed into a single or combined solvent. It was found that small solvent molecules diffused with relative ease, and they contributed to the higher ionic conductivity of electrolytes. It was clarified that the diffusion coefficient of lithium (Li) ions is greatly affected by the surrounding solvent molecules. We can conclude that high-permittivity solvents can be selectively coordinated around Li ions, and Li salts are sufficiently dissociated, even when there is only a small content of high-permittivity solvent. Thus, we can confirm solely by MD simulation that one of the better candidates for solvent molecules, formamide (F), will exhibit higher performance than the current solvents.
Therapeutic Role of Antimicrobial Peptides in Diabetes Mellitus
Authors: Depta Julia , Małkowska Paulina , Wysokińska Monika , Todorska Karolina , Sierawska Olga , Hrynkiewicz Rafał , Bębnowska Dominika , Niedźwiedzka-Rystwej Paulina
Published: March 2022

Antimicrobial peptides (AMPs) have recently become widely publicized because they have the potential to function in alternative therapies as “natural” antibiotics, with their main advantage being a broad spectrum of activity. The potential for antimicrobial peptides to treat diabetes mellitus (DM) has been reported. In diabetes mellitus type I (T1D), cathelicidin-related antimicrobial peptide (CRAMP), cathelicidin antimicrobial peptide (CAMP) and mouse-β- defensin 14 (mBD14) are positively affected. Decreased levels of LL-37 and human neutrophil peptide 1-3 (HNP1-3) have been reported in diabetes mellitus type II (T2D) relative to healthy patients. Moreover, AMPs from amphibians and social wasps have antidiabetic effects. In infections occurring in patients with tuberculosis-diabetes or diabetic foot, granulysin, HNP1, HNP2, HNP3, human beta-defensin 2 (HBD2), and cathelicidins are responsible for pathogen clearance. An interesting alternative is also the use of modified M13 bacteriophages containing encapsulated AMPs genes or phagemids.
Significance of Shewanella Species for the Phytoavailability and Toxicity of Arsenic—A Review
Authors: Darma Aminu , Yang Jianjun , Zandi Peiman , Liu Jin , Możdżeń Katarzyna , Xia Xing , Sani Ali , Wang Yihao , Schnug Ewald
Published: March 2022

The distribution of arsenic continues due to natural and anthropogenic activities, with varying degrees of impact on plants, animals, and the entire ecosystem. Interactions between iron (Fe) oxides, bacteria, and arsenic are significantly linked to changes in the mobility, toxicity, and availability of arsenic species in aquatic and terrestrial habitats. As a result of these changes, toxic As species become available, posing a range of threats to the entire ecosystem. This review elaborates on arsenic toxicity, the mechanisms of its bioavailability, and selected remediation strategies. The article further describes how the detoxification and methylation mechanisms used by Shewanella species could serve as a potential tool for decreasing phytoavailable As and lessening its contamination in the environment. If taken into account, this approach will provide a globally sustainable and cost-effective strategy for As remediation and more information to the literature on the unique role of this bacterial species in As remediation as opposed to conventional perception of its role as a mobiliser of As.
The Impact of NRF2 Inhibition on Drug-Induced Colon Cancer Cell Death and p53 Activity: A Pilot Study
Authors: Garufi Alessia , Pistritto Giuseppa , D’Orazi Valerio , Cirone Mara , D’Orazi Gabriella
Published: March 2022

Nuclear factor erythroid 2 (NF-E2) p45-related factor 2 (NRF2) protein is the master regulator of oxidative stress, which is at the basis of various chronic diseases including cancer. Hyperactivation of NRF2 in already established cancers can promote cell proliferation and resistance to therapies, such as in colorectal cancer (CRC), one of the most lethal and prevalent malignancies in industrialized countries with limited patient overall survival due to its escape mechanisms in both chemo- and targeted therapies. In this study, we generated stable NRF2 knockout colon cancer cells (NRF2-Cas9) to investigate the cell response to chemotherapeutic drugs with regard to p53 oncosuppressor, whose inhibition we previously showed to correlate with NRF2 pathway activation. Here, we found that NRF2 activation by sulforaphane (SFN) reduced cisplatin (CDDP)-induced cell death only in NRF2-proficient cells (NRF2-ctr) compared to NRF2-Cas9 cells. Mechanistically, we found that NRF2 activation protected NRF2-ctr cells from the drug-induced DNA damage and the apoptotic function of the unfolded protein response (UPR), in correlation with reduction of p53 activity, effects that were not observed in NRF2-Cas9 cells. Finally, we found that ZnCl2 supplementation rescued the cisplatin cytotoxic effects, as it impaired NRF2 activation, restoring p53 activity. These findings highlight NRF2′s key role in neutralizing the cytotoxic effects of chemotherapeutic drugs in correlation with reduced DNA damage and p53 activity. They also suggest that NRF2 inhibition could be a useful strategy for efficient anticancer chemotherapy and support the use of ZnCl2 to inhibit NRF2 pathway in combination therapies.
A Systematic Review of Common and Brain-Disease-Specific RNA Editing Alterations Providing Novel Insights into Neurological and Neurodegenerative Disease Manifestations
Authors: Karagianni Korina , Pettas Spyros , Christoforidou Georgia , Kanata Eirini , Bekas Nikolaos , Xanthopoulos Konstantinos , Dafou Dimitra , Sklaviadis Theodoros
Published: March 2022

RNA editing contributes to transcriptome diversification through RNA modifications in relation to genome-encoded information (RNA–DNA differences, RDDs). The deamination of Adenosine (A) to Inosine (I) or Cytidine (C) to Uridine (U) is the most common type of mammalian RNA editing. It occurs as a nuclear co- and/or post-transcriptional event catalyzed by ADARs (Adenosine deaminases acting on RNA) and APOBECs (apolipoprotein B mRNA editing enzyme catalytic polypeptide-like genes). RNA editing may modify the structure, stability, and processing of a transcript. This review focuses on RNA editing in psychiatric, neurological, neurodegenerative (NDs), and autoimmune brain disorders in humans and rodent models. We discuss targeted studies that focus on RNA editing in specific neuron-enriched transcripts with well-established functions in neuronal activity, and transcriptome-wide studies, enabled by recent technological advances. We provide comparative editome analyses between human disease and corresponding animal models. Data suggest RNA editing to be an emerging mechanism in disease development, displaying common and disease-specific patterns. Commonly edited RNAs represent potential disease-associated targets for therapeutic and diagnostic values. Currently available data are primarily descriptive, calling for additional research to expand global editing profiles and to provide disease mechanistic insights. The potential use of RNA editing events as disease biomarkers and available tools for RNA editing identification, classification, ranking, and functional characterization that are being developed will enable comprehensive analyses for a better understanding of disease(s) pathogenesis and potential cures.
Assessment of Two Different Glucagon Assays in Healthy Individuals and Type 1 and Type 2 Diabetes Patients
Authors: Brunner Martina , Moser Othmar , Raml Reingard , Haberlander Maximilian , Boulgaropoulos Beate , Obermayer-Pietsch Barbara , Svehlikova Eva , Pieber Thomas R. , Sourij Harald
Published: March 2022

Methods for glucagon analysis suffered in the past from lack of specificity and a narrow sensitivity range, which has led to inaccurate results and to the suggestion that type 1 diabetes (T1D) and type 2 diabetes (T2D) patients have elevated fasting glucagon levels. However, the availability of more specific and more sensitive methods to detect intact glucagon has shown that actual glucagon levels are lower than previously assumed. This study aimed to characterize fasting plasma glucagon levels in healthy individuals and T1D and T2D patients with two different glucagon assays. The study included 20 healthy individuals, 20 T1D and 20 T2D patients. Blood was collected under fasting conditions. A double-antibody sandwich enzyme-linked immunosorbent assay (ELISA) and a conventional radioimmunoassay (RIA) were used. A significant difference in fasting glucagon levels between healthy individuals and T2D was observed by ELISA, but not by RIA. ELISA also yielded lower glucagon levels in healthy individuals than in T1D and T2D patients which RIA did not. RIA produced significantly (p = 0.0001) higher overall median glucagon values than ELISA in a pooled analysis. These results underline the notion that the choice of selective laboratory methods is highly relevant for mechanistic endocrine research.
Evaluation of Adipose Cell-Based Therapies for the Treatment of Thumb Carpometacarpal Joint Osteoarthritis
Authors: Karagergou Eleni , Ligomenou Theodora , Chalidis Byron , Kitridis Dimitrios , Papadopoulou Sophia , Givissis Panagiotis
Published: March 2022

Adipose tissue and its regenerative products which are isolated with enzymatic or mechanical processing of the harvested fat have been studied in a wide range of degenerative diseases, including osteoarthritis of the knee and hip. Intra-articular injection of these products can provide symptomatic relief of pain and postpone surgery. However, their use in the treatment of thumb carpometacarpal joint (CMCJ) osteoarthritis is limited and just a few studies have been published on that topic. For this reason, a review of the literature was performed by a thorough search of eight terms using the Pubmed database. In total, seven human studies met the selection criteria, including case-control studies, case-series and one case report. In all studies, intra-articular injection of autologous fat in osteoarthritic thumb CMCJ provided reduction in pain and improvement in hand function. Grip and pinch strength showed variable results, from no change to significant improvement. Fat-processing techniques were based on centrifugation and mechanical homogenization but biological characterization of the injected cells was not performed in any study. Although the results are encouraging, a uniformly standardized method of fat processing and the conduction of randomized controlled trials in the future could better evaluate the effectiveness of this procedure for thumb CMCJ osteoarthritis.
Identification and Characterization of Circular RNAs in Mammary Tissue from Holstein Cows at Early Lactation and Non-Lactation
Authors: Liang Yan , Gao Qisong , Wang Haiyang , Guo Mengling , Arbab Abdelaziz Adam Idriss , Nazar Mudasir , Li Mingxun , Yang Zhangping , Karrow Niel A. , Mao Yongjiang
Published: March 2022

In this study, circular RNAs (circRNAs) from Holstein cow mammary tissues were identified and compared between early lactation and non-lactation. After analysis, 10,684 circRNAs were identified, ranging from 48 to 99,406 bp, and the average size was 882 bp. The circRNAs were mainly distributed on chromosomes 1 to 11, and 89.89% of the circRNAs belonged to sense-overlapping circRNA. The exons contained with circRNAs ranged from 1 to 47 and were concentrated from 1 to 5. Compared with the non-lactating cows, 87 circRNAs were significantly differentially expressed in the peak lactation cows. There were 68 upregulated circRNAs and 19 downregulated circRNAs. Enrichment analysis of circRNAs showed that GO analysis mainly focused on immune response, triglyceride transport, T cell receptor signaling pathway, etc. Pathway analysis mainly focused on cytokine-cytokine receptor interaction, T helper 17 cell differentiation, fatty acid biosynthesis, the JAK-STAT signaling pathway, etc. Specific primers were designed for two proximal ends of the circRNA junction sites to allow for PCR validation of four randomly selected circRNAs and carry out circRNA-miRNA interaction research. This study revealed the expression profile and characteristics of circRNAs in mammary tissue from Holstein cows at early lactation and non-lactation, thus providing rich information for the study of circRNA functions and mechanisms, as well as potential candidate miRNA genes for studying lactation in Holstein cows.
hTERT DNA Methylation Analysis Identifies a Biomarker for Retinoic Acid-Induced hTERT Repression in Breast Cancer Cell Lines
Authors: Nguyen Eric , Richerolle Andréa , Sánchez-Bellver Júlia , Varennes Jacqueline , Ségal-Bendirdjian Evelyne
Published: March 2022

Telomerase reactivation is responsible for telomere preservation in about 90% of cancers, providing cancer cells an indefinite proliferating potential. Telomerase consists of at least two main subunits: a catalytic reverse transcriptase protein (hTERT) and an RNA template subunit. Strategies to inhibit hTERT expression seem promising for cancer treatment. Previous works showed that all-trans retinoic acid (ATRA) induces hTERT repression in acute promyelocytic leukemia cells, resulting in their death. Here, we investigated the effects of ATRA in a subset of breast cancer cell lines. The mutational status of hTERT promoter and the methylation patterns at a single CpG resolution were assessed. We observed an inverse relationship between hTERT expression after ATRA treatment and the methylation level of a specific CpG at chr5: 1,300,438 in a region of hTERT gene at −5 kb of the transcription initiation site. This observation highlighted the significance of this region, whose methylation profile could represent a promising biomarker to predict the sensitivity to ATRA-induced hTERT repression in specific breast cancer subtypes. As hTERT repression promotes drug-induced cell death, checking the methylation status of this unique region and the specific CpG included can help in decision-making to include ATRA in combination therapy and contributes to a better clinical outcome.
Reporting on the Value of Artificial Intelligence in Predicting the Optimal Embryo for Transfer: A Systematic Review including Data Synthesis
Authors: Sfakianoudis Konstantinos , Maziotis Evangelos , Grigoriadis Sokratis , Pantou Agni , Kokkini Georgia , Trypidi Anna , Giannelou Polina , Zikopoulos Athanasios , Angeli Irene , Vaxevanoglou Terpsithea , Pantos Konstantinos , Simopoulou Mara
Published: March 2022

Artificial intelligence (AI) has been gaining support in the field of in vitro fertilization (IVF). Despite the promising existing data, AI cannot yet claim gold-standard status, which serves as the rationale for this study. This systematic review and data synthesis aims to evaluate and report on the predictive capabilities of AI-based prediction models regarding IVF outcome. The study has been registered in PROSPERO (CRD42021242097). Following a systematic search of the literature in Pubmed/Medline, Embase, and Cochrane Central Library, 18 studies were identified as eligible for inclusion. Regarding live-birth, the Area Under the Curve (AUC) of the Summary Receiver Operating Characteristics (SROC) was 0.905, while the partial AUC (pAUC) was 0.755. The Observed: Expected ratio was 1.12 (95%CI: 0.26–2.37; 95%PI: 0.02–6.54). Regarding clinical pregnancy with fetal heartbeat, the AUC of the SROC was 0.722, while the pAUC was 0.774. The O:E ratio was 0.77 (95%CI: 0.54–1.05; 95%PI: 0.21–1.62). According to this data synthesis, the majority of the AI-based prediction models are successful in accurately predicting the IVF outcome regarding live birth, clinical pregnancy, clinical pregnancy with fetal heartbeat, and ploidy status. This review attempted to compare between AI and human prediction capabilities, and although studies do not allow for a meta-analysis, this systematic review indicates that the AI-based prediction models perform rather similarly to the embryologists’ evaluations. While AI models appear marginally more effective, they still have some way to go before they can claim to significantly surpass the clinical embryologists’ predictive competence.
Bacterial and Viral Infection and Sepsis in Kidney Transplanted Patients
Authors: Mella Alberto , Mariano Filippo , Dolla Caterina , Gallo Ester , Manzione Ana Maria , Di Vico Maria Cristina , Cavallo Rossana , De Rosa Francesco Giuseppe , Costa Cristina , Biancone Luigi
Published: March 2022

Kidney transplanted patients are a unique population with intrinsic susceptibility to viral and bacterial infections, mainly (but not exclusively) due to continuous immunosuppression. In this setting, infectious episodes remain among the most important causes of death, with different risks according to the degree of immunosuppression, time after transplantation, type of infection, and patient conditions. Prevention, early diagnosis, and appropriate therapy are the goals of infective management, taking into account that some specific characteristics of transplanted patients may cause a delay (the absence of fever or inflammatory symptoms, the negativity of serological tests commonly adopted for the general population, or the atypical anatomical presentation depending on the surgical site and graft implantation). This review considers the recent available findings of the most common viral and bacterial infection in kidney transplanted patients and explores risk factors and outcomes in septic evolution.
Calculated Tumor-Associated Neutrophils Are Associated with the Tumor—Stroma Ratio and Predict a Poor Prognosis in Advanced Gastric Cancer
Authors: Kim Eun Young , Abdul-Ghafar Jamshid , Chong Yosep , Yim Kwangil
Published: March 2022

The tumor-associated neutrophils (TANs) value and tumor—stroma ratio (TSR) are promising prognostic parameters in the tumor microenvironment. We aimed to evaluate the prognostic role and relationship of TANs and TSR in gastric cancer. Our study comprised 157 patients who underwent gastrectomy for advanced gastric cancer. TANs were assessed by immunohistochemical staining (CD15 and CD66b) and were analyzed with an image analyzer. TANs have been known to have different functional subpopulations of N1 (anti-tumor) and N2 (pro-tumor). We developed “calculated TANs with pro-tumor function (cN2; CD15 minus CD66b)”. The TSR was evaluated using hematoxylin and eosin staining. High-grade CD15-positive, cN2 in the tumor center, and TSR were significantly related to poor disease-free survival (DFS). TSR and cN2 were independent prognostic factors for DFS (hazard ratio (HR) = 2.614; p = 0.001, HR = 3.976; p = 0.002) and cN2 in the tumor center showed a positive correlation with TSR (R = 0.179, p = 0.025). While CD66b stained both N1 and N2, CD15 detected most of N2. Combining both markers revealed a novel cN2, which was an independent marker of poor prognosis. The transformation from N1 to N2 predominantly occurred in the tumor center, and was associated with TSR.
Production and Secretion of Gelsolin by Both Human Macrophage- and Fibroblast-like Synoviocytes and GSN Modulation in the Synovial Fluid of Patients with Various Forms of Arthritis
Authors: Feldt Jessica , Schicht Martin , Welss Jessica , Gelse Kolja , Sesselmann Stefan , Tsokos Michael , Socher Eileen , Garreis Fabian , Müller Thomas , Paulsen Friedrich
Published: March 2022

Gelsolin (GSN) is an actin-binding protein involved in cell formation, metabolism and wound closure processes. Since this protein is known to play a role in arthritis, here we investigate how the synovial membrane with its specific synoviocytes contributes to the expression of GSN and how the amount of GSN expressed is modulated by different types of arthritis. Synovial membranes from adult healthy subjects and patients with rheumatoid arthritis (RA) and osteoarthritis (OA) are analyzed by immunofluorescence, Western blot and ELISA. Macrophage-like synoviocytes (MLS) and fibroblast-like synoviocytes (FLS) were isolated, cultured and analyzed for their potential to produce and secrete GSN. In addition, the GSN concentrations in the synovial fluid of various forms of arthritis are determined by ELISA. GSN is produced by the healthy and arthritic synovial membranes. Both forms of synoviocytes (MLS and FLS) release GSN. The results show that there is a significant reduction in GSN in the synovial fluid in adult patients with OA. This reduction is also detectable in adult patients with RA but is not as evident. In juvenile arthritis, there is a slight increase in GSN concentration in the synovial fluid. This study shows that primary MLS and FLS express GSN and that these cells, in addition to articular chondrocytes, contribute to GSN levels in synovial fluid. Furthermore, GSN concentrations are modulated in different types of arthritis. Further studies are needed to fully understand how GSN is involved in joint homeostasis.
Detection of TERT Promoter Mutations as a Prognostic Biomarker in Gliomas: Methodology, Prospects, and Advances
Authors: Hasanau Tsimur , Pisarev Eduard , Kisil Olga , Nonoguchi Naosuke , Le Calvez-Kelm Florence , Zvereva Maria
Published: March 2022

This article reviews the existing approaches to determining the TERT promoter mutational status in patients with various tumoral diseases of the central nervous system. The operational characteristics of the most common methods and their transferability in medical practice for the selection or monitoring of personalized treatments based on the TERT status and other related molecular biomarkers in patients with the most common tumors, such as glioblastoma, oligodendroglioma, and astrocytoma, are compared. The inclusion of new molecular markers in the course of CNS clinical management requires their rapid and reliable assessment. Availability of molecular evaluation of gliomas facilitates timely decisions regarding patient follow-up with the selection of the most appropriate treatment protocols. Significant progress in the inclusion of molecular biomarkers for their subsequent clinical application has been made since 2016 when the WHO CNS classification first used molecular markers to classify gliomas. In this review, we consider the methodological approaches used to determine mutations in the promoter region of the TERT gene in tumors of the central nervous system. In addition to classical molecular genetical methods, other methods for determining TERT mutations based on mass spectrometry, magnetic resonance imaging, next-generation sequencing, and nanopore sequencing are reviewed with an assessment of advantages and disadvantages. Beyond that, noninvasive diagnostic methods based on the determination of the mutational status of the TERT promoter are discussed.
Innovation in Gastroenterology—Can We Do Better?
Authors: Klang Eyal , Soffer Shelly , Tsur Abraham , Shachar Eyal , Lahat Adi
Published: March 2022

The health system can reap significant benefits by adopting and implementing innovative measures, as was recently demonstrated and emphasized during the COVID-19 pandemic. Herein, we present our bird’s eye view of gastroenterology’s innovative technologies via utilizing a text-mining technique. We analyzed five research fields that comply with innovation: artificial intelligence (AI), virtual reality (VR), telemedicine, the microbiome, and advanced endoscopy. According to gastroenterology literature, the two most innovative fields were the microbiome and advanced endoscopy. Though artificial intelligence (AI), virtual reality (VR), and telemedicine trailed behind, the number of AI publications in gastroenterology has shown an exponential trend in the last couple of years. While VR and telemedicine are neglected compared to other fields, their implementation could improve physician and patient training, patient access to care, cost reduction, and patient outcomes.