bluuebunny/crossref_metadata_2025 huggingface dataset:
Strategies of Pathogens to Escape from NO-Based Host Defense
Authors: De Simone Giovanna , di Masi Alessandra , Ascenzi Paolo
Published: November 2022

Nitric oxide (NO) is an essential signaling molecule present in most living organisms including bacteria, fungi, plants, and animals. NO participates in a wide range of biological processes including vasomotor tone, neurotransmission, and immune response. However, NO is highly reactive and can give rise to reactive nitrogen and oxygen species that, in turn, can modify a broad range of biomolecules. Much evidence supports the critical role of NO in the virulence and replication of viruses, bacteria, protozoan, metazoan, and fungi, thus representing a general mechanism of host defense. However, pathogens have developed different mechanisms to elude the host NO and to protect themselves against oxidative and nitrosative stress. Here, the strategies evolved by viruses, bacteria, protozoan, metazoan, and fungi to escape from the NO-based host defense are overviewed.
Effect of Tomato, Beetroot and Carrot Juice Addition on Physicochemical, Antioxidant and Texture Properties of Wheat Bread
Authors: Raczyk Marianna , Kruszewski Bartosz , Zachariasz Ewa
Published: November 2022

Bakery products, including bread, are important components of the diet of people all over the world. One of the food industry’s goals is to improve its quality in the context of healthiness and physical parameters. Consumers’ perception of sensory quality is an important aspect of food choice. Thus, the study aimed to enhance nutritional parameters (antioxidant capacity, content of phenolic compounds) together with maintaining or increasing bread quality (texture, color, volume and sensory properties). Among vegetable juices, tomato, beetroot and carrot were selected, as they are easily accessible in Europe and are inexpensive. At the same time, those juices are known to be high in antioxidants. In this study, the effect of substituting recipe water with tomato, beetroot and carrot juices (replacement level: 15, 30, 50% v/v) was evaluated in terms of the specific volume, texture, color, acidity, polyphenol contents, antioxidant and sensory properties. It was concluded that juice content had a significant positive impact on physicochemical parameters such as volume, color, acidity, as well as the antioxidant activity of breads. The carrot and beetroot juices were the most efficient in terms of shaping wheat bread properties, especially in terms of antioxidant activity.
Numerical Investigation of Asphalt Concrete Fracture Based on Heterogeneous Structure and Cohesive Zone Model
Authors: Chen Jiaqi , Ouyang Xu , Sun Xiao
Published: November 2022

The fracture behavior of asphalt concrete is closely related to its internal structure. A deep understanding of the relationship between the internal structure and fracture behavior of asphalt concrete is very important for sustainable and durable pavement design. In this paper, a CZM-based FE model was developed to investigate the fracture behavior of asphalt concrete. An image-aided approach was used to generate the 3-D internal heterogeneous structure of asphalt concrete. A series of 2-D cross sections were extracted from the 3-D structure for finite element modeling. Then numerical simulations of SCB tests were conducted and validated with experimental results. With the validated CZM-based FE model, the effects of some critical factors, including temperature, loading rate, aggregate geometry, fracture strength, and fracture energy, on the fracture behavior of asphalt concrete were investigated. The analysis results showed that the average damage of the adhesive elements was higher than that of the cohesive elements at the peak load. At lower temperatures, asphalt concrete tends to crack earlier, and the cracking path tends to be marginally closer to the aggregates. A higher loading rate may induce more, but minor, element damage since the CZM elements in asphalt mortar cannot bear much more stress through deformation. Angular aggregates may induce a higher percentage of damaged elements, especially adhesive-damaged elements. On average, each 10% increase in fracture energy allows the specimen to bear 2.31% more load and 2.82% more displacement. Sufficient fracture energy could improve the ability of asphalt concrete to resist fracture.
Probabilistic and Scenario-Based Seismic Hazard Assessment on the Western Gulf of Corinth (Central Greece)
Authors: Kaviris George , Zymvragakis Angelos , Bonatis Pavlos , Kapetanidis Vasilis , Voulgaris Nicholas
Published: November 2022

The Gulf of Corinth (Central Greece) is one of the most rapidly extending rifts worldwide, with its western part being the most seismically active, hosting numerous strong (M ≥ 6.0) earthquakes that have caused significant damage. The main objective of this study was the evaluation of seismic hazard through a probabilistic and stochastic methodology. The implementation of three seismotectonic models in the form of area source zones via a logic tree framework revealed the expected level of peak ground acceleration and velocity for return periods of 475 and 950 years. Moreover, PGA values were obtained through the stochastic simulation of strong ground motion by adopting worst-case seismic scenarios of potential earthquake occurrences for known active faults in the area. Site-specific analysis of the most populated urban areas (Patras, Aigion, Nafpaktos) was performed by constructing uniform hazard spectra in terms of spectral acceleration. The relative contribution of each selected fault segment to the seismic hazard characterizing each site was evaluated through response spectra obtained for the adopted scenarios. Almost all parts of the study area were found to exceed the reference value proposed by the current Greek National Building Code; however, the three urban areas are covered by the Eurocode 8 regulations.
Forecasting of PM2.5 Concentration in Beijing Using Hybrid Deep Learning Framework Based on Attention Mechanism
Authors: Li Dong , Liu Jiping , Zhao Yangyang
Published: November 2022

Air pollution has become a critical factor affecting the health of human beings. Forecasting the trend of air pollutants will be of considerable help to public health, including improving early-warning systems. The article designs a novel hybrid deep learning framework FPHFA (FPHFA is the abbreviation of the title of this paper) for PM2.5 concentration forecasting is proposed, which learns spatially correlated features and long-term dependencies of time series data related to PM2.5. Owing to the complex nonlinear dynamic and spatial features of pollutant data, the FPHFFA model combines multi-channel one-dimensional convolutional neural networks, bi-directional long short-term memory neural networks, and attention mechanisms for the first time. Multi-channel 1D CNNs are applied to capture trend features between some sites and overall spatial characteristics of PM2.5 concentration, Bi LSTMs are used to learn the temporal correlation of PM2.5 concentration, and the attention mechanism is used to focus more effective information at different moments. We carried out experimental evaluations using the Beijing dataset, and the outcomes show that our proposed model can effectively handle PM2.5 concentration prediction with satisfactory accuracy. For the prediction task from 1 to 12 h, our proposed prediction model performs well. The FPHFA also achieves satisfactory results for prediction tasks from 13 to 96 h.
Towards an Efficient Multi-Generation System Providing Power, Cooling, Heating, and Freshwater for Residential Buildings Operated with Solar-Driven ORC
Authors: Almehmadi Fahad Awjah , Elattar Hassan Fawzy , Fouda Ali , Alqaed Saeed , Alharthi Mathkar A. , Refaey Hassanein Abdelmohsen
Published: November 2022

In buildings, multi-generation systems are a promising technology that can replace discrete traditional energy production methods. A multi-generation system makes it possible to efficiently produce electricity, cooling, heating, and freshwater simultaneously. This study involved the numerical analysis of a modified proposed novel solar-driven multi-generation system (MGS-II) integrated with the Organic Rankine Cycle (ORC), Humidification–Dehumidification Desalination System (HDH), and Desiccant Cooling System (DCS) by using heat recovery and thermal energy storage (TES) units. In addition, a comparison study with the basic multi-generation system (MGS-I) is performed. The proposed system is designed to supply electricity, air conditioning, domestic heating, and fresh water to small/medium-sized buildings. How operating conditions affect system productivity and performance metrics have been investigated. The results show that the proposed multi-generation system (MGS-II) can produce electrical power, space cooling, domestic heating and fresh water while maintaining comfortable conditions inside the conditioned space. Moreover, the MGS-II outperforms the MGS-I system, and the maximum MGS-II system productivity; electricity production (\({W_{net}^{\bullet}}\)), freshwater (\({m_{fresh}^{\bullet} }\)), space cooling (\({Q_{cooling}^{\bullet} }\)), and domestic heating (\({Q_{heating}^{\bullet} }\)) are 102.3 kW, 141.5 kg/h, 20.77 kW, and 225 kW, respectively. In addition, the highest total gained output ratio (TGOR), specific total gained energy (STG), and specific total gained energy equivalent price (STGP) of the MGS-II system are 0.6303, 3.824 kWh/m2, and 0.149 USD/m2, respectively. The accepted ranges of comfortable space-supplied air conditions (temperature and humidity) are 15.5–18.2 °C and 9.2–12.00 gv/kga for both systems, MGS-I and MGS-II. Finally, the current system (MGS-II) has the maximum of the system’s performance indicators and productivity (TGOR and \({{\overset{.}{m}}_{fresh} }\)) compared with the other reported systems.
Derivation and Verification of Laminated Composite T-Beam Theory
Authors: Lyu Yu-Ting , Hung Tsung-Pin , Ay Herchang , Tsai Hsiu-An , Chiang Yih-Cherng , Lin Ah-Der
Published: November 2022

This study analyzes the composite laminated T-beams using the composite beam and laminated composite plate theories. The theoretical formula was derived assuming that the composite T-beam has one- and two-dimensional (1D and 2D) structures. The 1D analysis was performed according to the Kirchhoff-Love hypothesis, thereby considering only the axial strain to derive a relationship between the strain and displacement. The 2D analysis was performed considering the T-beam as a combination of two composite sheets. The effective stiffness of the beam was derived from the stress-strain and moment-curvature relationships. Furthermore, the deflection of the beam and the stress of each laminate were calculated. A simple support beam, made of AS4/3501-6 carbon/epoxy, was used as a composite laminated T-beam. MSC/NASTRAN finite element software was used for analysis. The accuracy of the theoretical formula and limitations of its use was verified using the finite element analysis. Higher accuracy of the theoretical formula was obtained at a composite beam aspect ratio greater than 15. The formula derived in this study is suitable for thin and long beams.
Emotional Stress Recognition Using Electroencephalogram Signals Based on a Three-Dimensional Convolutional Gated Self-Attention Deep Neural Network
Authors: Kim Hyoung-Gook , Jeong Dong-Ki , Kim Jin-Young
Published: November 2022

The brain is more sensitive to stress than other organs and can develop many diseases under excessive stress. In this study, we developed a method to improve the accuracy of emotional stress recognition using multi-channel electroencephalogram (EEG) signals. The method combines a three-dimensional (3D) convolutional neural network with an attention mechanism to build a 3D convolutional gated self-attention neural network. Initially, the EEG signal is decomposed into four frequency bands, and a 3D convolutional block is applied to each frequency band to obtain EEG spatiotemporal information. Subsequently, long-range dependencies and global information are learned by capturing prominent information from each frequency band via a gated self-attention mechanism block. Using frequency band mapping, complementary features are learned by connecting vectors from different frequency bands, which is reflected in the final attentional representation for stress recognition. Experiments conducted on three benchmark datasets for assessing the performance of emotional stress recognition indicate that the proposed method outperforms other conventional methods. The performance analysis of proposed methods confirms that EEG pattern analysis can be used for studying human brain activity and can accurately distinguish the state of stress.
Building Networks with a New Cross-Bubble Transition Entropy for Quantitative Assessment of Mental Arithmetic Electroencephalogram
Authors: Chen Xiaobi , Xu Guanghua , Zhang Sicong , Zhang Xun , Teng Zhicheng
Published: November 2022

The complex network nature of human brains has led an increasing number of researchers to adopt a complex network to assess the cognitive load. The method of constructing complex networks has a direct impact on assessment results. During the process of using the cross-permutation entropy (CPE) method to construct complex networks for cognitive load assessment, it is found that the CPE method has the shortcomings of ignoring the transition relationship between symbols and the analysis results are vulnerable to parameter settings. In order to address this issue, a new method based on the CPE principle is proposed by combining the advantages of the transition networks and the bubble entropy. From an interaction perspective, this method suggested that the node-wise out-link transition entropy of the cross-transition network between two time series is used as the edge weight to build a complex network. The proposed method was tested on the unidirectional coupled Henon model and the results demonstrated its suitability for the analysis of short time series by decreasing the influence of the embedding dimension and improving the reliability under the weak coupling conditions. The proposed method was further tested on the publicly available EEG dataset and showed significant superiority compared with the conventional CPE method.
A Study of Microdrilling of Fused Silica Using EDMed PCD Tools
Authors: Lee Pyeong An , Kim Bo Hyun
Published: November 2022

In microbiochips and microfluidic devices, microholes are a basic and important feature. The microdrilling of glass materials without cracks is still challenging in the fabrication of glass-based microdevices. This paper investigates the characteristics of microdrilling fused silica using polycrystalline diamond (PCD) tools fabricated by electrical discharge machining (EDM). In particular, peak forces, which are observed at the beginning of drilling, are discussed because crack formations are related to peak forces. To reduce peak forces and to minimize cracks, the effects of drilling conditions, such as tool shape, the surface roughness of a tool, and axial feedrate, were therefore investigated. It was observed that D-shape tools with high surface roughness was useful to reduce the peak force. In through-hole drilling, a sacrificial layer was used to prevent exit cracks, and a variable feedrate was applied to increase drilling speeds. Finally, a dressing process using EDM was conducted to recondition the worn tool’s surface.
Model-Free Adaptive Control Based on Fractional Input-Output Data Model
Authors: Treestayapun Chidentree , Muñoz-Vázquez Aldo Jonathan
Published: November 2022

Memory properties of fractional-order operators are considered for an input-output data model for highly uncertain nonlinear systems. The model arises by relating the fractional-order variation of the output to the fractional-order variation of the input; the instantaneous gain is computed through a fuzzy inference network, whose output consequences are adapted online on a gradient descent rule. The fractional-order nature of the proposed model relaxes the stringent conditions on data-driven schemes, allowing instantaneous changes in the output signal with a null variation in the controller. The main contribution consists of taking advantage of the memory properties of fractional-order operators and the flexibility of fuzzy logic rules to construct a data-driven model for highly uncertain discrete-time nonlinear systems. The relevance of the proposed method is assessed through experiments in a real-world scenario.
Cyber Trust Index: A Framework for Rating and Improving Cybersecurity Performance
Authors: Malaivongs Sasawat , Kiattisin Supaporn , Chatjuthamard Pattanaporn
Published: November 2022

Cybersecurity risk is among the top risks that every organization must consider and manage, especially during this time wherein technology has become an integral part of our lives; however, there is no efficient and simplified measurement method that organizations or regulators could use, as frequently as they need, to evaluate and compare the outcome of cybersecurity efforts that have been put in place. Consequently, this has resulted in an absence of critical data for cybersecurity improvement. This research proposes a Cyber Trust Index (CTI), a novel and simplified framework for evaluating, benchmarking, and improving organizations’ cybersecurity performance. Methods: The researchers analyzed prominent scientific research papers and widely used security standards to develop baseline security controls that serve as a measurement foundation. Then, they identified Control Enablers and Capability Tiers that were used as base measures and measurement methods. The CTI framework was evaluated by experts and tested with 35 organizations from the critical information infrastructure (CII) sector, as well as other generic sectors, in Thailand to confirm its validity and reliability in real organization settings and identify the priorities and factors that can contribute to better cybersecurity performance. Results: The CTI has two key elements: the baseline controls and rating methods. The baseline controls comprise 12 dimensions, 25 clusters, and 70 controls. The rating methods utilize five control enablers and five capability tiers to compute scores. A binary questionnaire is used to capture data for the rating process. Based on a statistical analysis of CTI results from 35 pilot organizations, 28.57% are in the beginner group with high-risk exposure, 31.43% are in the leader group with low-risk exposure, and 40% of organizations are in between (the intermediate and advanced groups). Two key factors distinguish between the beginner and leader groups: (1) an internal factor, which is the Control Enablers; and (2) an external factor, which is the influence of a cyber regulating body. Our study confirms that Control Enablers in higher Tiers will help organizations achieve better cybersecurity performance (R = 0.98021) and highlights the significance of cyber regulating bodies by showing a shear difference of 197.53% in cyber performance between highly regulated and low-regulated industries. Conclusions: This research reveals key insights into the importance of Control Enablers, which are the internal factors that organizations must leverage to drive better cybersecurity performance, and the positive return on enforcement, which emphasizes the need for cyber regulating bodies. The CTI framework has proven to be valid and efficient for measuring cybersecurity performance. At the very least, a step-wise roadmap is provided for organizations and regulators to adopt and adapt the CTI framework for their cybersecurity measurement and improvement mission.
CO2 Corrosion Rate Prediction for Submarine Multiphase Flow Pipelines Based on Multi-Layer Perceptron
Authors: Wang Guoqing , Wang Changquan , Shi Lihong
Published: November 2022

The implementation of corrosion detection in submarine pipelines is difficult, and a combined PCA-MLP prediction model is proposed to improve the accuracy of corrosion prediction in submarine pipelines. Firstly, the corrosion rate of a submarine multiphase flow pipeline in the South China Sea is simulated by the De Waard 95 model in the multiphase flow transient simulation software OLGA and compared with the actual corrosion rate; then, according to the corrosion data simulated by OLGA, principal component analysis (PCA) is used to reduce the dimensionality of the corrosion factors in the pipeline, and the multiple linear regression model (MLR), multi-layer perceptron neural network (MLPNN), and radial basis function neural network (RBFNN) were optimized. The PCA-MLPNN model has an average relative error of 3.318%, an average absolute error of 0.0034, a root mean square error of 0.0082, a residual sum of squares of 0.0020, and a coefficient of determination of 0.8609. Compared with five models, including MLR, MLPNN, RBFNN, PCA-MLR, PCA-MLPNN, and PCA-RBFNN, PCA-MLPNN has higher prediction accuracy and better prediction performance. The above results indicate that the combined PCA-MLPNN model has a more reliable application capability in CO2 corrosion prediction of submarine pipelines.
About the Analysis of 18S rDNA Sequence Data from Trypanosomes in Barcoding and Phylogenetics: Tracing a Continuation Error Occurring in the Literature
Authors: Rackevei Antonia S. , Borges Alyssa , Engstler Markus , Dandekar Thomas , Wolf Matthias
Published: November 2022

The variable regions (V1–V9) of the 18S rDNA are routinely used in barcoding and phylogenetics. In handling these data for trypanosomes, we have noticed a misunderstanding that has apparently taken a life of its own in the literature over the years. In particular, in recent years, when studying the phylogenetic relationship of trypanosomes, the use of V7/V8 was systematically established. However, considering the current numbering system for all other organisms (including other Euglenozoa), V7/V8 was never used. In Maia da Silva et al. [Parasitology 2004, 129, 549–561], V7/V8 was promoted for the first time for trypanosome phylogenetics, and since then, more than 70 publications have replicated this nomenclature and even discussed the benefits of the use of this region in comparison to V4. However, the primers used to amplify the variable region of trypanosomes have actually amplified V4 (concerning the current 18S rDNA numbering system).
Role of AMPK-SREBP Signaling in Regulating Fatty Acid Binding-4 (FABP4) Expression following Ethanol Metabolism
Authors: Attal Neha , Marrero Emilio , Thompson Kyle J. , McKillop Iain H.
Published: November 2022

Fatty acid binding protein-4 (FABP4) is not normally expressed in the liver but is induced in alcohol-dependent liver disease (ALD)). This study sought to identify mechanisms whereby ethanol (EtOH) metabolism alters triglyceride accumulation and FABP4 production. Human hepatoma cells which were stably transfected to express alcohol dehydrogenase (ADH) or cytochrome P4502E1 (CYP2E1) were exposed to EtOH in the absence/presence of inhibitors of ADH (4-methylpyrazole) or CYP2E1 (chlormethiazole). Cells were analyzed for free fatty acid (FFA) content and FABP4 mRNA, then culture medium assayed for FABP4 levels. Cell lysates were analyzed for AMP-activated protein kinase-α (AMPKα), Acetyl-CoA carboxylase (ACC), sterol regulatory element binding protein-1c (SREBP-1c), and Lipin-1β activity and localization in the absence/presence of EtOH and pharmacological inhibitors. CYP2E1-EtOH metabolism led to increased FABP4 mRNA/protein expression and FFA accumulation. Analysis of signaling pathway activity revealed decreased AMPKα activation and increased nuclear-SREBP-1c localization following CYP2E1-EtOH metabolism. The role of AMPKα-SREBP-1c in regulating CYP2E1-EtOH-dependent FFA accumulation and increased FABP4 was confirmed using pharmacological inhibitors and over-expression of AMPKα. Inhibition of ACC or Lipin-1β failed to prevent FFA accumulation or changes in FABP4 mRNA expression or protein secretion. These data suggest that CYP2E1-EtOH metabolism inhibits AMPKα phosphorylation to stimulate FFA accumulation and FABP4 protein secretion via an SREBP-1c dependent mechanism.
Inhibition of Autophagy Promotes the Elimination of Liver Cancer Stem Cells by CD133 Aptamer-Targeted Delivery of Doxorubicin
Authors: Yin Wang , Pham Cuong V. , Wang Tao , Al Shamaileh Hadi , Chowdhury Rocky , Patel Shweta , Li Yong , Kong Lingxue , Hou Yingchu , Zhu Yimin , Chen Sunrui , Xu Huo , Jia Lee , Duan Wei , Xiang Dongxi
Published: November 2022

Doxorubicin is the most frequently used chemotherapeutic agent for the treatment of hepatocellular carcinoma. However, one major obstacle to the effective management of liver cancer is the drug resistance derived from the cancer stem cells. Herein, we employed a CD133 aptamer for targeted delivery of doxorubicin into liver cancer stem cells to overcome chemoresistance. Furthermore, we explored the efficacy of autophagy inhibition to sensitize liver cancer stem cells to the treatment of CD133 aptamer-doxorubicin conjugates based on the previous observation that doxorubicin contributes to the survival of liver cancer stem cells by activating autophagy. The kinetics and thermodynamics of aptamer-doxorubicin binding, autophagy induction, cell apoptosis, and self-renewal of liver cancer stem cells were studied using isothermal titration calorimetry, Western blot analysis, annexin V assay, and tumorsphere formation assay. The aptamer-cell binding andintracellular accumulation of doxorubicin were quantified via flow cytometry. CD133 aptamer-guided delivery of doxorubicin resulted in a higher doxorubicin concentration in the liver cancer stem cells. The combinatorial treatment strategy of CD133 aptamer-doxorubicin conjugates and an autophagy inhibitor led to an over 10-fold higher elimination of liver cancer stem cells than that of free doxorubicin in vitro. Future exploration of cancer stem cell-targeted delivery of doxorubicin in conjunction with autophagy inhibition in vivo may well lead to improved outcomes in the treatment of hepatocellular carcinoma.
Pyroptosis: A Newly Discovered Therapeutic Target for Ischemia-Reperfusion Injury
Authors: Zheng Yu , Xu Xinda , Chi Fanglu , Cong Ning
Published: November 2022

Ischemia-reperfusion (I/R) injury, uncommon among patients suffering from myocardial infarction, stroke, or acute kidney injury, can result in cell death and organ dysfunction. Previous studies have shown that different types of cell death, including apoptosis, necrosis, and autophagy, can occur during I/R injury. Pyroptosis, which is characterized by cell membrane pore formation, pro-inflammatory cytokine release, and cell burst, and which differentiates itself from apoptosis and necroptosis, has been found to be closely related to I/R injury. Therefore, targeting the signaling pathways and key regulators of pyroptosis may be favorable for the treatment of I/R injury, which is far from adequate at present. This review summarizes the current status of pyroptosis and its connection to I/R in different organs, as well as potential treatment strategies targeting it to combat I/R injury.
Polymer-Nanodiscs as a Novel Alignment Medium for High-Resolution NMR-Based Structural Studies of Nucleic Acids
Authors: Krishnarjuna Bankala , Ravula Thirupathi , Faison Edgar M. , Tonelli Marco , Zhang Qi , Ramamoorthy Ayyalusamy
Published: November 2022

Residual dipolar couplings (RDCs) are increasingly used for high-throughput NMR-based structural studies and to provide long-range angular constraints to validate and refine structures of various molecules determined by X-ray crystallography and NMR spectroscopy. RDCs of a given molecule can be measured in an anisotropic environment that aligns in an external magnetic field. Here, we demonstrate the first application of polymer-based nanodiscs for the measurement of RDCs from nucleic acids. Polymer-based nanodiscs prepared using negatively charged SMA-EA polymer and zwitterionic DMPC lipids were characterized by size-exclusion chromatography, 1H NMR, dynamic light-scattering, and 2H NMR. The magnetically aligned polymer-nanodiscs were used as an alignment medium to measure RDCs from a 13C/15N-labeled fluoride riboswitch aptamer using 2D ARTSY-HSQC NMR experiments. The results showed that the alignment of nanodiscs is stable for nucleic acids and nanodisc-induced RDCs fit well with the previously determined solution structure of the riboswitch. These results demonstrate that SMA-EA-based lipid-nanodiscs can be used as a stable alignment medium for high-resolution structural and dynamical studies of nucleic acids, and they can also be applicable to study various other biomolecules and small molecules in general.
Current and Novel Therapeutic Approaches for Treatment of Neovascular Age-Related Macular Degeneration
Authors: ElSheikh Reem H. , Chauhan Muhammad Z. , Sallam Ahmed B.
Published: November 2022

Age-related macular degeneration AMD is one of the leading causes of blindness in the elderly population. An advanced form of AMD known as neovascular AMD (nAMD) is implicated as the main attributor of visual loss among these patients. The hallmark feature of nAMD is the presence of neovascular structures known as choroidal neovascular membranes (CNVs), along with fluid exudation, hemorrhages, and subretinal fibrosis. These pathological changes eventually result in anatomical and visual loss. A type of proangiogenic factor known as vascular endothelial growth factor (VEGF) has been known to mediate the pathological process behind nAMD. Therefore, therapy has transitioned over the years from laser therapy that ablates the lesions to using Anti-VEGF to target the pathology directly. In this work, we provide an overview of current and emerging therapies for the treatment of nAMD. Currently approved Anti-VEGF agents include ranibizumab, aflibercept, and brolucizumab. Bevacizumab, also an Anti-VEGF agent, is used to manage nAMD even though this is an off-label use. While Anti-VEGF agents have provided a favorable prognosis for nAMD, they are associated with a substantial financial burden for patients and the healthcare system, due to their high cost as well as the need for frequent repeat treatments and visits. Emerging therapies and studies aim to extend the intervals between required treatments and introduce new treatment modalities that would improve patients’ compliance and provide superior results.
Assessing the Formation of Purine Lesions in Mitochondrial DNA of Cockayne Syndrome Cells
Authors: Chatgilialoglu Chryssostomos , Krokidis Marios G. , Masi Annalisa , Barata-Vallejo Sebastian , Ferreri Carla , Pascucci Barbara , D’Errico Mariarosaria
Published: November 2022

Mitochondrial (mt) DNA and nuclear (n) DNA have known structures and roles in cells; however, they are rarely compared under specific conditions such as oxidative or degenerative environments that can create damage to the DNA base moieties. Six purine lesions were ascertained in the mtDNA of wild type (wt) CSA (CS3BE–wtCSA) and wtCSB (CS1AN–wtCSB) cells and defective counterparts CS3BE and CS1AN in comparison with the corresponding total (t) DNA (t = n + mt). In particular, the four 5′,8–cyclopurine (cPu) and the two 8–oxo–purine (8–oxo–Pu) lesions were accurately quantified by LC–MS/MS analysis using isotopomeric internal standards after an enzymatic digestion procedure. The 8–oxo–Pu levels were found to be in the range of 25–50 lesions/107 nucleotides in both the mtDNA and tDNA. The four cPu were undetectable in the mtDNA both in defective cells and in the wt counterparts (CSA and CSB), contrary to their detection in tDNA, indicating a nonappearance of hydroxyl radical (HO•) reactivity within the mtDNA. In order to assess the HO• reactivity towards purine nucleobases in the two genetic materials, we performed γ–radiolysis experiments coupled with the 8–oxo–Pu and cPu quantifications on isolated mtDNA and tDNA from wtCSB cells. In the latter experiments, all six purine lesions were detected in both of the DNA, showing a higher resistance to HO• attack in the case of mtDNA compared with tDNA, likely due to their different DNA helical topology influencing the relative abundance of the lesions.
A Pan-Draft Metabolic Model Reflects Evolutionary Diversity across 332 Yeast Species
Authors: Lu Hongzhong , Kerkhoven Eduard J. , Nielsen Jens
Published: November 2022

Yeasts are increasingly employed in synthetic biology as chassis strains, including conventional and non-conventional species. It is still unclear how genomic evolution determines metabolic diversity among various yeast species and strains. In this study, we constructed draft GEMs for 332 yeast species using two alternative procedures from the toolbox RAVEN v 2.0. We found that draft GEMs could reflect the difference in yeast metabolic potentials, and therefore, could be utilized to probe the evolutionary trend of metabolism among 332 yeast species. We created a pan-draft metabolic model to account for the metabolic capacity of every sequenced yeast species by merging all draft GEMs. Further analysis showed that the pan-reactome of yeast has a “closed” property, which confirmed the great conservatism that exists in yeast metabolic evolution. Lastly, the quantitative correlations among trait similarity, evolutionary distances, genotype, and model similarity were thoroughly investigated. The results suggest that the evolutionary distance and genotype, to some extent, determine model similarity, but not trait similarity, indicating that multiple mechanisms shape yeast trait evolution. A large-scale reconstruction and integrative analysis of yeast draft GEMs would be a valuable resource to probe the evolutionary mechanism behind yeast trait variety and to further refine the existing yeast species-specific GEMs for the community.
Endoplasmic Reticulum Stress in Chronic Obstructive Pulmonary Disease: Mechanisms and Future Perspectives
Authors: Yu Yue , Yang Ailin , Yu Ganggang , Wang Haoyan
Published: November 2022

The endoplasmic reticulum (ER) is an integral organelle for maintaining protein homeostasis. Multiple factors can disrupt protein folding in the lumen of the ER, triggering ER stress and activating the unfolded protein response (UPR), which interrelates with various damage mechanisms, such as inflammation, apoptosis, and autophagy. Numerous studies have linked ER stress and UPR to the progression of chronic obstructive pulmonary disease (COPD). This review focuses on the mechanisms of other cellular processes triggered by UPR and summarizes drug intervention strategies targeting the UPR pathway in COPD to explore new therapeutic approaches and preventive measures for COPD.
Gelatin-Based Electrospun Nanofibers Cross-Linked Using Horseradish Peroxidase for Plasmid DNA Delivery
Authors: Furuno Kotoko , Suzuki Keiichiro , Sakai Shinji
Published: November 2022

The delivery of nucleic acids is indispensable for tissue engineering and gene therapy. However, the current approaches involving DNA/RNA delivery by systemic and local injections face issues such as clearance, off-target distribution, and tissue damage. In this study, we report plasmid DNA (pDNA) delivery using gelatin electrospun nanofibers obtained through horseradish peroxidase (HRP)-mediated insolubilization. The nanofibers were obtained through the electrospinning of an aqueous solution containing gelatin possessing phenolic hydroxyl (Ph) moieties (Gelatin-Ph) and HRP with subsequent HRP-mediated cross-linking of the Ph moieties by exposure to air containing 16 ppm H2O2 for 30 min. Then, Lipofectamine/pDNA complexes were immobilized on the nanofibers through immersion in the solution containing the pDNA complexes, resulting in transfection and sustained delivery of pDNA. Cells cultured on the resultant nanofibers expressed genome-editing molecules including Cas9 protein and guide RNA (gRNA), resulting in targeted gene knock-in and knock-out. These results demonstrated the potential of Gelatin-Ph nanofibers obtained through electrospinning and subsequent HRP-mediated cross-linking for gene therapy and tissue regeneration by genome editing.
Rota-Lithotripsy as a Novel Bail-Out Strategy for Highly Calcified Coronary Lesions in Acute Coronary Syndrome
Authors: Rola Piotr , Furtan Łukasz , Włodarczak Szymon , Kulczycki Jan Jakub , Barycki Mateusz , Szudrowicz Marek , Kędzierska Michalina , Pszonka Anna , Korus Justyna , Doroszko Adrian , Lesiak Maciej , Włodarczak Adrian
Published: November 2022

Background: Heavily calcified lesions in acute coronary syndrome (ACS) still represent a challenging subset for percutaneous coronary intervention (PCI). Rota-lithotripsy—a marriage of rotational atherectomy and intravascular lithotripsy—has recently been introduced to clinical practice as a novel therapeutic option. Methods: This study is among the to present the 6-month clinical outcomes of rota-lithotripsy when performed in the ACS setting. The study cohort consisted of 15 consecutive ACS patients who underwent a rota-lithotripsy-PCI due to the presence of a highly calcified, undilatable lesion. Results: The procedural success ratio reached 100%. During the 6-month follow-up, in two of the patients, instances of MACE (major adverse cardiac events) occurred, including one fatal event. Additionally, during the observation period, one target lesion failure, due to subacute stent thrombosis, was identified. Conclusions: Rotational atherectomy with the subsequent use of shockwave intravascular lithotripsy appears to be a safe and effective therapeutic bail-out option for the management of highly calcified coronary artery lesions. Despite, these initial favorable outcomes, carrying out a large number of studies with long-term observations is still necessary in order to establish the potential benefits and shortcomings of rota-lithotripsy.
A Deep Convolutional Neural Network for the Early Detection of Heart Disease
Authors: Arooj Sadia , Rehman Saif ur , Imran Azhar , Almuhaimeed Abdullah , Alzahrani A. Khuzaim , Alzahrani Abdulkareem
Published: November 2022

Heart disease is one of the key contributors to human death. Each year, several people die due to this disease. According to the WHO, 17.9 million people die each year due to heart disease. With the various technologies and techniques developed for heart-disease detection, the use of image classification can further improve the results. Image classification is a significant matter of concern in modern times. It is one of the most basic jobs in pattern identification and computer vision, and refers to assigning one or more labels to images. Pattern identification from images has become easier by using machine learning, and deep learning has rendered it more precise than traditional image classification methods. This study aims to use a deep-learning approach using image classification for heart-disease detection. A deep convolutional neural network (DCNN) is currently the most popular classification technique for image recognition. The proposed model is evaluated on the public UCI heart-disease dataset comprising 1050 patients and 14 attributes. By gathering a set of directly obtainable features from the heart-disease dataset, we considered this feature vector to be input for a DCNN to discriminate whether an instance belongs to a healthy or cardiac disease class. To assess the performance of the proposed method, different performance metrics, namely, accuracy, precision, recall, and the F1 measure, were employed, and our model achieved validation accuracy of 91.7%. The experimental results indicate the effectiveness of the proposed approach in a real-world environment.
Epigenome-Wide Association Study in Peripheral Tissues Highlights DNA Methylation Profiles Associated with Episodic Memory Performance in Humans
Authors: Sommerer Yasmine , Dobricic Valerija , Schilling Marcel , Ohlei Olena , Bartrés-Faz David , Cattaneo Gabriele , Demuth Ilja , Düzel Sandra , Franzenburg Sören , Fuß Janina , Lindenberger Ulman , Pascual-Leone Álvaro , Sabet Sanaz Sedghpour , Solé-Padullés Cristina , Tormos Josep M. , Vetter Valentin Max , Wesse Tanja , Franke Andre , Lill Christina M. , Bertram Lars
Published: November 2022

The decline in episodic memory (EM) performance is a hallmark of cognitive aging and an early clinical sign in Alzheimer’s disease (AD). In this study, we conducted an epigenome-wide association study (EWAS) using DNA methylation (DNAm) profiles from buccal and blood samples for cross-sectional (n = 1019) and longitudinal changes in EM performance (n = 626; average follow-up time 5.4 years) collected under the auspices of the Lifebrain consortium project. The mean age of participants with cross-sectional data was 69 ± 11 years (30–90 years), with 50% being females. We identified 21 loci showing suggestive evidence of association (p < 1 × 10−5) with either or both EM phenotypes. Among these were SNCA, SEPW1 (both cross-sectional EM), ITPK1 (longitudinal EM), and APBA2 (both EM traits), which have been linked to AD or Parkinson’s disease (PD) in previous work. While the EM phenotypes were nominally significantly (p < 0.05) associated with poly-epigenetic scores (PESs) using EWASs on general cognitive function, none remained significant after correction for multiple testing. Likewise, estimating the degree of “epigenetic age acceleration” did not reveal significant associations with either of the two tested EM phenotypes. In summary, our study highlights several interesting candidate loci in which differential DNAm patterns in peripheral tissue are associated with EM performance in humans.
Prospective Clinical Evaluation of the Diagnostic Accuracy of a Highly Sensitive Rapid Antigen Test Using Silver Amplification Technology for Emerging SARS-CoV-2 Variants
Authors: Obata Kazuaki , Miyakawa Kei , Takei Toshiki , Wada Atsuhiko , Hatayama Yasuyoshi , Kato Hideaki , Kimura Yayoi , Sekino Hisakuni , Katada Junichi , Ryo Akihide
Published: November 2022

The COVID-19 pandemic caused by SARS-CoV-2 remains a serious health concern worldwide due to outbreaks of SARS-CoV-2 variants that can escape vaccine-acquired immunity and infect and transmit more efficiently. Therefore, an appropriate testing method for COVID-19 is essential for effective infection control and the prevention of local outbreaks. Compared to reverse-transcription polymerase chain reaction (RT-PCR) tests, antigen tests are used for simple point-of-care testing, enabling the identification of viral infections. In this study, we tested the clinical usefulness of the FUJIFILM COVID-19 Ag test, an antigen test based on silver amplification and immunochromatographic technology. The FUJIFILM COVID-19 Ag test was shown to detect a lower viral concentration as compared to other conventional kits without significant performance loss in detecting prevalent SARS-CoV-2 variants. We tested nasopharyngeal and nasal swabs from a single patient during two different epidemic periods dominated by various SARS-CoV-2 variants. We observed that the sensitivity of the FUJIFILM COVID-19 Ag test was 95.7% and 85.7% in nasopharyngeal and nasal swabs, respectively. These results suggest that the FUJIFILM COVID-19 Ag test is highly sensitive and applicable when RT-PCR testing is unavailable. Furthermore, these results indicate that high-frequency testing using nasal swab specimens may be a valuable screening strategy.
Low Intensity Respiratory Muscle Training in COVID-19 Patients after Invasive Mechanical Ventilation: A Retrospective Case-Series Study
Authors: Villelabeitia-Jaureguizar Koldo , Calvo-Lobo César , Rodríguez-Sanz David , Vicente-Campos Davinia , Castro-Portal José Adrián , López-Cañadas Marta , Becerro-de-Bengoa-Vallejo Ricardo , Chicharro José López
Published: November 2022

Worldwide, healthcare systems had to respond to an exponential increase in COVID-19 patients with a noteworthy increment in intensive care units (ICU) admissions and invasive mechanical ventilation (IMV). The aim was to determine low intensity respiratory muscle training (RMT) effects in COVID-19 patients upon medical discharge and after an ICU stay with IMV. A retrospective case-series study was performed. Forty COVID-19 patients were enrolled and divided into twenty participants who received IMV during ICU stay (IMV group) and 20 participants who did not receive IMV nor an ICU stay (non-IMV group). Maximal expiratory pressure (PEmax), maximal inspiratory pressure (PImax), COPD assessment test (CAT) and Medical Research Council (MRC) dyspnea scale were collected at baseline and after 12 weeks of low intensity RMT. A greater MRC dyspnea score and lower PImax were shown at baseline in the IMV group versus the non-IMV group (p < 0.01). RMT effects on the total sample improved all outcome measurements (p < 0.05; d = 0.38–0.98). Intragroup comparisons after RMT improved PImax, CAT and MRC scores in the IMV group (p = 0.001; d = 0.94–1.09), but not for PImax in the non-IMV group (p > 0.05). Between-groups comparison after RMT only showed MRC dyspnea improvements (p = 0.020; d = 0.74) in the IMV group versus non-IMV group. Furthermore, PImax decrease was only predicted by the IMV presence (R2 = 0.378). Low intensity RMT may improve respiratory muscle strength, health related quality of life and dyspnea in COVID-19 patients. Especially, low intensity RMT could improve dyspnea level and maybe PImax in COVID-19 patients who received IMV in ICU.
Immune Checkpoint Molecules and Glucose Metabolism in HIV-Induced T Cell Exhaustion
Authors: Chan Yee Teng , Cheong Heng Choon , Tang Ting Fang , Rajasuriar Reena , Cheng Kian-Kai , Looi Chung Yeng , Wong Won Fen , Kamarulzaman Adeeba
Published: November 2022

The progressive decline of CD8+ cytotoxic T cells in human immunodeficiency virus (HIV)-infected patients due to infection-triggered cell exhaustion and cell death is significantly correlated with disease severity and progression into the life-threatening acquired immunodeficiency syndrome (AIDS) stage. T cell exhaustion is a condition of cell dysfunction despite antigen engagement, characterized by augmented surface expression of immune checkpoint molecules such as programmed cell death protein 1 (PD-1), which suppress T cell receptor (TCR) signaling and negatively impact the proliferative and effector activities of T cells. T cell function is tightly modulated by cellular glucose metabolism, which produces adequate energy to support a robust reaction when battling pathogen infection. The transition of the T cells from an active to an exhausted state following pathogen persistence involves a drastic change in metabolic activity. This review highlights the interplay between immune checkpoint molecules and glucose metabolism that contributes to T cell exhaustion in the context of chronic HIV infection, which could deliver an insight into the rational design of a novel therapeutic strategy.