bluuebunny/crossref_metadata_2025 huggingface dataset:
Genomic Analysis Reveals New Integrative Conjugal Elements and Transposons in GBS Conferring Antimicrobial Resistance
Authors: Khan Uzma Basit , Portal Edward A. R. , Sands Kirsty , Lo Stephanie , Chalker Victoria J. , Jauneikaite Elita , Spiller Owen B.
Published: March 2023

Streptococcus agalactiae or group B streptococcus (GBS) is a leading cause of neonatal sepsis and increasingly found as an invasive pathogen in older patient populations. Beta-lactam antibiotics remain the most effective therapeutic with resistance rarely reported, while the majority of GBS isolates carry the tetracycline resistance gene tet(M) in fixed genomic positions amongst five predominant clonal clades. In the UK, GBS resistance to clindamycin and erythromycin has increased from 3% in 1991 to 11.9% (clindamycin) and 20.2% (erythromycin), as reported in this study. Here, a systematic investigation of antimicrobial resistance genomic content sought to fully characterise the associated mobile genetic elements within phenotypically resistant GBS isolates from 193 invasive and non-invasive infections of UK adult patients collected during 2014 and 2015. Resistance to erythromycin and clindamycin was mediated by erm(A) (16/193, 8.2%), erm(B) (16/193, 8.2%), mef(A)/msr(D) (10/193, 5.1%), lsa(C) (3/193, 1.5%), lnu(C) (1/193, 0.5%), and erm(T) (1/193, 0.5%) genes. The integrative conjugative elements (ICEs) carrying these genes were occasionally found in combination with high gentamicin resistance mediating genes aac(6′)-aph(2″), aminoglycoside resistance genes (ant(6-Ia), aph(3′-III), and/or aad(E)), alternative tetracycline resistance genes (tet(O) and tet(S)), and/or chloramphenicol resistance gene cat(Q), mediating resistance to multiple classes of antibiotics. This study provides evidence of the retention of previously reported ICESag37 (n = 4), ICESag236 (n = 2), and ICESpy009 (n = 3), as well as the definition of sixteen novel ICEs and three novel transposons within the GBS lineage, with no evidence of horizontal transfer.
A Preclinical Model for Parkinson’s Disease Based on Transcriptional Gene Activation via KEAP1/NRF2 to Develop New Antioxidant Therapies
Authors: Segura-Aguilar Juan , Mannervik Bengt
Published: March 2023

Investigations of the effect of antioxidants on idiopathic Parkinson’s disease have been unsuccessful because the preclinical models used to propose these clinical studies do not accurately represent the neurodegenerative process of the disease. Treatment with certain exogenous neurotoxins induces massive and extremely rapid degeneration; for example, MPTP causes severe Parkinsonism in just three days, while the degenerative process of idiopathic Parkinson´s disease proceeds over many years. The endogenous neurotoxin aminochrome seems to be a good alternative target since it is formed in the nigrostriatal system neurons where the degenerative process occurs. Aminochrome induces all the mechanisms reported to be involved in the degenerative processes of idiopathic Parkinson’s disease. The presence of neuromelanin-containing dopaminergic neurons in the postmortem brain of healthy elderly people suggests that neuromelanin synthesis is a normal and harmless process despite the fact that it requires oxidation of dopamine to three ortho-quinones that are potentially toxic, especially aminochrome. The apparent contradiction that neuromelanin synthesis is harmless, despite its formation via neurotoxic ortho-quinones, can be explained by the protective roles of DT-diaphorase and glutathione transferase GSTM2-2 as well as the neuroprotective role of astrocytes secreting exosomes loaded with GSTM2-2. Increasing the expression of DT-diaphorase and GSTM2-2 may be a therapeutic goal to prevent the degeneration of new neuromelanin-containing dopaminergic neurons. Several phytochemicals that induce DT-diaphorase have been discovered and, therefore, an interesting question is whether these phytochemical KEAP1/NRF2 activators can inhibit or decrease aminochrome-induced neurotoxicity.
Imaging Microstructure on Optically Rough Surfaces Using Spatially Resolved Acoustic Spectroscopy
Authors: Li Wenqi , Dryburgh Paul , Pieris Don , Patel Rikesh , Clark Matt , Smith Richard J.
Published: March 2023

The microstructure of a material defines many of its mechanical properties. Tracking the microstructure of parts during their manufacturing is needed to ensure the designed performance can be obtained, especially for additively manufactured parts. Measuring the microstructure non-destructively on real parts is challenging for optical techniques such as laser ultrasound, as the optically rough surface impacts the ability to generate and detect acoustic waves. Spatially resolved acoustic spectroscopy can be used to measure the microstructure, and this paper presents the capability on a range of surface finishes. We discuss how to describe ’roughness’ and how this influences the measurements. We demonstrate that measurements can be made on surfaces with Ra up to 28 μm for a selection of roughness comparators. Velocity images on a range of real surface finishes, including machined, etched, and additively manufactured finishes in an as-deposited state, are presented. We conclude that the Ra is a poor descriptor for the ability to perform measurements as the correlation length of the roughness has a large impact on the ability to detected the surface waves. Despite this issue, a wide range of real industrially relevant surface conditions can be measured.
An Explainable Brain Tumor Detection Framework for MRI Analysis
Authors: Yan Fei , Chen Yunqing , Xia Yiwen , Wang Zhiliang , Xiao Ruoxiu
Published: March 2023

Explainability in medical images analysis plays an important role in the accurate diagnosis and treatment of tumors, which can help medical professionals better understand the images analysis results based on deep models. This paper proposes an explainable brain tumor detection framework that can complete the tasks of segmentation, classification, and explainability. The re-parameterization method is applied to our classification network, and the effect of explainable heatmaps is improved by modifying the network architecture. Our classification model also has the advantage of post-hoc explainability. We used the BraTS-2018 dataset for training and verification. Experimental results show that our simplified framework has excellent performance and high calculation speed. The comparison of results by segmentation and explainable neural networks helps researchers better understand the process of the black box method, increase the trust of the deep model output, and make more accurate judgments in disease identification and diagnosis.
Association of Ground Reaction Force Measurements in Runners with Symptomatic Iliotibial Band Friction Syndrome: A Cross-Sectional Study
Authors: de Souza Júnior José Roberto , Bradach Molly M. , Gaudette Logan W. , Tenforde Adam S.
Published: March 2023

Iliotibial band syndrome (ITBS) is a common running related injury. While previous studies have evaluated the relationship between biomechanical variables and ITBS, most have found limited evidence, particularly with measures related to ground reaction force (GRF). The purpose of this study was to use a classification and regression tree (CART) analysis to determine whether the combination of GRF measures would be strongly associated in runners with ITBS. A cross-sectional study was performed at an outpatient center focused on running injuries. A convenience sample of 52 runners with ITBS, assessed between September 2012 and July 2022, were evaluated for eligibility, from which, 30 rearfoot strike runners with ITBS and no secondary running-related injuries were selected. Injured runners were matched to 30 healthy controls from a normative database. Each ran on an instrumented treadmill at a self-selected speed. GRF variables were calculated, including peak GRFs, loading rates, and impulses. CART analysis was performed to identify interactions between GRF data and runners with ITBS. An ROC curve was executed, to determine the accuracy of the model. Posterior GRF impulse (PGRFI), anterior GRF (AGRFI), peak anterior GRF (PAGRF), and vertical stiffness at initial loading (VSIL) all emerged as variables associated with ITBS in the CART analysis. The model was able to correctly identify 25 (83.3%) runners with ITBS and 25 (83.3%) controls. The area under the ROC curve (accuracy) was 0.87 (95% CI, 0.77–0.96; SE, 0.04; p < 0.001). In conclusion, interactions between GRF variables were associated with ITBS in runners. The best classification included interactions between PGRFI, AGRFI, AGRFP, and VSIL, using specific cut-off values. Loading rates were not independently associated with ITBS.
Is Probiotics Supplementation an Appropriate Strategy to Modulate Inflammation in Physically Active Healthy Adults or Athletes? A Systematic Review
Authors: Fernández-Lázaro Diego , Sánchez-Serrano Nerea , Rabail Roshina , Aadil Rana Muhammad , Mielgo-Ayuso Juan , Radesca Fabiano Krizia , Garrosa Evelina
Published: March 2023

Supplementation with probiotics in sports is on the rise with the aim of improving health and athletic performance. Since intense exercise-induced muscle damage leads to an inflammatory process by increasing circulating inflammatory cytokines, probiotic supplementation may modulate and correct the inflammation. We systematically reviewed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines in the Scopus, Web of Science, and Medline databases for the 10 years until January 2023. This review aimed to evaluate probiotic supplementation as a strategy for modulating inflammation in healthy physically active adults or athletes. Studies were indexed to assess the effect of probiotic supplementation on cytokine behavior in the inflammatory response in physically active individuals. Of the 136 studies identified in the search, 13 met the inclusion criteria, and their quality was assessed using the McMaster Critical Review Form. The results of these trials indicated a significant improvement in inflammatory cytokines in probiotic-supplemented participants, with a significant increase in anti-inflammatory cytokines (IL-10) and a significant decrease in proinflammatory cytokines (IL-6, TNF-α, and IL-8). This would create uncertainty about probiotics’ effect on interleukins’ behavior after exercise, and further clinical trials are needed to establish a solid basis.
Wireless Covert Communication with Polarization Dirty Constellation
Authors: Hu Mingyu , Qiao Sen , Ji Xiaopeng
Published: March 2023

Wireless covert communication is an emerging communication technique that prevents eavesdroppers. This paper presents a novel approach to wireless covert communication based on polar codes with dirty constellation polarization. The feasibility of dirty constellation polarization is analyzed, and the impact of covert transmission power on undetectability is investigated. We polarize the covert channel and decode the covert information using a successive-cancellation decoder. Simulation results demonstrate that polar codes can significantly improve the undetectability and reliability of covert communication when compared to BCH codes. Additionally, we find that polarized covert channels achieve better undetectability and reliability when using a successive-cancellation list decoder. The proposed algorithm shows significant improvement in the undetectability and reliability of wireless covert communication with dirty constellations. This research provides a promising direction for future development in the field of covert communication, with potential applications in secure communication systems.
Reliability Assessment of Cyber–Physical Distribution Systems Considering Cyber Disturbances
Authors: Zhou Buxiang , Cai Yating , Zang Tianlei , Wu Jiale , Sun Binjie , Chen Shi
Published: March 2023

With the development of communication technology, traditional distribution networks have gradually developed into cyber–physical systems (CPSs), from which the cyber system provides more protection for the grid and brings new security threat–cyber disturbances. Current research cannot scientifically measure the impact of cyber disturbances on the system and lacks reliability indices for a comprehensive quantitative assessment of CPS reliability from the perspective of cyber–physical fusion. If the impact of information disturbances on system reliability is not assessed accurately, it will not be possible to provide a scientific and reasonable decision basis for system planning and operation. Therefore, a set of reliability assessment methods and indices for distribution network CPSs considering cyber disturbances is proposed. Firstly, a reliability modeling method combining fault tree and Petri net is proposed to model the reliability of a distribution network CPS, which can improve the efficiency and accuracy of the modeling. Secondly, the system state is divided into two categories: normal operation state and cyberattack state. Then, generalized reliability indices considering cyber disturbances for distribution network CPSs are defined. Finally, through the tests on the modified IEEE RBTS BUS2 distribution network CPS, an analysis of the effects of information component failures, cyberattacks, and access network structures on system reliability is conducted in this paper to verify the efficiency of the proposed method and the rationality of the newly defined reliability indices.
Vision Transformer Approach for Classification of Alzheimer’s Disease Using 18F-Florbetaben Brain Images
Authors: Shin Hyunji , Jeon Soomin , Seol Youngsoo , Kim Sangjin , Kang Doyoung
Published: March 2023

Dementia is a degenerative disease that is increasingly prevalent in an aging society. Alzheimer’s disease (AD), the most common type of dementia, is best mitigated via early detection and management. Deep learning is an artificial intelligence technique that has been used to diagnose and predict diseases by extracting meaningful features from medical images. The convolutional neural network (CNN) is a representative application of deep learning, serving as a powerful tool for the diagnosis of AD. Recently, vision transformers (ViT) have yielded classification performance exceeding that of CNN in some diagnostic image classifications. Because the brain is a very complex network with interrelated regions, ViT, which captures direct relationships between images, may be more effective for brain image analysis than CNN. Therefore, we propose a method for classifying dementia images by applying 18F-Florbetaben positron emission tomography (PET) images to ViT. Data were evaluated via binary (normal control and abnormal) and ternary (healthy control, mild cognitive impairment, and AD) classification. In a performance comparison with the CNN, VGG19 was selected as the comparison model. Consequently, ViT yielded more effective performance than VGG19 in binary classification. However, in ternary classification, the performance of ViT cannot be considered excellent. These results show that it is hard to argue that the ViT model is better at AD classification than the CNN model.
Frontier Research in Food Microbiology
Authors: Gervasi Teresa
Published: March 2023

I am pleased to introduce this Special Issue, which covers a wide range of areas [...]
On Selecting, Ranking, and Quantifying Features for Building a Liver CT Diagnosis Aiding Computational Intelligence Method
Authors: Kovács Melinda , Lilik Ferenc , Nagy Szilvia
Published: March 2023

The liver is one of the most common locations for incidental findings during abdominal CT scans. There are multiple types of disease that can arise within the liver and many of them are nodular. The ultimate goal of our research is to develop an expert knowledge-based system using fuzzy signatures, to support decisions during diagnosis of the most frequent of these nodular lesions. Since the literature contains limited information about the graphical properties of CT images that must be taken into consideration and their relationship to one another, in this paper we focused on selecting and ranking the input parameters using expert knowledge and determining their importance. Six visual attributes of lesions (size, shape, density, homogeneity contour, and other features) were selected based on textbooks of radiology and expert opinion. The importance of these attributes was ranked by radiologist experts using questionnaires and a pairwise comparison technique. The most important feature was found to be the density of the lesion on the various CT phases, and the least important was the size, the order of the other attributes was other features, contour, homogeneity, and shape, with a Kendall concordance coefficient of 0.612. Weights for the attributes, to be used in the future fuzzy signatures, were also determined. As a last step, several statistical parameter-based quantities were generated to represent the above abstract attributes and evaluated by comparing them to expert opinions.
Evaluation and Improvement of Internet Printing Protocol Based on HCPN Model Detection Method
Authors: Feng Tao , Bei Hong-Ru
Published: March 2023

The Internet Printing Protocol (IPP) is a bridge between hosts and printers, and is supported by more than 98 percent of printers today. In addition to supporting local use, the IPP protocol also supports online use. Although this can expand the scope of its application, it has also introduced potential risks to user data. IPP has security components that should be able to guarantee confidentiality, integrity, and non-repudiation. In order to verify whether its security components can achieve this goal, this study modeled the 0-RTT authentication process of the IPP protocol based on Petri net theory and CPN Tools, introducing the improved Dolev–Yao adversary model to perform security evaluation on the protocol model. The result showed that the server could not resist the adversary’s replay attacks on early data. Accordingly, we proposed an improved authentication scheme that introduced a random number signature to enhance the server’s anti-replay capability. Using the same attack model to verify, the result proved that the new scheme was feasible and effective. The method used in this article could easily observe the movement of the security protocol message flow and the specific actions of each participant (including the adversary), which ensured researchers could easily locate the protocol defects and make improvements.
A Domain-Based, Adaptive, Multi-Scale, Inter-Subject Sleep Stage Classification Network
Authors: Zhang Zhiwei , Tang Minfang
Published: March 2023

Sleep stage classification is of great importance in sleep analysis, which provides information for the diagnosis and monitoring of sleep-related conditions. To accurately analyze sleep structure under comfortable conditions, many studies have applied deep learning to sleep staging based on single-lead electrocardiograms (ECGs). However, there is still great room for improvement in inter-subject classification. In this paper, we propose an end-to-end, multi-scale, subject-adaptive network that improves the performance of the model according to the model architecture, training method, and loss calculation. In our investigation, a multi-scale residual feature encoder extracted various details to support the feature extraction of single-lead ECGs in different situations. After taking the domain shift caused by individual differences and acquisition conditions into consideration, we introduced a domain-aligning layer to confuse the domain. Moreover, to enhance the performance of the model, the multi-class focal loss was used to reduce the negative impact of class imbalance on the learning of the model, and the loss of sequence prediction was added to the classification task to assist the model in judging sleep stages. The model was evaluated on the public test datasets SHHS2, SHHS1, and MESA, and we obtained mean accuracies (Kappa) of 0.849 (0.837), 0.827 (0.790), and 0.868 (0.840) for awake/light sleep/deep sleep/REM stage classification, which confirms that this is an improved solution compared to the baseline. The model also performed outstandingly in cross-dataset testing. Hence, this article makes valuable contributions toward improving the reliability of sleep staging.
Large Scale Optical Assisted Mm-Wave Beam-Hopping System for Multi-Hop Bent-Pipe LEO Satellite Networks
Authors: Xia Shiyi , Liu Peilong , Zhao Mingyang , Zou Cheng , Shao Fengwei , Jin Jifeng , Wang Haiwang , Li Guotong
Published: March 2023

By introducing the arrayed waveguide router (AWGR) optical true time-delay (OTTD) architecture in bent-pipe satellite optical inter-link to optically assist the RF phased array in Low-earth orbit satellites will extend the multi-hop bent-pipe satellite beam-hopping protocol proposed in DVB-S2X. It solves the challenge of beam steering with the support of precise, broadband, and wide-range scanning. This architecture utilizes a subarray to combine the advantages of AWGR and a high-precision RF phase shifter to realize the beam pointing without an oblique view. Unlike the traditional digital and analog phased array architecture, the introduction of OTTD can solve the problem of beam squint and also ensure the high-precision scanning of the beam.
A Skin to Live in: Geometric Parietal Paintings in the Residential Architecture of al-Andalus
Authors: Blanco-Guzmán Rafael
Published: March 2023

Andalusi residential architecture is often described through planimetry or its internal constructive materiality. However, the real architectural vision of those who inhabited or visited Andalusi palaces or houses was completed by an important decorative epidermis that covered the structural materials and gave these Islamic buildings their final visual impact. Traditionally, the three-dimensional stone and plaster ornamentation has been the most analysed; the pictorial decoration that widely covered plinths has rarely been studied as a whole, despite the numerous remnants documented in recent decades. In this work, we propose a holistic and synthetic approach to this decorative architectural element, from its technical elaboration to its role in the three-dimensionality of Andalusi residential spaces. We also address its influences and its aesthetic evolution over the centuries.
A Perspective on the Link between Mitochondria-Associated Membranes (MAMs) and Lipid Droplets Metabolism in Neurodegenerative Diseases
Authors: Fernandes Tânia , Domingues M. Rosário , Moreira Paula I. , Pereira Cláudia F.
Published: March 2023

Mitochondria interact with the endoplasmic reticulum (ER) through contacts called mitochondria-associated membranes (MAMs), which control several processes, such as the ER stress response, mitochondrial and ER dynamics, inflammation, apoptosis, and autophagy. MAMs represent an important platform for transport of non-vesicular phospholipids and cholesterol. Therefore, this region is highly enriched in proteins involved in lipid metabolism, including the enzymes that catalyze esterification of cholesterol into cholesteryl esters (CE) and synthesis of triacylglycerols (TAG) from fatty acids (FAs), which are then stored in lipid droplets (LDs). LDs, through contact with other organelles, prevent the toxic consequences of accumulation of unesterified (free) lipids, including lipotoxicity and oxidative stress, and serve as lipid reservoirs that can be used under multiple metabolic and physiological conditions. The LDs break down by autophagy releases of stored lipids for energy production and synthesis of membrane components and other macromolecules. Pathological lipid deposition and autophagy disruption have both been reported to occur in several neurodegenerative diseases, supporting that lipid metabolism alterations are major players in neurodegeneration. In this review, we discuss the current understanding of MAMs structure and function, focusing on their roles in lipid metabolism and the importance of autophagy in LDs metabolism, as well as the changes that occur in neurogenerative diseases.
Impact of High-Performance Expansion and Shrinkage-Reducing Agents on the Mechanical Properties and Shrinkage Compensation of High-Strength Concrete
Authors: Xi Yun-Feng , Lee Jin , Chen Bao-Ling , Yang Bing , Yu Miao-Zhang , Yan Xiao-Zhou , Zhu Li
Published: March 2023

A large number of binder ingredients such as cement and active mineral admixtures are used in the preparation of high-strength concrete, and the water:binder ratio is extremely low. This leads to a large amount of shrinkage of concrete at the early stage of curing, which poses a great threat to the safety and durability of the structure. To solve the cracking problem of high-strength concrete induced by high shrinkage, we choose to change the admixture to solve it. In this study, a high-performance expansion agent (HPEA) and shrinkage-reducing agent, which are currently studied in a small number, were selected by changing the way of admixture, and their effects on the strength and shrinkage of high-strength concrete were compared and analyzed. The results show that the addition of a HPEA is beneficial to the compressive strength of concrete and sufficient expansion can be obtained by using a high amount of HPEA, but there is an excessive and delayed expansion to produce cracks in the later stage. A shrinkage-reducing agent plays an adverse role in the development of concrete strength, but it performs better in inhibiting shrinkage. The combination of a HPEA and shrinkage reducing agent can largely avoid the formation of cracks, and the two have a certain synergy. The main reason is that a HPEA compensates for some of the negative effects of a shrinkage-reducing agent on concrete strength, and the shrinkage-reducing agent further strengthens the inhibition effect of a HPEA on concrete shrinkage, and to some extent avoids the risk of cracks caused by delayed expansion caused by admixture problems.
Biowaste-Derived Heteroatom-Doped Porous Carbon as a Sustainable Electrocatalyst for Hydrogen Evolution Reaction
Authors: Atchudan Raji , Perumal Suguna , Jebakumar Immanuel Edison Thomas Nesakumar , Sundramoorthy Ashok K. , Karthik Namachivayam , Sangaraju Sambasivam , Choi Seung Tae , Lee Yong Rok
Published: March 2023

Heteroatom-doped porous carbon material (H-PCM) was synthesized using Anacardium occidentale (cashew) nut’s skin by a simple pyrolysis route. The resulting H-PCM was thoroughly characterized by various analytical techniques such as field emission scanning electron microscopy (FE-SEM) with energy-dispersive X-ray (EDX) spectroscopy, high-resolution transmittance electron microscopy (HRTEM), X-ray diffraction (XRD), Raman spectroscopy, nitrogen adsorption–desorption isotherms, X-ray photoelectron spectroscopy (XPS), and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy. The obtained results strongly demonstrated that the synthesized H-PCM exhibited a porous nature, continuous sponge-like and sheet-like smooth morphology, and a moderate degree of graphitization/crystallinity with oxygen-, nitrogen-, and sulfur-containing functionalities in the carbon matrix. After the structural confirmation, as-prepared H-PCM has used a sustainable electrocatalyst for hydrogen evolution reaction (HER) because the metal-free carbonaceous catalysts are one of the most promising candidates. The H-PCM showed excellent HER activities with a lowest Tafel slope of 75 mV dec−1 and durable stability in 0.5 M H2SO4 aqueous solution. Moreover, this work provides a versatile and effective strategy for designing excellent metal-free electrocatalysts from the cheapest biowaste/biomass for large-scale production of hydrogen gas through electrochemical water splitting.
Recent Developments and Perspectives of Cobalt Sulfide-Based Composite Materials in Photocatalysis
Authors: Chen Hui-Qi , Hao Jin-Ge , Wei Yu , Huang Wei-Ya , Zhang Jia-Lin , Deng Tao , Yang Kai , Lu Kang-Qiang
Published: March 2023

Photocatalysis, as an inexpensive and safe technology to convert solar energy, is essential for the efficient utilization of sustainable renewable energy sources. Earth-abundant cobalt sulfide-based composites have generated great interest in the field of solar fuel conversion because of their cheap, diverse structures and facile preparation. Over the past 10 years, the number of reports on cobalt sulfide-based photocatalysts has increased year by year, and more than 500 publications on the application of cobalt sulfide groups in photocatalysis can be found in the last three years. In this review, we initially summarize the four common strategies for preparing cobalt sulfide-based composite materials. Then, the multiple roles of cobalt sulfide-based cocatalysts in photocatalysis have been discussed. After that, we present the latest progress of cobalt sulfide in four fields of photocatalysis application, including photocatalytic hydrogen production, carbon dioxide reduction, nitrogen fixation, and photocatalytic degradation of pollutants. Finally, the development prospects and challenges of cobalt sulfide-based photocatalysts are discussed. This review is expected to provide useful reference for the construction of high-performance cobalt sulfide-based composite photocatalytic materials for sustainable solar-chemical energy conversion.
Recent Emerging Immunological Treatments for Primary Brain Tumors: Focus on Chemokine-Targeting Immunotherapies
Authors: Ardizzone Alessio , Basilotta Rossella , Filippone Alessia , Crupi Lelio , Lanza Marika , Lombardo Sofia Paola , Colarossi Cristina , Sciacca Dorotea , Cuzzocrea Salvatore , Esposito Emanuela , Campolo Michela
Published: March 2023

Primary brain tumors are a leading cause of death worldwide and are characterized by extraordinary heterogeneity and high invasiveness. Current drug and radiotherapy therapies combined with surgical approaches tend to increase the five-year survival of affected patients, however, the overall mortality rate remains high, thus constituting a clinical challenge for which the discovery of new therapeutic strategies is needed. In this field, novel immunotherapy approaches, aimed at overcoming the complex immunosuppressive microenvironment, could represent a new method of treatment for central nervous system (CNS) tumors. Chemokines especially are a well-defined group of proteins that were so named due to their chemotactic properties of binding their receptors. Chemokines regulate the recruitment and/or tissue retention of immune cells as well as the mobilization of tumor cells that have undergone epithelial–mesenchymal transition, promoting tumor growth. On this basis, this review focuses on the function and involvement of chemokines and their receptors in primary brain tumors, specifically examining chemokine-targeting immunotherapies as one of the most promising strategies in neuro-oncology.
Sestrin2 Mediates Metformin Rescued the Age-Related Cardiac Dysfunctions of Cardiorenal Syndrome Type 3
Authors: Iglesias Migdalia , Wang Hao , Krause-Hauch Meredith , Ren Di , Zoungrana Linda Ines , Li Zehui , Zhang Jie , Wei Jin , Yadav Nikita , Patel Kshama , Fatmi Mohammad Kasim , Liu Ruisheng , Lesnefsky Edward J. , Li Ji
Published: March 2023

Acute kidney injury (AKI) leads to acute cardiac injury and dysfunction in cardiorenal syndrome Type 3 (CRS3) through oxidative stress (OS). The stress-inducible Sestrin2 (Sesn2) protein reduces reactive oxygen species (ROS) accumulation and activates AMP-dependent protein kinase (AMPK) to regulate cellular metabolism and energetics during OS. Sesn2 levels and its protective effects decline in the aged heart. Antidiabetic drug metformin upregulates Sesn2 levels in response to ischemia–reperfusion (IR) stress. However, the role of metformin in CRS3 remains unknown. This study seeks to explore how the age-related decrease in cardiac Sesn2 levels contributes to cardiac intolerance to AKI-induced insults, and how metformin ameliorates CRS3 through Sesn2. Young (3–5 months) and aged (21–23 months) C57BL/6J wild-type mice along with cardiomyocyte-specific knockout (cSesn2−/−) and their wild type of littermate (Sesn2f/f) C57BL/6J mice were subjected to AKI for 15 min followed by 24 h of reperfusion. Cardiac and mitochondrial functions were evaluated through echocardiograms and seahorse mitochondria respirational analysis. Renal and cardiac tissue was collected for histological analysis and immunoblotting. The results indicate that metformin could significantly rescue AKI-induced cardiac dysfunction and injury via Sesn2 through an improvement in systolic and diastolic function, fibrotic and cellular damage, and mitochondrial function in young, Sesn2f/f, and especially aged mice. Metformin significantly increased Sesn2 expression under AKI stress in the aged left-ventricular tissue. Thus, this study suggests that Sesn2 mediates the cardioprotective effects of metformin during post-AKI.
Circulating Tumor Cells Predict Response of Neoadjuvant Chemotherapy in Patients with Bladder Cancer: A Preliminary Study
Authors: Jhuo Yu-Cing , Cha Tai-Lung , Kao Chien-Chang , Tsai Yi-Ta , Wu Sheng-Tang , Meng En , Tsao Chih-Wei , Chen Chin-Li , Ting Hui-Kung , Sun Guang-Huan , Yu Dah-Shyong , Chang Sun-Yran , Yang Ming-Hsin
Published: March 2023

This study aimed to explore the existence of circulating tumor cells (CTCs) in patients with muscle-invasive bladder cancer (MIBC) and their predictive potential for response to neoadjuvant chemotherapy (NAC). From 33 blood samples of MIBC patients, CTCs were isolated by cell surface markers and enriched by the IsoFlux™ device, followed by morphological and immunofluorescent identification. CTCs were detected at baseline in all samples. Immunofluorescence confirmed the tumor origin. MIBC patients were stratified by NAC response into the disease control (DC) and progressive disease (PD) groups. In the DC group, the number of CTCs decreased significantly after four courses of NAC (p < 0.0001). CTC counts in 7.5 mL after four NAC cycles were highly correlated with postoperative pathological T stage (p < 0.0001). Our study demonstrated that CTCs might represent a valuable predictive marker for NAC response in MIBC. CTC detection in MIBC patients could allow early arrangement of radical cystectomy for NAC non-responders to prevent disease progression while receiving the NAC courses.
The Prevalence of Virulence Factor Genes among Carbapenem-Non-Susceptible Acinetobacter baumannii Clinical Strains and Their Usefulness as Potential Molecular Biomarkers of Infection
Authors: Depka Dagmara , Bogiel Tomasz , Rzepka Mateusz , Gospodarek-Komkowska Eugenia
Published: March 2023

Healthcare-associated infections caused by multidrug-resistant Acinetobacter baumannii strains are a serious global threat. Therefore, it is important to expand the knowledge on the mechanisms of pathogenicity of these particular bacteria. The aim of this study was to assess the distribution of selected virulence factor genes (bap, surA1, omp33-36, bauA, bauS, and pld) among carbapenem-non-susceptible clinical A. baumannii isolates and to evaluate their potential usefulness as genetic markers for rapid diagnostics of A. baumannii infections. Moreover, we aimed to compare the virulence genes prevalence with the occurrence of carbapenemases genes. A total of 100 carbapenem-non-susceptible A. baumannii clinical isolates were included in the study. The presence of virulence factors and blaOXA genes was evaluated by real-time PCR. The occurrence of virulence factors genes was as follows: 100.0% for the bap and surA1 genes, 99.0% for the basD and pld genes. The bauA and omp33-36 genes were absent among the studied strains. The predominant genes (bap and surA1) are involved in biofilm formation and their presence among all clinical strains can be applied as a genetic marker to recognize A. baumannii infection. High frequencies of the basD gene—involved in siderophore biosynthesis and the gene encoding phospholipase D (pld)—were also noted among blaOXA-positive strains, showing their potential role in a pathogenicity of blaOXA-positive A. baumannii clinical strains.
Citizenship Outcomes and Place-Based Learning Environments in an Integrated Environmental Studies Program
Authors: Sturrock Gordon Robert , Zandvliet David Bryan
Published: March 2023

This paper discusses the effects of the learning environment on an important and unique 21st century learning outcome—that of active citizenship, in contrast to more conventionally measured cognitive and attitudinal outcomes. In our study, we utilized a learning environment instrument, the Place-Based Learning and Constructivist Environment Survey (PLACES) with an integrated environmental studies program prepared for high school students in the Canadian context. Our research used a retrospective case study design to investigate how aspects of this unique learning environment are related to long-term, active citizenship outcomes as perceived by students from two previous student cohorts (N = 24 and N = 36) who were contacted several years after the culmination of the program. To access information about student perceptions, PLACES was implemented as part of a range of mixed methods which also included focus groups and interviews. This study is important because it links key aspects of the learning environment to long-term citizenship outcomes and is unique in that the data were collected five and eight years later as part of a longitudinal study. Our findings demonstrate that the learning environment and citizenship outcomes were closely linked, and that students’ perceptions as measured by the PLACES instrument (past and present) were remarkably stable across all dimensions. These findings further indicate significant and positive implications for future learning environments research.
A Lightweight Anomaly Detection System for Black Hole Attack
Authors: Abdelhamid Ashraf , Elsayed Mahmoud Said , Jurcut Anca D. , Azer Marianne A.
Published: March 2023

Mobile ad hoc networks (MANETs) are now key in today’s new world. They are critically needed in many situations when it is crucial to form a network on the fly while not having the luxury of time or resources to configure devices, build infrastructure, or even have human interventions. Ad hoc networks have many applications. For instance, they can be used in battlefields, education, rescue missions, and many other applications. Such networks are characterized by high mobility, low resources of power, storage, and processing. They are infrastructure-less; this means that they don’t use infrastructure equipment for communication. These networks rely instead on each other for routing and communication. MANETs use a hopping mechanism where each node in a network finds another node within its communication range and use it as a hop for delivering the message through another node and so on. In standard networks, there is dedicated equipment for specific functions such as routers, servers, firewalls, etc., while in ad hoc networks, every node performs multiple functions. For example, the routing function is performed by nodes. Hence, they are more vulnerable to attacks than standard networks. The main goal of this paper is to propose a solution for detecting black hole attacks using anomaly detection based on a support vector machine (SVM). This detection system aims at analyzing the traffic of the network and identifying anomalies by checking node behaviors. In the case of black hole attacks, the attacking nodes have some behavioral characteristics that are different from normal nodes. These characteristics can be effectively detected using our lightweight detection system. To experiment with the effectiveness of this solution, an OMNET++ simulator is used to generate traffic under a black hole attack. The traffic is then classified into malicious and non-malicious based on which the malicious node is identified. The results of the proposed solution showed very high accuracy in detecting black hole attacks.
Night Vision Anti-Halation Algorithm Based on Different-Source Image Fusion Combining Visual Saliency with YUV-FNSCT
Authors: Guo Quanmin , Yang Fan , Wang Hanlei
Published: March 2023

In order to address driver’s dazzle caused by the abuse of high beams when vehicles meet at night, a night vision anti-halation algorithm based on image fusion combining visual saliency with YUV-FNSCT is proposed. Improved Frequency-turned (FT) visual saliency detection is proposed to quickly lock on the objects of interest, such as vehicles and pedestrians, so as to improve the salient features of fusion images. The high- and low-frequency sub-bands of infrared saliency images and visible luminance components can quickly be obtained using fast non-subsampled contourlet transform (FNSCT), which has the characteristics of multi-direction, multi-scale, and shift-invariance. According to the halation degree in the visible image, the nonlinear adaptive fusion strategy of low-frequency weight reasonably eliminates halation while retaining useful information from the original image to the maximum extent. The statistical matching feature fusion strategy distinguishes the common and unique edge information from the high-frequency sub-bands by mutual matching so as to obtain more effective details of the original images such as the edges and contours. Only the luminance Y decomposed by YUV transform is involved in image fusion, which not only avoids color shift of the fusion image but also reduces the amount of computation. Considering the night driving environment and the degree of halation, the visible images and infrared images were collected for anti-halation fusion in six typical halation scenes on three types of roads covering most night driving conditions. The fused images obtained by the proposed algorithm demonstrate complete halation elimination, rich color details, and obvious salient features and have the best comprehensive index in each halation scene. The experimental results and analysis show that the proposed algorithm has advantages in halation elimination and visual saliency and has good universality for different night vision halation scenes, which help drivers to observe the road ahead and improve the safety of night driving. It also has certain applicability to rainy, foggy, smoggy, and other complex weather.
Evolution of CCUS Technologies Using LDA Topic Model and Derwent Patent Data
Authors: Huang Liangchao , Hou Zhengmeng , Fang Yanli , Liu Jianhua , Shi Tianle
Published: March 2023

Carbon capture, utilization, and storage (CCUS) technology is considered an effective way to reduce greenhouse gases, such as carbon dioxide (CO2), which is significant for achieving carbon neutrality. Based on Derwent patent data, this paper explored the technology topics in CCUS patents by using the latent Dirichlet allocation (LDA) topic model to analyze technology’s hot topics and content evolution. Furthermore, the logistic model was used to fit the patent volume of the key CCUS technologies and predict the maturity and development trends of the key CCUS technologies to provide a reference for the future development of CCUS technology. We found that CCUS technology patents are gradually transforming to the application level, with increases in emerging fields, such as computer science. The main R&D institutes in the United States, Europe, Japan, Korea, and other countries are enterprises, while in China they are universities and research institutes. Hydride production, biological carbon sequestration, dynamic monitoring, geological utilization, geological storage, and CO2 mineralization are the six key technologies of CCUS. In addition, technologies such as hydride production, biological carbon sequestration, and dynamic monitoring have good development prospects, such as CCUS being coupled with hydrogen production to regenerate synthetic methane and CCUS being coupled with biomass to build a dynamic monitoring and safety system.
Reduction in CO Emission from Small Reciprocating Engine Operated with Wood Gasifier by Mixture LHV Changing
Authors: Enomoto Hiroshi , Nakagawa Ryo
Published: March 2023

In order to exchange the wood biomass energy for electric power with small capacity and high efficiency, it is most effective to use a reciprocating engine operated with a wood gasifier. On the other hand, such a small-capacity system is often installed in urban areas. Therefore, strict emission regulation should be observed. Normally, as the low heating value (LHV) of bio-syngas is small, the engine should be operated with a stoichiometric mixture to achieve a maximum power density. However, the emission with a stoichiometric mixture contains much unburned CO. This means that a stoichiometric mixture operation shows low efficiency and can’t observe the regulations. In this report, a mechanism of the unburned CO is considered, and a method to reduce the unburned CO ratio is shown with experimental results. In the experiment, a commercial reciprocating engine (4-stroke, modified single cylinder) is used. The bio-syngas, a producer gas from a fixed bed gasifier, is produced by a self-made wood pellet gasifier (fixed bed, auto thermal down-draft). The bio-syngas flow rate is calculated with the nitrogen ratio between input air and bio-syngas. The LHV is adjusted with the city gas (as an alternative to methane) and hydrogen. The CO volume ratio of the exhaust from the engine is more than 3 v% when the excess air ratio of bio-syngas/air mixture is 1.3, as the LHV of bio-syngas is less than 5.0 MJ/m3-LHV. On the other hand, the CO volume ratio of the exhaust under operation of the mixture, the bio-syngas, and methane with more than 7.0 MJ/m3-LHV was less than 0.2 v%. The CO in the exhaust with low LHV fuel means that the combustion is not finished in the chamber. The unburned ratio could be predicted in consideration of the gap/clearance as crevice, the temperature boundary layer, and the quenching distance.
Analysis of Surrogate Models for Vapour Transport and Distribution in a Hollow Fibre Membrane Humidifier
Authors: Pollak Markus , Bekemeyer Philipp , Lemke Nicholas , Tegethoff Wilhelm , Koehler Juergen
Published: March 2023

To achieve high efficiency and low degradation of a polymer electrolyte fuel cell (PEMFC), it is necessary to maintain an appropriate level of humidification in the fuel cell membrane. Thus, membrane humidifiers are typically used in PEMFC systems. Parameter studies are important to evaluate membrane humidifiers under various operating conditions to reduce the amount of physical tests. However, simulative studies are computationally expensive when using detailed models. To reduce the computational cost, surrogate models are set up. In our study, a 3D computational fluid dynamics (CFD) model of a hollow fibre membrane humidifier is presented and validated using measurement data. Based on the results of the validated CFD model, a surrogate model of the humidifier is constructed using proper orthogonal decomposition (POD) in combination with different interpolation methods. To evaluate the surrogate models, their results are compared against reference solutions from the CFD model. Our results show that a Halton design combined with a thin-plate-spline interpolation results in the most accurate surrogate humidifier model. Its normalised mean absolute error for 18 test points when predicting the water mass fraction in the membrane humidifier is 0.58%. Furthermore, it is demonstrated that the solutions of the POD model can be used to initialise CFD calculations and thus accelerate the calculation of steady state CFD solutions.