bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization of the Random Forest Hyperparameters for Power Industrial Control Systems Intrusion Detection Using an Improved Grid Search Algorithm
Authors: Zhu Ningyuan , Zhu Chaoyang , Zhou Liang , Zhu Yayun , Zhang Xiaojuan
Published: October 2022

The intrusion detection method of power industrial control systems is a crucial aspect of assuring power security. However, traditional intrusion detection methods have two drawbacks: first, they are mainly used for defending information systems and lack the ability to detect attacks against power industrial control systems; and second, although machine learning-based intrusion detection methods perform well with the default hyperparameters, optimizing the hyperparameters can significantly improve its performance. In response to these limitations, a random forest (RF)-based intrusion detection model for power industrial control systems is proposed. Simultaneously, this paper proposes an improved grid search algorithm (IGSA) for optimizing the hyperparameters of the RF intrusion detection model to improve its efficiency and effectiveness. The proposed IGSA boosts the speed of calculation from O(nm) to O(n × m). The suggested model is evaluated based on the public power industrial control system dataset after hyperparameter optimization. The experiment results show that our method achieves a superior detection performance with the accuracy of 98% and has more outstanding performance than the same type of work.
Spatiotemporal Variation of Land Surface Temperature Retrieved from FY-3D MERSI-II Data in Pakistan
Authors: Abbasi Bilawal , Qin Zhihao , Du Wenhui , Fan Jinlong , Li Shifeng , Zhao Chunliang
Published: October 2022

The concept of land surface temperature (LST) encompasses both surface energy balance and land surface activities. The study of climate change greatly benefits from an understanding of the geographical and temporal fluctuations of LST. In this study, we utilized an improved version of the TFSW algorithm to retrieve the LST from the Medium resolution spectral imager II (MERSI-II) data for the first time in Pakistan. MERSI-II is a payload for the Chinese meteorological satellite Fengyun 3D (FY-3D), and it has the capability for use in various remote sensing applications such as climate change and drought monitoring, with higher spatial and temporal resolutions. Once the LSTs were retrieved, accuracy of the LSTs were investigated. Later, LST datasets were used to detect the spatiotemporal variations of LST in Pakistan. Monthly, seasonal, and annual datasets were utilized to detect increasing and decreasing LST trends in the regions, with Mann–Kendall and Sen’s slope estimator tool. In addition, we further revealed the long-term spatiotemporal variations of LST by utilizing Moderate Resolution Imaging Spectrometer (MODIS) LST observations. The cross-validation analysis shows that the retrieved LST of MERSI-II was more consistent with the MODIS MYD11A1 LST product compared to the MYD21A1. The spatial distribution of LSTs demonstrates that the mean LST exhibits a pattern of spatial variability, with high values in the southern areas and low values in the northern areas; there are areas that do not follow this trend, possibly due to reasons of elevation and types of land cover also influencing the LST’s spatial distribution. The annual mean LST trend increases in the northern regions and decreases in the southern regions, ranging between −0.013 and 0.019 °C/year. The trend of long-term analysis were also consistent with MERSI-II, excepting region II, with increasing effects. This study will be helpful for various environmental and climate change studies.
Classification of Valvular Regurgitation Using Echocardiography
Authors: Wahlang Imayanmosha , Hassan Sk Mahmudul , Maji Arnab Kumar , Saha Goutam , Jasinski Michal , Leonowicz Zbigniew , Jasinska Elzbieta
Published: October 2022

Echocardiography (echo) is a commonly utilized tool in the diagnosis of various forms of valvular heart disease for its ability to detect types of cardiac regurgitation. Regurgitation represents irregularities in cardiac function and the early detection of regurgitation is necessary to avoid invasive cardiovascular surgery. In this paper, we focussed on the classification of regurgitations from videographic echo images. Three different types of regurgitation are considered in this work, namely, aortic regurgitation (AR), mitral regurgitation (MR), and tricuspid regurgitation (TR). From the echo images, texture features are extracted, and classification is performed using Random Forest (RF) classifier. Extraction of keyframe is performed from the video file using two approaches: a reference frame keyframe extraction technique and a redundant frame removal technique. To check the robustness of the model, we have considered both segmented and nonsegmented frames. Segmentation is carried out after keyframe extraction using the Level Set (LS) with Fuzzy C-means (FCM) approach. Performances are evaluated in terms of accuracy, precision, recall, and F1-score and compared for both reference frame and redundant frame extraction techniques. K-fold cross-validation is used to examine the performance of the model. The performance result shows that our proposed approach outperforms other state-of-art machine learning approaches in terms of accuracy, precision, recall, and F1-score.
Optimal Selection of the Diesel Generators Supplying a Ship Electric Power System
Authors: Michalopoulos Panayiotis , Tsekouras George J. , Kanellos Fotios D. , Prousalidis John M.
Published: October 2022

It is very common for ships to have electric power systems comprised of generators of the same type. This uniformity allows for easier and lower-cost maintenance. The classic way to select these generators is primarily by power and secondarily by dimensions and acquisition cost. In this paper, a more comprehensive way to select them, using improved cost indicators, is proposed. These take into account many factors that have a significant impact in the life-cycle cost of the equipment. A realistic and detailed profile of the ship’s electric load spanning a full year of her operation is also developed to allow for a solution that is tailor-made to a specific case. The method used is highly iterative. All combinations of genset quantities and capacities are individually considered to populate a power plant, taking into account the existing redundancy requirements. For each of these and for every time interval in the load profile, the engine consumption is Lagrange-optimized to determine the most efficient combination to run the generators and the resulting cost. The operating cost throughout the year is thus derived. In this way, the method can lead to optimal results as large data sets regarding ship operation and her power system’s technical characteristics can be utilized. This intense calculation process is greatly accelerated using memorization techniques. The reliability cost of the current power plant is also considered along with other cost factors, such as flat annual cost, maintenance, and personnel. The acquisition and installation cost are also included, after being distributed in annuities for various durations and interest rates. The results provide valuable insight into the total cost from every aspect and present the optimum generator selection for minimal expenditure and maximum return of investment. This methodology may be used to enhance the current power-plant design processes and provide investors with more feasible alternatives, as it takes into consideration a multitude of technical and operational characteristics of the examined ship power system.
Relationship between the Polymorphism of the AKT1 Gene and the Consumption of Cannabis in the Appearance of Psychosis
Authors: López-Martín Mónica , Astasio-Picado Álvaro , Jurado-Palomo Jesús , Zabala-Baños María del Carmen
Published: October 2022

Introduction: Psychotic disorders are a mental illness that affect 3% of the world’s population. The external (cannabis) and internal vulnerability factors (polymorphisms of the AKT1 gene, the COMT gene and the DAT1 gene) acquire special relevance in the appearance of psychosis; this is known as the vulnerability–stress model. Objective: To analyze the scientific evidence that reflects the relationship between the polymorphism of the AKT1 gene and the consumption of cannabis in the appearance of psychosis. Material and Methods: The bibliographic search was made using databases such as Scopus, WoS, Cochrane Library, TRIP Database, PubPsych and PubMed. The criteria of the “MeSH” terminology and the inclusion and exclusion criteria were followed, obtaining a total of 22 articles that comprises this narrative review. Results: The presence of genetic variation in the locus rs2494732 of the AKT1 gene in a cannabis user raises the risk of the appearance of psychosis, especially if homozygous with the C allele. Likewise, consumption entails a slowdown in the functionality of the AKT1 gene, releasing a greater amount of dopamine in the striatum through the involvement of indirect mechanisms. Similarly, the COMT gene and the interaction of the AKT1 gene with the DAT1 gene raise the risk of developing psychotic disorder. Conclusion: The genetic polymorphism rs2494732 of AKT1 is the main factor responsible for the appearance of psychosis, although polymorphisms of the COMT and DAT1 gene are also implicated. Regarding the AKT1 gene, subjects with two copies of the C allele have a higher risk of developing psychosis compared to subjects with two copies of the T allele. It should also be noted that the muscarinic receptors rs115455482 and rx74722579 are related to a greater vulnerability to psychosis and the development of psychotic disorders.
Model Compression and Acceleration: Lip Recognition Based on Channel-Level Structured Pruning
Authors: Lu Yuanyao , Ni Ran , Wen Jing
Published: October 2022

In recent years, with the rapid development of deep learning, the requirements for the performance of the corresponding real-time recognition system are getting higher and higher. However, the rapid expansion of data volume means that time delay, power consumption, and cost have become problems that cannot be ignored. In this case, the traditional neural network is almost impossible to use to achieve productization. In order to improve the potential problems of a neural network facing a huge number of datasets without affecting the recognition effect, the model compression method has gradually entered people’s vision. However, the existing model compression methods still have some shortcomings in some aspects, such as low rank decomposition, transfer/compact convolution filter, knowledge distillation, etc. These problems enable the traditional model compression to cope with the huge amount of computation brought by large datasets to a certain extent, but also make the results unstable on some datasets, and the system performance has not been improved satisfactorily. To address this, we proposed a structured network compression and acceleration method for the convolutional neural network, which integrates the pruned convolutional neural network and the recurrent neural network, and applied it to the lip-recognition system in this paper.
Effects of Mini-Implant-Assisted Rapid Palatal Expansion on Incisive Canal Morphology and Tooth–Canal Relationship
Authors: Choi Sung-Kwon , Kim Yu-Rim , Park Jae Hyun , Kang Kyung-Hwa , Chang Na-Young , Chae Jong-Moon
Published: October 2022

The objective of this study was to identify the change in incisive canal (IC) morphology and tooth–canal relationship after mini-implant-assisted rapid palatal expansion (MARPE). Pretreatment and posttreatment cone-beam computed tomography images of 30 subjects were retrospectively evaluated. The dimensional and volume changes of the IC after MARPE treatment were evaluated, and the tooth–canal relationship and positional relationship between the maxillary central incisors were additionally compared in the group where the root apex of the maxillary central incisors was higher than the IC oral opening. The mediolateral and labiopalatal widths of the IC were significantly increased in all three levels after MARPE treatment (p < 0.01). The amount of increase was greater in the mediolateral direction than in the labiopalatal direction. The anteroposterior distance from the mesial point of the maxillary central incisors to the anterior margin of the IC was significantly decreased only in the oral opening level in the samples where the apices of the maxillary central incisors were located more superior to the oral opening of the IC (p < 0.05). The mediolateral distance between the mesial points of the maxillary central incisors and the distance between the root apex of the maxillary central incisors significantly increased after MARPE (p < 0.001). However, the distance between the crown tips of the maxillary central incisors did not significantly increase, even after MARPE treatment (p > 0.05). The volume of the IC significantly increased after MARPE treatment (p < 0.001), and the average increase in the total volume of the IC was about 65%. MARPE increased the width and volume of the IC and did not result in a clinically significant change in the root–canal relationship.
CMD-Net: Self-Supervised Category-Level 3D Shape Denoising through Canonicalization
Authors: Sahin Caner
Published: October 2022

Point clouds provide a compact representation of 3D shapes however, the imperfections in acquisition processes corrupt point clouds by noise and give rise to a decrease in their power for representing 3D shapes. Learning-based denoising methods operate displacement prediction and suffer from shrinkage and outliers. In addition, they require pre-aligned datasets. In this paper, we present a self-supervised learning-based method, Canonical Mapping and Denoising Network (CMD-Net), and address category-level 3D shape denoising through canonicalization. We formulate denoising as a 3D semantic shape correspondence estimation task where we explore ordered 3D intrinsic structure points. Utilizing the convex hull of the explored structure points, the corruption on objects’ surfaces is eliminated. Our method is capable of canonicalizing noise-corrupted clouds under arbitrary rotations, therefore circumventing the requirement on pre-aligned data. The complete model learns to canonicalize the input through a novel transformer that serves as a proxy in the downstream denoising task. The analyses on the experiments validate the promising performance of the presented method on both synthetic and real data. We show that our method can not only eliminate corruption, but also remove clutter from the test data. We additionally create a novel dataset for the problem in hand and will make it publicly available in our project web-page.
Machine-Learning-Based Methods for Acoustic Emission Testing: A Review
Authors: Ciaburro Giuseppe , Iannace Gino
Published: October 2022

Acoustic emission is a nondestructive control technique as it does not involve any input of energy into the materials. It is based on the acquisition of ultrasonic signals spontaneously emitted by a material under stress due to irreversible phenomena such as damage, microcracking, degradation, and corrosion. It is a dynamic and passive-receptive technique that analyzes the ultrasonic pulses emitted by a crack when it is generated. This technique allows for an early diagnosis of incipient structural damage by capturing the precursor signals of the fracture. Recently, the scientific community is making extensive use of methodologies based on machine learning: the use of machine learning makes a machine capable of receiving a series of data, modifying the algorithms as they receive information on what they are processing. In this way, the machine can learn without being explicitly programmed, and this implies a huge use of data and an efficient algorithm to adapt. This review described the methodologies for the implementation of the acoustic emission (AE) technique in the evaluation of the conditions and in the monitoring of materials and structures. The latest research products were also analyzed in the development of new methodologies based on machine learning for the detection and localization of damage for the characterization of the fracture and the prediction of the failure mode. The work carried out highlighted the strong use of these methods, which confirms the extreme usefulness of these techniques in identifying structural damage in scenarios heavily contaminated by residual noise.
Numerical Simulation of the Elastic–Ideal Plastic Material Behavior of Short Fiber-Reinforced Composites Including Its Spatial Distribution with an Experimental Validation
Authors: Rauter Natalie
Published: October 2022

For the numerical simulation of components made of short fiber-reinforced composites, the correct prediction of the deformation including the elastic and plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches, the information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields. In this study, numerical simulations of tensile test specimens were conducted utilizing a finite deformation elastic–ideal plastic material model. A selection of the material parameters covering the elastic and plastic domain are represented by cross-correlated second-order Gaussian random fields to incorporate the probabilistic nature of the material parameters. To validate the modeling approach, tensile tests until failure were carried out experimentally, which confirmed the assumption of the spatially distributed material behavior in both the elastic and plastic domain. Since the correlation lengths of the random fields cannot be determined by pure analytic treatments, additionally numerical simulations were performed for different values of the correlation length. The numerical simulations endorsed the influence of the correlation length on the overall behavior. For a correlation length of 5 mm, a good conformity with the experimental results was obtained. Therefore, it was concluded that the presented modeling approach was suitable to predict the elastic and plastic deformation of a set of tensile test specimens made of short fiber-reinforced composite sufficiently.
Airborne Wear Particles from Dry Clutches
Authors: Hjelm Rikard , Wahlström Jens , Yenibayrak Isa , Sabani Driton , Runsten Paula , Lyu Yezhe
Published: October 2022

A significant part of non-exhaust particle emissions in cities comes from the wear of vehicle components. Several studies on airborne particles from the wear of disc brakes and tires have been completed. However, few publications can be found in the scientific literature regarding airborne emissions from dry clutches used in road vehicles. With this in mind, this preliminary study designs a clutch tribometer for the generation of airborne wear particles in a controlled environment. The number concentration and the size distribution of airborne wear particles generated from a typical dry clutch used in passenger cars are investigated. The tests are run at a constant rotational speed, and normal load. The results show that the particle number concentration from dry clutches exhibits a running-in period and a steady state, similar to the particle emissions from disc brake contact. A significant number of nanoparticles (aerodynamic diameter < 100 nm) are emitted from the dry clutch contact.
Aerosols in Northern Morocco-2: Chemical Characterization and PMF Source Apportionment of Ambient PM2.5
Authors: Benchrif Abdelfettah , Tahri Mounia , Guinot Benjamin , Chakir El Mahjoub , Zahry Fatiha , Bagdhad Bouamar , Bounakhla Moussa , Cachier Hélène , Costabile Francesca
Published: October 2022

Insufficient data on the chemical composition of PM2.5 and its emission sources in the southwestern (SW) Mediterranean area has been identified. Ambient PM2.5 samples were collected in an urban area of Tetouan city, northern Morocco. Chemical mass closure calculations and positive matrix factorization were performed for the comprehensive dataset of PM2.5 chemical analyses. Mass closure improved when multipliers (1.2 and 0.23, respectively) were used for the conversion of organic carbon (OC) and calcium ion (Ca2+) into particulate organic matter (POM) and mineral dust masses, respectively. The mass closure model performed well in this SW Mediterranean region, with a significant correlation (r2 = 0.97) obtained between gravimetrically measured and chemically determined PM2.5 mass. The one-year average concentration of PM2.5 was 17.96 μg/m3, and the major chemical components were POM (34%), secondary inorganic aerosol (SIA) (28%), and black carbon (18%), while unidentified mass was 4%. The mass concentration and most of the chemical components of PM2.5 showed clear seasonal variations, with a summer-high and winter-low pattern for SIA, dust, and BC. In the winter months, POM was the dominant component. Source apportionment analysis revealed that PM2.5 emission sources, regarding their typical tracers, were ammonium sulfate (SO42−, NH4+, K+, NO3−), road traffic and biomass burning emissions (OC, BC), fresh sea salt (Cl−, K+, NO3−), aged sea salt (Mg2+, Na+, Ca2+), and oxalate-rich (oxalate, NO3−) factors. Further, it is hoped that these findings help to improve the scientific understanding of SW Mediterranean aerosols.
Gas Emissions and Environmental Benefits of Wheat Cultivated under Different Fertilization Managements in Mollisols
Authors: Liu Chunzhu , Zhou Meng , Zhu Yingxue , Ma Xianfa , Wang Qi , Xu Lianzhou , Zhao Ying , Zou Wenxiu
Published: October 2022

The NH3, N2O and CO2 emissions from farmland soil pose a great threat to the environment, and the application of organic fertilizer and other reasonable fertilization measures can reduce soil gas emissions. However, research into greenhouse gas emissions and environmental benefits under the combined measures of partial substitution of organic fertilizer and phased application of chemical fertilizer is limited. Herein, a field experiment involving soil gas emission monitoring was conducted to study the effects of chemical fertilizer application in stages on Mollisols’ gas emissions and environmental benefits based on the partial replacement of chemical fertilizer with organic fertilizer. Five treatments were set up, including conventional nitrogen application (CF); no nitrogen application (N0); and one-stage (N1), two-stage (N2) and three-stage (N3) application of chemical nitrogen based on 25% of chemical nitrogen being replaced with organic fertilizer. The results showed that N1 had the best emission reduction. Compared with CF, N1 reduced NH3 volatilization and N2O and CO2 emission accumulation by 27.64%, 12.09% and 15.48%, respectively. Compared with N2 and N3, N1 could better reduce the soil urease, nitrate reductase, catalase and β-glucosidase activities, reduce the rate of the conversion of urea and organic carbon, increase the content of NH4+-N in the soil and reduce the NH3 volatilization rate and N2O and CO2 emission rates. A comprehensive analysis showed that N1 showed the best effects in reducing the soil gas emission rate, and environmental cost.
Fixed Point Theory for Multi-Valued Feng–Liu–Subrahmanyan Contractions
Authors: Mihiţ Claudia Luminiţa , Moţ Ghiocel , Petruşel Adrian
Published: October 2022

In this paper, we consider several problems related to the so-called multi-valued Feng–Liu–Subrahmanyan contractions in complete metric spaces. Existence of the fixed points and of the strict fixed points, as well as data dependence and stability properties for the fixed point problem, are discussed. Some results are presented, under appropriate conditions, and some open questions are pointed out. Our results extend recent results given for multi-valued graph contractions and multi-valued Subrahmanyan contractions.
Was There a Cambrian Explosion on Land? The Case of Arthropod Terrestrialization
Authors: Tihelka Erik , Howard Richard J. , Cai Chenyang , Lozano-Fernandez Jesus
Published: October 2022

Arthropods, the most diverse form of macroscopic life in the history of the Earth, originated in the sea. Since the early Cambrian, at least ~518 million years ago, these animals have dominated the oceans of the world. By the Silurian–Devonian, the fossil record attests to arthropods becoming the first animals to colonize land, However, a growing body of molecular dating and palaeontological evidence suggests that the three major terrestrial arthropod groups (myriapods, hexapods, and arachnids), as well as vascular plants, may have invaded land as early as the Cambrian–Ordovician. These dates precede the oldest fossil evidence of those groups and suggest an unrecorded continental “Cambrian explosion” a hundred million years prior to the formation of early complex terrestrial ecosystems in the Silurian–Devonian. We review the palaeontological, phylogenomic, and molecular clock evidence pertaining to the proposed Cambrian terrestrialization of the arthropods. We argue that despite the challenges posed by incomplete preservation and the scarcity of early Palaeozoic terrestrial deposits, the discrepancy between molecular clock estimates and the fossil record is narrower than is often claimed. We discuss strategies for closing the gap between molecular clock estimates and fossil data in the evolution of early ecosystems on land
SNRPD2 Is a Novel Substrate for the Ubiquitin Ligase Activity of the Salmonella Type III Secretion Effector SlrP
Authors: Bullones-Bolaños Andrea , Araujo-Garrido Juan Luis , Fernández-García Jesús , Romero Francisco , Bernal-Bayard Joaquín , Ramos-Morales Francisco
Published: October 2022

SlrP is a protein with E3 ubiquitin ligase activity that is translocated by Salmonella enterica serovar Typhimurium into eukaryotic host cells through a type III secretion system. A yeast two-hybrid screen was performed to find new human partners for this protein. Among the interacting proteins identified by this screen was SNRPD2, a core component of the spliceosome. In vitro ubiquitination assays demonstrated that SNRPD2 is a substrate for the catalytic activity of SlrP, but not for other members of the NEL family of E3 ubiquitin ligases, SspH1 and SspH2. The lysine residues modified by this activity were identified by mass spectrometry. The identification of a new ubiquitination target for SlrP is a relevant contribution to the understanding of the role of this Salmonella effector.
Mechanisms of Peritoneal Mesothelial Cells in Peritoneal Adhesion
Authors: Wang Ruipeng , Guo Tiankang , Li Junliang
Published: October 2022

A peritoneal adhesion (PA) is a fibrotic tissue connecting the abdominal or visceral organs to the peritoneum. The formation of PAs can induce a variety of clinical diseases. However, there is currently no effective strategy for the prevention and treatment of PAs. Damage to peritoneal mesothelial cells (PMCs) is believed to cause PAs by promoting inflammation, fibrin deposition, and fibrosis formation. In the early stages of PA formation, PMCs undergo mesothelial–mesenchymal transition and have the ability to produce an extracellular matrix. The PMCs may transdifferentiate into myofibroblasts and accelerate the formation of PAs. Therefore, the aim of this review was to understand the mechanism of action of PMCs in PAs, and to offer a theoretical foundation for the treatment and prevention of PAs.
High-Resolution Ribosome Profiling Reveals Gene-Specific Details of UGA Re-Coding in Selenoprotein Biosynthesis
Authors: Bohleber Simon , Fradejas-Villar Noelia , Zhao Wenchao , Reuter Uschi , Schweizer Ulrich
Published: October 2022

Co-translational incorporation of selenocysteine (Sec) into selenoproteins occurs at UGA codons in a process in which translational elongation competes with translational termination. Selenocysteine insertion sequence-binding protein 2 (SECISBP2) greatly enhances Sec incorporation into selenoproteins by interacting with the mRNA, ribosome, and elongation factor Sec (EFSEC). Ribosomal profiling allows to study the process of UGA re-coding in the physiological context of the cell and at the same time for all individual selenoproteins expressed in that cell. Using HAP1 cells expressing a mutant SECISBP2, we show here that high-resolution ribosomal profiling can be used to assess read-through efficiency at the UGA in all selenoproteins, including those with Sec close to the C-terminus. Analysis of ribosomes with UGA either at the A-site or the P-site revealed, in a transcript-specific manner, that SECISBP2 helps to recruit tRNASec and stabilize the mRNA. We propose to assess the effect of any perturbation of UGA read-through by determining the proportion of ribosomes carrying UGA in the P-site, pUGA. An additional, new observation is frameshifting that occurred 3′ of the UGA/Sec codon in SELENOF and SELENOW in SECISBP2-mutant HAP1 cells, a finding corroborated by reanalysis of neuron-specific Secisbp2R543Q-mutant brains.
Diverse and Composite Roles of miRNA in Non-Neuronal Cells and Neuronal Synapses in Alzheimer’s Disease
Authors: Li Xinrong , Chen Shih-Chi , Ip Jacque Pak Kan
Published: October 2022

Neurons interact with astrocytes, microglia, and vascular cells. These interactions become unbalanced in disease states, resulting in damage to neurons and synapses, and contributing to cognitive impairment. Importantly, synaptic loss and synaptic dysfunction have been considered for years as a main pathological factor of cognitive impairment in Alzheimer’s disease (AD). Recently, miRNAs have emerged as essential regulators of physiological and pathological processes in the brain. Focusing on the role of miRNAs in regulating synaptic functions, as well as different cell types in the brain, offers opportunities for the early prevention, diagnosis, and potential treatment of AD-related cognitive impairment. Here, we review the recent research conducted on miRNAs regulating astrocytes, microglia, cerebrovasculature, and synaptic functions in the context of AD-related cognitive impairment. We also review potential miRNA-related biomarkers and therapeutics, as well as emerging imaging technologies relevant for AD research.
The Arrival of the Metaverse in Neurorehabilitation: Fact, Fake or Vision?
Authors: Calabrò Rocco Salvatore , Cerasa Antonio , Ciancarelli Irene , Pignolo Loris , Tonin Paolo , Iosa Marco , Morone Giovanni
Published: October 2022

The metaverse is a new technology thought to provide a deeper, persistent, immersive 3D experience combining multiple different virtual approaches in a full continuum of physical–digital interaction spaces. Different from virtual reality (VR) and augmented reality (AR), the metaverse has a service-oriented solid model with an emphasis on social and content dimensions. It has widely been demonstrated that motor or cognitive deficits can be more effectively treated using VR/AR tools, but there are several issues that limit the real potential of immersive technologies applied to neurological patients. In this scoping review, we propose future research directions for applying technologies extracted from the metaverse in clinical neurorehabilitation. The multisensorial properties of the metaverse will boost the embodied cognition experience, thus influencing the internal body representations as well as learning strategies. Moreover, the immersive social environment shared with other patients will contribute to recovering social and psychoemotional abilities. In addition to the many potential pros, we will also discuss the cons, providing readers with the available information to better understand the complexity and limitations of the metaverse, which could be considered the future of neurorehabilitation.
A Review of Compartmentalised Inflammation and Tertiary Lymphoid Structures in the Pathophysiology of Multiple Sclerosis
Authors: Kee Rachael , Naughton Michelle , McDonnell Gavin V. , Howell Owain W. , Fitzgerald Denise C.
Published: October 2022

Multiple sclerosis (MS) is a chronic, immune-mediated, demyelinating disease of the central nervous system (CNS). The most common form of MS is a relapsing–remitting disease characterised by acute episodes of demyelination associated with the breakdown of the blood–brain barrier (BBB). In the relapsing–remitting phase there is often relative recovery (remission) from relapses characterised clinically by complete or partial resolution of neurological symptoms. In the later and progressive stages of the disease process, accrual of neurological disability occurs in a pathological process independent of acute episodes of demyelination and is accompanied by a trapped or compartmentalised inflammatory response, most notable in the connective tissue spaces of the vasculature and leptomeninges occurring behind an intact BBB. This review focuses on compartmentalised inflammation in MS and in particular, what we know about meningeal tertiary lymphoid structures (TLS; also called B cell follicles) which are organised clusters of immune cells, associated with more severe and progressive forms of MS. Meningeal inflammation and TLS could represent an important fluid or imaging marker of disease activity, whose therapeutic abrogation might be necessary to stop the most severe outcomes of disease.
Implantable Peripheral Nerve Stimulation for Peripheral Neuropathic Pain: A Systematic Review of Prospective Studies
Authors: Char Steven , Jin Max Y. , Francio Vinicius Tieppo , Hussain Nasir , Wang Eric J. , Morsi Mahmoud , Orhurhu Vwaire , Prokop Larry J. , Fink Adam , D’Souza Ryan S.
Published: October 2022

Peripheral nerve stimulation (PNS) has been utilized for over 50 years with accumulating evidence of efficacy in a variety of chronic pain conditions. The level and strength of evidence supporting the use of PNS for peripheral neuropathic pain remains unclear. The purpose of this review is to synthesize data from prospective studies on the efficacy of PNS for neuropathic pain as it pertains to pain intensity, neurological deficits/neuropathy (e.g., weakness, sensory deficits, gait/balance), and other secondary outcomes (quality of life, satisfaction, emotional functioning, and adverse events). In compliance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, this review identified articles from MEDLINE(R), EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus. Overall, per the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria, pooled results demonstrate very low quality or low quality of evidence supporting modest to substantial improvement in pain and neurological function after PNS implantation for treatment of peripheral neuropathic pain. PNS for phantom limb pain was the only indication that had moderate level evidence. Future prospective and well-powered studies are warranted to assess the efficacy of PNS for peripheral neuropathic pain.
Obesity-Related Genes Expression in Testes and Sperm Parameters Respond to GLP-1 and Caloric Restriction
Authors: Correia Ana S. , Pereira Sara C. , Morais Tiago , Martins Ana D. , Monteiro Mariana P. , Alves Marco G. , Oliveira Pedro F.
Published: October 2022

Aim: Calorie restriction (CR) diets and glucagon-Like Peptide-1 (GLP-1) analogs are known to alter energy homeostasis with the potential to affect the expression of obesity-related genes (ORGs). We hypothesized that CR and GLP-1 administration can alter ORGs expression in spermatozoa and testes, as well as the sperm parameters implicated in male fertility. Materials and Methods: Six-week-old adult male Wistar rats (n = 16) were divided into three groups, submitted either to CR (n = 6, fed with 30% less chow diet than the control rats), GLP-1 administration (n = 5, 3.5 pmol/min/kg intraperitoneal) for 28 days, or used as controls (n = 5, fed ad libitum). Selected ORGs expression, namely the fat mass and obesity-associated (FTO), melanocortin-4 receptor (MC4R), glucosamine-6-phosphate deaminase 2 (GNPDA2), and transmembrane protein 18 (TMEM18) were evaluated in testes and spermatozoa by a quantitative polymerase chain reaction (qPCR). Results: CR resulted in lower body weight gain and insulin resistance, but a higher percentage of sperm head defects. GLP-1 administration, despite showing no influence on body weight or glucose homeostasis, resulted in a lower percentage of sperm head defects. CR and GLP-1 administration were associated with a higher expression of all ORGs in the testes. Under CR conditions, the genes FTO and TMEM18 expression in the testes and the MC4R and TMEM18 transcripts abundance in sperm were positively correlated with the spermatozoa oxidative status. The abundance of FTO and TMEM18 in the spermatozoa of rats under CR were positively correlated with sperm concentration, while the testes’ TMEM18 expression was also positively correlated with sperm vitality and negatively correlated with insulin resistance. Testes GNPDA2 expression was negatively correlated with sperm head defects. Conclusions: CR and GLP-1 administration results in higher ORGs expression in testes, and these were correlated with several alterations in sperm fertility parameters.
Quantitative SERS Detection of TBBPA in Electronic Plastic Based on Hydrophobic Cu-Ag Chips
Authors: Dai Pei , Huang Xianzhi , Cui Yaqian , Zhu Lihua
Published: October 2022

Tetrabromobisphenol A (TBBPA) was one of the most widely used brominated flame retardants. However, it easily contaminates nature and harms the environment and human health during its production and use. Therefore, it is necessary to strictly control the content of TBBPA in electronics. Surface-enhanced Raman spectroscopy has the advantages of being fast and sensitive, but it is difficult to obtain the SERS spectra of TBBPA because the hydrophobic TBBPA molecule is difficult to approach with the hydrophilic surface of common noble metal SERS substrates. In the present work, a hydrophobic Cu-Ag chip was developed for the SERS detection of TBBPA. The integration of the hydrophobic interaction and the Ag-Br bonding promoted the adsorption of TBBPA on the Cu-Ag chip, allowing for SERS detection. It was observed that both the hydrophobicity and bimetallic composition of the Cu-Ag chip played important roles in the SERS detection of TBBPA. Under the optimized conditions, the low limit of detection of the established SERS method for TBBPA was 0.01 mg L−1, within a linear range of 0.1–10 mg L−1. Combined with ultrasonic-assisted extraction, the substrate could be used for the quantitative determination of TBBPA in electronic products. Compared with the HPLC-UV method used as a national standard, the relative error of the SERS method for quantifying the TBBPA content in a mouse cable and shell was ±3% and ±7.7%, respectively. According to the SERS results, the recovery of TBBPA in the spiked mouse shell was 95.6%.
Graphene-Binding Peptide in Fusion with SARS-CoV-2 Antigen for Electrochemical Immunosensor Construction
Authors: Braz Beatriz A. , Hospinal-Santiani Manuel , Martins Gustavo , Pinto Cristian S. , Zarbin Aldo J. G. , Beirão Breno C. B. , Thomaz-Soccol Vanete , Bergamini Márcio F. , Marcolino-Junior Luiz H. , Soccol Carlos R.
Published: October 2022

The development of immunosensors to detect antibodies or antigens has stood out in the face of traditional methods for diagnosing emerging diseases such as the one caused by the SARS-CoV-2 virus. The present study reports the construction of a simplified electrochemical immunosensor using a graphene-binding peptide applied as a recognition site to detect SARS-CoV-2 antibodies. A screen-printed electrode was used for sensor preparation by adding a solution of peptide and reduced graphene oxide (rGO). The peptide-rGO suspension was characterized by scanning electron microscopy (SEM), Raman spectroscopy, and Fourier transform infrared spectroscopy (FT-IR). The electrochemical characterization (electrochemical impedance spectroscopy—EIS, cyclic voltammetry—CV and differential pulse voltammetry—DPV) was performed on the modified electrode. The immunosensor response is based on the decrease in the faradaic signal of an electrochemical probe resulting from immunocomplex formation. Using the best set of experimental conditions, the analytic curve obtained showed a good linear regression (r2 = 0.913) and a limit of detection (LOD) of 0.77 μg mL−1 for antibody detection. The CV and EIS results proved the efficiency of device assembly. The high selectivity of the platform, which can be attributed to the peptide, was demonstrated by the decrease in the current percentage for samples with antibody against the SARS-CoV-2 S protein and the increase in the other antibodies tested. Additionally, the DPV measurements showed a clearly distinguishable response in assays against human serum samples, with sera with a response above 95% being considered negative, whereas responses below this value were considered positive. The diagnostic platform developed with specific peptides is promising and has the potential for application in the diagnosis of other infections that lead to high antibody titers.
Colorimetric Detection of Urease-Producing Microbes Using an Ammonia-Responsive Flexible Film Sensor
Authors: Chang Yunsoo , Park Tae-Eon , Lee Seung-Woo , Lee Eun-Hee
Published: October 2022

Urease-producing (ureolytic) microbes have given rise to environmental and public health concerns because they are thought to contribute to emissions of ammonia and to be a virulence factor for infections. Therefore, it is highly important to have the ability to detect such microbes. In this study, a poly(dimethylsiloxane) (PDMS)-based colorimetric film sensor was employed for the detection of urease-producing microbes. The sensor was able to detect the enzyme activity of commercially available urease, as the color and absorbance spectrum of the sensor was observed to change upon being exposed to the reaction catalyzed by urease. The ratio of the absorbance of the sensor at 640 nm to that at 460 nm (A640/A460) was linearly proportional to the amount of urease present. The performance of the sensor was validated by the results of a sensitivity and selectivity analysis towards thirteen different bacterial strains. Based on the development of blue color of the sensor, the tested bacteria were classified as strongly positive, moderately positive, weakly positive, or negative urease producers. The response of the sensor to ureolytic bacteria was verified using the urease inhibitor phenyl phosphorodiamidate (PPDA). Additionally, the sensor achieved the selective detection of ureolytic bacteria even in the presence of non-ureolytic bacteria. In addition, a used sensor could be reverted to its original state by being subjected to simple aeration, and in this way the same sensor could be used at least five times for the detection of bacterial urease activity.
A Sensitive Aptamer Fluorescence Anisotropy Sensor for Cd2+ Using Affinity-Enhanced Aptamers with Phosphorothioate Modification
Authors: Yu Hao , Zhao Qiang
Published: October 2022

Rapid and sensitive detection of heavy metal cadmium ions (Cd2+) is of great significance to food safety and environmental monitoring, as Cd2+ contamination and exposure cause serious health risk. In this study we demonstrated an aptamer-based fluorescence anisotropy (FA) sensor for Cd2+ with a single tetramethylrhodamine (TMR)-labeled 15-mer Cd2+ binding aptamer (CBA15), integrating the strengths of aptamers as affinity recognition elements for preparation, stability, and modification, and the advantages of FA for signaling in terms of sensitivity, simplicity, reproducibility, and high throughput. In this sensor, the Cd2+-binding-induced aptamer structure change provoked significant alteration of FA responses. To acquire better sensing performance, we further introduced single phosphorothioate (PS) modification of CBA15 at a specific phosphate backbone position, to enhance aptamer affinity by possible strong interaction between sulfur and Cd2+. The aptamer with PS modification at the third guanine (G) nucleotide (CBA15-G3S) had four times higher affinity than CBA15. Using as an aptamer probe CBA15-G3S with a TMR label at the 12th T, we achieved sensitive selective FA detection of Cd2+, with a detection limit of 6.1 nM Cd2+. This aptamer-based FA sensor works in a direct format for detection without need for labeling Cd2+, overcoming the limitations of traditional competitive immuno-FA assay using antibodies and fluorescently labeled Cd2+. This FA method enabled the detection of Cd2+ in real water samples, showing broad application potential.
Kinetics of Drug Molecule Interactions with a Newly Developed Nano-Gold-Modified Spike Protein Electrochemical Receptor Sensor
Authors: Lu Dingqiang , Liu Danyang , Wang Xinqian , Liu Yujiao , Liu Yixuan , Ren Ruijuan , Pang Guangchang
Published: October 2022

In March 2020, the World Health Organization (WHO) declared COVID-19 a pandemic, and the spike protein has been reported to be an important drug target for anti-COVID-19 treatment. As such, in this study, we successfully developed a novel electrochemical receptor biosensor by immobilizing the SARS-CoV-2 spike protein and using AuNPs-HRP as an electrochemical signal amplification system. Moreover, the time-current method was used to quantify seven antiviral drug compounds, such as arbidol and chloroquine diphosphate. The results show that the spike protein and the drugs are linearly correlated within a certain concentration range and that the detection sensitivity of the sensor is extremely high. In the low concentration range of linear response, the kinetics of receptor–ligand interactions are similar to that of an enzymatic reaction. Among the investigated drug molecules, bromhexine exhibits the smallest Ka value, and thus, is most sensitively detected by the sensor. Hydroxychloroquine exhibits the largest Ka value. Molecular docking simulations of the spike protein with six small-molecule drugs show that residues of this protein, such as Asp, Trp, Asn, and Gln, form hydrogen bonds with the -OH or -NH2 groups on the branched chains of small-molecule drugs. The electrochemical receptor biosensor can directly quantify the interaction between the spike protein and drugs such as abidor and hydroxychloroquine and perform kinetic studies with a limit of detection 3.3 × 10−20 mol/L, which provides a new research method and idea for receptor–ligand interactions and pharmacodynamic evaluation.
Interoception in Old Age
Authors: Ulus Gili , Aisenberg-Shafran Daniela
Published: October 2022

Emotion regulation in old age was found to be more efficient; seniors seem to focus less on the negative aspects of experiences. Here, we ask, do older individuals regulate their emotions more efficiently or are they numb to the physiological changes that modulate these emotions? Interoception, the perception of physical feelings, influences a person’s mood, emotions, and sense of well-being, and was hardly tested among older adults. We examined the awareness of physiological changes (physiological arousal—blood pressure and heart rate) of 47 older adults, compared to 18 young adults, and their subjective reports of emotional experiences while viewing emotional stimuli. Interoception was decreased in old age. Blood pressure medications had a partial role in this reduction. Moreover, interoception mediated emotional experience, such that low interoception led to lower experiences of changes in physiological arousal. These findings may account for the emotional changes in old age, suggesting a decline in sensitivity with age, which leads to a positive interpretation of information.