bluuebunny/crossref_metadata_2025 huggingface dataset:
Merging-Squeeze-Excitation Feature Fusion for Human Activity Recognition Using Wearable Sensors
Authors: Laitrakun Seksan
Published: February 2023

Human activity recognition (HAR) has been applied to several advanced applications, especially when individuals may need to be monitored closely. This work focuses on HAR using wearable sensors attached to various locations of the user body. The data from each sensor may provide unequally discriminative information and, then, an effective fusion method is needed. In order to address this issue, inspired by the squeeze-and-excitation (SE) mechanism, we propose the merging-squeeze-excitation (MSE) feature fusion which emphasizes informative feature maps and suppresses ambiguous feature maps during fusion. The MSE feature fusion consists of three steps: pre-merging, squeeze-and-excitation, and post-merging. Unlike the SE mechanism, the set of feature maps from each branch will be recalibrated by using the channel weights also computed from the pre-merged feature maps. The calibrated feature maps from all branches are merged to obtain a set of channel-weighted and merged feature maps which will be used in the classification process. Additionally, a set of MSE feature fusion extensions is presented. In these proposed methods, three deep-learning models (LeNet5, AlexNet, and VGG16) are used as feature extractors and four merging methods (addition, maximum, minimum, and average) are applied as merging operations. The performances of the proposed methods are evaluated by classifying popular public datasets.
UHPLC-QTOF/MS Untargeted Lipidomics and Caffeine Carry-Over in Milk of Goats under Spent Coffee Ground Enriched Diet
Authors: Casula Mattia , Scano Paola , Manis Cristina , Tolle Giulia , Nudda Anna , Carta Silvia , Pulina Giuseppe , Caboni Pierluigi
Published: February 2023

Supplementing the diet of ruminants with agro-industrial by-products is a common practice. In this study, we applied an untargeted lipidomics approach to study the changes in the milk lipid metabolite profiles linked to the addition of different doses of spent coffee grounds (SCG) to the diet of lactating goats. The carryover of caffeine from feed to milk was also studied. Compared to controls, the milk of goats on the SCG diet showed higher levels of cholesteryl esters, sphingomyelins, and phospholipids, while nonesterified fatty acids were downregulated. After 12 h from the last SCG dose, the carry-over of caffeine was, on average, 3%. Collectively, our results establish that SCG supplementation induces changes in the milk levels of complex lipid molecules and causes the transfer of caffeine and caffeine metabolites from feed to milk.
MRCIF: A Memory-Reverse-Based Code Injection Forensics Algorithm
Authors: Zhang Heyu , Li Binglong , Li Wanpeng , Zhu Lin , Chang Chaowen , Yu Shilong
Published: February 2023

The new DLL injection method and its variants can prevent the injected process from calling the common system API to load the injected DLL module so that the malicious module is invisible to the LDR linked list of the process. Traditional injection detection methods have low accuracy in forensic detection of new injection attacks. To solve this problem, this paper proposes a code injection covert memory page detection and forensic detection forensic algorithm based on a memory structure reverse analysis named MRCIF. First, the physical memory pages containing DLL features from the memory image are located, and a sub-algorithm is designed for mapping physical memory space and virtual memory space, thus realizing the reverse reconstruction of the physical page subset corresponding to the DLL code module. Then, in the virtual memory space, the LDR linked list structure of the process is reversely reconstructed, and a reverse reconstruction algorithm of the DLL virtual page subset is developed to reconstruct its virtual space. Finally, a DLL injection covert page detection sub-algorithm is designed based on the physical memory page subset and virtual space page subset. The experimental results indicate that MRCIF achieves an accuracy of 88.89%, which is much higher than that of the traditional DLL module injection detection method, and only MRCIF can accurately detect the Virtual Address Descriptor (VAD) remapping attack.
An Ensemble Tree-Based Model for Intrusion Detection in Industrial Internet of Things Networks
Authors: Awotunde Joseph Bamidele , Folorunso Sakinat Oluwabukonla , Imoize Agbotiname Lucky , Odunuga Julius Olusola , Lee Cheng-Chi , Li Chun-Ta , Do Dinh-Thuan
Published: February 2023

With less human involvement, the Industrial Internet of Things (IIoT) connects billions of heterogeneous and self-organized smart sensors and devices. Recently, IIoT-based technologies are now widely employed to enhance the user experience across numerous application domains. However, heterogeneity in the node source poses security concerns affecting the IIoT system, and due to device vulnerabilities, IIoT has encountered several attacks. Therefore, security features, such as encryption, authorization control, and verification, have been applied in IIoT networks to secure network nodes and devices. However, the requisite machine learning models require some time to detect assaults because of the diverse IIoT network traffic properties. Therefore, this study proposes ensemble models enabled with a feature selection classifier for Intrusion Detection in the IIoT network. The Chi-Square Statistical method was used for feature selection, and various ensemble classifiers, such as eXtreme gradient boosting (XGBoost), Bagging, extra trees (ET), random forest (RF), and AdaBoost can be used for the detection of intrusion applied to the Telemetry data of the TON_IoT datasets. The performance of these models is appraised based on accuracy, recall, precision, F1-score, and confusion matrix. The results indicate that the XGBoost ensemble showed superior performance with the highest accuracy over other models across the datasets in detecting and classifying IIoT attacks.
Properties of Dyes for Painting with Spectroscopy in the Visible and Near Infrared Range
Authors: Žiljak Gršić Jana , Plehati Silvio , Žiljak Stanimirović Ivana , Bogović Tomislav
Published: February 2023

This study focuses on the properties of reflection and absorption of light in the visible and near infrared range of acrylic dyes and related materials for coloring. The research aims to understand the use of acrylic dyes in fine arts and to simulate these dyes for printing purposes. Two groups of acrylic dyes were studied using spectroscopy to determine their light absorption properties in the visible (VIS) and near infrared (NIR) regions. The measurements were performed with forensic cameras equipped with 24 light filters in the range of 400–1000 nm. The results of the digital recordings were compared with video surveillance cameras that operate and record during the day and night. The same color had at least two formulations of dyes for print reproduction to simulate what the naked eye sees and to simulate light absorption in the NIR spectrum. The study aimed to gain a deeper understanding of the properties of acrylic paints and related materials, considering how they can be used in fine arts and how to simulate them in printing.
A New Framework for Visual Classification of Multi-Channel Malware Based on Transfer Learning
Authors: Zhao Zilin , Yang Shumian , Zhao Dawei
Published: February 2023

With the continuous development and popularization of the Internet, there has been an increasing number of network security problems appearing. Among them, the rapid growth in the number of malware and the emergence of variants have seriously affected the security of the Internet. Traditional malware detection methods require heavy feature engineering, which seriously affects the efficiency of detection. Existing deep-learning-based malware detection methods have problems such as poor generalization ability and long training time. Therefore, we propose a malware classification method based on transfer learning for multi-channel image vision features and ResNet convolutional neural networks. Firstly, the features of malware samples are extracted and converted into grayscale images of three different types. Then, the grayscale image sizes are processed using the bilinear interpolation algorithm to make them uniform in size. Finally, the three grayscale images are synthesized into three-dimensional RGB images, and the RGB images processed using data enhancement are used for training and classification. For the classification model, we used the previous ImageNet dataset (>10 million) and trained all the parameters of ResNet after loading the weights. For the evaluations, an experiment was conducted using the Microsoft BIG benchmark dataset. The experimental results showed that the accuracy on the Microsoft dataset reached 99.99%. We found that our proposed method can better extract the texture features of malware, effectively improve the accuracy and detection efficiency, and outperform the compared models on all performance metrics.
Redundancy-Reduction-Based Hierarchical Design in Synchronization of Multi-Agent Systems
Authors: Que Haoyi , Xu Zhaowen , Su Hongye
Published: February 2023

In this paper, a layered, undirected-network-structure, optimization approach is proposed to reduce the redundancy in multi-agent information synchronization and improve the computing rate. Based on the traversing binary tree and aperiodic sampling of the complex delayed networks theory, we proposed a network-partitioning method for pinning dynamic networks, with a more simplified, analyzable structure, and all of the traversed nodes are mathematically asymptotically synchronized at the same time. Moreover, a systematic implementable approach is proposed for application. The approach could be separated into two main steps: the first is a method of network partition that reduces the trivial interaction, which does not affect the information traversal, and the second involves applying the time-dependent functional approach of Lyapunov to give global exponential conditions, under the criteria for the synchronization of multiple agents, with a lower conservatism of the decision variables compared to some other results, so that the information available could fully benefit from the actual discrete-time communication pattern. Both mathematical proofs and numerical example evidence are presented to demonstrate the effectiveness of the implemented approach. This class contains a number of practically interesting systems, for instance, unmanned aerial vehicle (UAV) formation systems or the ground-air coordinated unmanned aerial system.
Changes on Grape Aroma Composition as a Consequence of Foliar Application of Methyl Jasmonate and Nano-Sized Particles Doped with Methyl Jasmonate
Authors: Marín-San Román Sandra , Pérez-Álvarez Eva Pilar , Sáenz de Urturi Itziar , Parra-Torrejón Belén , Ramírez-Rodríguez Gloria B. , Delgado-López José Manuel , Garde-Cerdán Teresa
Published: February 2023

In recent years, foliar application of elicitors to the vineyard has been increasingly used, in particular, elicitation with methyl jasmonate (MeJ). However, due to the high cost of this compound, it is necessary to find a form of application in which the amount to be used is considerably reduced. Therefore, the aim of this work was study for the first time the influence of foliar application of nanoparticles doped with MeJ (ACP-MeJ) and foliar application of methyl jasmonate (MeJ), using a dose of 1 mM versus 10 mM, respectively, on volatile composition of Tempranillo grapes during two consecutive vintages. Grape volatile composition was determined by SPME-GC-MS. The obtained results reveal that MeJ application increased the concentration of terpenoids, and total C6 compounds in 2019 and 2020, and C13 norisoprenoids in 2019. In addition, ACP-MeJ enhanced the amount of terpenoids, and benzenoids in 2020. These are encouraging results considering that the ACP-MeJ dose was 10 times lower than that of MeJ. Therefore, the foliar application of MeJ supported on nanoparticles could be a tool in order to improve grape volatile composition, favoring a more viable and sustainable viticulture.
Automatic Ship Object Detection Model Based on YOLOv4 with Transformer Mechanism in Remote Sensing Images
Authors: Sun Bowen , Wang Xiaofeng , Oad Ammar , Pervez Amjad , Dong Feng
Published: February 2023

Despite significant advancements in object detection technology, most existing detection networks fail to investigate global aspects while extracting features from the inputs and cannot automatically adjust based on the characteristics of the inputs. The present study addresses this problem by proposing a detection network consisting of three stages: preattention, attention, and prediction. In the preattention stage, the network framework is automatically selected based on the features of the images’ objects. In the attention stage, the transformer structure is introduced. Taking into account the global features of the target, this study combines a self-attention module in the transformer model and convolution operation to integrate image features from global to local and for detection, thus improving the ship target accuracy. This model uses mathematical methods to obtain results of predictive testing in the prediction stage. The above improvements are based on the You Only Look Once version 4 (YOLOv4) framework, named “Auto-T-YOLO”. The model achieves the highest accuracy of 96.3% on the SAR Ship Detection dataset (SSDD) compared to the other state-of-the-art (SOTA) model. It achieves 98.33% and 91.78% accuracy in the offshore and inshore scenes, respectively. The experimental results verify the practicality, validity, and robustness of the proposed model.
Simulation, Analysis, and Experimentation of the Compliant Finger as a Part of Hand-Compliant Mechanism Development
Authors: Stojiljković Dušan , Milošević Maša , Ristić-Durrant Danijela , Nikolić Vlastimir , Pavlović Nenad T. , Ćirić Ivan , Ivačko Nikola
Published: February 2023

Compliant mechanisms are gaining popularity in many different fields, such as in microelectromechanical systems (MEMS), medical applications and health care, opto-mechatronic technology, aerospace engineering, and semiconductor equipment. One of the areas for utilizing compliant mechanisms is building models of human hand counterparts. These models are often used as grasping and rehabilitation devices. Because of their properties, creating a human hand counterpart with compliant mechanisms is a much better choice compared with the models with traditional mechanisms; it looks more realistic, and its movements are much more natural compared with models with a traditional mechanism. A method of modeling and designing such a bio-inspired mechanism, as well as its experimental analysis with various forces applied, is presented in this paper. Two prototypes of the compliant fingers were obtained by 3D printing, and the calculation of the bending angle values was achieved by applying image processing to camera images of the compliant fingers’ prototypes. Image processing was conducted on images taken for both loaded and unloaded 3D-printed compliant finger prototype positions. Finally, these bending angle results are compared with the results obtained by Finite Element Method (FEM) analysis and experimental results acquired by a digital protractor.
Investigation of Compressive Strength Characteristics of Hardfill Material and Seismic Stability of Hardfill Dams
Authors: Kim Soogeun , Choi Wonhyuk , Kim Yunhee , Shin Jaewoo , Kim Bumjoo
Published: February 2023

A hardfill dam can reduce the natural damage caused by the development of quarries and recycle submerged resources. However, the particle size distribution of the aggregate can result in large variations in the mix design, resulting in a wide range of strengths in the hardfill dam body. Therefore, quality control during construction is crucial, and the stability of the dam body after construction should be thoroughly examined in advance. This study investigated the strength characteristics of hardfill dam materials according to the particle size and mixing ratio through indoor uniaxial compressive strength tests using large specimens and uniaxial compressive strength tests for field compaction and collected cores. Furthermore, the stability of hardfill dams with three types of slopes during earthquakes was evaluated through a finite element analysis. The distributions of stress in the hardfill dam body and the strength required to stabilize the dam body were investigated. Except for a 1:0.6 inclined hardfill dam body to which artificial seismic waves were applied, the overall strength range calculated from the indoor specimens and field compaction cores exceeded the required hardfill strength, thereby ensuring stability in the event of an earthquake.
Three-Dimensional Modeling of Heart Soft Tissue Motion
Authors: Liu Mingzhe , Zhang Xuan , Yang Bo , Yin Zhengtong , Liu Shan , Yin Lirong , Zheng Wenfeng
Published: February 2023

The modeling and simulation of biological tissue is the core part of a virtual surgery system. In this study, the geometric and physical methods related to soft tissue modeling were investigated. Regarding geometric modeling, the problem of repeated inverse calculations of control points in the Bezier method was solved via re-parameterization, which improved the calculation speed. The base surface superposition method based on prior information was proposed to make the deformation model not only have the advantages of the Bezier method but also have the ability to fit local irregular deformation surfaces. Regarding physical modeling, the fitting ability of the particle spring model to the anisotropy of soft tissue was improved by optimizing the topological structure of the particle spring model. Then, the particle spring model had a more extensive nonlinear fitting ability through the dynamic elastic coefficient parameter. Finally, the secondary modeling of the elastic coefficient based on the virtual body spring enabled the model to fit the creep and relaxation characteristics of biological tissue according to the elongation of the virtual body spring.
Tannin Extraction from Chestnut Wood Waste: From Lab Scale to Semi-Industrial Plant
Authors: Aimone Clelia , Grillo Giorgio , Boffa Luisa , Giovando Samuele , Cravotto Giancarlo
Published: February 2023

The chestnut tree (Castanea sativa, Mill.) is a widespread plant in Europe whose fruits and wood has a relevant economic impact. Chestnut wood (CW) is rich in high-value compounds that exhibit various biological activities, such as antioxidant as well as anticarcinogenic and antimicrobial properties. These metabolites can be mainly divided into monomeric polyphenols and tannins. In this piece of work, we investigated a sustainable protocol to isolate enriched fractions of the above-mentioned compounds from CW residues. Specifically, a sequential extraction protocol, using subcritical water, was used as a pre-fractionation step, recovering approximately 88% of tannins and 40% of monomeric polyphenols in the first and second steps, respectively. The optimized protocol was also tested at pre-industrial levels, treating up to 13.5 kg CW and 160 L of solution with encouraging results. Ultra- and nanofiltrations were used to further enrich the recovered fractions, achieving more than 98% of the tannin content in the heavy fraction, whilst the removed permeate achieved up to 752.71 mg GAE/gext after the concentration (75.3%). Samples were characterized by means of total phenolic content (TPC), antioxidant activity (DPPH· and ABTS·), and tannin composition (hydrolysable and condensed). In addition, LC-MS-DAD was used for semiqualitative purposes to detect vescalagin/castalagin and vescalin/castalin, as well as gallic acid and ellagic acid. The developed valorization protocol allows the efficient fractionation and recovery of the major polyphenolic components of CW with a sustainable approach that also evaluates pre-industrial scaling-up.
Barriers to Enduring Pro-Environmental Habits among Urban Residents
Authors: Akram Farheen , Gill Abid Rashid , Abrar ul Haq Muhammad , Arshad Afrasiyab , Malik Hafiz Abid Mahmood
Published: February 2023

This research article examines the impact of economic, health, environmental, and social-economic factors on diverse forms of pro-environmental consumption: energy conservation, water conservation, and recycling. Primary data concerning these variables were collected from 430 individuals using a structured questionnaire following the cluster sampling methodology. Results indicate that one unit increase in environmental, economic, and health concerns improve pro-environment behavior by 52, 64, and 25 units, respectively. In contrast, a 1 unit increase in income deteriorates pro-environment behavior by 0.01 units. Education, age, gender, and owning a home have an insignificant impact on pro-environmental habits. The model explains a 52% variation in pro-environmental habits. The study recommends that effective electronic and social media campaigns increase environmental, economic, and health concerns and improve green behavior. More courses on environmental sustainability in schools and universities can effectively increase ecological knowledge and concerns.
Negative Effect Prediction and Refueling Traffic Flow Equilibrium of Urban Energy Supply Network during Weekends and Holidays
Authors: Ge Xianlong , Yin Zuofa , Zou Yuanqiu , Wang Bo
Published: February 2023

With the continuous improvement of people’s living standards, the travel demand for vehicles increases rapidly during weekends and holidays. This situation leads to a number of negative impacts on the transport network, such as traffic congestion, carbon emissions, and long queues at refueling stations. The impact of vehicles requiring energy replenishment on the negative effect is nonlinear. Therefore, the negative effect data of working days cannot be directly used to evaluate the cost, and the traffic equilibrium allocation problem also needs to be solved. An equilibrium allocation model of hybrid vehicles considering the energy replenishment demand in holidays is established, aiming at minimizing the total time cost and energy consumption cost. The Frank–Wolfe algorithm is used to solve the traffic allocation problem in advance, and the negative effect of the urban energy network during holidays is predicted by the Genetic Algorithm—Back Propagation (GA-BP) algorithm. Then, the energy-replenishing vehicles in the traffic network are induced to reduce the total cost. Finally, taking the actual road network in Jiulongpo District of Chongqing City, southwest of China, as an example, the negative effects of multiple stations are predicted. The results show that the prediction method proposed in this paper is effective during holiday periods. In addition, as the market share of electric vehicles increases, the negative cost can decrease gradually. The predicted results can provide a reference for traffic managers.
Inspirations and Traces in the Works of Pál Frenák
Authors: Horváth Nóra
Published: February 2023

I have known Frenák’s choreographies for almost twenty years, and since 2017, I have been regularly presenting discussions at domestic and international conferences regarding studies of the aesthetic and philosophical aspects of Frenák’s work. We started to work together some years ago. I assisted in the creation of the productions Cage (2019), Spid_er (2020), Fig_Ht (2021) and Secret Off_Man (2022) as a philosophical consultant. When researching and collecting the inspirational material, I experienced impressions that affected my other works as well. My work as a philosopher with dance and the conversations with Frenák opened new pathways to self-knowledge. When it seems that everything points in the same direction and everything is about the same topic, it is time to create a trace. This was my feeling when I wrote and published my book on Frenák in 2022, entitled L’abécédaire of Pál Frenák—Transverses Between Philosophy and the Organic Movement Language of FrenÁk (Published in Hungarian and in English in one book: Frenák Pál Abécédaire-je—Átjárások a filozófia és FrenÁk organikus mozgásnyelve között, Kortárs Táncért és Jelelő Színházért Alapítvány, Budapest, 2022). In this paper, I am going to display some essential inspirations of the fantastically creative art world of Frenák.
Grounding the Landscape: Epistemic Aspects of Materiality in Late-Nineteenth-Century American Open-Air Painting
Authors: Gonnen Noam
Published: February 2023

This article examines how notions of “material” and “materiality” were infused, both technically and discursively, into American landscape painting in the late nineteenth century. Focusing particularly on the praxis of open-air painting as consolidating a new mode in landscape painting as well as a new artistic identity, this article argues that painting outdoors was perceived by artists in terms of agency, uniting painter, painting, and landscape; but unlike earlier romantic or Transcendentalist approaches, this idea was not conceived of as a solely spiritual union but, rather, as a mode that is embedded in the mundane, in the existence of objects, of embodied engagement and material means. The overt affinity between the basic idea of the praxis—painting outdoors in ‘real’ nature—and material aspects of art-making, is discussed as the underpinning of a new emerging episteme of American landscape painting, while considering the environment wherein this phenomenon was cultivated within a specific moment in American culture. Paintings and texts, generated by American painters and critics between the late 1870s and the 1890s, are read in this article through the lens of recent theoretical phenomenological approaches to landscape, illuminating the unique role that materiality played in these representations. Moreover, tying the findings to the changing conceptions of both landscape and art in the Gilded Age, the article concludes that landscape painters of the ‘new generation’ sought to evade commodifying tendencies of image-making by deliberately engaging with materiality, devising a mode of landscape representation that would not succumb to the flattening steamroller of capitalist consumer culture.
Dynamic Multi-Compartment Vehicle Routing Problem for Smart Waste Collection
Authors: Bouleft Yousra , Elhilali Alaoui Ahmed
Published: February 2023

The rapid increase in urbanization results in an increase in the volume of municipal solid waste produced every day, causing overflow of the garbage cans and thus distorting the city’s appearance; for this and environmental reasons, smart cities involve the use of modern technologies for intelligent and efficient waste management. Smart bins in urban environments contain sensors that measure the status of containers in real-time and trigger wireless alarms if the container reaches a predetermined threshold, and then communicate the information to the operations center, which then sends vehicles to collect the waste from the selected stations in order to collect a significant waste amount and reduce transportation costs. In this article, we will address the issue of the Dynamic Multi-Compartmental Vehicle Routing Problem (DM-CVRP) for selective and intelligent waste collection. This problem is summarized as a linear mathematical programming model to define optimal dynamic routes to minimize the total cost, which are the transportation costs and the penalty costs caused by exceeding the bin capacity. The hybridized genetic algorithm (GA) is proposed to solve this problem, and the effectiveness of the proposed approach is verified by extensive numerical experiments on instances given by Valorsul, with some modifications to adapt these data to our problem. Then we were able to ensure the effectiveness of our approach based on the results in the static and dynamic cases, which are very encouraging.
L1-Norm Robust Regularized Extreme Learning Machine with Asymmetric C-Loss for Regression
Authors: Wu Qing , Wang Fan , An Yu , Li Ke
Published: February 2023

Extreme learning machines (ELMs) have recently attracted significant attention due to their fast training speeds and good prediction effect. However, ELMs ignore the inherent distribution of the original samples, and they are prone to overfitting, which fails at achieving good generalization performance. In this paper, based on expectile penalty and correntropy, an asymmetric C-loss function (called AC-loss) is proposed, which is non-convex, bounded, and relatively insensitive to noise. Further, a novel extreme learning machine called L1 norm robust regularized extreme learning machine with asymmetric C-loss (L1-ACELM) is presented to handle the overfitting problem. The proposed algorithm benefits from L1 norm and replaces the square loss function with the AC-loss function. The L1-ACELM can generate a more compact network with fewer hidden nodes and reduce the impact of noise. To evaluate the effectiveness of the proposed algorithm on noisy datasets, different levels of noise are added in numerical experiments. The results for different types of artificial and benchmark datasets demonstrate that L1-ACELM achieves better generalization performance compared to other state-of-the-art algorithms, especially when noise exists in the datasets.
Axiomatics of the Observer Manifold and Relativity
Authors: Kichenassamy Satyanad
Published: February 2023

We show that Special and General Relativity lead to the introduction of an observer manifold, in addition to the usual event manifold. Axiomatics that require that manifolds be Hausdorff are not appropriate for the observer manifold. We propose an alternative axiomatics and show how most of the usual local computations extend to this framework without difficulty. The derivation of the Lorentz transformation takes a new meaning in this context, enabling the identification of the representations of several observers and hence reducing the observer manifold to the event manifold. However, we show in an example relevant to the radiation of accelerated electrons that this identification is not always correct. This appears to be relevant in any situation where gravitational fields in remote locations have to be measured on Earth, such as the detection of gravitational waves, or when high accelerations are involved, such as in electron radiation or laser cooling.
Correction: Marconi et al. Human Periodontal Ligament Stem Cells Response to Titanium Implant Surface: Extracellular Matrix Deposition. Biology 2021, 10, 931
Authors: Marconi Guya Diletta , Fonticoli Luigia , Rocca Ylenia Della , Rajan Thangavelu Soundara , Piattelli Adriano , Trubiani Oriana , Pizzicannella Jacopo , Diomede Francesca
Published: February 2023

In the original publication [...]
Pathways for Cardioprotection in Perspective: Focus on Remote Conditioning and Extracellular Vesicles
Authors: Comità Stefano , Rubeo Chiara , Giordano Magalì , Penna Claudia , Pagliaro Pasquale
Published: February 2023

Despite the development of cutting-edge treatments, coronary artery disease (CAD) morbidity and mortality rates remain present at high levels. Therefore, new cardioprotective approaches are crucial to improve the health of patients. To date, experimental investigations of acute ischemia-reperfusion injury (IRI) have generally demonstrated the efficacy of local ischemic preconditioning and postconditioning cardioprotection techniques as well as of remote conditioning. However, application in clinical settings is still highly controversial and debated. Currently, remote ischemic conditioning (RIC) seems to be the most promising method for heart repair. Protective factors are released into the bloodstream, and protection can be transferred within and across species. For a long time, the cross-function and cross-transmission mechanisms of cardioprotection were largely unknown. Recently, it has been shown that small, anuclear, bilayered lipid membrane particles, known as extracellular vesicles (EVs), are the drivers of signal transduction in cardiac IRI and RIC. EVs are related to the pathophysiological processes of cardiovascular diseases (CVDs), according to compelling evidence. In this review, we will first review the current state of knowledge on myocardial IRI and cardioprotective strategies explored over the past 37 years. Second, we will briefly discuss the role of EVs in CVD and the most recent improvements on EVs as prognostic biomarkers, diagnostic, and therapeutic agents. We will discuss how EVs can be used as a new drug delivery mechanism and how they can be employed in cardiac treatment, also from a perspective of overcoming the impasse that results from neglecting confounding factors.
Raised FGF23 Correlates to Increased Mortality in Critical Illness, Independent of Vitamin D
Authors: Thein Onn Shaun , Ali Naeman Akbar , Mahida Rahul Y. , Dancer Rachel C. A. , Ostermann Marlies , Amrein Karin , Martucci Gennaro , Scott Aaron , Thickett David R. , Parekh Dhruv
Published: February 2023

Background: Fibroblast Growth Factor (FGF23) is an endocrine hormone classically associated with the homeostasis of vitamin D, phosphate, and calcium. Elevated serum FGF23 is a known independent risk factor for mortality in chronic kidney disease (CKD) patients. We aimed to determine if there was a similar relationship between FGF23 levels and mortality in critically ill patients. Methods: Plasma FGF23 levels were measured by ELISA in two separate cohorts of patients receiving vitamin D supplementation: critical illness patients (VITdAL-ICU trial, n = 475) and elective oesophagectomy patients (VINDALOO trial, n = 76). Mortality data were recorded at 30 and 180 days or at two years, respectively. FGF23 levels in a healthy control cohort were also measured (n = 27). Results: Elevated FGF23 (quartile 4 vs. quartiles 1–3) was associated with increased short-term (30 and 180 day) mortality in critical illness patients (p < 0.001) and long-term (two-year) mortality in oesophagectomy patients (p = 0.0149). Patients who died had significantly higher FGF23 levels than those who survived: In the critical illness cohort, those who died had 1194.6 pg/mL (range 0–14,000), while those who survived had 120.4 pg/mL (range = 15–14,000) (p = 0.0462). In the oesophagectomy cohort, those who died had 1304 pg/mL (range = 154–77,800), while those who survived had 644 pg/mL (range = 179–54,894) (p < 0.001). This was found to be independent of vitamin D or CKD status (critical illness p = 0.3507; oesophagectomy p = 0.3800). FGF23 levels in healthy controls were similar to those seen in oesophagectomy patients (p = 0.4802). Conclusions: Elevated baseline serum FGF23 is correlated with increased mortality in both the post-oesophagectomy cohort and the cohort of patients with critical illness requiring intensive care admission. This was independent of vitamin D status, supplementation, or CKD status, which suggests the presence of vitamin D-independent mechanisms of FGF23 action during the acute and convalescent stages of critical illness, warranting further investigation.
Cortisol Rapidly Facilitates Glucocorticoid Receptor Translocation to the Plasma Membrane in Primary Trout Hepatocytes
Authors: Das Chinmayee , Vijayan Mathilakath M.
Published: February 2023

Glucocorticoids (GCs) stimulate rapid cell signalling by activating the membrane-anchored intracellular glucocorticoid receptor (GR). However, the recruitment of the GR to the plasma membrane to facilitate nongenomic signalling is far from clear. As cytosolic free calcium ([Ca2+]i) is involved in intracellular protein dynamics, we tested the hypothesis that acute elevation in cortisol levels rapidly stimulates GR translocation to the plasma membrane via a calcium-dependent process in rainbow trout (Oncorhynchus mykiss) hepatocytes. To test this, we monitored temporal changes in intracellular GR distribution in response to cortisol exposure. Immunofluorescence labelling showed that the GR was present in cytosolic and nuclear compartments in trout hepatocytes. However, upon cortisol exposure, the GR rapidly (within 5 min) formed punctate and colocalized with caveolin-1, suggesting plasma membrane localization of the receptor. This redistribution of the GR to the plasma membrane was transient and lasted for 30 min and was evident even upon exposure to cortisol-BSA, a membrane-impermeable analogue of the steroid. The rapid cortisol-mediated GR translocation to the plasma membrane involved F-actin polymerization and was completely abolished in the presence of either EGTA or Cpd5J-4, a calcium release–activated calcium (CRAC) channel blocker. Additionally, the modulation of the biophysical properties of the plasma membrane by cholesterol or methyl β-cyclodextrin, which led to changes in ([Ca2+]i) levels, modified GR translocation to the plasma membrane. Altogether, acute cortisol-mediated rise in ([Ca2+]i) levels rapidly stimulated the translocation of intracellular GR to the plasma membrane, and we propose this as a mechanism promoting the nongenomic action of the GR for hepatocyte stress resistance.
Salmonella Phage CKT1 Effectively Controls the Vertical Transmission of Salmonella Pullorum in Adult Broiler Breeders
Authors: Cui Ketong , Li Peiyong , Huang Jiaqi , Lin Fang , Li Ruibo , Cao Dingguo , Hao Guijuan , Sun Shuhong
Published: February 2023

Phage therapy is widely being reconsidered as an alternative to antibiotics for the treatment of multidrug-resistant bacterial infections, including salmonellosis caused by Salmonella. As facultative intracellular parasites, Salmonella could spread by vertical transmission and pose a great threat to both human and animal health; however, whether phage treatment might provide an optional strategy for controlling bacterial vertical infection remains unknown. Herein, we explored the effect of phage therapy on controlling the vertical transmission of Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum), a poultry pathogen that causes economic losses worldwide due to high mortality and morbidity. A Salmonella phage CKT1 with lysis ability against several S. enterica serovars was isolated and showed that it could inhibit the proliferation of S. Pullorum in vitro efficiently. We then evaluated the effect of phage CKT1 on controlling the vertical transmission of S. Pullorum in an adult broiler breeder model. The results demonstrated that phage CKT1 significantly alleviated hepatic injury and decreased bacterial load in the liver, spleen, heart, ovary, and oviduct of hens, implying that phage CKT1 played an active role in the elimination of Salmonella colonization in adult chickens. Additionally, phage CKT1 enabled a reduction in the Salmonella-specific IgG level in the serum of infected chickens. More importantly, the decrease in the S. Pullorum load on eggshells and in liquid whole eggs revealed that phage CKT1 effectively controlled the vertical transmission of S. Pullorum from hens to laid eggs, indicating the potential ability of phages to control bacterial vertical transmission.
Phylogenetic Diversity of the Red Swamp Crayfish Procambarus clarkii and Its Dispersal Pattern in Northern and Central Italy
Authors: Scoparo Melissa , Cardinali Irene , La Porta Gianandrea , Caldaroni Barbara , Magara Gabriele , Dörr Ambrosius Josef Martin , Elia Antonia Concetta , Lancioni Hovirag
Published: February 2023

The red swamp crayfish Procambarus clarkii is one of the most threatening freshwater species in the world. The aim of this study is to provide a better understanding of the phylogeography and the invasion routes of P. clarkii populations in the Italian Peninsula through the analysis of mitochondrial phylogeny. Mitochondrial control region and cytochrome c oxidase subunit I (COI) sequences of 153 samples collected from six Italian basins were analyzed and compared to worldwide data. Except for the lakes Bolsena and Posta Fibreno, a high genetic variability was found in the other basins. The mitochondrial DNA pattern of P. clarkii from the lakes Candia and Massaciuccoli confirmed the hypothesis of double introduction events. Another entry point could be represented by Lake Trasimeno, which shows haplotypes originating from Louisiana and not shared with other Italian basins. Moreover, unique lineages were also found in the Stella River, thus enhancing the hypothesis that multiple introductions of P. clarkii occurred in northern and Central Italy and strengthening the idea that knowledge about the dispersion routes of this alien species can be useful to predict its invasiveness and elaborate control strategies to preserve biodiversity.
The Constitutive Activity of Spinal 5-HT6 Receptors Contributes to Diabetic Neuropathic Pain in Rats
Authors: Mokhtar Nazarine , Drop Marcin , Jacquot Florian , Lamoine Sylvain , Chapuy Eric , Prival Laetitia , Aissouni Youssef , Canale Vittorio , Lamaty Frédéric , Zajdel Paweł , Marin Philippe , Doly Stéphane , Courteix Christine
Published: February 2023

Diabetic neuropathy is often associated with chronic pain. Serotonin type 6 (5-HT6) receptor ligands, particularly inverse agonists, have strong analgesic potential and may be new candidates for treating diabetic neuropathic pain and associated co-morbid cognitive deficits. The current study addressed the involvement of 5-HT6 receptor constitutive activity and mTOR signaling in an experimental model of diabetic neuropathic pain induced by streptozocin (STZ) injection in the rat. Here, we show that mechanical hyperalgesia and associated cognitive deficits are suppressed by the administration of 5-HT6 receptor inverse agonists or rapamycin. The 5-HT6 receptor ligands also reduced tactile allodynia in traumatic and toxic neuropathic pain induced by spinal nerve ligation and oxaliplatin injection. Furthermore, both painful and co-morbid cognitive symptoms in diabetic rats are reduced by intrathecal delivery of a cell-penetrating peptide that disrupts 5-HT6 receptor-mTOR physical interaction. These findings demonstrate the deleterious influence of the constitutive activity of spinal 5-HT6 receptors upon painful and cognitive symptoms in diabetic neuropathic pains of different etiologies. They suggest that targeting the constitutive activity of 5-HT6 receptors with inverse agonists or disrupting the 5-HT6 receptor-mTOR interaction might be valuable strategies for the alleviation of diabetic neuropathic pain and cognitive co-morbidities.
Commonly Used Therapeutics Associated with Changes in Arousal Inhibit GABAAR Activation
Authors: Kaplan Anling , Nash Abigail I. , Freeman Amanda A. H. , Lewicki Lauren G. , Rye David B. , Trotti Lynn Marie , Brandt Asher L. , Jenkins Andrew
Published: February 2023

GABAA receptor-positive modulators are well-known to induce sedation, sleep, and general anesthesia. Conversely, GABAA receptor negative allosteric modulators (GABAARNAMs) can increase arousal and induce seizures. Motivated by our studies with patients with hypersomnia, and our discovery that two GABAARNAMs can restore the Excitation/Inhibition (E/I) balance in vitro and arousal in vivo, we chose to screen 11 compounds that have been reported to modulate arousal, to see if they shared a GABA-related mechanism. We determined modulation with both conventional and microfluidic patch clamp methods. We found that receptor activation was variably modulated by all 11 compounds: Rifampicin (RIF), Metronidazole (MET), Minocycline (MIN), Erythromycin (ERY), Ofloxacin (OFX), Chloroquine (CQ), Hydroxychloroquine sulfate (HCQ), Flumazenil (FLZ), Pentylenetetrazol (PTZ), (-)-Epigallocatechin Gallate (EGCG), and clarithromycin (CLR). The computational modeling of modulator–receptor interactions predicted drug action at canonical binding sites and novel orphan sites on the receptor. Our findings suggest that multiple avenues of investigation are now open to investigate large and brain-penetrant molecules for the treatment of patients with diminished CNS E/I balance.
Multi-Parameter Detection of Urine Based on Electropolymerized PANI: PSS/AuNPs/SPCE
Authors: Wang Dong , Mao Xiyu , Liang Yitao , Cai Yu , Tu Tingting , Zhang Shanshan , Li Tianyu , Fang Lu , Zhou Yue , Wang Zhaoyang , Jiang Yu , Ye Xuesong , Liang Bo
Published: February 2023

Urine analysis is widely used in clinical practice to indicate human heathy status and is important for diagnosing chronic kidney disease (CKD). Ammonium ions (NH4+), urea, and creatinine metabolites are main clinical indicators in urine analysis of CKD patients. In this paper, NH4+ selective electrodes were prepared using electropolymerized polyaniline-polystyrene sulfonate (PANI: PSS), and urea- and creatinine-sensing electrodes were prepared by modifying urease and creatinine deiminase, respectively. First, PANI: PSS was modified on the surface of an AuNPs-modified screen-printed electrode, as a NH4+-sensitive film. The experimental results showed that the detection range of the NH4+ selective electrode was 0.5~40 mM, and the sensitivity reached 192.6 mA M−1 cm−2 with good selectivity, consistency, and stability. Based on the NH4+-sensitive film, urease and creatinine deaminase were modified by enzyme immobilization technology to achieve urea and creatinine detection, respectively. Finally, we further integrated NH4+, urea, and creatinine electrodes into a paper-based device and tested real human urine samples. In summary, this multi-parameter urine testing device offers the potential for point-of-care testing of urine and benefits the efficient chronic kidney disease management.
SERS Determination of Oxidative Stress Markers in Saliva Using Substrates with Silver Nanoparticle-Decorated Silicon Nanowires
Authors: Kanioura Anastasia , Geka Georgia , Kochylas Ioannis , Likodimos Vlassis , Gardelis Spiros , Dimitriou Anastasios , Papanikolaou Nikolaos , Kakabakos Sotirios , Petrou Panagiota
Published: February 2023

Glutathione and malondialdehyde are two compounds commonly used to evaluate the oxidative stress status of an organism. Although their determination is usually performed in blood serum, saliva is gaining ground as the biological fluid of choice for oxidative stress determination at the point of need. For this purpose, surface-enhanced Raman spectroscopy (SERS), which is a highly sensitive method for the detection of biomolecules, could offer additional advantages regarding the analysis of biological fluids at the point of need. In this work, silicon nanowires decorated with silver nanoparticles made by metal-assisted chemical etching were evaluated as substrates for the SERS determination of glutathione and malondialdehyde in water and saliva. In particular, glutathione was determined by monitoring the reduction in the Raman signal obtained from substrates modified with crystal violet upon incubation with aqueous glutathione solutions. On the other hand, malondialdehyde was detected after a reaction with thiobarbituric acid to produce a derivative with a strong Raman signal. The detection limits achieved after optimization of several assay parameters were 50 and 3.2 nM for aqueous solutions of glutathione and malondialdehyde, respectively. In artificial saliva, however, the detection limits were 2.0 and 0.32 μM for glutathione and malondialdehyde, respectively, which are, nonetheless, adequate for the determination of these two markers in saliva.