bluuebunny/crossref_metadata_2025 huggingface dataset:
Nanomaterials-Based Combinatorial Therapy as a Strategy to Combat Antibiotic Resistance
Authors: León-Buitimea Angel , Garza-Cárdenas Cesar R. , Román-García María Fernanda , Ramírez-Díaz César Agustín , Ulloa-Ramírez Martha , Morones-Ramírez José Rubén
Published: June 2022

Since the discovery of antibiotics, humanity has been able to cope with the battle against bacterial infections. However, the inappropriate use of antibiotics, the lack of innovation in therapeutic agents, and other factors have allowed the emergence of new bacterial strains resistant to multiple antibiotic treatments, causing a crisis in the health sector. Furthermore, the World Health Organization has listed a series of pathogens (ESKAPE group) that have acquired new and varied resistance to different antibiotics families. Therefore, the scientific community has prioritized designing and developing novel treatments to combat these ESKAPE pathogens and other emergent multidrug-resistant bacteria. One of the solutions is the use of combinatorial therapies. Combinatorial therapies seek to enhance the effects of individual treatments at lower doses, bringing the advantage of being, in most cases, much less harmful to patients. Among the new developments in combinatorial therapies, nanomaterials have gained significant interest. Some of the most promising nanotherapeutics include polymers, inorganic nanoparticles, and antimicrobial peptides due to their bactericidal and nanocarrier properties. Therefore, this review focuses on discussing the state-of-the-art of the most significant advances and concludes with a perspective on the future developments of nanotherapeutic combinatorial treatments that target bacterial infections.
Self-Medication with Antibiotics: Prevalence, Practices and Related Factors among the Pakistani Public
Authors: Aslam Adeel , Zin Che Suraya , Jamshed Shazia , Rahman Norny Syafinaz Ab , Ahmed Syed Imran , Pallós Péter , Gajdács Márió
Published: June 2022

Self-medication with antibiotics (SMA) has become considerably common in developing countries, which is a critical factor for driving antibiotic resistance. Individuals involved in SMA generally do not have adequate knowledge regarding the appropriate use, indications and dosage of these drugs. The objective of the present study was to investigate population SMA practices, knowledge and sociodemographic factors associated with SMA in Islamabad, Pakistan. The study adopted a cross-sectional methodology and data collection was performed through an anonymous, structured and pilot-tested questionnaire, which was interview-administered. Inferential statistics and multivariate logistic regression were performed. Out of 480 participants, 55.6% (n = 267) were male with a mean age of 37.1 ± 10.1 years; the total prevalence of SMA was 32.5%. Ciprofloxacin (42.9%) was the most commonly used antibiotic to treat coughs or colds, a runny nose, flu or sore throat, diarrhea or fevers, which were relevant reasons for SMA. Findings from multivariate logistic regression showed that predictors of SMA were: male gender (95% CI: 0.383–1.005), age (95% CI: 0.317–0.953) and highest level of education (95% CI: 0.961–0.649). Despite reasonable access to healthcare facilities, people are still obtaining antibiotics without prescription, bypassing diagnostic and consultative healthcare services. Thus, the government must implement strict healthcare policies to restrict the sale of antibiotics without prescriptions, while at the same time, targeted public awareness campaigns about the proper use of antibiotics are also required.
Mitochondrial Dysfunction and Oxidative Stress in Rheumatoid Arthritis
Authors: López-Armada María José , Fernández-Rodríguez Jennifer Adriana , Blanco Francisco Javier
Published: June 2022

Control of excessive mitochondrial oxidative stress could provide new targets for both preventive and therapeutic interventions in the treatment of chronic inflammation or any pathology that develops under an inflammatory scenario, such as rheumatoid arthritis (RA). Increasing evidence has demonstrated the role of mitochondrial alterations in autoimmune diseases mainly due to the interplay between metabolism and innate immunity, but also in the modulation of inflammatory response of resident cells, such as synoviocytes. Thus, mitochondrial dysfunction derived from several danger signals could activate tricarboxylic acid (TCA) disruption, thereby favoring a vicious cycle of oxidative/mitochondrial stress. Mitochondrial dysfunction can act through modulating innate immunity via redox-sensitive inflammatory pathways or direct activation of the inflammasome. Besides, mitochondria also have a central role in regulating cell death, which is deeply altered in RA. Additionally, multiple evidence suggests that pathological processes in RA can be shaped by epigenetic mechanisms and that in turn, mitochondria are involved in epigenetic regulation. Finally, we will discuss about the involvement of some dietary components in the onset and progression of RA.
Antioxidants and Male Infertility
Authors: Silva Ricardo , Carrageta David F. , Alves Marco G. , Silva Branca M. , Oliveira Pedro F.
Published: June 2022

Oxidative stress has been associated with decreased sperm quality and male infertility [...]
Characterization of Neurochemical Signature Alterations in the Enteric Nervous System in Autoimmune Encephalomyelitis
Authors: Kicherer Julia , Weier Alicia , Enders Michael , Neuhuber Winfried , Heider Thorsten , Kuerten Stefanie
Published: June 2022

To date, it has remained unclear whether gastrointestinal symptoms, which are frequently observed in patients with multiple sclerosis (MS), are accompanied by pathology of the enteric nervous system (ENS). Here, the neurotransmitter signature of ENS neurons and morphological alterations of interstitial cells of Cajal (ICCs) were studied in patients with MS and mice with experimental autoimmune encephalomyelitis (EAE), which is an animal model of MS. Immunohistochemical analysis was performed on colonic whole mounts from mice with EAE and on paraffin-embedded sections of intestinal tissue from patients with MS. Antibodies against neurotransmitters or their enzymes (including vasoactive intestinal peptide (VIP), neuronal nitric oxide synthase (nNOS), and choline acetyltransferase (ChAT)) were used in conjunction with pan-neuronal markers. In addition, the presence of anoctamin 1 (ANO1)-expressing ICCs was studied. ENS changes were observed in the myenteric plexus, but they were absent in the submucosal plexus of both EAE mice and patients with MS. There was a significant decrease in the percentage of ChAT-positive neurons in EAE mice as opposed to a trend toward an increase in patients with MS. Moreover, while ANO1 expression was decreased in EAE mice, patients with MS displayed a significant increase. Although additional studies are necessary to accomplish an in-depth characterization of ENS alterations in MS, our results imply that such alterations exist and may reveal novel insights into the pathophysiology of MS.
Focus on Point: Parallel Multiscale Feature Aggregation for Lane Key Points Detection
Authors: Zuo Chao , Zhang Yanyan
Published: June 2022

Lane detection, as a basic environmental perception task, plays a significant role in the safety of automatic driving. Modern lane detection methods have obtained a better performance in most scenarios, but many are unsatisfactory in various scenarios, with a weak appearance (e.g., serious vehicle occlusion, dark shadows, ambiguous markings, etc.), and have issues in simplifying model predictions and flexibly detecting lanes of a non-fixed structure and number. In this work, we abstracted the lane lines as a series of discrete key points and proposed a lane detection method of parallel multi-scale feature aggregation based on key points, FPLane. The main task of FPLane is to focus on the precise location of key points in the global lanes and aggregate the global detection results into the local geometric modeling of lane lines by using the idea of association embedding. Furthermore, this work proposes the parallel Multi-scale Feature Aggregation network (MFANet) in FPLane integrating the context information of multi-scale feature mappings to take full advantage of the prior information of adjacent positions. In addition, MFANet incorporates the Double-headed Attention Feature Fusion Up-sampling module, which can facilitate the network to accurately recognize and detect objects under extreme scale variation. Finally, our method is tested on Tusimple and CULane lane detection datasets; the results show that the proposed method outperforms the current mainstream methods: the accuracy and F1-score of the model are 96.82% and 75.6%, respectively, and the real-time detection efficiency of the model can maintain 28 ms.
Seismic Response Study of L-Shaped Frame Structure with Magnetorheological Dampers
Authors: You Jiangtao , Yang Yang , Fan Yongfeng , Zhang Xiangcheng
Published: June 2022

To analyze the multi-dimensional seismic mitigation performance and the torsional vibration characteristic of an L-shaped frame structure with a magnetorheological damper (MRD). Firstly, the mechanical property of the MRD is experimentally studied. Then, the calculation models of the L-shaped frame structure without and with MRDs are found through theoretical analysis, and the programs of the calculation models are compiled. Finally, the time history responses of the calculation models are calculated during the excitation of bi-directional seismic wave; the responses of displacement, acceleration, story drift ratio, shear force and bending moment and torsional vibration are then compared and analyzed. The results show that by adjusting the current, the damping force provided by the MRD can be adjusted continuously in the range of 3.1 to 120 kN. The compiled calculation model programs of the L-shaped frame structure without and with MRDs can effectively simulate the multi-dimensional seismic response of the structure. Reasonable arrangement of MR dampers can effectively reduce the displacement, acceleration, shear force, bending moment, multi-dimensional vibration, and torsional vibration response of L-shaped frame structures.
Visual Object Detection with DETR to Support Video-Diagnosis Using Conference Tools
Authors: Biró Attila , Jánosi-Rancz Katalin Tünde , Szilágyi László , Cuesta-Vargas Antonio Ignacio , Martín-Martín Jaime , Szilágyi Sándor Miklós
Published: June 2022

Real-time multilingual phrase detection from/during online video presentations—to support instant remote diagnostics—requires near real-time visual (textual) object detection and preprocessing for further analysis. Connecting remote specialists and sharing specific ideas is most effective using the native language. The main objective of this paper is to analyze and propose—through DEtection TRansformer (DETR) models, architectures, hyperparameters—recommendation, and specific procedures with simplified methods to achieve reasonable accuracy to support real-time textual object detection for further analysis. The development of real-time video conference translation based on artificial intelligence supported solutions has a relevant impact in the health sector, especially on clinical practice via better video consultation (VC) or remote diagnosis. The importance of this development was augmented by the COVID-19 pandemic. The challenge of this topic is connected to the variety of languages and dialects that the involved specialists speak and that usually needs human translator proxies which can be substituted by AI-enabled technological pipelines. The sensitivity of visual textual element localization is directly connected to complexity, quality, and the variety of collected training data sets. In this research, we investigated the DETR model with several variations. The research highlights the differences of the most prominent real-time object detectors: YOLO4, DETR, and Detectron2, and brings AI-based novelty to collaborative solutions combined with OCR. The performance of the procedures was evaluated through two research phases: a 248/512 (Phase1/Phase2) record train data set, with a 55/110 set of validated data instances for 7/10 application categories and 3/3 object categories, using the same object categories for annotation. The achieved score breaks the expected values in terms of visual text detection scope, giving high detection accuracy of textual data, the mean average precision ranging from 0.4 to 0.65.
Ab Initio Studies of Work Function Changes of CO Adsorption on Clean and Pd-Doped ZnGa2O4(111) Surfaces for Gas Sensors
Authors: Tung Jen-Chuan , Huang Shih-Wei , Pai Che-An , Horng Ray-Hua , Chang Cheng-Chung , Hung Dun-Ru , Liu Po-Liang
Published: June 2022

We performed first-principles calculations to study the adsorption of the CO molecules on both clean and Pd-doped ZnGa2O4(111) surfaces. The adsorption reaction and work function of the CO adsorption models were examined. The CO molecules on the clean and Pd-doped ZnGa2O4(111) surfaces exhibit maximum work function changes of −0.55 eV and −0.79 eV, respectively. The work function change of Pd-doped ZnGa2O4(111) for detecting CO is 1.43 times higher than that of the clean ZnGa2O4(111). In addition, the adsorption energy is also significantly reduced from −1.88 eV to −3.36 eV without and with Pd atoms, respectively. The results demonstrate ZnGa2O4-based gas sensors doped by palladium can improve the sensitivity of detecting CO molecules.
Hardware Development and Safety Control Strategy Design for a Mobile Rehabilitation Robot
Authors: Lee Lian-Wang , Li I-Hsum , Lu Liang-Yu , Hsu Yu-Bin , Chiou Shean-Juinn , Su Te-Jen
Published: June 2022

The use of bodyweight unloading force control on a treadmill with therapist manual assistance for gait training imposes constraints on natural walking. It influences the patient’s training effect for a full range of natural walks. This study presents a prototype and a safety controller for a mobile rehabilitation robot (MRR). The prototype integrates an autonomous mobile bodyweight support system (AMBSS) with a lower-limb exoskeleton system (LES) to simultaneously achieve natural over-ground gait training and motion relearning. Human-centered rehabilitation robots must guarantee the safety of patients in the presence of significant tracking errors. It is difficult for traditional stiff controllers to ensure safety and excellent tracking accuracy concurrently, because they cannot explicitly guarantee smooth, safe, and overdamped motions without overshoot. This paper integrated a linear extended state observer (LESO) into proxy-based sliding mode control (ILESO-PSMC) to overcome this problem. The LESO was used to observe the system’s unknown states and total disturbance simultaneously, ensuring that the “proxy” tracks the reference target accurately and avoids the unsafe control of the MRR. Based on the Lyapunov theorem to prove the closed-loop system stability, the proposed safety control strategy has three advantages: (1) it provides an accurate and safe control without worsening tracking performance during regular operation, (2) it guarantees safe recoveries and overdamped properties after abnormal events, and (3) it need not identify the system model and measure unknown system states as well as external disturbance, which is quite difficult for human–robot interaction (HRI) systems. The results demonstrate the feasibility of the proposed ILESO-PSMC for MRR. The experimental comparison also indicates better safety performance for the ILESO-PSMC than for the conventional proportional–integral–derivative (PID) control.
A Spike Neural Network Model for Lateral Suppression of Spike-Timing-Dependent Plasticity with Adaptive Threshold
Authors: Zhong Xueyan , Pan Hongbing
Published: June 2022

Aiming at the practical constraints of high resource occupancy and complex calculations in the existing Spike Neural Network (SNN) image classification model, in order to seek a more lightweight and efficient machine vision solution, this paper proposes an adaptive threshold Spike Neural Network (SNN) model of lateral inhibition of Spike-Timing-Dependent Plasticity (STDP). The conversion from grayscale image to pulse sequence is completed by convolution normalization and first pulse time coding. The network self-classification is realized by combining the classical Spike-Timing-Dependent Plasticity algorithm (STDP) and lateral suppression algorithm. The occurrence of overfitting is effectively suppressed by introducing an adaptive threshold. The experimental results on the MNIST data set show that compared with the traditional SNN classification model, the complexity of the weight update algorithm is reduced from O(n2) to O(1), and the accuracy rate can still remain stable at about 96%. The provided model is conducive to the migration of software algorithms to the bottom layer of the hardware platform, and can provide a reference for the realization of edge computing solutions for small intelligent hardware terminals with high efficiency and low power consumption.
Double-Cell Prefabricated Utility Tunnel Composed of Groove-Shaped Elements: An Extended Study of Stiffness Reduction Method
Authors: Wang Qinghua , Gong Guobin , Hao Jian Li
Published: June 2022

Based on the semi-rigid characteristics of a double-cell prefabricated utility tunnel composed of groove-shaped elements (PUTCGE), this paper proposes an extended study of a stiffness reduction method for PUTCGEs by introducing the stiffness reduction and bending moment adjustment coefficients of the sidewalls. The effects of the joint stiffness ratio, the aspect ratio of width to height, the coefficient of subgrade reaction, and the embedment depth of the utility tunnel on the stiffness reduction and bending moment adjustment coefficients were investigated, and calculation formulas were established. The results showed that the stiffness reduction coefficient increased with the increase in the joint stiffness ratio, while the bending moment adjustment coefficient decreased with the increase in the joint stiffness ratio. The stiffness reduction coefficient increased with the decrease in the aspect ratio of width to height, while the effect of the aspect ratio of width to height on the bending moment adjustment coefficient was found to be very small. It was also found that neither the coefficient of subgrade reaction nor the embedment depth had a significant effect on the stiffness reduction and bending moment adjustment coefficients. The stiffness reduction method for the PUTCGE was validated through comparison with a full-scale physical model test. The proposed method can provide a reference for designing PUTCGEs for underground construction.
Passenger Volumes and Dwell Times for Commuter Trains: A Case Study Using Automatic Passenger Count Data in Stockholm
Authors: Kuipers Ruben Alaric , Palmqvist Carl-William
Published: June 2022

This study investigates the relationship between passenger volumes and the frequency and size of dwell times for commuter trains. We use data collected by automatic passenger count systems in Stockholm and show that dwell times often take longer than scheduled. To understand the effect of passenger volumes on delays, we use the frequencies of delays for different passenger volumes and delay sizes. We find that these frequencies differ significantly from a frequency distribution independent of passenger volumes, indicating that passenger volumes have an effect on the frequency of dwell time delays. Neglecting passenger volumes underestimates the frequency of delays in most cases, especially for smaller delays. Although the frequency of dwell time delays increases as passenger volumes increase, the same is not necessarily true for their size. The relationship between passenger volumes and delay sizes is thus non-linear, and it depends on scheduled dwell times. We conclude that small increases in dwell times can result in sharp increases in on-time performance but that only increasing dwell times is not sufficient. Measures to speed up the boarding and alighting process are also necessary.
CDTNet: Improved Image Classification Method Using Standard, Dilated and Transposed Convolutions
Authors: Zhou Yuepeng , Chang Huiyou , Lu Yonghe , Lu Xili
Published: June 2022

Convolutional neural networks (CNNs) have achieved great success in image classification tasks. In the process of a convolutional operation, a larger input area can capture more context information. Stacking several convolutional layers can enlarge the receptive field, but this increases the parameters. Most CNN models use pooling layers to extract important features, but the pooling operations cause information loss. Transposed convolution can increase the spatial size of the feature maps to recover the lost low-resolution information. In this study, we used two branches with different dilated rates to obtain different size features. The dilated convolution can capture richer information, and the outputs from the two channels are concatenated together as input for the next block. The small size feature maps of the top blocks are transposed to increase the spatial size of the feature maps to recover low-resolution prediction maps. We evaluated the model on three image classification benchmark datasets (CIFAR-10, SVHN, and FMNIST) with four state-of-the-art models, namely, VGG16, VGG19, ResNeXt, and DenseNet. The experimental results show that CDTNet achieved lower loss, higher accuracy, and faster convergence speed in the training and test stages. The average test accuracy of CDTNet increased by 54.81% at most on SVHN with VGG19 and by 1.28% at least on FMNIST with VGG16, which proves that CDTNet has better performance and strong generalization abilities, as well as fewer parameters.
NDE Characterization of Surface Defects on Piston Rods in Shock Absorbers Using Rayleigh Waves
Authors: Im Kwang-Hee , Yeom Yun-Taek , Lee Hyung-Ho , Kim Sun-Kyu , Cho Young-Tae , Woo Yong-Deuck , Zhang Peng , Zhang Gui-Lin , Kwon Sung-Duk
Published: June 2022

In general, shock absorbers are components that can absorb shock and vibration energy caused by wheel behavior, and they provide handling stability. As a piston rod is an important component in shock absorbers, multiple processes are performed in order to guarantee its quality during manufacturing. Micro-defects can be generated on the surfaces of piston rods after processing. Because these defects can degrade the function of shock absorbers, proper non-destructive techniques are necessary to monitor the surfaces of piston rods. In this study, micro-defects were artificially machined on the surfaces of piston rods. In particular, a Rayleigh wave technique was adopted to detect defects on the surfaces of the piston rods, and Rayleigh wave behaviors were analyzed to establish beam profiles. In terms of the experimental method, defects were fabricated on the piston rods, and the optimal Rayleigh angle was determined using the pulse-echo method with ultrasonic transducers in a water tank. This was performed to evaluate the characteristics of the Rayleigh waves. In testing, regardless of the types of micro-defects on the surfaces of the pistons, it was found that the optimal inspection condition could be in the range of 5–10 mm, where ultrasonic signals were received with a high resolution. Moreover, the behaviors of the transmitted Rayleigh waves were simulated, and reflection, transmission, and scattering occurred due to defects at the interface between the water and steel. Thus, the propagation of Rayleigh waves and the optimal test conditions were implemented through FEM simulation to generate effective Rayleigh waves.
A Deep Attention Model for Environmental Sound Classification from Multi-Feature Data
Authors: Guo Jinming , Li Chuankun , Sun Zepeng , Li Jian , Wang Pan
Published: June 2022

Automated environmental sound recognition has clear engineering benefits; it allows audio to be sorted, curated, and searched. Unlike music and language, environmental sound is loaded with noise and lacks the rhythm and melody of music or the semantic sequence of language, making it difficult to find common features representative enough of various environmental sound signals. To improve the accuracy of environmental sound recognition, this paper proposes a recognition method based on multi-feature parameters and time–frequency attention module. It begins with a pretreatment that relies on multi-feature parameters to extract the sound, which supplements the phase information lost by the Log-Mel spectrogram in the current mainstream methods, and enhances the expressive ability of input features. A time–frequency attention module with multiple convolutions is designed to extract the attention weight of the input feature spectrogram and reduce the interference coming from the background noise and irrelevant frequency bands in the audio. Comparative experiments were conducted on three general datasets: environmental sound classification datasets (ESC-10, ESC-50) and an UrbanSound8K dataset. Experiments demonstrated that the proposed method performs better.
PM-Net: A Multi-Level Keypoints Detector and Patch Feature Learning Network for Optical and SAR Image Matching
Authors: Li Ziqian , Fu Zhitao , Nie Han , Chen Sijing
Published: June 2022

Due to the differences in radiation and geometric characteristics of optical and synthetic aperture radar (SAR) images, there is still a huge challenge for accurate matching. In this paper, we propose a patch-matching network (PM-Net) to improve the matching performance of optical and SAR images. First, a multi-level keypoints detector (MKD) with fused high-level and low-level features is presented to extract more robust keypoints from optical and SAR images. Second, we use a two-channel network structure to improve the image patch matching performance. Benefiting from this design, the proposed method can directly learn the similarity between optical and SAR image patches without manually designing features and descriptors. Finally, the MKD and two-channel net-work are trained separately on GL3D and QXS-SAROPT data sets, and the PM-Net is tested on multiple pairs of optical and SAR images. The experimental results demonstrate that the proposed method outperforms four advanced image matching networks on qualitative and quantitative assessments. The quantitative experiment results show that using our method correct matching points numbers are increased by more than 1.15 times, the value of F1-measure is raised by an average of 7.4% and the root mean squared error (RMSE) is reduced by more than 15.3%. The advantages of MKD and the two-channel network are also verified through ablation experiments.
Multiple Cusp Signatures in Ionograms Associated with Rocket-Induced Infrasonic Waves
Authors: Mabie Justin , Bullett Terence
Published: June 2022

We are interested in understanding how and when infrasonic waves propagate in the thermosphere, specifying the physical properties of those waves, and understanding how they affect radio wave propagation. We use a combination of traditional ionosonde observations and fixed frequency Doppler soundings to make high quality observations of vertically propagating infrasonic waves in the lower thermosphere/bottom side ionosphere. The presented results are the first simultaneous observations of infrasonic wave-induced deformations in ionograms and high-time-resolution observations of corresponding plasma displacements. Deformations in ionospheric echoes, which manifest as additional cusps and range variations, are shown to be caused by infrasonic wave-induced plasma displacements.
Production and Characterisation of Fibre-Reinforced All-Solid-State Electrodes and Separator for the Application in Structural Batteries
Authors: Vogt Daniel , Michalowski Peter , Kwade Arno
Published: June 2022

The electrification of the air transport sector demands for an energy storage that adds as little volume and weight to the overall system as possible. Regarding this so-called structural battery, composites enable the storage of electrical energy in commonly used load bearing fibre composite structures. A structural battery composite can store electrical energy while bearing mechanical loads, thus reducing parasitic mass and volume. In this study, structural cathodes were prepared by slurry coating carbon fibres with lithium iron phosphate (LFP), polyethylene oxide (PEO), lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) and carbon black. For the structural anodes, the carbon fibres were utilised as active material and slurry coated with PEO and LiTFSI. These structural electrodes as well as a structural separator were characterised by electrochemical cycling. With 139 mAhgAM−1, the structural cathodes demonstrated good utilisation of the active material. The carbon fibres used in the anode exhibited capacities of up to 92 mAhgAM−1. High irreversible lithium losses were observed, which are attributed to the poor electrolyte wetting behaviour of the carbon fibres. A structural battery demonstrator with a lithium metal anode was realised and reached a maximum specific energy of 64 Whkg−1 with respect to electrode and separator weight.
Assessment and Scientific Progresses in the Analysis of Olfactory Evoked Potentials
Authors: Arpaia Pasquale , Cataldo Andrea , Criscuolo Sabatina , De Benedetto Egidio , Masciullo Antonio , Schiavoni Raissa
Published: June 2022

The human sense of smell is important for many vital functions, but with the current state of the art, there is a lack of objective and non-invasive methods for smell disorder diagnostics. In recent years, increasing attention is being paid to olfactory event-related potentials (OERPs) of the brain, as a viable tool for the objective assessment of olfactory dysfunctions. The aim of this review is to describe the main features of OERPs signals, the most widely used recording and processing techniques, and the scientific progress and relevance in the use of OERPs in many important application fields. In particular, the innovative role of OERPs is exploited in olfactory disorders that can influence emotions and personality or can be potential indicators of the onset or progression of neurological disorders. For all these reasons, this review presents and analyzes the latest scientific results and future challenges in the use of OERPs signals as an attractive solution for the objective monitoring technique of olfactory disorders.
Effect of Diet Consistency on Rat Mandibular Growth: A Geometric Morphometric and Linear Cephalometric Study
Authors: Tsolakis Ioannis A. , Verikokos Christos , Perrea Despoina , Alexiou Konstantina , Gizani Sotiria , Tsolakis Apostolos I.
Published: June 2022

Background: Our study intended to investigate the null hypothesis that there is no effect of diet consistency on rat mandibular growth. Methods: A total sample of 24 female wistar rats, 30 days old, was used in this study. In the first group, the rats were fed soft diet and in the second group, they were fed hard diet for 60 days. On the 60th day, the rats were sedated and lateral cephalometric X-rays were taken. Lateral cephalometric X-rays were digitized with 7 craniofacial landmarks for the linear measurements, as well as with 12 curves and 90 landmarks, of which 74 were semilandmarks and 16 were fixed landmarks for morphometric analysis. These landmarks were exposed to Procrustes superimposition and Principal Component Analysis (PCA) to describe the shape variability of the mandible. Results: Means measurements of the soft diet group compared to those of the hard diet group were significantly different in linear and morphometric analysis measurements. The soft diet group of wistar rats revealed significant changes on the condyle (smaller), the angle of the mandible, and on the body of the mandible. Conclusions: Diet consistency affects the craniofacial growth of rats. Soft diet could be responsible for less mandibular growth.
Concordance Analysis between the Segments and the Overall Performance in Olympic Triathlon in Elite Triathletes
Authors: Olaya-Cuartero Javier , Fernández-Sáez José , Østerlie Ove , Ferriz-Valero Alberto
Published: June 2022

To date, the performance in triathlon has been measured through time or position. Although this is what defines the medals and the goal of the competition, it can have some limitations. As an alternative, the purpose of this study is to assess the degree of concordance of performance between each of the triathlon disciplines with overall performance through the triathlon performance indicator for the Olympic distance event. The official results from the World Triathlon Series for Olympic distance events from 2000 to 2019 were examined. A total of 11,263 entries were analysed, 6273 corresponding to elite men and 4990 to elite women. Moderate agreement was found between the running performance and overall performance in both elite men ICCa = 0.538 and elite women ICCa = 0.581. Moreover, moderate agreement was found between swimming performance and overall performance in both elite men ICCa = 0.640 and elite women ICCa = 0.613. Finally, good agreement was found between cycling performance and overall performance also in both elite men ICCa = 0.777 and elite women ICCa = 0.816. The main results of the present study show that the cycling performance indicator could be an alternative to anticipate the overall performance in the competition for the Olympic distance event.
An Overview of the Importance and Value of Porcine Species in Sialic Acid Research
Authors: Ogun Oluwamayowa Joshua , Thaller Georg , Becker Doreen
Published: June 2022

Humans frequently interact with pigs, whose meat is also one of the primary sources of animal protein. They are one of the main species at the center of sialic acid (Sia) research. Sias are sugars at terminals of glycoconjugates, are expressed at the cell surfaces of mammals, and are important in cellular interactions. N-glycolylneuraminic acid (Neu5Gc) and N-acetylneuraminic acid (Neu5Ac) are notable Sias in mammals. Cytidine monophospho-N-acetylneuraminic acid hydroxylase (CMAH) encodes the CMAH enzyme that biosynthesizes Neu5Gc. Although humans cannot endogenously synthesize Neu5Gc due to the inactivation of this gene by a mutation, Neu5Gc can be metabolically incorporated into human tissues from red meat consumption. Interactions between Neu5Gc and human anti-Neu5Gc antibodies have been associated with certain diseases and disorders. In this review, we summarized the sialic acid metabolic pathway, its regulation and link to viral infections, as well as the importance of the pig as a model organism in Sia research, making it a possible source of Neu5Gc antigens affecting human health. Future research in solving the structures of crucial enzymes involved in Sia metabolism, as well as their regulation and interactions with other enzymes, especially CMAH, could help to understand their function and reduce the amount of Neu5Gc.
Analysis of Physiological and Transcriptomic Differences between a Premature Senescence Mutant (GSm) and Its Wild-Type in Common Wheat (Triticum aestivum L.)
Authors: Lu Juan , Sun Lili , Jin Xiujuan , Islam Md Ashraful , Guo Feng , Tang Xiaosha , Zhao Kai , Hao Huifang , Li Ning , Zhang Wenjun , Shi Yugang , Wang Shuguang , Sun Daizhen
Published: June 2022

Premature leaf senescence has a profound influence on crop yield and quality. Here, a stable premature senescence mutant (GSm) was obtained from the common wheat (Triticum aestivum L.) cultivar Chang 6878 by mutagenesis with ethyl methanesulfonate. The differences between the GSm mutant and its wild-type (WT) were analyzed in terms of yield characteristics, photosynthetic fluorescence indices, and senescence-related physiological parameters. RNA sequencing was used to reveal gene expression differences between GSm and WT. The results showed that the yield of GSm was considerably lower than that of WT. The net photosynthetic rate, transpiration rate, maximum quantum yield, non-photochemical quenching coefficient, photosynthetic electron transport rate, soluble protein, peroxidase activity, and catalase activity all remarkably decreased in flag leaves of GSm, whereas malondialdehyde content distinctively increased compared with those of WT. The analysis of differentially expressed genes indicated blockade of chlorophyll and carotenoid biosynthesis, accelerated degradation of chlorophyll, and diminished photosynthetic capacity in mutant leaves; brassinolide might facilitate chlorophyll breakdown and consequently accelerate leaf senescence. NAC genes positively regulated the senescence process. Compared with NAC genes, expression of WRKY and MYB genes was induced earlier in the mutant possibly due to increased levels of reactive oxygen species and plant hormones (e.g., brassinolide, salicylic acid, and jasmonic acid), thereby accelerating leaf senescence. Furthermore, the antioxidant system played a role in minimizing oxidative damage in the mutant. These results provides novel insight into the molecular mechanisms of premature leaf senescence in crops.
Occurrence of Lymphangiogenesis in Peripheral Nerve Autografts Contrasts Schwann Cell-Induced Apoptosis of Lymphatic Endothelial Cells In Vitro
Authors: Hromada Carina , Hartmann Jaana , Oesterreicher Johannes , Stoiber Anton , Daerr Anna , Schädl Barbara , Priglinger Eleni , Teuschl-Woller Andreas H. , Holnthoner Wolfgang , Heinzel Johannes , Hercher David
Published: June 2022

Peripheral nerve injuries pose a major clinical concern world-wide, and functional recovery after segmental peripheral nerve injury is often unsatisfactory, even in cases of autografting. Although it is well established that angiogenesis plays a pivotal role during nerve regeneration, the influence of lymphangiogenesis is strongly under-investigated. In this study, we analyzed the presence of lymphatic vasculature in healthy and regenerated murine peripheral nerves, revealing that nerve autografts contained increased numbers of lymphatic vessels after segmental damage. This led us to elucidate the interaction between lymphatic endothelial cells (LECs) and Schwann cells (SCs) in vitro. We show that SC and LEC secretomes did not influence the respective other cell types’ migration and proliferation in 2D scratch assay experiments. Furthermore, we successfully created lymphatic microvascular structures in SC-embedded 3D fibrin hydrogels, in the presence of supporting cells; whereas SCs seemed to exert anti-lymphangiogenic effects when cultured with LECs alone. Here, we describe, for the first time, increased lymphangiogenesis after peripheral nerve injury and repair. Furthermore, our findings indicate a potential lymph-repellent property of SCs, thereby providing a possible explanation for the lack of lymphatic vessels in the healthy endoneurium. Our results highlight the importance of elucidating the molecular mechanisms of SC–LEC interaction.
Matrices and Affinity Ligands for Antibody Purification and Corresponding Applications in Radiotherapy
Authors: Xue Aiying , Fan Saijun
Published: June 2022

Antibodies have become an important class of biological products in cancer treatments such as radiotherapy. The growing therapeutic applications have driven a demand for high-purity antibodies. Affinity chromatography with a high affinity and specificity has always been utilized to separate antibodies from complex mixtures. Quality chromatographic components (matrices and affinity ligands) have either been found or generated to increase the purity and yield of antibodies. More importantly, some matrices (mainly particles) and affinity ligands (including design protocols) for antibody purification can act as radiosensitizers or carriers for therapeutic radionuclides (or for radiosensitizers) either directly or indirectly to improve the therapeutic efficiency of radiotherapy. This paper provides a brief overview on the matrices and ligands used in affinity chromatography that are involved in antibody purification and emphasizes their applications in radiotherapy to enrich potential approaches for improving the efficacy of radiotherapy.
Human Angiotensin I-Converting Enzyme Produced by Different Cells: Classification of the SERS Spectra with Linear Discriminant Analysis
Authors: Boginskaya Irina , Safiullin Robert , Tikhomirova Victoria , Kryukova Olga , Nechaeva Natalia , Bulaeva Naida , Golukhova Elena , Ryzhikov Ilya , Kost Olga , Afanasev Konstantin , Kurochkin Ilya
Published: June 2022

Angiotensin I-converting enzyme (ACE) is a peptidase widely presented in human tissues and biological fluids. ACE is a glycoprotein containing 17 potential N-glycosylation sites which can be glycosylated in different ways due to post-translational modification of the protein in different cells. For the first time, surface-enhanced Raman scattering (SERS) spectra of human ACE from lungs, mainly produced by endothelial cells, ACE from heart, produced by endothelial heart cells and miofibroblasts, and ACE from seminal fluid, produced by epithelial cells, have been compared with full assignment. The ability to separate ACEs’ SERS spectra was demonstrated using the linear discriminant analysis (LDA) method with high accuracy. The intervals in the spectra with maximum contributions of the spectral features were determined and their contribution to the spectrum of each separate ACE was evaluated. Near 25 spectral features forming three intervals were enough for successful separation of the spectra of different ACEs. However, more spectral information could be obtained from analysis of 50 spectral features. Band assignment showed that several features did not correlate with band assignments to amino acids or peptides, which indicated the carbohydrate contribution to the final spectra. Analysis of SERS spectra could be beneficial for the detection of tissue-specific ACEs.
Role and Function of Mesenchymal Stem Cells on Fibroblast in Cutaneous Wound Healing
Authors: Tanaka Kotaro , Ogino Ryohei , Yamakawa Sho , Suda Shota , Hayashida Kenji
Published: June 2022

Skin wounds often repair themselves completely over time; however, this is true only for healthy individuals. Although various studies are being conducted to improve wound-healing therapy outcomes, the mechanisms of wound healing and regeneration are not completely understood yet. In recent years, mesenchymal stem cells (MSCs) have been reported to contribute significantly to wound healing and regeneration. Understanding the function of MSCs will help to elucidate the fundamentals of wound healing. MSCs are multipotent stem cells that are used in regenerative medicine for their ability to self-renew and differentiate into bone, fat, and cartilage, with few ethical problems associated with cell harvesting. Additionally, they have anti-inflammatory and immunomodulatory properties and antifibrotic effects via paracrine signaling, and many studies have been conducted to use them to treat graft-versus-host disease, inflammatory bowel disease, and intractable cutaneous wounds. Many substances derived from MSCs are involved in the wound-healing process, and specific cascades and pathways have been elucidated. This review aims to explain the fundamental role of MSCs in wound healing and the effects of MSCs on fibroblasts.
Isolated Gastric Metastases of Pancreatic Ductal Adenocarcinoma following Radical Resection—Impact of Endosonography-Guided Fine Needle Aspiration Tract Seeding
Authors: Loveček Martin , Skalický Pavel , Urban Ondřej , Tesaříková Jana , Kliment Martin , Psár Róbert , Švébišová Hana , Urban Kateřina , Mohelníková-Duchoňová Beatrice , Klos Dušan , Stašek Martin
Published: June 2022

Background: Endosonography-guided fine needle aspiration biopsy (EUS-FNA)-associated metachronous gastric seeding metastases (GSM) of pancreatic ductal adenocarcinoma (PDAC) represent a serious condition with insufficient evidence. Methods: Retrospective analysis of PDAC resections with a curative-intent, proven pathological diagnosis of PDAC, preoperative EUS-FNA and post-resection follow-up of at least 60 months. The systematic literature search of published data was used for the GSM growth evaluation using Pearson correlation and the linear regression analyses. Results: The inclusion criteria met 59/134 cases, 16 (27%) had retained needle tract (15 following distal pancreatectomy, 1 following pylorus-sparing head resection). In total, 3/16 cases (19%) developed identical solitary GSM (10–26th month following primary surgery) and were radically resected. A total of 30 published cases of PDAC GSM following EUS-FNA were identified. Lesion was resected in 20 distal pancreatectomy cases with complete information in 14 cases. A correlation between the metastasis size and time (r = 0.612) was proven. The regression coefficient b = 0.72 expresses the growth of 0.72 mm per month. Conclusions: The GSM represent a preventable and curable condition. A remarkably high number of GSM following EUS-FNA was identified, leading to follow-up recommendation of EUS-FNA sampled patients. Multimodal management (gastric resection, adjuvant chemotherapy) may prolong survival.
Pilot Behavior Recognition Based on Multi-Modality Fusion Technology Using Physiological Characteristics
Authors: Li Yuhan , Li Ke , Wang Shaofan , Chen Xiaodan , Wen Dongsheng
Published: June 2022

With the development of the autopilot system, the main task of a pilot has changed from controlling the aircraft to supervising the autopilot system and making critical decisions. Therefore, the human–machine interaction system needs to be improved accordingly. A key step to improving the human–machine interaction system is to improve its understanding of the pilots’ status, including fatigue, stress, workload, etc. Monitoring pilots’ status can effectively prevent human error and achieve optimal human–machine collaboration. As such, there is a need to recognize pilots’ status and predict the behaviors responsible for changes of state. For this purpose, in this study, 14 Air Force cadets fly in an F-35 Lightning II Joint Strike Fighter simulator through a series of maneuvers involving takeoff, level flight, turn and hover, roll, somersault, and stall. Electro cardio (ECG), myoelectricity (EMG), galvanic skin response (GSR), respiration (RESP), and skin temperature (SKT) measurements are derived through wearable physiological data collection devices. Physiological indicators influenced by the pilot’s behavioral status are objectively analyzed. Multi-modality fusion technology (MTF) is adopted to fuse these data in the feature layer. Additionally, four classifiers are integrated to identify pilots’ behaviors in the strategy layer. The results indicate that MTF can help to recognize pilot behavior in a more comprehensive and precise way.
Omitting Hyperventilation in Electroencephalogram during the COVID-19 Pandemic May Reduce Interictal Epileptiform Discharges in Patients with Juvenile Myoclonic Epilepsy
Authors: Hatano Keisuke , Fujimoto Ayataka , Sato Keishiro , Yamamoto Takamichi , Enoki Hideo
Published: June 2022

Background: To prevent the spread of coronavirus disease 2019 (COVID-19), hyperventilation (HV) activation has been avoided in electroencephalograms (EEGs) since April 2020. The influence of omitting HV in EEG on epilepsy diagnosis remains uncertain for patients with epilepsies other than child absence epilepsy. We hypothesized that EEGs with HV would show more interictal epileptiform discharges (IEDs) than EEGs without HV in patients with juvenile myoclonic epilepsy (JME). Methods: We reviewed the EEGs of seizure-free patients with JME who underwent EEG, both with and without HV, from January 2019 to October 2021, in our institution, and compared IEDs between EEG with and without HV. Results: This study analyzed 23 JME patients. The IED-positive rate was significantly higher in EEG with HV (65.2%) than in EEG without HV (34.8%, p = 0.016). The mean ± standard deviation number of IEDs per minute was significantly larger during HV (1.61 ± 2.25 × 10−1) than during non-activation of both first EEG (0.57 ± 0.93 × 10−1, p = 0.039) and second EEG (0.39 ± 0.76 × 10−1, p = 0.009). Conclusions: In JME patients, performing HV during EEG may increase IEDs and appears to facilitate the accurate diagnosis of epilepsy.