bluuebunny/crossref_metadata_2025 huggingface dataset:
Mineral Composite Plaster Containing Hollow Glass Microspheres and CSA Cement for Building Insulation
Authors: Zelder Stefan , Rosin Andreas , Helling Dominik , Gerdes Thorsten , Scharfe Friedbert , Schafföner Stefan
Published: January 2022

Renovation of old buildings plays a key role in the sustainable energy transition because they are often poorly insulated and, therefore, lose a lot of heat through walls and ceilings. An important measure of renovation is façade insulation. Established and widely used materials include rigid expanded polystyrene (EPS) and extruded polystyrene (XPS) insulation boards. However, these boards do not easily follow the form of non-planar surfaces such as individually formed, ornamented, or bent façades. Furthermore, fire protection of these boards requires the addition of, for example, hazardous brominated flame retardants that impede recycling. This paper investigates a novel alternative insulating composite plaster. It is purely inorganic and can be applied easily by casting or wet spraying to any wall or ceiling element. The composite material consists of only two components: micro hollow glass microspheres as the insulating light component and calcium sulfoaluminate cement as the binder. Various compositions containing these components were cast, hydraulically set, and characterized with respect to microstructure, phase development during hydration, and thermal conductivity. With an increasing amount of hollow glass spheres, the density decreased to less than 0.2 g·cm−1, and the thermal conductivity reached 0.04 to 0.05 W·m−1K−1, fulfilling the demands of building insulation.
Injury Incidence and Pattern in Elite Young Male and Female Trail Runners
Authors: Sanchez-Garcia Luis F. , Penichet-Tomas Alfonso , Pueo Basilio , Jimenez-Olmedo Jose M.
Published: January 2022

The aim of this study was to analyze the injury incidence in young trail runners according to the body region, type, mode of onset, and moment of occurrence, both in total and detailed by sex. Thirty-five male and sixteen female young elite trail runners, aged between 15 and 22 years, completed a questionnaire regarding the injury incidence in the last 2 years. Comparison of the proportions of the injury incidence within groups (all, male, and female runners) and between groups (male vs. female runners) was computed using z and Fisher’s exact tests. Results showed that most of the injuries in male runners occurred in ankle (54.3%; p < 0.001; ES = 0.520). New injuries were the most common type in male (60.0%; p < 0.001; ES = 0.829) and female runners (52.0%; p = 0.005; ES = 0.585). Acute sudden onset (55.7%; p = 0.002; ES = 0.722) and repetitive sudden onset injuries (48.0%; p = 0.002; ES = 0.141) were the most frequent in male and female athletes, respectively. Joint sprains (48.6%; p < 0.001; 0.464) were the most reported injuries in male runners. Comparative analysis between sexes showed that exacerbation injuries were higher in females (24.0%) than in male runners (8.6%), with p = 0.046 (ES = 0.205). However, female runners reported less incidence by acute sudden onset injuries (32.0%) than male runners (55.7%), with p = 0.042 (ES = 0.209). Young trail runners showed a specific injury profile due to the distinctive characteristics of the mountain terrain compared to the athletic modalities.
Facial Recognition Method Based on Thin-Film Solar Cells
Authors: Chen Ruei-Tang , Wu Fong-Long
Published: January 2022

In this study, we developed a new facial recognition system using thin-film solar cells as sensors. When the face of a user is illuminated by LED lights on the left and right sides of the system and the reflected light enters the cells at the corresponding positions, differences in facial skin colors and 3D contours lead to different output voltages and currents of the thin-film solar cells. This is the basis of facial feature identification. We found that the accuracy of thin-film-solar-cell-based facial recognition can be improved by precisely controlling changes in LED light intensity. The facial features of six different users were successfully distinguished by this method, thus verifying that thin-film solar cells can be used for green power generation, as well as for facial recognition.
Hot Stamping Parts Shear Mold Manufacturing via Metal Additive Manufacturing
Authors: Hong Myoung-Pyo
Published: January 2022

Hot stamping uses boron (B) steel to simultaneously form parts at high temperatures while cooling the parts in a mold, which is advantageous because of the ability to freeze the forms. However, compared to conventional cold forming, this technique requires additional facilities that include heating devices and additional time for cooling after forming at high temperatures. Additionally, because of the high strengths of hot stamping parts, shear process operations after molding tend to be difficult to perform as a continuous operation via press processing; thus, most operations depend on separate laser processing, which results in lower productivity and increased manufacturing costs. This limitation continues to be the most significant problem with this technology, therefore, restricting its commercialization because of increased mold manufacturing costs and durability problems. This study investigated a low-cost, high-functionality shear mold manufacturing method for 1.5 GPa grade hot-stamped components using heterogeneous metal additive manufacturing. After the concentrated stress in steel during the shearing processes was analyzed using a multi-physical analysis, metal additive manufacturing was used to fabricate the shear mold. Its life was evaluated through trial molding and compared with that for conventional technology. Finally, the commercialization potential of the newly developed method was assessed.
Differential Expression of Genes Associated with Chromatin Modifications in Skeletal Muscle during Aerobic Training Program
Authors: Mina-Paz Yecid , Rodríguez-Ortiz Alejandra , Hernández-Pérez Daniela , Montoya-Villegas Julio César , Sánchez-Gómez Adalberto , García-Vallejo Felipe
Published: January 2022

Introduction: Skeletal muscle plasticity in exercise can be modulated by epigenomic events such as gene silencing, histone modifications and DNA methylation. In this context, our objective was to analyze the expression of genes associated with chromatin modifications in human muscle biopsies of vastus lateralis after a 20 week training program. Methods: Using data from DNA microarray experiments registered in the NCBI GEO DataSet database GSE117070, we calculated the Z ratio values as the criterion to evaluate the differential expression of genes associated with chromatin modification during aerobic training in skeletal muscle. Using the web interface GENEMANIA, we built a co-expression interaction network with the overexpressed genes. We compared Z-score values obtained from pre-trained and post-trained samples through nonparametric tests. Results: We found 10 overexpressed genes after the 20 week training program, namely, EZH1, KMT2A, KMT2D, KDM4C, KDM6A, CREBBP, HDAC10, HDAC4, DNMT3L, and H2AX. The most relevant biological processes obtained from the network included chromatin organization (FDR 9.04 × 10−9) and histone modification (FDR 9.04 × 10−9). Conclusions: In skeletal muscle, after aerobic training, there is overexpression of genes associated with the modification of the chromatin through alterations in histones and DNA, resulting in epigenetic transcriptional changes.
Short-Term Prediction of Bike-Sharing Demand Using Multi-Source Data: A Spatial-Temporal Graph Attentional LSTM Approach
Authors: Ma Xinwei , Yin Yurui , Jin Yuchuan , He Mingjia , Zhu Minqing
Published: January 2022

As a convenient, economical, and eco-friendly travel mode, bike-sharing greatly improved urban mobility. However, it is often very difficult to achieve a balanced utilization of shared bikes due to the asymmetric spatio-temporal user demand distribution and the insufficient numbers of shared bikes, docks, or parking areas. If we can predict the short-run bike-sharing demand, it will help operating agencies rebalance bike-sharing systems in a timely and efficient way. Compared to the statistical methods, deep learning methods can automatically learn the relationship between the inputs and outputs, requiring less assumptions and achieving higher accuracy. This study proposes a Spatial-Temporal Graph Attentional Long Short-Term Memory (STGA-LSTM) neural network framework to predict short-run bike-sharing demand at a station level using multi-source data sets. These data sets include historical bike-sharing trip data, historical weather data, users’ personal information, and land-use data. The proposed model can extract spatio-temporal information of bike-sharing systems and predict the short-term bike-sharing rental and return demand. We use a Graph Convolutional Network (GCN) to mine spatial information and adopt a Long Short-Term Memory (LSTM) network to mine temporal information. The attention mechanism is focused on both temporal and spatial dimensions to enhance the ability of learning temporal information in LSTM and spatial information in GCN. Results indicate that the proposed model is the most accurate compared with several baseline models, the attention mechanism can help improve the model performance, and models that include exogenous variables perform better than the models that only consider historical trip data. The proposed short-term prediction model can be used to help bike-sharing users better choose routes and to help operators implement dynamic redistribution strategies.
Modeling and Control of an Articulated Multibody Aircraft
Authors: Ogunwa Titilayo , Abdullah Ermira , Chahl Javaan
Published: January 2022

Insects use dynamic articulation and actuation of their abdomen and other appendages to augment aerodynamic flight control. These dynamic phenomena in flight serve many purposes, including maintaining balance, enhancing stability, and extending maneuverability. The behaviors have been observed and measured by biologists but have not been well modeled in a flight dynamics framework. Biological appendages are generally comparatively large, actuated in rotation, and serve multiple biological functions. Technological moving masses for flight control have tended to be compact, translational, internally mounted and dedicated to the task. Many flight characteristics of biological flyers far exceed any technological flyers on the same scale. Mathematical tools that support modern control techniques to explore and manage these actuator functions may unlock new opportunities to achieve agility. The compact tensor model of multibody aircraft flight dynamics developed here allows unified dynamic and aerodynamic simulation and control of bioinspired aircraft with wings and any number of idealized appendage masses. The demonstrated aircraft model was a dragonfly-like fixed-wing aircraft. The control effect of the moving abdomen was comparable to the control surfaces, with lateral abdominal motion substituting for an aerodynamic rudder to achieve coordinated turns. Vertical fuselage motion achieved the same effect as an elevator, and included potentially useful transient torque reactions both up and down. The best performance was achieved when both moving masses and control surfaces were employed in the control solution. An aircraft with fuselage actuation combined with conventional control surfaces could be managed with a modern optimal controller designed using the multibody flight dynamics model presented here.
FDA-SSD: Fast Depth-Assisted Single-Shot MultiBox Detector for 3D Tracking Based on Monocular Vision
Authors: Wang Zihao , Yang Sen , Shi Mengji , Qin Kaiyu
Published: January 2022

In this study, a set of benchmarks for object tracking with motion parameters (OTMP) was first designed. The sample images were matched with the spatial depth of the camera, the pose of the camera, and other spatial parameters for the training of the detection model. Then, a Fast Depth-Assisted Single-Shot MultiBox Detector (FDA-SSD) algorithm suitable for 3D target tracking was proposed by combining the depth information of the sample into the original Single-Shot MultiBox Detector (SSD). Finally, an FDA-SSD-based monocular motion platform target detection and tracking algorithm framework were established. Specifically, the spatial geometric constraints of the target were adapted to solve the target depth information, which was fed back to the detection model. Then, the normalized depth information of the target was employed to select the feature window of the convolutional layer for the detector at a specific scale. This significantly reduces the computational power for simultaneously calculating detectors of all scales. This framework effectively combines the two-dimensional detection model and the three-dimensional positioning algorithm. Compared with the original SSD method, the network model designed in this study has fewer actual operating parameters; the measured detection operation speed was increased by about 18.1% on average; the recognition rate was maintained at a high level consistent with that of the original SSD. Furthermore, several groups of experiments were conducted on target detection and target space tracking based on monocular motion platforms indoors. The root mean square error (RMSE) of the spatial tracking trajectory was less than 4.72 cm. The experimental results verified that the algorithm framework in this study can effectively realize tasks such as visual detection, classification, and spatial tracking based on a monocular motion platform.
Task Migration with Partitioning for Load Balancing in Collaborative Edge Computing
Authors: Moon Sungwon , Lim Yujin
Published: January 2022

Multi-access edge computing (MEC) has emerged as a promising technology to facilitate efficient vehicular applications, such as autonomous driving, path planning and navigation. By offloading tasks from vehicles to MEC servers (MECSs), the MEC system can facilitate computation-intensive applications with hard latency constraints in vehicles with limited computing resources. However, owing to the mobility of vehicles, the vehicles are not evenly distributed across the MEC system. Therefore, some MECSs are heavily congested, whereas others are lightly loaded. If a task is offloaded to a congested MECS, it can be blocked or have high latency. Moreover, service interruption would occur because of the high mobility and limited coverage of the MECS. In this paper, we assume that the task can be divided into a set of subtasks and computed by multiple MECSs in parallel. Therefore, we propose a method of task migration with partitioning. To balance loads, the MEC system migrates the set of subtasks of tasks in an overloaded MECS to one or more underloaded MECSs according to the load difference. Simulations have indicated that, compared with conventional methods, the proposed method can increase the satisfaction of quality-of-service requirements, such as low latency, service reliability, and MEC system throughput by optimizing load balancing and task partitioning.
Late Fusion-Based Video Transformer for Facial Micro-Expression Recognition
Authors: Hong Jiuk , Lee Chaehyeon , Jung Heechul
Published: January 2022

In this article, we propose a novel model for facial micro-expression (FME) recognition. The proposed model basically comprises a transformer, which is recently used for computer vision and has never been used for FME recognition. A transformer requires a huge amount of data compared to a convolution neural network. Then, we use motion features, such as optical flow and late fusion to complement the lack of FME dataset. The proposed method was verified and evaluated using the SMIC and CASME II datasets. Our approach achieved state-of-the-art (SOTA) performance of 0.7447 and 73.17% in SMIC in terms of unweighted F1 score (UF1) and accuracy (Acc.), respectively, which are 0.31 and 1.8% higher than previous SOTA. Furthermore, UF1 of 0.7106 and Acc. of 70.68% were shown in the CASME II experiment, which are comparable with SOTA.
Which Features Are More Correlated to Illuminant Estimation: A Composite Substitute
Authors: Luo Yunhui , Wang Xingguang , Wang Qing
Published: January 2022

Computational color constancy (CCC) is to endow computers or cameras with the capability to remove the color bias effect caused by different scene illuminations. The first procedure of CCC is illuminant estimation, i.e., to calculate the illuminant color for a given image scene. Recently, some methods directly mapping image features to illuminant estimation provide an effective and robust solution for this issue. Nevertheless, due to diverse image features, it is uncertain to select which features to model illuminant color. In this research, a series of artificial features weaved into a mapping-based illuminant estimation framework is extensively investigated. This framework employs a multi-model structure and integrates the functions of kernel-based fuzzy c-means (KFCM) clustering, non-negative least square regression (NLSR), and fuzzy weighting. By comparing the resulting performance of different features, the features more correlated to illuminant estimation are found in the candidate feature set. Furthermore, the composite features are designed to achieve the outstanding performances of illuminant estimation. Extensive experiments are performed on typical benchmark datasets and the effectiveness of the proposed method has been validated. The proposed method makes illuminant estimation an explicit transformation of suitable image features with regressed and fuzzy weights, which has significant potential for both competing performances and fast implementation against state-of-the-art methods.
Evolution of Shear Band in Plane Strain Compression of Naturally Structured Clay with a High Sensitivity
Authors: Liu Bingheng , Kong Lingwei , Li Chengsheng , Wang Juntao
Published: January 2022

The formation of the shear band is associated with the failure of soil. However, there has been relatively little investigation on the evolution of shear bands in naturally structured clay with a high sensitivity. In this study, undrained plane strain compression tests, digital image correlation (DIC) analyses, and scanning electron microscopy (SEM) tests were performed to investigate the characteristics of shear bands in naturally structured clay. The basic mechanical properties and stress–strain relationships show that naturally structured clay exhibits a strong structure and high sensitivity. Compared with plane strain compression tests under low confining pressure, more localized shear bands emerge in the specimens during the tests under high confining pressures; however, when the specimens fail, only one shear band is fully developed, and the local deformation in the developed shear band is much larger than those in other localized shear bands. Moreover, the local stress–strain relationships inside and outside the shear band show distinct discrepancies. The SEM results show distinct micro-structures of clays inside and outside the shear band, which are caused by the development of the shear band. The findings in this work provide new insight into the failure of structured clay.
Variations in Rainbow Trout Immune Responses against A. salmonicida: Evidence of an Internal Seasonal Clock in Oncorhynchus mykiss
Authors: Montero Ruth , Chan Justin Tze Ho , Müller Claudia , Just Philip Niclas , Ostermann Sven , Øverland Margareth , Maisey Kevin , Korytář Tomáš , Köllner Bernd
Published: January 2022

In poikilothermic vertebrates, seasonality influences different immunological parameters such as leukocyte numbers, phagocytic activity, and antibody titers. This phenomenon has been described in different teleost species, with immunological parameters peaking during warmer months and decreased levels during winter. In this study, the cellular immune responses of rainbow trout (Oncorhynchus mykiss) kept under constant photoperiod and water temperature against intraperitoneally injected Aeromonas salmonicida during the summer and winter were investigated. The kinetics of different leukocyte subpopulations from peritoneal cavity, spleen, and head kidney in response to the bacteria was measured by flow cytometry. Furthermore, the kinetics of induced A. salmonicida-specific antibodies was evaluated by ELISA. Despite maintaining the photoperiod and water temperature as constant, different cell baselines were detected in all organs analyzed. During the winter months, B- and T-cell responses were decreased, contrary to what was observed during summer months. However, the specific antibody titers were similar between the two seasons. Natural antibodies, however, were greatly increased 12 h post-injection only during the wintertime. Altogether, our results suggest a bias toward innate immune responses and potential lymphoid immunosuppression in the wintertime in trout. These seasonal differences, despite photoperiod and water temperature being kept constant, suggest an internal inter-seasonal or circannual clock controlling the immune system and physiology of this teleost fish.
Using Species Groups to Approach the Large and Taxonomically Unresolved Freshwater Fish Family Nemacheilidae (Teleostei: Cypriniformes)
Authors: Dvořák Tomáš , Šlechtová Vendula , Bohlen Jörg
Published: January 2022

Large animal families with unresolved taxonomy are notoriously difficult to handle with respect to their biodiversity, systematics, and evolutionary history. We approach a large and taxonomically unresolved family of freshwater fishes (Nemacheilidae, >600 species) by proposing, on the basis of morphologic data, a species group within the family and study its phylogeny with conclusions regarding its diversity, taxonomy, and biogeographic history. Phylogenetic analyses of two mitochondrial and three nuclear genes of 139 specimens, representing about 46 species (17 candidate species from the proposed species-group, plus 29 comparative species), revealed that the proposed species group does not form a distinct monophyletic lineage, but that the candidate and comparative species mixed in three different lineages. However, the results revealed more than 20% of undescribed species within the ingroup and showed that species do not cluster according to the presently recognised genera. At least one of the genetic clades shows signs of an eastward range expansion during the second half of Miocene from north India via Myanmar into Laos, western China, and western Thailand. We conclude that the approach of picking monophyletic lineages to study biodiversity, systematics, and evolutionary history helps to open the door to large animal families.
The Proper Motor Control Model Revealed by Wheelchair Curling Quantification of Elite Athletes
Authors: Wang Xiangdong , Liu Ruijiao , Zhang Tian , Shan Gongbing
Published: January 2022

Background: Wheelchair users are disadvantaged when it comes to accruing the benefits of physical activities. Hence, promoting various sports is crucial for keeping this population healthy. Since wheelchair curling can be played by individuals from a wide range of ages, strengths, and endurance levels, it has potential to improve wheelchair users’ well-being. Yet, hardly any motion studies exist. This study aimed to facilitate understanding of optimized control of wheelchair curling for promoting wheelchair users’ participation. Methods: Using motion capture technology, nine national-level athletes were tested. Kinematic parameters related to segment/joint control and their coordination were quantified for both slow and fast curling. Descriptive statistics (means and standard deviations) and correlation analysis were applied for characterizing the skill. Results: (1) Curling control consists of an acceleration phase and a stabilizing delivery phase; (2) the control of trunk, shoulder, and wrist are responsible for accelerating the rock; (3) elbow control is accountable for the accurate delivery of the rock; and (4) during the slow curling, a synchronized effort of trunk, shoulder, and wrist is used for accelerating the rock, while a sequential control among the segment/joints is applied in fast curling. Conclusions: The results supply valuable motor learning markers that could have a significant positive impact on the teaching and learning of wheelchair curling, as such, the findings have great potential for the health promotion of wheelchair users.
Viral and Host Genetic and Epigenetic Biomarkers Related to SARS-CoV-2 Cell Entry, Infection Rate, and Disease Severity
Authors: Gaspersic Jernej , Dolzan Vita
Published: January 2022

The rapid spread of COVID-19 outbreak lead to a global pandemic declared in March 2020. The common features of corona virus family helped to resolve structural characteristics and entry mechanism of SARS-CoV-2. However, rapid mutagenesis leads to the emergence of new strains that may have different reproduction rates or infectivity and may impact the course and severity of the disease. Host related factors may also play a role in the susceptibility for infection as well as the severity and outcomes of the COVID-19. We have performed a literature and database search to summarize potential viral and host-related genomic and epigenomic biomarkers, such as genetic variability, miRNA, and DNA methylation in the molecular pathway of SARS-CoV-2 entry into the host cell, that may be related to COVID-19 susceptibility and severity. Bioinformatics tools may help to predict the effect of mutations in the spike protein on the binding to the ACE2 receptor and the infectivity of the strain. SARS-CoV-2 may also target several transcription factors and tumour suppressor genes, thus influencing the expression of different host genes and affecting cell signalling. In addition, the virus may interfere with RNA expression in host cells by exploiting endogenous miRNA and its viral RNA. Our analysis showed that numerous human miRNA may form duplexes with different coding and non-coding regions of viral RNA. Polymorphisms in human genes responsible for viral entry and replication, as well as in molecular damage response and inflammatory pathways may also contribute to disease prognosis and outcome. Gene ontology analysis shows that proteins encoded by such polymorphic genes are highly interconnected in regulation of defense response. Thus, virus and host related genetic and epigenetic biomarkers may help to predict the course of the disease and the response to treatment.
PEPscan: A Broad Spectrum Approach for the Characterization of Protein-Binder Interactions?
Authors: Rebollo Angelita , Fliedel Louise , Tuffery Pierre
Published: January 2022

In a previous study, we have shown that PEPscan can provide a cheap and rapid means to identify candidate interfering peptides (IPs), i.e., peptides able to disrupt a target protein-protein interaction. PEPscan was shown to be effective in identifying a limited number of candidate IPs specific to the target interaction. Here, we investigate the results of 14 new PEPscan experiments for protein complexes of known 3D structures. We show that for almost all complexes, PEPscan is able to identify candidate IPs that are located at the protein-protein interface. The information it provides about the binding site seems, however, too ambiguous to be exploited in a simple manner to assist the modeling of protein complexes. Moreover, these candidates are associated with false positives. For these, we suggest they could correspond to non-specific binders, which leaves room for further optimization of the PEPscan protocol. Another unexpected advance comes from the observation of the applicability of PEPscan for polysaccharides and labeled peptides, suggesting that PEPscan could become a large spectrum approach to investigate protein-binder interactions, the binder not necessarily being a protein.
Similarity and Diversity of Presynaptic Molecules at Neuromuscular Junctions and Central Synapses
Authors: Takikawa Kenji , Nishimune Hiroshi
Published: January 2022

Synaptic transmission is essential for controlling motor functions and maintaining brain functions such as walking, breathing, cognition, learning, and memory. Neurotransmitter release is regulated by presynaptic molecules assembled in active zones of presynaptic terminals. The size of presynaptic terminals varies, but the size of a single active zone and the types of presynaptic molecules are highly conserved among neuromuscular junctions (NMJs) and central synapses. Three parameters play an important role in the determination of neurotransmitter release properties at NMJs and central excitatory/inhibitory synapses: the number of presynaptic molecular clusters, the protein families of the presynaptic molecules, and the distance between presynaptic molecules and voltage-gated calcium channels. In addition, dysfunction of presynaptic molecules causes clinical symptoms such as motor and cognitive decline in patients with various neurological disorders and during aging. This review focuses on the molecular mechanisms responsible for the functional similarities and differences between excitatory and inhibitory synapses in the peripheral and central nervous systems, and summarizes recent findings regarding presynaptic molecules assembled in the active zone. Furthermore, we discuss the relationship between functional alterations of presynaptic molecules and dysfunction of NMJs or central synapses in diseases and during aging.
Lactococcus lactis, an Attractive Cell Factory for the Expression of Functional Membrane Proteins
Authors: Frelet-Barrand Annie
Published: January 2022

Membrane proteins play key roles in most crucial cellular processes, ranging from cell-to-cell communication to signaling processes. Despite recent improvements, the expression of functionally folded membrane proteins in sufficient amounts for functional and structural characterization remains a challenge. Indeed, it is still difficult to predict whether a protein can be overproduced in a functional state in some expression system(s), though studies of high-throughput screens have been published in recent years. Prokaryotic expression systems present several advantages over eukaryotic ones. Among them, Lactococcus lactis (L. lactis) has emerged in the last two decades as a good alternative expression system to E. coli. The purpose of this chapter is to describe L. lactis and its tightly inducible system, NICE, for the effective expression of membrane proteins from both prokaryotic and eukaryotic origins.
Examining the Effect of Charged Lipids on Mitochondrial Outer Membrane Dynamics Using Atomistic Simulations
Authors: Oliveira Aline A. , Róg Tomasz , da Silva Albérico B. F. , Amaro Rommie E. , Johnson Mark S. , Postila Pekka A.
Published: January 2022

The outer mitochondrial membrane (OMM) is involved in multiple cellular functions such as apoptosis, inflammation and signaling via its membrane-associated and -embedded proteins. Despite the central role of the OMM in these vital phenomena, the structure and dynamics of the membrane have regularly been investigated in silico using simple two-component models. Accordingly, the aim was to generate the realistic multi-component model of the OMM and inspect its properties using atomistic molecular dynamics (MD) simulations. All major lipid components, phosphatidylinositol (PI), phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylserine (PS), were included in the probed OMM models. Because increased levels of anionic PS lipids have potential effects on schizophrenia and, more specifically, on monoamine oxidase B enzyme activity, the effect of varying the PS concentration was explored. The MD simulations indicate that the complex membrane lipid composition (MLC) behavior is notably different from the two-component PC-PE model. The MLC changes caused relatively minor effects on the membrane structural properties such as membrane thickness or area per lipid; however, notable effects could be seen with the dynamical parameters at the water-membrane interface. Increase of PS levels appears to slow down lateral diffusion of all lipids and, in general, the presence of anionic lipids reduced hydration and slowed down the PE headgroup rotation. In addition, sodium ions could neutralize the membrane surface, when PI was the main anionic component; however, a similar effect was not seen for high PS levels. Based on these results, it is advisable for future studies on the OMM and its protein or ligand partners, especially when wanting to replicate the correct properties on the water-membrane interface, to use models that are sufficiently complex, containing anionic lipid types, PI in particular.
CNS-Sparing Histamine H3 Receptor Antagonist as a Candidate to Prevent the Diabetes-Associated Gastrointestinal Symptoms
Authors: Rosa Arianna Carolina , Nardini Patrizia , Sgambellone Silvia , Gurrieri Maura , Spampinato Simona Federica , Dell’Accio Alfonso , Chazot Paul L , Obara Ilona , Liu Wai L , Pini Alessandro
Published: January 2022

Among the histamine receptors, growing evidence points to the histamine H3 receptor as a pharmacological candidate to counteract the autonomic neuropathy associated with diabetes. The study aimed to evaluate the effect of PF00868087 (also known as ZPL-868), a CNS-sparing histamine H3 receptor antagonist, on the autonomic neuropathy of the intestinal tract associated with diabetes. Diabetes was induced in male BALB/c mice by a single high dose of streptozotocin (150 mg/kg). Colorectal specimens from control and diabetic mice, randomized to vehicle or PF0086087 (10, 30, 100 mg/kg/day by oral gavage for 14 days), were processed for morphological and immunohistochemical analysis. A significant overproduction of mucus in the intestinal mucosa of diabetic mice compared to the controls was observed. PF0086087 at the highest dose prevented mucin overproduction. The immunohistochemistry analysis demonstrated that diabetes causes a decrease in the inhibitory component of enteric motility, measured as the percentage of neuronal nitric oxide synthase-positive neurons (p < 0.05) and a parallel increase in the excitatory component evaluated as substance P-positive fibres (p < 0.01). PF0086087 dose-dependently prevented these pathophysiological events. In conclusion, PF0086087 may be an essential tool in preventing nitrergic dysfunction in the myenteric plexus of the distal colon and diabetes-induced gastrointestinal complications.
Exploring the Interactome of Cytochrome P450 2E1 in Human Liver Microsomes with Chemical Crosslinking Mass Spectrometry
Authors: Davydov Dmitri R. , Dangi Bikash , Yue Guihua , Ahire Deepak S. , Prasad Bhagwat , Zgoda Victor G.
Published: January 2022

Aiming to elucidate the system-wide effects of the alcohol-induced increase in the content of cytochrome P450 2E1 (CYP2E1) on drug metabolism, we explored the array of its protein-protein interactions (interactome) in human liver microsomes (HLM) with chemical crosslinking mass spectrometry (CXMS). Our strategy employs membrane incorporation of purified CYP2E1 modified with photoreactive crosslinkers benzophenone-4-maleimide and 4-(N-succinimidylcarboxy)benzophenone. Exposure of bait-incorporated HLM samples to light was followed by isolating the His-tagged bait protein and its crosslinked aggregates on Ni-NTA agarose. Analyzing the individual bands of SDS-PAGE slabs of thereby isolated protein with the toolset of untargeted proteomics, we detected the crosslinked dimeric and trimeric complexes of CYP2E1 with other drug-metabolizing enzymes. Among the most extensively crosslinked partners of CYP2E1 are the cytochromes P450 2A6, 2C8, 3A4, 4A11, and 4F2, UDP-glucuronosyltransferases (UGTs) 1A and 2B, fatty aldehyde dehydrogenase (ALDH3A2), epoxide hydrolase 1 (EPHX1), disulfide oxidase 1α (ERO1L), and ribophorin II (RPN2). These results demonstrate the exploratory power of the proposed CXMS strategy and corroborate the concept of tight functional integration in the human drug-metabolizing ensemble through protein-protein interactions of the constituting enzymes.
piRNAs and PIWI Proteins as Diagnostic and Prognostic Markers of Genitourinary Cancers
Authors: Hanusek Karolina , Poletajew Sławomir , Kryst Piotr , Piekiełko-Witkowska Agnieszka , Bogusławska Joanna
Published: January 2022

piRNAs (PIWI-interacting RNAs) are small non-coding RNAs capable of regulation of transposon and gene expression. piRNAs utilise multiple mechanisms to affect gene expression, which makes them potentially more powerful regulators than microRNAs. The mechanisms by which piRNAs regulate transposon and gene expression include DNA methylation, histone modifications, and mRNA degradation. Genitourinary cancers (GC) are a large group of neoplasms that differ by their incidence, clinical course, biology, and prognosis for patients. Regardless of the GC type, metastatic disease remains a key therapeutic challenge, largely affecting patients’ survival rates. Recent studies indicate that piRNAs could serve as potentially useful biomarkers allowing for early cancer detection and therapeutic interventions at the stage of non-advanced tumour, improving patient’s outcomes. Furthermore, studies in prostate cancer show that piRNAs contribute to cancer progression by affecting key oncogenic pathways such as PI3K/AKT. Here, we discuss recent findings on biogenesis, mechanisms of action and the role of piRNAs and the associated PIWI proteins in GC. We also present tools that may be useful for studies on the functioning of piRNAs in cancers.
Drug Combinations: A New Strategy to Extend Drug Repurposing and Epithelial-Mesenchymal Transition in Breast and Colon Cancer Cells
Authors: Duarte Diana , Rêma Alexandra , Amorim Irina , Vale Nuno
Published: January 2022

Despite the progressive research and recent advances in drug therapy to treat solid tumours, the number of cases and deaths in patients with cancer is still a major health problem. Drug repurposing coupled to drug combination strategies has been gaining interest among the scientific community. Recently, our group proposed novel drug combinations for breast and colon cancer using repurposed drugs from different classes (antimalarial and central nervous system (CNS)) and chemotherapeutic agents such as 5-fluorouracil (5-FU), paclitaxel (PTX), and found promising results. Here, we proposed a novel drug combination using different CNS drugs and doxorubicin (DOX), an antineoplastic used in breast cancer therapy, and studied their anticancer potential in MCF-7 breast cancer cells. Cells were treated with each drug alone and combined with increasing concentrations of DOX and cell viability was evaluated by MTT and SRB assays. Studies were also complemented with morphological evaluation. Assessment of drug interaction was performed using the CompuSyn and SynergyFinder software. We also compiled our previously studied drug pairs and selected the most promising ones for evaluation of the expression of EMT biomarkers (E-cadherin, P-cadherin, vimentin, and β-catenin) by immunohistochemistry (IHC) to assess if these drug combinations affect the expression of these proteins and eventually revert EMT. These results demonstrate that combination of DOX plus fluoxetine, benztropine, and thioridazine at their IC50 can improve the anticancer effect of DOX but to a lesser degree than when combined with PTX (previous results), resulting in most of the drug interactions being antagonist or additive. This suggests that the choice of the antineoplastic drug influences the success of the drug combination. Collectively, these results also allow us to conclude that antimalarial drugs as repurposed drugs have enhanced effects in MCF-7 breast cancer cells, while combination with CNS drugs seems to be more effective in HT-29 colon cancer cells. The IHC results demonstrate that combination treatments increase E-cadherin expression while reducing P-cadherin, vimentin, and β-catenin, suggesting that these treatments could induce EMT reversal. Taken together, these results could provide promising approaches to the design of novel drug combinations to treat breast and colon cancer patients.
miR-27b-3p Attenuates Muscle Atrophy by Targeting Cbl-b in Skeletal Muscles
Authors: Yang Xin , Li Zhenhui , Wang Zhijun , Yu Jiaao , Ma Manting , Nie Qinghua
Published: January 2022

As it is well known, muscle atrophy is a process in which protein degradation increases and protein synthesis decreases. This process is regulated by a variety of links. Among them, microRNAs play an essential role in this process, which has attracted widespread attention. In this paper, we find that miR-27b-3p and Cbl-b genes are significantly differentially expressed in the induced atrophy model. The dual-luciferase experiment and Western blot analysis confirmed that miR-27b-3p could regulate the expression of Cbl-b. In C2C12-differentiated myotubes, the overexpression of the Cbl-b gene showed that Cbl-b could upregulate the expression of MuRF-1 and Atrogin-1, which are related marker genes of muscle atrophy, at both the mRNA and protein levels, indicating that the Cbl-b gene can specifically affect muscle atrophy. The knockdown of the Cbl-b gene after C2C12-differentiated myotubes induced atrophy treatment can downregulate the expression of muscle-atrophy-related genes, indicating that manual intervention to downregulate the expression of Cbl-b has a certain alleviating effect on muscle atrophy. These data suggest that miR-27b-3p can regulate the expression of the Cbl-b gene and then exert a particular influence on muscle atrophy through the Cbl-b gene.
A Parallel Dissipation-Free and Dispersion-Optimized Explicit Time-Domain FEM for Large-Scale Room Acoustics Simulation
Authors: Yoshida Takumi , Okuzono Takeshi , Sakagami Kimihiro
Published: January 2022

Wave-based acoustics simulation methods such as finite element method (FEM) are reliable computer simulation tools for predicting acoustics in architectural spaces. Nevertheless, their application to practical room acoustics design is difficult because of their high computational costs. Therefore, we propose herein a parallel wave-based acoustics simulation method using dissipation-free and dispersion-optimized explicit time-domain FEM (TD-FEM) for simulating room acoustics at large-scale scenes. It can model sound absorbers with locally reacting frequency-dependent impedance boundary conditions (BCs). The method can use domain decomposition method (DDM)-based parallel computing to compute acoustics in large rooms at kilohertz frequencies. After validation studies of the proposed method via impedance tube and small cubic room problems including frequency-dependent impedance BCs of two porous type sound absorbers and a Helmholtz type sound absorber, the efficiency of the method against two implicit TD-FEMs was assessed. Faster computations and equivalent accuracy were achieved. Finally, acoustics simulation of an auditorium of 2271 m3 presenting a problem size of about 150,000,000 degrees of freedom demonstrated the practicality of the DDM-based parallel solver. Using 512 CPU cores on a parallel computer system, the proposed parallel solver can compute impulse responses with 3 s time length, including frequency components up to 3 kHz within 9000 s.
High-Rise Building Construction Progress Measurement from Top View Based on Component Detection
Authors: Xue Jingguo , Hou Xueliang
Published: January 2022

The construction progress of a high-rise building is hidden by clutter such as formwork, wood slats, and rebar, making it difficult to measure its progress through existing automated techniques. In this paper, we propose a method to monitor the construction process of high-rise buildings. Specifically, by using the target detection technique, unfinished building components are identified from the top view, and then the identified components are registered to the BIM elements one by one. This is achieved by comparing the position relationship between the target detection results and the projection area of the BIM elements on the imaging plane. Finally, the overall construction progress is inferred by calculating the number of identified and registered components. The method was tested on a high-rise building construction site. The experimental results show that the method is promising and is expected to provide a solid basis for the successful automatic acquisition of the construction process. The use of top view reduces occlusion compared to similar methods, and the identification of the unfinished component makes the method more suitable for the actual construction sites of high-rise buildings. In addition, the combination of target detection and rough registration allows this method to take full advantage of the contextual information in the images and avoid errors caused by misidentification.
The Impact of Climate Change on a University Campus’ Energy Use: Use of Machine Learning and Building Characteristics
Authors: Im Haekyung , Srinivasan Ravi S. , Maxwell Daniel , Steiner Ruth L. , Karmakar Sayar
Published: January 2022

Global warming is expected to increase 1.5 °C between 2030 and 2052. This may lead to an increase in building energy consumption. With the changing climate, university campuses need to prepare to mitigate risks with building energy forecasting models. Although many scholars have developed buildings energy models (BEMs), only a few have focused on the interpretation of the meaning of BEM, including climate change and its impacts. Additionally, despite several review papers on BEMs, there is no comprehensive guideline indicating which variables are appropriate to use to explain building energy consumption. This study developed building energy prediction models by using statistical analysis: multivariate regression models, multiple linear regression (MLR) models, and relative importance analysis. The outputs are electricity (ELC) and steam (STM) consumption. The independent variables used as inputs are building characteristics, temporal variables, and meteorological variables. Results showed that categorizing the campus buildings by building type is critical, and the equipment power density is the most important factor for ELC consumption, while the heating degree is the most critical factor for STM consumption. The laboratory building type is the most STM-consumed building type, so it needs to be monitored closely. The prediction models give an insight into which building factors remain essential and applicable to campus building policy and campus action plans. Increasing STM is to raise awareness of the severity of climate change through future weather scenarios.