bluuebunny/crossref_metadata_2025 huggingface dataset:
An Ensemble Feature Selection Approach to Identify Relevant Features from EEG Signals
Authors: Mera-Gaona Maritza , López Diego M. , Vargas-Canas Rubiel
Published: July 2021

Identifying relevant data to support the automatic analysis of electroencephalograms (EEG) has become a challenge. Although there are many proposals to support the diagnosis of neurological pathologies, the current challenge is to improve the reliability of the tools to classify or detect abnormalities. In this study, we used an ensemble feature selection approach to integrate the advantages of several feature selection algorithms to improve the identification of the characteristics with high power of differentiation in the classification of normal and abnormal EEG signals. Discrimination was evaluated using several classifiers, i.e., decision tree, logistic regression, random forest, and Support Vecctor Machine (SVM); furthermore, performance was assessed by accuracy, specificity, and sensitivity metrics. The evaluation results showed that Ensemble Feature Selection (EFS) is a helpful tool to select relevant features from the EEGs. Thus, the stability calculated for the EFS method proposed was almost perfect in most of the cases evaluated. Moreover, the assessed classifiers evidenced that the models improved in performance when trained with the EFS approach’s features. In addition, the classifier of epileptiform events built using the features selected by the EFS method achieved an accuracy, sensitivity, and specificity of 97.64%, 96.78%, and 97.95%, respectively; finally, the stability of the EFS method evidenced a reliable subset of relevant features. Moreover, the accuracy, sensitivity, and specificity of the EEG detector are equal to or greater than the values reported in the literature.
Partial Discharge Pattern Recognition of Transformers Based on MobileNets Convolutional Neural Network
Authors: Sun Yuanyuan , Ma Shuo , Sun Shengya , Liu Ping , Zhang Lina , Ouyang Jun , Ni Xianfeng
Published: July 2021

The power system on the offshore platform is of great importance since it is the power source for oil and gas exploitation, procession and transportation. Transformers constitute key equipment in the power system, and partial discharge (PD) is its most common fault that should be monitored and identified ın a timely and accurate manner. However, the existing PD classifiers cannot meet the demand for real-time online monitoring due to their disadvantages of high memory consumption and poor timeliness. Therefore, a new MobileNets convolutional neural network (MCNN) model is proposed to identify the PD pattern of transformers based on the phase resolved partial discharge (PRPD) spectrum. The model has the advantages of low computational complexity, fast reasoning speed and excellent classification performance. Firstly, we make four typical defect models of PD and conduct a test in a laboratory to collect the PRPD spectra as the data sample. In order to further improve the feature expression ability and recognition accuracy of the model, the lightweight attention mechanism Squeeze-and-Excitation (SE) module and the nonlinear function hard-swish (h-swish) are added after constructing the MCNN model to eliminate the potential accuracy loss in PD pattern recognition. The MCNN model is trained and tested with the pre-processed PRPD spectrum, and a variety of methods are used to visualize the model to verify the effectiveness of the model. Finally, the performance of MCNN is compared with many existing PD pattern recognition models based on convolutional neural network (CNN), the results show that the proposed MCNN can further reduce the number of parameters of the model and improve the calculation speed to achieve the best performance on the premise of good recognition accuracy.
Analysis of the Landfill Leachate Treatment System Using Arima Models: A Case Study in a Megacity
Authors: Zafra-Mejía Carlos Alfonso , Zuluaga-Astudillo Daniel Alberto , Rondón-Quintana Hugo Alexander
Published: July 2021

Leachate has been reported as the most significant source of landfill pollution. Predicting the characteristics of untreated and treated leachate may be useful during optimal scheduling of leachate treatment systems. The objective of this paper is to show an analysis of the operation of a landfill leachate treatment system in a Latin American megacity (Bogota, Colombia) by means of auto-regressive integrated moving average (ARIMA) models. A comparative analysis of the leachate treated with respect to reference legislation is carried out. The influence of climate variables during the operation of the treatment system is also considered. The results suggest that the concentrations of heavy metals (HMs), BOD5, and COD in untreated leachate do not follow the same annual cycles observed for the quantity of solid waste disposed within the landfill. This difference is possibly associated with the hydraulic retention time (HRT) of the leachate inside the conduction and pre-treatment system (storage/homogenization ponds). The ARIMA analysis suggests an HRT of up to one month (AR = 1) for the HMs identified as indicators of untreated leachate (Cu, Pb, and Zn). It is noted that the removal efficiency of HM indicators of the operation of the leachate treatment plant (Fe and Ni) is probably conditioned by operations carried out over a period of one month (AR = 1). The high input concentration of these HM indicators may prevent changing their ARIMA temporal structure during leachate treatment. This is reflected in the low removal efficiencies for all HMs under study (average = 26.1%).
Evaluation of Selected Thermal Changes in Textile Materials Arising in the Wake of the Impact of Heat Radiation
Authors: Machnowski Waldemar , Wąs-Gubała Jolanta
Published: July 2021

The detection of changes in the morphological and chemical structure of four cotton/polyester blend fabrics and their constituent fibres caused by thermal radiation was the purpose of the study. Relatively short exposure times, i.e., 20 s, 25 s, 30 s and 40 s, of fabrics for an incident heat flux density of 10 kW/m2 were applied so that they did not cause changes visible to the naked eye. Such experimental conditions have been selected to resemble the ones that may occur during firefighting, rescue operations, some professional activities as well as during criminal events. The assumption that using the sequence of physicochemical methods, i.e., optical microscopy, scanning electron microscopy and FTIR spectroscopy, will make it possible to identify selected thermal changes in examined materials caused by a short-term temperature increase has been positively verified. Out of applied techniques, scanning electron microscopy showed the highest efficiency in tracking morphological changes in fibres occurring under the influence of heat radiation, while the FTIR method allows for the identification of thermal changes in the chemical structure of cotton fibres. Optical microscopic methods were also characterised by relatively high usefulness in the detection of thermal changes, especially in terms of the physical microstructure of PES fibres. The changes occurring in the fibres due to the action of heat radiation depend not only on the thermal behaviour of a particular type of fibre but also on the structural parameters of the examined textiles, i.e., porosity, and the mutual position of particular types of fibres in the three-dimensional structure of yarns and fabrics. Moreover, the studies revealed the presence of tiny, deformed balls at the ends of the thermoplastic fibres, visible on the surface of some original polyester-cotton textiles, caused by a singeing technological process, which should be taken into account during interpretation of analytical findings.
Harvesting of Antimicrobial Peptides from Insect (Hermetia illucens) and Its Applications in the Food Packaging
Authors: Sultana Afreen , Luo Hongrong , Ramakrishna Seeram
Published: July 2021

About one-third of the total food produced is wasted, rising the concern to adopt proper management. Simultaneously with the increase in population, demand for food is increasing which may lead to scarcity. Adequate packaging is one of the ways to avoid deterioration of food and prevent wastage. In recent years, active packaging has attained interest due to its commendable results in food preservation. Several studies proved that the embodiment of antimicrobial components into the packaging material has the ability to prevent microbial contamination. Antimicrobial peptides (AMP) are newly discovered antimicrobial agents for impregnation into packaging material. Among various sources for AMP, insects have shown great resistivity against a wide spectrum of microorganisms. Insects feed on substances consisting of a varying range of contaminations, which often results in infections. Insects synthesise AMPs to fight such infections and survive in that atmosphere. The disease-causing agents in humans are the same as those found in insects. Hence, AMPs extracted from insects have the potential to fight the microorganisms that act as hazards to human health. This review highlights the harvesting and synthesis of AMPs from Hermetia illucens, which is a promising source for AMP and its applications in the food packaging industry.
High Sensitivity Continuous Monitoring of Chloroform Gas by Using Wavelength Modulation Photoacoustic Spectroscopy in the Near-Infrared Range
Authors: Zhang Tie , Xing Yuxin , Wang Gaoxuan , He Sailing
Published: July 2021

An optical system for gaseous chloroform (CHCl3) detection based on wavelength modulation photoacoustic spectroscopy (WMPAS) is proposed for the first time by using a distributed feedback (DFB) laser with a center wavelength of 1683 nm where chloroform has strong and complex absorption peaks. The WMPAS sensor developed possesses the advantages of having a simple structure, high-sensitivity, and direct measurement. A resonant cavity made of stainless steel with a resonant frequency of 6390 Hz was utilized, and eight microphones were located at the middle of the resonator at uniform intervals to collect the sound signal. All of the devices were integrated into an instrument box for practical applications. The performance of the WMPAS sensor was experimentally demonstrated with the measurement of different concentrations of chloroform from 63 to 625 ppm. A linear coefficient R2 of 0.999 and a detection sensitivity of 0.28 ppm with a time period of 20 s were achieved at room temperature (around 20 °C) and atmosphere pressure. Long-time continuous monitoring for a fixed concentration of chloroform gas was carried out to demonstrate the excellent stability of the system. The performance of the system shows great practical value for the detection of chloroform gas in industrial applications.
QRS Detection Based on Medical Knowledge and Cascades of Moving Average Filters
Authors: Bachi Lorenzo , Billeci Lucia , Varanini Maurizio
Published: July 2021

Heartbeat detection is the first step in automatic analysis of the electrocardiogram (ECG). For mobile and wearable devices, the detection process should be both accurate and computationally efficient. In this paper, we present a QRS detection algorithm based on moving average filters, which affords a simple yet robust signal processing technique. The decision logic considers the rhythmic and morphological features of the QRS complex. QRS enhancing is performed with channel-specific moving average cascades selected from a pool of derivative systems we designed. We measured the effectiveness of our algorithm on well-known benchmark databases, reporting F1 scores, sensitivity on abnormal beats and processing time. We also evaluated the performances of other available detectors for a direct comparison with the same criteria. The algorithm we propose achieved satisfying performances on par with or higher than the other QRS detectors. Despite the performances we report are not the highest that have been published so far, our approach to QRS detection enhances computational efficiency while maintaining high accuracy.
Optimization of Relief Well Design Using Artificial Neural Network during Geological CO2 Storage in Pohang Basin, South Korea
Authors: Song Youngsoo , Wang Jihoon
Published: July 2021

This study aims at the development of an artificial neural network (ANN) model to optimize relief well design in Pohang Basin, South Korea. Relief well design in carbon capture and geological storage (CCS) requires complex processes and excessive iterative procedures to obtain optimal operating parameters, such as CO2 injection rate, water production rate, distance between the wells, and pressure at the wells. To generate training and testing datasets for ANN model development, optimization processes for a relief well with various injection scenarios were performed. Training and testing were conducted, where the best iteration and regression were considered based on the calculated coefficient of determination (R2) and root mean square error (RMSE) values. According to validation with a 20-year injection scenario, which was not included in the training datasets, the model showed great performance with R2 values of 0.96 or higher for all the output parameters. In addition, the RMSE values for the BHP and the trapping mechanisms were lower than 0.04. Moreover, the location of the relief well was reliably predicted with a distance difference of only 20.1 m. The ANN model can be robust tool to optimize relief well design without a time-consuming reservoir simulations.
Modeling Software Fault-Detection and Fault-Correction Processes by Considering the Dependencies between Fault Amounts
Authors: Li Qiuying , Pham Hoang
Published: July 2021

Many NHPP software reliability growth models (SRGMs) have been proposed to assess software reliability during the past 40 years, but most of them have focused on modeling the fault detection process (FDP) in two ways: one is to ignore the fault correction process (FCP), i.e., faults are assumed to be instantaneously removed after the failure caused by the faults is detected. However, in real software development, it is not always reliable as fault removal usually needs time, i.e., the faults causing failures cannot always be removed at once and the detected failures will become more and more difficult to correct as testing progresses. Another way to model the fault correction process is to consider the time delay between the fault detection and fault correction. The time delay has been assumed to be constant and function dependent on time or random variables following some kind of distribution. In this paper, some useful approaches to the modeling of dual fault detection and correction processes are discussed. The dependencies between fault amounts of dual processes are considered instead of fault correction time-delay. A model aiming to integrate fault-detection processes and fault-correction processes, along with the incorporation of a fault introduction rate and testing coverage rate into the software reliability evaluation is proposed. The model parameters are estimated using the Least Squares Estimation (LSE) method. The descriptive and predictive performance of this proposed model and other existing NHPP SRGMs are investigated by using three real data-sets based on four criteria, respectively. The results show that the new model can be significantly effective in yielding better reliability estimation and prediction.
Mechanical and Metallurgical Properties of CO2 Laser Beam INCONEL 625 Welded Joints
Authors: Vemanaboina Harinadh , Gundabattini Edison , Akella Suresh , Rao A. C. Uma Maheshwer , Buddu Ramesh Kumar , Ferro Paolo , Berto Filippo
Published: July 2021

In the frame of the circular economy, welding of Ni-based superalloys has gained increasing importance when applied, for instance, to repairing highly expensive components widely used in strategical sectors, such as the defense and aerospace industries. However, correct process parameters avoiding metallurgical defects and premature failures need to be known. To reach this goal, Inconel 625 butt-welded joints were produced by CO2 laser beam welding and different combinations of process parameters. The experimental investigation was carried out with three parameters in two levels with an L4 orthogonal array. Laser power, welding speed, and shielding gas flow rate were varied, and the results were reported in terms of mechanical properties, such as microhardness, tensile strength, distortion, residual stress, and weld bead geometry, and metallurgy. At a lower welding speed of 1 m/min, the full penetration was observed for 3.0 kW and 3.3 kW laser powers. However, sound welds (porosity-free) were produced with a laser power of 3.3 kW. Overall, the obtained full-penetration specimens showed a tensile strength comparable with that of the parent material with residual stresses and distortions increasing with the increase in heat input.
Exploiting Spatial Information to Enhance DTI Segmentations via Spatial Fuzzy c-Means with Covariance Matrix Data and Non-Euclidean Metrics
Authors: Elsheikh Safa , Fish Andrew , Zhou Diwei
Published: July 2021

A diffusion tensor models the covariance of the Brownian motion of water at a voxel and is required to be symmetric and positive semi-definite. Therefore, image processing approaches, designed for linear entities, are not effective for diffusion tensor data manipulation, and the existence of artefacts in diffusion tensor imaging acquisition makes diffusion tensor data segmentation even more challenging. In this study, we develop a spatial fuzzy c-means clustering method for diffusion tensor data that effectively segments diffusion tensor images by accounting for the noise, partial voluming, magnetic field inhomogeneity, and other imaging artefacts. To retain the symmetry and positive semi-definiteness of diffusion tensors, the log and root Euclidean metrics are used to estimate the mean diffusion tensor for each cluster. The method exploits spatial contextual information and provides uncertainty information in segmentation decisions by calculating the membership values for assigning a diffusion tensor at one voxel to different clusters. A regularisation model that allows the user to integrate their prior knowledge into the segmentation scheme or to highlight and segment local structures is also proposed. Experiments on simulated images and real brain datasets from healthy and Spinocerebellar ataxia 2 subjects showed that the new method was more effective than conventional segmentation methods.
On the Possibility to Use the Charge Imbalance in Patients Undergoing Radiotherapy: A New Online, In Vivo, Noninvasive Dose Monitoring System
Authors: Cirrone G A Pablo , Amato Nino , Catalano Roberto , Di Domenico Alessandro , Cuttone Giacomo , Lojacono Pietro , Mazzaglia Alfio , Pace Fabrizio , Pittà Giuseppe , Raffaele Luigi , Salamone Vincenzo , Spatola Corrado , Petringa Giada
Published: July 2021

This paper describes a new real-time, in vivo, noninvasive, biasless detector system acting as a beam monitoring and relative dose measurement system. The detector is based on the idea that when a beam current is injected into the body of a patient undergoing a charged particle therapy, the current itself can be collected using a conductive electrode in contact with the patient’s skin. This new approach was studied in vitro using an electrically isolated water tank irradiated with monoenergetic proton beams. The conductive electrode was immersed in water and positioned outside the irradiation field. The detection system performance was evaluated by comparing its response against a SEM (Secondary Emission Monitor) detector, used as a reference beam current monitor, and an Advanced Markus ionization chamber. Short-, mid- and long-term reproducibility, current monitoring capability, field size dependence, electrode position and environment temperature dependence, linearity with dose, and dose rate dependence were investigated. Few preliminary in vivo tests were also performed that demonstrated the possibility to apply the system in clinical practice. The potential of the proposed method is considerable, representing a simple and economical system for online, in vivo, and noninvasive monitoring of the beam current and relative released dose into the patient during treatment, without perturbing the irradiation field. The system presented in this work is protected with both a National Italian (N. 102017000087851) and an International N. WO 2019/025933 patent.
A Decoupling Strategy for Reliability Analysis of Multidisciplinary System with Aleatory and Epistemic Uncertainties
Authors: Fu Chao , Liu Jihong , Xu Wenting
Published: July 2021

In reliability-based multidisciplinary design optimization, both aleatory and epistemic uncertainties may exist in multidisciplinary systems simultaneously. The uncertainty propagation through coupled subsystems makes multidisciplinary reliability analysis computationally expensive. In order to improve the efficiency of multidisciplinary reliability analysis under aleatory and epistemic uncertainties, a comprehensive reliability index that has clear geometric meaning under multisource uncertainties is proposed. Based on the comprehensive reliability index, a sequential multidisciplinary reliability analysis method is presented. The method provides a decoupling strategy based on performance measure approach (PMA), probability theory and convex model. In this strategy, the probabilistic analysis and convex analysis are decoupled from each other and performed sequentially. The probabilistic reliability analysis is implemented sequentially based on the concurrent subspace optimization (CSSO) and PMA, and the non-probabilistic reliability analysis is replaced by convex model extreme value analysis, which improves the efficiency of multidisciplinary reliability analysis with aleatory and epistemic uncertainties. A mathematical example and an engineering application are demonstrated to verify the effectiveness of the proposed method.
Implementation of a Lagrangian Stochastic Particle Trajectory Model (LaStTraM) to Simulate Concentration and Flux Footprints Using the Microclimate Model ENVI-Met
Authors: Simon Helge , Heusinger Jannik , Sinsel Tim , Weber Stephan , Bruse Michael
Published: July 2021

The number of studies evaluating flux or concentration footprints has grown considerably in recent years. These footprints are vital to understand surface–atmosphere flux measurements, for example by eddy covariance. The newly developed backwards trajectory model LaStTraM (Lagrangian Stochastic Trajectory Model) is a post-processing tool, which uses simulation results of the holistic 3D microclimate model ENVI-met as input. The probability distribution of the particles is calculated using the Lagrangian Stochastic method. Combining LaStTraM with ENVI-met should allow us to simulate flux and concentration footprints in complex urban environments. Applications and evaluations were conducted through a comparison with the commonly used 2D models Kormann Meixner and Flux Footprint Predictions in two different meteorological cases (stable, unstable) and in three different detector heights. LaStTraM is capable of reproducing the results of the commonly used 2D models with high accuracy. In addition to the comparison with common footprint models, studies with a simple heterogeneous and a realistic, more complex model domain are presented. All examples show plausible results, thus demonstrating LaStTraM’s potential for the reliable calculation of footprints in homogeneous and heterogenous areas.
Hypoxia Signaling in Parkinson’s Disease: There Is Use in Asking “What HIF?”
Authors: Lestón Pinilla Laura , Ugun-Klusek Aslihan , Rutella Sergio , De Girolamo Luigi A.
Published: July 2021

Hypoxia is a condition characterized by insufficient tissue oxygenation, which results in impaired oxidative energy production. A reduction in cellular oxygen levels induces the stabilization of hypoxia inducible factor α (HIF-1α), master regulator of the molecular response to hypoxia, involved in maintaining cellular homeostasis and driving hypoxic adaptation through the control of gene expression. Due to its high energy requirement, the brain is particularly vulnerable to oxygen shortage. Thus, hypoxic injury can cause significant metabolic changes in neural cell populations, which are associated with neurodegeneration. Recent evidence suggests that regulating HIF-1α may ameliorate the cellular damage in neurodegenerative diseases. Indeed, the hypoxia/HIF-1α signaling pathway has been associated to several processes linked to Parkinson’s disease (PD) including gene mutations, risk factors and molecular pathways such as mitochondrial dysfunction, oxidative stress and protein degradation impairment. This review will explore the impact of hypoxia and HIF-1α signaling on these specific molecular pathways that influence PD development and will evaluate different novel neuroprotective strategies involving HIF-1α stabilization.
Quantitative Assessment of Choroidal Parameters in Patients with Various Types of Diabetic Macular Oedema: A Single-Centre Cross-Sectional Analysis
Authors: Dmuchowska Diana Anna , Sidorczuk Patryk , Pieklarz Barbara , Konopińska Joanna , Mariak Zofia , Obuchowska Iwona
Published: July 2021

Diabetic macular oedema (DME) is an outcome of multiple, complex and not fully understood mechanisms. The aim of this study was to define the role of choroidopathy in the pathogenesis of various DME types. The retrospective cross-sectional single-centre study included 140 eyes from 105 patients with DME and 76 eyes from 52 non-diabetic controls. The eyes were stratified according to the type of DME: cystoid, diffuse, and with subretinal fluid. Optical coherence tomography-based choroidal parameters: thickness, volume, choroidal vascularity index (CVI), luminal area (LA), stromal area (SA), and total choroidal area (TCA) were compared. Eyes with DME, regardless of the type thereof, had lower choroidal thickness, volume, and CVI values than the controls. Further, the eyes with some specific DME types differed significantly from the controls in terms of LA and SA. While the eyes with various DME types did not differ significantly in terms of their choroidal thickness, volume and CVI, some between-group differences were found in LA, SA and TCA. Diabetic choroidopathy seems to play a role in the development of DME but is less likely involved in the pathogenesis of specific types thereof.
Biomedical Relevance of Novel Anticancer Peptides in the Sensitive Treatment of Cancer
Authors: Bakare Olalekan Olanrewaju , Gokul Arun , Wu Ruomou , Niekerk Lee-Ann , Klein Ashwil , Keyster Marshall
Published: July 2021

The global increase in cancer mortality and economic losses necessitates the cautious quest for therapeutic agents with compensatory advantages over conventional therapies. Anticancer peptides (ACPs) are a subset of host defense peptides, also known as antimicrobial peptides, which have emerged as therapeutic and diagnostic candidates due to several compensatory advantages over the non-specificity of the current treatment regimens. This review aimed to highlight the ravaging incidence of cancer, the use of ACPs in cancer treatment with their mechanisms, ACP discovery and delivery methods, and the limitations for their use. This would create awareness for identifying more ACPs with better specificity, accuracy and sensitivity towards the disease. It would also promote their efficacious utilization in biotechnology, medical sciences and molecular biology to ease the severity of the disease and enable the patients living with these conditions to develop an accommodating lifestyle.
Analysis of the Relationships between Balance Ability and Walking in Terms of Muscle Activities and Lower Limb Kinematics and Kinetics
Authors: Cinthuja Pathmanathan , Arnold Graham , Abboud Rami J. , Wang Weijie
Published: July 2021

There is a lack of evidence about the ways in which balance ability influences the kinematic and kinetic parameters and muscle activities during gait among healthy individuals. The hypothesis is that balance ability would be associated with the lower limb kinematics, kinetics and muscle activities during gait. Twenty-nine healthy volunteers (Age 32.8 ± 9.1; 18 males and 11 females) performed a Star Excursion Balance test to measure their dynamic balance and walked for at least three trials in order to obtain a good quality of data. A Vicon® 3D motion capture system and AMTI® force plates were used for the collection of the movement data. The selected muscle activities were recorded using Delsys® Electromyography (EMG). The EMG activities were compared using the maximum values and root mean squared (RMS) values within the participants. The joint angle, moment, force and power were calculated using a Vicon Plug-in-Gait model. Descriptive analysis, correlation analysis and multivariate linear regression analysis were performed using SPSS version 23. In the muscle activities, positive linear correlations were found between the walking and balance test in all muscles, e.g., in the multifidus (RMS) (r = 0.800 p < 0.0001), vastus lateralis (RMS) (r = 0.639, p < 0.0001) and tibialis anterior (RMS) (r = 0.539, p < 0.0001). The regression analysis models showed that there was a strong association between balance ability (i.e., reaching distance) and the lower limb muscle activities (i.e., vastus medialis–RMS) (R = 0.885, p < 0.0001), and also between balance ability (i.e., reaching distance) and the lower limb kinematics and kinetics during gait (R = 0.906, p < 0.0001). In conclusion, the results showed that vastus medialis (RMS) muscle activity mainly contributes to balance ability, and that balance ability influences the lower limb kinetics and kinematics during gait.
Translation of ABCE1 Is Tightly Regulated by Upstream Open Reading Frames in Human Colorectal Cells
Authors: Silva Joana , Nina Pedro , Romão Luísa
Published: July 2021

ATP-binding cassette subfamily E member 1 (ABCE1) belongs to the ABC protein family of transporters; however, it does not behave as a drug transporter. Instead, ABCE1 actively participates in different stages of translation and is also associated with oncogenic functions. Ribosome profiling analysis in colorectal cancer cells has revealed a high ribosome occupancy in the human ABCE1 mRNA 5′-leader sequence, indicating the presence of translatable upstream open reading frames (uORFs). These cis-acting translational regulatory elements usually act as repressors of translation of the main coding sequence. In the present study, we dissect the regulatory function of the five AUG and five non-AUG uORFs identified in the human ABCE1 mRNA 5′-leader sequence. We show that the expression of the main coding sequence is tightly regulated by the ABCE1 AUG uORFs in colorectal cells. Our results are consistent with a model wherein uORF1 is efficiently translated, behaving as a barrier to downstream uORF translation. The few ribosomes that can bypass uORF1 (and/or uORF2) must probably initiate at the inhibitory uORF3 or uORF5 that efficiently repress translation of the main ORF. This inhibitory property is slightly overcome in conditions of endoplasmic reticulum stress. In addition, we observed that these potent translation-inhibitory AUG uORFs function equally in cancer and in non-tumorigenic colorectal cells, which is consistent with a lack of oncogenic function. In conclusion, we establish human ABCE1 as an additional example of uORF-mediated translational regulation and that this tight regulation contributes to control ABCE1 protein levels in different cell environments.
Time-Resolved Studies of Ytterbium Distribution at Interfacial Surfaces of Ferritin-like Dps Protein Demonstrate Metal Uptake and Storage Pathways
Authors: Zeth Kornelius , Pretre Gabriela , Okuda Mitsuhiro
Published: July 2021

Cage-shaped protein (CSP) complexes are frequently used in bionanotechnology, and they have a variety of different architectures and sizes. The smallest cage-shaped protein, Dps (DNA binding protein from starved cells), can naturally form iron oxide biominerals in a multistep process of ion attraction, translocation, oxidation, and nucleation. The structural basis of this biomineralization mechanism is still unclear. The aim of this paper is to further develop understanding of this topic. Time-resolved metal translocation of Yb3+ ions has been investigated on Dps surfaces using X-ray crystallography. The results reveal that the soak time of protein crystals with Yb3+ ions strongly affects metal positions during metal translocation, in particular, around and inside the ion translocation pore. We have trapped a dynamic state with ongoing translocation events and compared this to a static state, which is reached when the cavity of Dps is entirely filled by metal ions and translocation is therefore blocked. By comparison with La3+ and Co2+ datasets, the time-dependence together with the coordination sphere chemistry primarily determine metal−protein interactions. Our data can allow structure-based protein engineering to generate CSPs for the production of tailored nanoparticles.
A Visual Encoding Model Based on Contrastive Self-Supervised Learning for Human Brain Activity along the Ventral Visual Stream
Authors: Li Jingwei , Zhang Chi , Wang Linyuan , Ding Penghui , Hu Lulu , Yan Bin , Tong Li
Published: July 2021

Visual encoding models are important computational models for understanding how information is processed along the visual stream. Many improved visual encoding models have been developed from the perspective of the model architecture and the learning objective, but these are limited to the supervised learning method. From the view of unsupervised learning mechanisms, this paper utilized a pre-trained neural network to construct a visual encoding model based on contrastive self-supervised learning for the ventral visual stream measured by functional magnetic resonance imaging (fMRI). We first extracted features using the ResNet50 model pre-trained in contrastive self-supervised learning (ResNet50-CSL model), trained a linear regression model for each voxel, and finally calculated the prediction accuracy of different voxels. Compared with the ResNet50 model pre-trained in a supervised classification task, the ResNet50-CSL model achieved an equal or even relatively better encoding performance in multiple visual cortical areas. Moreover, the ResNet50-CSL model performs hierarchical representation of input visual stimuli, which is similar to the human visual cortex in its hierarchical information processing. Our experimental results suggest that the encoding model based on contrastive self-supervised learning is a strong computational model to compete with supervised models, and contrastive self-supervised learning proves an effective learning method to extract human brain-like representations.
Centrally Projecting Edinger-Westphal Nucleus in the Control of Sympathetic Outflow and Energy Homeostasis
Authors: Cano Georgina , Hernan Shelby L. , Sved Alan F.
Published: July 2021

The centrally projecting Edinger-Westphal nucleus (EWcp) is a midbrain neuronal group, adjacent but segregated from the preganglionic Edinger-Westphal nucleus that projects to the ciliary ganglion. The EWcp plays a crucial role in stress responses and in maintaining energy homeostasis under conditions that require an adjustment of energy expenditure, by virtue of modulating heart rate and blood pressure, thermogenesis, food intake, and fat and glucose metabolism. This modulation is ultimately mediated by changes in the sympathetic outflow to several effector organs, including the adrenal gland, heart, kidneys, brown and white adipose tissues and pancreas, in response to environmental conditions and the animal’s energy state, providing for appropriate energy utilization. Classic neuroanatomical studies have shown that the EWcp receives inputs from forebrain regions involved in these functions and projects to presympathetic neuronal populations in the brainstem. Transneuronal tracing with pseudorabies virus has demonstrated that the EWcp is connected polysynaptically with central circuits that provide sympathetic innervation to all these effector organs that are critical for stress responses and energy homeostasis. We propose that EWcp integrates multimodal signals (stress, thermal, metabolic, endocrine, etc.) and modulates the sympathetic output simultaneously to multiple effector organs to maintain energy homeostasis under different conditions that require adjustments of energy demands.
The Emerging Role of Circulating Tumor DNA in the Management of Breast Cancer
Authors: Shoukry Mira , Broccard Sacha , Kaplan Jamie , Gabriel Emmanuel
Published: July 2021

With the incidence of breast cancer steadily rising, it is important to explore novel technologies that can allow for earlier detection of disease as well more a personalized and effective treatment approach. The concept of “liquid biopsies” and the data they provide have been increasingly studied in the recent decades. More specifically, circulating tumor DNA (ctDNA) has emerged as a potential biomarker for various cancers, including breast cancer. While methods such as mammography and tissue biopsies are the current standards for the detection and surveillance of breast cancer, ctDNA analysis has shown some promise. This review discusses the versatility of ctDNA by exploring its multiple emerging uses for the management of breast cancer. Its efficacy is also compared to current biomarkers and technologies.
Clinical Outcomes for Primary and Radiation-Associated Angiosarcoma of the Breast with Multimodal Treatment: Long-Term Survival Is Achievable
Authors: Kronenfeld Joshua P. , Crystal Jessica S. , Ryon Emily L. , Yadegarynia Sina , Chitters Celeste , Yechieli Raphael , D’Amato Gina , Rosenberg Andrew E. , Kesmodel Susan B. , Trent Jonathan C. , Goel Neha
Published: July 2021

Background: The optimal management of primary angiosarcoma (PAS) and radiation-associated angiosarcoma (RAAS) of the breast remains undefined. Available data show persistently poor survival outcomes following treatment with surgery or chemotherapy alone. The objective of this study was to evaluate long-term outcomes in patients treated with multimodality therapy. Methods: Patients diagnosed with stage I–III PAS or RAAS of the breast were identified from our local tumor registry (2010–2020). Patient demographics, tumor characteristics, and treatment were collected. Primary outcomes were local recurrence (LR), distant recurrence (DR), and median overall survival (OS). A secondary outcome was pathologic complete response (pCR) following neoadjuvant chemotherapy (NAC). Mann–Whitney U, chi-squared, or Fisher exact tests were used to analyze data. Kaplan–Meier curves compared OS for PAS and RAAS. Results: Twenty-two patients met inclusion criteria, including 11 (50%) with RAAS and 11 (50%) with PAS. Compared to PAS patients, RAAS patients were older and had more comorbidities. For RAAS patients, median time from radiation to diagnosis was 6 years (IQR: 5–11). RAAS patients were more likely to have a pCR to NAC (40% vs. 20%, p = 0.72). RAAS patients had a higher LR rate (43% vs. 38%, p = 0.83), and PAS patients were more likely to develop a DR (38% vs. 0%, p = 0.07). Median OS was 81 months in PAS patients and 90 months in RAAS patients (p = 1.00). Discussion: Long-term survival can be achieved in patients with PAS and RAAS who undergo multimodality treatment. NAC can result in pCR. The long-term clinical implications of pCR warrant further investigation.
Doxorubicin-Loaded Mixed Micelles Using Degradable Graft and Diblock Copolymers to Enhance Anticancer Sensitivity
Authors: Chen Yi-Chun , Chang Chang-Jung , Hsiue Ging-Ho , Chiang Yi-Ting
Published: July 2021

In this study, a graft copolymer, poly(N-(2-hydroxypropyl) methacrylamide dilactate)-co-(N-(2-hydroxypropyl) methacrylamide-co-histidine)-graft-poly(d,l-lactide), and a diblock copolymer, methoxy poly(ethylene glycol)-b-poly(d,l-lactide), were assembled into a mixed micellar system to encapsulate the anticancer drug doxorubicin (Dox). This mixed micellar system possesses the hydrophobic lactide segment of both copolymers, which reinforces its stability in physiological milieus; the histidine molecules appended on the graft copolymer provide the desired pH-responsive behavior to release Dox during internalization in cancer cells. The results demonstrate that the two copolymers were successfully prepared, and their ratios in the mixed micelles were optimized on the basis of the results of the stability tests. Under acidic conditions, the mixed micelles swell and are able to release their payloads. Therefore, the in vitro results indicate that the Dox in the mixed micelles is released effectively in response to the environmental pH of the mimetic internalization process, increasing cancer cells’ sensitivity toward Dox. The mixed micelles display low cytotoxicity due to the degradability of the polymers. The in vivo images show that the high stability of the mixed micelles ensures a high tumor accumulation. This selective tumor accumulation results in an excellent inhibition of in vivo tumor growth and a high rate of apoptosis in cancerous tissues, with low toxicity. This highly stable, mixed micellar system with a pH-dependent drug release, which enables the precise delivery of drugs to the tumor lesions, is feasible to employ clinically in cancer therapy.
Clinical Characteristics and Outcomes of Colorectal Cancer in the ColoCare Study: Differences by Age of Onset
Authors: Himbert Caroline , Figueiredo Jane C. , Shibata David , Ose Jennifer , Lin Tengda , Huang Lyen C. , Peoples Anita R. , Scaife Courtney L. , Pickron Bartley , Lambert Laura , Cohan Jessica N. , Bronner Mary , Felder Seth , Sanchez Julian , Dessureault Sophie , Coppola Domenico , Hoffman David M. , Nasseri Yosef F. , Decker Robert W. , Zaghiyan Karen , Murrell Zuri A. , Hendifar Andrew , Gong Jun , Firoozmand Eiman , Gangi Alexandra , Moore Beth A. , Cologne Kyle G. , El-Masry Maryliza S. , Hinkle Nathan , Monroe Justin , Mutch Matthew , Bernadt Cory , Chatterjee Deyali , Sinanan Mika , Cohen Stacey A. , Wallin Ulrike , Grady William M. , Lampe Paul D. , Reddi Deepti , Krane Mukta , Fichera Alessandro , Moonka Ravi , Herpel Esther , Schirmacher Peter , Kloor Matthias , von Knebel-Doeberitz Magnus , Nattenmueller Johanna , Kauczor Hans-Ulrich , Swanson Eric , Jedrzkiewicz Jolanta , Schmit Stephanie L. , Gigic Biljana , Ulrich Alexis B. , Toriola Adetunji T. , Siegel Erin M. , Li Christopher I. , Ulrich Cornelia M. , Hardikar Sheetal
Published: July 2021

Early-onset colorectal cancer has been on the rise in Western populations. Here, we compare patient characteristics between those with early- (<50 years) vs. late-onset (≥50 years) disease in a large multinational cohort of colorectal cancer patients (n = 2193). We calculated descriptive statistics and assessed associations of clinicodemographic factors with age of onset using mutually-adjusted logistic regression models. Patients were on average 60 years old, with BMI of 29 kg/m2, 52% colon cancers, 21% early-onset, and presented with stage II or III (60%) disease. Early-onset patients presented with more advanced disease (stages III–IV: 63% vs. 51%, respectively), and received more neo and adjuvant treatment compared to late-onset patients, after controlling for stage (odds ratio (OR) (95% confidence interval (CI)) = 2.30 (1.82–3.83) and 2.00 (1.43–2.81), respectively). Early-onset rectal cancer patients across all stages more commonly received neoadjuvant treatment, even when not indicated as the standard of care, e.g., during stage I disease. The odds of early-onset disease were higher among never smokers and lower among overweight patients (1.55 (1.21–1.98) and 0.56 (0.41–0.76), respectively). Patients with early-onset colorectal cancer were more likely to be diagnosed with advanced stage disease, to have received systemic treatments regardless of stage at diagnosis, and were less likely to be ever smokers or overweight.
CD14 Expressing Precursors Give Rise to Highly Functional Conventional Dendritic Cells for Use as Dendritic Cell Vaccine
Authors: Plantinga Maud , van den Beemt Denise A. M. H. , Dünnebach Ester , Nierkens Stefan
Published: July 2021

Induction of long-lasting immunity by dendritic cells (DCs) makes them attractive candidates for anti-tumor vaccination. Although DC vaccinations are generally considered safe, clinical responses remain inconsistent in clinical trials. This initiated studies to identify subsets of DCs with superior capabilities to induce effective and memory anti-tumor responses. The use of primary DCs has been suggested to overcome the functional limitations of ex vivo monocyte-derived DCs (moDC). The ontogeny of primary DCs has recently been revised by the introduction of DC3, which phenotypically resembles conventional (c)DC2 as well as moDC. Previously, we developed a protocol to generate cDC2s from cord blood (CB)-derived stem cells via a CD115-expressing precursor. Here, we performed index sorting and single-cell RNA-sequencing to define the heterogeneity of in vitro developed DC precursors and identified CD14+CD115+ expressing cells that develop into CD1c++DCs and the remainder cells brought about CD123+DCs, as well as assessed their potency. The maturation status and T-cell activation potential were assessed using flow cytometry. CD123+DCs were specifically prone to take up antigens but only modestly activated T-cells. In contrast, CD1c++ are highly mature and specialized in both naïve as well as antigen-experienced T-cell activation. These findings show in vitro functional diversity between cord blood stem cell-derived CD123+DC and CD1c++DCs and may advance the efficiency of DC-based vaccines.
Proteins from the DNA Damage Response: Regulation, Dysfunction, and Anticancer Strategies
Authors: Molinaro Caroline , Martoriati Alain , Cailliau Katia
Published: July 2021

Cells respond to genotoxic stress through a series of complex protein pathways called DNA damage response (DDR). These monitoring mechanisms ensure the maintenance and the transfer of a correct genome to daughter cells through a selection of DNA repair, cell cycle regulation, and programmed cell death processes. Canonical or non-canonical DDRs are highly organized and controlled to play crucial roles in genome stability and diversity. When altered or mutated, the proteins in these complex networks lead to many diseases that share common features, and to tumor formation. In recent years, technological advances have made it possible to benefit from the principles and mechanisms of DDR to target and eliminate cancer cells. These new types of treatments are adapted to the different types of tumor sensitivity and could benefit from a combination of therapies to ensure maximal efficiency.
Neuropilin-1 Expression Associates with Poor Prognosis in HNSCC and Elicits EGFR Activation upon CDDP-Induced Cytotoxic Stress
Authors: Napolitano Virginia , Russo Daniela , Morra Francesco , Merolla Francesco , Varricchio Silvia , Ilardi Gennaro , Di Crescenzo Rosa Maria , Martino Francesco , Mascolo Massimo , Celetti Angela , Tamagnone Luca , Staibano Stefania
Published: July 2021

Head and neck squamous cell carcinoma (HNSCC) includes a group of aggressive malignancies characterized by the overexpression of the epidermal growth factor receptor (EGFR) in 90% of cases. Neuropilin-1 (NRP-1) acts as an EGFR co-receptor, enhancing, upon ligand stimulation, EGFR signaling in several cellular models. However, NRP-1 remains poorly characterized in HNSCC. By utilizing in vitro cellular models of HNSCC, we report that NRP-1 is involved in the regulation of EGFR signaling. In fact, NRP-1 can lead to cisplatin-induced EGFR phosphorylation, an escape mechanism activated by cancer cells upon cytotoxic stress. Furthermore, we evaluated Neuropilin-1 staining in tissue samples of an HNSCC case series (n = 218), unraveling a prognostic value for the Neuropilin-1 tissue expression. These data suggest a potential role for NRP-1 in HNSCC cancer progression, expanding the repertoire of signaling in which NRP-1 is involved and eliciting the need for further investigations on NRP-1 as a suitable target for HNSCC novel therapeutic approaches.