bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Acute Oral Galactose Administration on the Redox System of the Rat Small Intestine
Authors: Homolak Jan , Babic Perhoc Ana , Knezovic Ana , Osmanovic Barilar Jelena , Virag Davor , Joja Mihovil , Salkovic-Petrisic Melita
Published: December 2021

Galactose is a ubiquitous monosaccharide with important yet incompletely understood nutritive and physiological roles. Chronic parenteral d-galactose administration is used for modeling aging-related pathophysiological processes in rodents due to its ability to induce oxidative stress (OS). Conversely, chronic oral d-galactose administration prevents and alleviates cognitive decline in a rat model of sporadic Alzheimer’s disease, indicating that galactose may exert beneficial health effects by acting in the gut. The present aim was to explore the acute time-response of intestinal redox homeostasis following oral administration of d-galactose. Male Wistar rats were euthanized at baseline (n = 6), 30 (n = 6), 60 (n = 6), and 120 (n = 6) minutes following orogastric administration of d-galactose (200 mg/kg). The overall reductive capacity, lipid peroxidation, the concentration of low-molecular-weight thiols (LMWT) and protein sulfhydryls (SH), the activity of Mn and Cu/Zn superoxide dismutases (SOD), reduced and oxidized fractions of nicotinamide adenine dinucleotide phosphates (NADPH/NADP), and the hydrogen peroxide dissociation rate were analyzed in duodenum and ileum. Acute oral administration of d-galactose increased the activity of SODs and decreased intestinal lipid peroxidation and nucleophilic substrates (LMWT, SH, NADPH), indicating activation of peroxidative damage defense pathways. The redox system of the small intestine can acutely tolerate even high luminal concentrations of galactose (0.55 M), and oral galactose treatment is associated with a reduction rather than the increment of the intestinal OS. The ability of oral d-galactose to modulate intestinal OS should be further explored in the context of intestinal barrier maintenance, and beneficial cognitive effects associated with long-term administration of low doses of d-galactose.
Modified 16-Quasi Log Periodic Antenna Array for Microwave Imaging of Breast Cancer Detection
Authors: Syed Avez , Sobahi Nebras , Sheikh Muntasir , Mittra Raj , Rmili Hatem
Published: December 2021

In this paper, an effective system for microwave imaging of breast tumor detection using modified 16-planar log periodic antenna (PLPA) array is presented. The modified PLPA operates in the band from 2 to 5 GHz with stable directional patterns in the end-fire direction. Once the results of a single antenna element have been validated, the design is extended to include 16 antenna elements. All 16 transceiver antennas are vertically placed around the phantom in a circular manner where one antenna acts as a transmitter and the rest work as receivers. Delay and Sum (DAS) algorithm is used for post processing the acquired scattered signals from the sensors to reconstruct the image of the breast and to identify the existence of breast tumors. The electromagnetic simulators CST and HFSS are used to design the system, while MATLAB is used to process the data. The developed PLPA array-based microwave imaging system performs admirably, making it one of the most effective systems for detecting tumor cells.
Convolutional Neural Networks for Breast Density Classification: Performance and Explanation Insights
Authors: Lizzi Francesca , Scapicchio Camilla , Laruina Francesco , Retico Alessandra , Fantacci Maria Evelina
Published: December 2021

We propose and evaluate a procedure for the explainability of a breast density deep learning based classifier. A total of 1662 mammography exams labeled according to the BI-RADS categories of breast density was used. We built a residual Convolutional Neural Network, trained it and studied the responses of the model to input changes, such as different distributions of class labels in training and test sets and suitable image pre-processing. The aim was to identify the steps of the analysis with a relevant impact on the classifier performance and on the model explainability. We used the grad-CAM algorithm for CNN to produce saliency maps and computed the Spearman’s rank correlation between input images and saliency maps as a measure of explanation accuracy. We found that pre-processing is critical not only for accuracy, precision and recall of a model but also to have a reasonable explanation of the model itself. Our CNN reaches good performances compared to the state-of-art and it considers the dense pattern to make the classification. Saliency maps strongly correlate with the dense pattern. This work is a starting point towards the implementation of a standard framework to evaluate both CNN performances and the explainability of their predictions in medical image classification problems.
Compatibility and Washing Performance of Compound Protease Detergent
Authors: Zhang Wei , Wu Jintao , Xiao Jing , Zhu Mingyao , Yang Haichuan
Published: December 2021

Protease is the main enzyme of detergent. Through the combination of different proteases and the combination of protease and detergent additives, it can adapt to different washing conditions to improve the washing effect. In this experiment, whiteness determination, microscope scanning, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy were used to detect the whiteness values of the cloth pieces before and after washing, as well as the stain residue between the fibers on the surface of the cloth pieces. The protease detergent formula with better decontamination and anti-deposition effects was selected. The combination of alkaline protease, keratinase, and trypsin was cost-effective in removing stains. Polyacrylamide gel electrophoresis showed that the molecular weight of the protein significantly changed after adding the enzyme preparation during washing, and the molecular weight of the protein was directly proportional to protein redeposition. The composite protease had a better comprehensive decontamination effect, and when compatible with suitable surfactants, anti-redeposition agents, and water-softening agents, the compound protease detergent exhibited a stronger decontamination ability than commercial detergents.
Examining the Effect of the Ratio of Biomedical Domain to General Domain Data in Corpus in Biomedical Literature Mining
Authors: Zhang Ziheng , Han Feng , Zhang Hongjian , Aoki Tomohiro , Ogasawara Katsuhiko
Published: December 2021

Biomedical terms extracted using Word2vec, the most popular word embedding model in recent years, serve as the foundation for various natural language processing (NLP) applications, such as biomedical information retrieval, relation extraction, and recommendation systems. The objective of this study is to examine how changes in the ratio of the biomedical domain to general domain data in the corpus affect the extraction of similar biomedical terms using Word2vec. We downloaded abstracts of 214,892 articles from PubMed Central (PMC) and the 3.9 GB Billion Word (BW) benchmark corpus from the computer science community. The datasets were preprocessed and grouped into 11 corpora based on the ratio of BW to PMC, ranging from 0:10 to 10:0, and then Word2vec models were trained on these corpora. The cosine similarities between the biomedical terms obtained from the Word2vec models were then compared in each model. The results indicated that the models trained with both BW and PMC data outperformed the model trained only with medical data. The similarity between the biomedical terms extracted by the Word2vec model increased when the ratio of the biomedical domain to general domain data was 3:7 to 5:5. This study allows NLP researchers to apply Word2vec based on more information and increase the similarity of extracted biomedical terms to improve their effectiveness in NLP applications, such as biomedical information extraction.
The Effect of a “Design-of-Awareness” Process on Recognition of AVAS Sound of Quiet Vehicles
Authors: Tsuruta-Hamamura Mariko , Kobayashi Toki , Kosuge Takahiro , Hasegawa Hiroshi
Published: December 2021

The development of quiet vehicles, such as hybrid and electric vehicles, has environmental benefits. However, the quietness of these vehicles may increase the risk to pedestrians, particularly those with visual impairment. We hypothesized that a “design-of-awareness” process based on the concept of sound education for hearing and recognizing the sound generated by the Acoustic Vehicle Alerting System (AVAS) installed in quiet vehicles may change peoples’ attitudes toward the sound and improve their ability to detect it. To verify this hypothesis, two experiments using a quiet vehicle were conducted to examine whether participants were able to detect the AVAS sound. The results revealed that few participants were initially able to detect the AVAS sound. After the design-of-awareness process was conducted, 1 and 3 month follow-up surveys were conducted to clarify its effects and longevity. The results revealed that approximately half of the participants became able to detect the sound, and that their attitudes toward the sound were changed. In addition, the number of participants who were able to detect the sound increased over time. These results indicate that a design-of-awareness process could be helpful for training people to detect the sound of quiet vehicles.
Development and Validation of an Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry Method for Quantitative Determination of N-((3S,4S)-4-(3,4-Difluorophenyl)piperidin-3-yl)-2-fluoro-4-(1-methyl-1H-pyrazol-5-yl)benzamide in Dog Plasma
Authors: Ping Li , Dong Xinwei , Zuo Minjuan , Hong Yawen , Zhu Difeng
Published: December 2021

The PI3K/AKT/MTOR signalling pathway plays an important role in the growth and proliferation of tumour cells. N-((3S,4S)-4-(3,4-Difluorophenyl)piperidin-3-yl)-2-fluoro-4-(1-methyl-1H-pyrazol-5-yl)benzamide (Hu7691) is a new-generation selective AKT inhibitor developed at Zhejiang University. In this study, we developed an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for the measurement of Hu7691 in dog plasma. Plasma was precipitated with acetonitrile and then separated on a trifunctionally bonded alkyl column. Excellent separation efficiency and selectivity were achieved by adjusting the mobile phase ratio, with a total running time of only 5 min. The linear dynamic range of the calibration curve was 5–1000 ng/mL. The method was fully validated, and all performance metrics met the criteria. The validated method was used for the pharmacokinetic monitoring and bioavailability assessment of Hu7691 in dogs. The results showed that the area under the curve and peak plasma concentration of Hu7691 increased with increasing dose (oral 5, 10, 20 mg/kg, intravenous 10 mg/kg), and oral bioavailabilities were 86.7%, 50.8%, and 50.5%, respectively, indicating a high bioavailability of Hu7691 in dogs. This provides a test basis for the clinical application of the compound.
Antioxidant and Antibacterial Properties of Extracts and Bioactive Compounds in Bryophytes
Authors: Cianciullo Piergiorgio , Maresca Viviana , Sorbo Sergio , Basile Adriana
Published: December 2021

Today global health problems such as increased risks of oxidative stress-related diseases and antibiotic resistance are issues of serious concern. Oxidative stress is considered to be the underlying cause of many contemporary pathological conditions such as neurological disorders, ischemia, cancer, etc. Antibiotic-resistant bacteria are a concerning issue in clinical practice, causing an increase in deadly infections. Bryophytes synthesize an outstanding number of secondary metabolites that have shown several potential therapeutic and nutraceutical applications. Research in the field has led to the isolation and characterization of several compounds (flavonoids, terpenoids, and bibenzyls). Some of these compounds have shown promising in vitro antibacterial activities and antioxidant potential comparable to known natural antioxidants such as ascorbic acid and α-tocopherol. However, the process of developing new drugs from naturally occurring molecules is often an impervious path. In this paper, the current state of research of bryophytic antioxidant and antibacterial applications is discussed.
On Unsupervised Methods for Medical Image Segmentation: Investigating Classic Approaches in Breast Cancer DCE-MRI
Authors: Militello Carmelo , Ranieri Andrea , Rundo Leonardo , D’Angelo Ildebrando , Marinozzi Franco , Bartolotta Tommaso Vincenzo , Bini Fabiano , Russo Giorgio
Published: December 2021

Unsupervised segmentation techniques, which do not require labeled data for training and can be more easily integrated into the clinical routine, represent a valid solution especially from a clinical feasibility perspective. Indeed, large-scale annotated datasets are not always available, undermining their immediate implementation and use in the clinic. Breast cancer is the most common cause of cancer death in women worldwide. In this study, breast lesion delineation in Dynamic Contrast Enhanced MRI (DCE-MRI) series was addressed by means of four popular unsupervised segmentation approaches: Split-and-Merge combined with Region Growing (SMRG), k-means, Fuzzy C-Means (FCM), and spatial FCM (sFCM). They represent well-established pattern recognition techniques that are still widely used in clinical research. Starting from the basic versions of these segmentation approaches, during our analysis, we identified the shortcomings of each of them, proposing improved versions, as well as developing ad hoc pre- and post-processing steps. The obtained experimental results, in terms of area-based—namely, Dice Index (DI), Jaccard Index (JI), Sensitivity, Specificity, False Positive Ratio (FPR), False Negative Ratio (FNR)—and distance-based metrics—Mean Absolute Distance (MAD), Maximum Distance (MaxD), Hausdorff Distance (HD)—encourage the use of unsupervised machine learning techniques in medical image segmentation. In particular, fuzzy clustering approaches (namely, FCM and sFCM) achieved the best performance. In fact, for area-based metrics, they obtained DI = 78.23% ± 6.50 (sFCM), JI = 65.90% ± 8.14 (sFCM), sensitivity = 77.84% ± 8.72 (FCM), specificity = 87.10% ± 8.24 (sFCM), FPR = 0.14 ± 0.12 (sFCM), and FNR = 0.22 ± 0.09 (sFCM). Concerning distance-based metrics, they obtained MAD = 1.37 ± 0.90 (sFCM), MaxD = 4.04 ± 2.87 (sFCM), and HD = 2.21 ± 0.43 (FCM). These experimental findings suggest that further research would be useful for advanced fuzzy logic techniques specifically tailored to medical image segmentation.
Residential Buildings Complex Boundaries Generation Based on Spatial Grid System
Authors: Lazić Marko , Perišić Ana , Perišić Branko
Published: December 2021

The automatic generation of building boundaries in contemporary research and engineering projects and practices is dominantly characterized by interior functional constraints. As a basis for the automated generation of various building boundaries, the solution presented in this paper is a novel approach that ignores the internal (functional) and focuses only on the external (non-functional) impacts. The primary orientation on external impacts may be, at any instance, extended by suitable complementary traditional methodology. The applied research methodology and presented method rely on a developed extendible rule-based system that simplifies floor plan creation by the recursive application of a formulated spatial grid generation algorithm. Based on starting parameter values (mainly the lot and building area spaces) the algorithm tends to create a set of grids that satisfy initial constraints by marking the individual grid cells as a part of the building or empty. The presented conceptual framework model served as a foundation for creating a prototype software application that supports the experimental generation of grid arrays that are transformed into readable images of residential building boundaries. For the initial validation of the developed methodology, method, and algorithm, the concrete parametric resolution is set to 1 m. The comparative analysis has shown that the presented approach overcomes some of the limitations of previous related research that generate building boundaries in simple rectangular form or with limited variability. The proposed method, in its current stage, outperforms discussed existing methods concerning complex shape boundary building plan generation. Besides that, there is a broad space for further enhancement directions concerning the interoperability with other, independently developed, frameworks, and software tools.
Evaluating the Design Criteria for Light Embankment Piling: Timber Piles in Road and Railway Foundations
Authors: Gunnvard Per , Mattsson Hans , Laue Jan
Published: December 2021

Three-dimensional finite element (FE) simulations were performed to further develop the Swedish design guidelines for geogrid-reinforced timber pile-supported embankments, also known as lightly piled embankments. Lightly piled embankments are constructed mainly in areas which typically have highly compressible soils, and the method utilises untreated timber piles as its key feature. The timber piles are installed in a triangular arrangement instead of the more common square arrangement, with a centre-to-centre distance of 0.8–1.2 m. The aim of this study was to evaluate the current standard using FE modelling setups with square and triangular pile arrangements with varying centre-to-centre distances, based on a typical road foundation case. The evaluation mainly focused on comparing the embankment settlements, as well as the load and stress distribution in the embankment, the piles and the geosynthetic reinforcement. As part of the evaluation, a state-of-the-art study was done on international design guidelines and analytical models. From the FE simulations, no evident difference in mechanical behaviour was found between the triangular and square piling patterns. The maximum allowed centre-to-centre distance between piles can potentially be increased to 1.4 m, decreasing the number of piles by as much as one third.
Synthetic Weyl Points of the Shear Horizontal Guided Waves in One-Dimensional Phononic Crystal Plates
Authors: Zhang Hongbo , Zhang Shaobo , Liu Jiang , Liu Bilong
Published: December 2021

Weyl physics in acoustic and elastic systems has drawn extensive attention. In this paper, Weyl points of shear horizontal guided waves are realized by one-dimensional phononic crystal plates, in which one physical dimension plus two geometrical parameters constitute a synthetic three-dimensional space. Based on the finite element method, we have not only observed the synthetic Weyl points but also explored the Weyl interface states and the reflection phase vortices, which have further proved the topological phase interface states. As the first realization of three-dimensional topological phases through one-dimensional phononic crystal plates in the synthetic dimension, this research demonstrates the great potential of applicable one-dimensional plate structural systems in detecting higher-dimensional topological phenomena.
Development and Experimental Validation of High Performance Embedded Intelligence and Fail-Operational Urban Surround Perception Solutions of the PRYSTINE Project
Authors: Novickis Rihards , Levinskis Aleksandrs , Fescenko Vitalijs , Kadikis Roberts , Ozols Kaspars , Ryabokon Anna , Schorn Rupert , Koszescha Jochen , Solmaz Selim , Stettinger Georg , Adu-Kyere Akwasi , Halla-aho Lauri , Nigussie Ethiopia , Isoaho Jouni
Published: December 2021

Automated Driving Systems (ADSs) commend a substantial reduction of human-caused road accidents while simultaneously lowering emissions, mitigating congestion, decreasing energy consumption and increasing overall productivity. However, achieving higher SAE levels of driving automation and complying with ISO26262 C and D Automotive Safety Integrity Levels (ASILs) is a multi-disciplinary challenge that requires insights into safety-critical architectures, multi-modal perception and real-time control. This paper presents an assorted effort carried out in the European H2020 ECSEL project—PRYSTINE. In this paper, we (1) investigate Simplex, 1oo2d and hybrid fail-operational computing architectures, (2) devise a multi-modal perception system with fail-safety mechanisms, (3) present a passenger vehicle-based demonstrator for low-speed autonomy and (4) suggest a trust-based fusion approach validated on a heavy-duty truck.
Seismic Active Earth Pressure of Limited Backfill with Curved Slip Surface Considering Intermediate Principal Stress
Authors: Liu Hui , Kong Dezhi , Gan Wensong , Wang Bingjie
Published: December 2021

The traditional method for seismic earth pressure calculation has certain limitations for retaining structures under complex conditions. For example, when the soil width is small, the results obtained by the traditional method will be much larger. Therefore, this paper assumes that the soil slip surface is a logarithmic spiral. Based on the plane strain unified strength theory formula, while also considering the soil arching effects and tension cracks, the analytical solutions of the lateral earth pressure coefficient and the active earth pressure under the earthquake action were deduced. The mechanism and distribution of seismic active earth pressure with limited width were discussed in terms of some relevant parameters. The results indicated that the seismic active earth pressure presented a “convex” nonlinear distribution along the retaining structure. As the contribution of the intermediate principal stress increased, the strength limit of the material was effectively utilized, and the earth pressure was reduced by 22.96%. The resultant force increased as the horizontal seismic coefficient increased. However, this effect was no longer evident when the wall–soil friction angle was close to the internal friction angle. The resultant force action point increased with the wall–soil friction angle, and it should be noted that ha>H/3 was true when δ/φ0>0.55. Finally, by drawing a comparison with previous studies, we verified that the method proposed in this paper is reasonable and can provide a new idea for subsequent 3D seismic earth pressure research.
Ransomware Detection Using the Dynamic Analysis and Machine Learning: A Survey and Research Directions
Authors: Urooj Umara , Al-rimy Bander Ali Saleh , Zainal Anazida , Ghaleb Fuad A. , Rassam Murad A.
Published: December 2021

Ransomware is an ill-famed malware that has received recognition because of its lethal and irrevocable effects on its victims. The irreparable loss caused due to ransomware requires the timely detection of these attacks. Several studies including surveys and reviews are conducted on the evolution, taxonomy, trends, threats, and countermeasures of ransomware. Some of these studies were specifically dedicated to IoT and android platforms. However, there is not a single study in the available literature that addresses the significance of dynamic analysis for the ransomware detection studies for all the targeted platforms. This study also provides the information about the datasets collection from its sources, which were utilized in the ransomware detection studies of the diverse platforms. This study is also distinct in terms of providing a survey about the ransomware detection studies utilizing machine learning, deep learning, and blend of both techniques while capitalizing on the advantages of dynamic analysis for the ransomware detection. The presented work considers the ransomware detection studies conducted from 2019 to 2021. This study provides an ample list of future directions which will pave the way for future research.
Effects of Visually Induced Self-Motion on Sound Localization Accuracy
Authors: Honda Akio , Maeda Kei , Sakamoto Shuichi , Suzuki Yôiti
Published: December 2021

The deterioration of sound localization accuracy during a listener’s head/body rotation is independent of the listener’s rotation velocity. However, whether this deterioration occurs only during physical movement in a real environment remains unclear. In this study, we addressed this question by subjecting physically stationary listeners to visually induced self-motion, i.e., vection. Two conditions—one with a visually induced perception of self-motion (vection) and the other without vection (control)—were adopted. Under both conditions, a short noise burst (30 ms) was presented via a loudspeaker in a circular array placed horizontally in front of a listener. The listeners were asked to determine whether the acoustic stimulus was localized relative to their subjective midline. The results showed that in terms of detection thresholds based on the subjective midline, the sound localization accuracy was lower under the vection condition than under the control condition. This indicates that sound localization can be compromised under visually induced self-motion perception. These findings support the idea that self-motion information is crucial for auditory space perception and can potentially enable the design of dynamic binaural displays requiring fewer computational resources.
Mobile On-Road Measurements of Aerosol Optical Properties during MOABAI Campaign in the North China Plain
Authors: Popovici Ioana Elisabeta , Deng Zhaoze , Goloub Philippe , Xia Xiangao , Chen Hongbin , Blarel Luc , Podvin Thierry , Hao Yitian , Chen Hongyan , Torres Benjamin , Victori Stéphane , Fan Xuehua
Published: December 2021

We present the mapping at fine spatial scale of aerosol optical properties using a mobile laboratory equipped with LIDAR (Light Detection And Ranging), sun photometer and in situ instruments for performing on-road measurements. The mobile campaign was conducted from 9 May to 19 May 2017 and had the main objective of mapping the distribution of pollutants in the Beijing and North China Plain (NCP) region. The highest AOD (Aerosol Optical Depth) at 440 nm of 1.34 and 1.9 were recorded during two heavy pollution episodes on 18 May and 19 May 2017, respectively. The lowest Planetary Boundary Layer (PBL) heights (0.5–1.5 km) were recorded during the heavy pollution events, correlating with the highest AOD and southern winds. The transport of desert dust from the Gobi Desert was captured during the mobile measurements, impacting Beijing during 9–13 May 2017. Exploring the NCP outside Beijing provided datasets for regions with scarce ground measurements and allowed the mapping of high aerosol concentrations when passing polluted cities in the NCP (Baoding, Tianjin and Tangshan) and along the Binhai New Area. For the first time, we provide mass concentration profiles from the synergy of LIDAR, sun photometer and in situ measurements. The case study along the Binhai New Area revealed mean extinction coefficients of 0.14 ± 0.10 km−1 at 532 nm and a mass concentration of 80 ± 62 μg/m3 in the PBL (<2 km). The highest extinction (0.56 km−1) and mass concentrations (404 μg/m3) were found in the industrial Binhai New Area. The PM10 and PM2.5 fractions of the total mass concentration profiles were separated using the columnar size distribution, derived from the sun photometer measurements. This study offers unique mobile datasets of the aerosol optical properties in the NCP for future applications, such as satellite validation and air quality studies.
Design, Analysis and Comparison of a Nonstandard Computational Method for the Solution of a General Stochastic Fractional Epidemic Model
Authors: Ahmed Nauman , Macías-Díaz Jorge E. , Raza Ali , Baleanu Dumitru , Rafiq Muhammad , Iqbal Zafar , Ahmad Muhammad Ozair
Published: December 2021

Malaria is a deadly human disease that is still a major cause of casualties worldwide. In this work, we consider the fractional-order system of malaria pestilence. Further, the essential traits of the model are investigated carefully. To this end, the stability of the model at equilibrium points is investigated by applying the Jacobian matrix technique. The contribution of the basic reproduction number, R0, in the infection dynamics and stability analysis is elucidated. The results indicate that the given system is locally asymptotically stable at the disease-free steady-state solution when R0<1. A similar result is obtained for the endemic equilibrium when R0>1. The underlying system shows global stability at both steady states. The fractional-order system is converted into a stochastic model. For a more realistic study of the disease dynamics, the non-parametric perturbation version of the stochastic epidemic model is developed and studied numerically. The general stochastic fractional Euler method, Runge–Kutta method, and a proposed numerical method are applied to solve the model. The standard techniques fail to preserve the positivity property of the continuous system. Meanwhile, the proposed stochastic fractional nonstandard finite-difference method preserves the positivity. For the boundedness of the nonstandard finite-difference scheme, a result is established. All the analytical results are verified by numerical simulations. A comparison of the numerical techniques is carried out graphically. The conclusions of the study are discussed as a closing note.
SARS-CoV-2 Infection and Pancreatic β Cell Failure
Authors: Mine Keiichiro , Nagafuchi Seiho , Mori Hitoe , Takahashi Hirokazu , Anzai Keizo
Published: December 2021

SARS-CoV-2 infection primarily causes pulmonary symptoms; however, accumulating reports indicate that some patients with COVID-19 have multiple organ dysfunction or failure. Although diabetes is considered a risk factor for severe COVID-19, SARS-CoV-2 infection may also be a causal factor for diabetes mellitus in patients with COVID-19. According to the research reviewed in this paper, the pancreas and pancreatic β cells appear to be targets of SARS-CoV-2 and are damaged by direct or indirect effects of the infection. However, controversial results have been reported between study groups, mainly due to the limited number of cases with diabetes precipitated by COVID-19. In this review, we comprehensively discuss the published findings on the potential association between SARS-CoV-2 infection or COVID-19 and pancreatic β-cell damage leading to diabetes onset. These findings will further contribute to our understanding of the pathogenesis of diabetes mellitus.
OSov: An Interactive Web Server to Evaluate Prognostic Biomarkers for Ovarian Cancer
Authors: Yan Zhongyi , Wang Qiang , Zhao Susu , Xie Longxiang , Zhang Lu , Han Yali , Zhang Baokun , Li Huimin , Guo Xiangqian
Published: December 2021

Ovarian cancer is one of the most aggressive and highly lethal gynecological cancers. The purpose of our study is to build a free prognostic web server to help researchers discover potential prognostic biomarkers by integrating gene expression profiling data and clinical follow-up information of ovarian cancer. We construct a prognostic web server OSov (Online consensus Survival analysis for Ovarian cancer) based on RNA expression profiles. OSov is a user-friendly web server which could present a Kaplan–Meier plot, forest plot, nomogram and survival summary table of queried genes in each individual cohort to evaluate the prognostic potency of each queried gene. To assess the performance of OSov web server, 163 previously published prognostic biomarkers of ovarian cancer were tested and 72% of them had their prognostic values confirmed in OSov. It is a free and valuable prognostic web server to screen and assess survival-associated biomarkers for ovarian cancer.
Sex-Related Factors in Cardiovascular Complications Associated to COVID-19
Authors: Megiorni Francesca , Pontecorvi Paola , Gerini Giulia , Anastasiadou Eleni , Marchese Cinzia , Ceccarelli Simona
Published: December 2021

Coronavirus disease 2019 (COVID-19), the pandemic infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), presents with an extremely heterogeneous spectrum of symptoms and signs. The clinical manifestations seem to be correlated with disease severity. COVID-19 susceptibility and mortality show a significant sex imbalance, with men being more prone to infection and showing a higher rate of hospitalization and mortality compared to women. Such variability can be ascribed to both sex-related biological factors and gender-related behavioral cues. This review will discuss the potential mechanisms accounting for sex/gender influence in vulnerability to COVID-19. Cardiovascular diseases play a central role in determining COVID-19 outcome, whether they are pre-existent or arose upon infection. We will pay particular attention to the impact of sex and gender on cardiovascular manifestations related to COVID-19. Finally, we will discuss the sex-dependent variability in some biomarkers for the evaluation of COVID-19 infection and prognosis. The aim of this work is to highlight the significance of gendered medicine in setting up personalized programs for COVID-19 prevention, clinical evaluation and treatment.
MDM2-Driven Ubiquitination Rapidly Removes p53 from Its Cognate Promoters
Authors: Henningsen Kester Mo , Manzini Valentina , Magerhans Anna , Gerber Sabrina , Dobbelstein Matthias
Published: December 2021

MDM2 is the principal antagonist of the tumor suppressor p53. p53 binds to its cognate DNA element within promoters and activates the transcription of adjacent genes. These target genes include MDM2. Upon induction by p53, the MDM2 protein binds and ubiquitinates p53, triggering its proteasomal degradation and providing negative feedback. This raises the question whether MDM2 can also remove p53 from its target promoters, and whether this also involves ubiquitination. In the present paper, we employ the MDM2-targeted small molecule Nutlin-3a (Nutlin) to disrupt the interaction of MDM2 and p53 in three different cancer cell lines: SJSA-1 (osteosarcoma), 93T449 (liposarcoma; both carrying amplified MDM2), and MCF7 (breast adenocarcinoma). Remarkably, removing Nutlin from the culture medium for less than five minutes not only triggered p53 ubiquitination, but also dissociated most p53 from its chromatin binding sites, as revealed by chromatin immunoprecipitation. This also resulted in reduced p53-responsive transcription, and it occurred much earlier than the degradation of p53 by the proteasome, arguing that MDM2 removes p53 from promoters prior to and thus independent of degradation. Accordingly, the short-term pharmacological inhibition of the proteasome did not alter the removal of p53 from promoters by Nutlin washout. However, when the proteasome inhibitor was applied for several hours, depleting non-conjugated ubiquitin prior to eliminating Nutlin, this compromised the removal of DNA-bound p53, as did an E1 ubiquitin ligase inhibitor. This suggests that the ubiquitination of p53 by MDM2 is necessary for its clearance from promoters. Depleting the MDM2 cofactor MDM4 in SJSA cells did not alter the velocity by that p53 was removed from promoters upon Nutlin washout. We conclude that MDM2 antagonizes p53 not only by covering its transactivation domain and by destabilization, but also by the rapid, ubiquitin-dependent termination of p53–chromatin interactions.
A Fiber-Optic Surface Plasmon Resonance Sensor for Bio-Detection in Visible to Near-Infrared Images
Authors: Chen Shimeng , Wu Haojun , Song Yongxin , Peng Wei , Liu Yun
Published: December 2021

In this paper, we demonstrate a fiber-optic surface plasmon resonance (FO-SPR) biosensor based on image processing and back propagation (BP) neural network. The transmitted light of the FO-SPR sensor was captured by using visible (VIS) and near-infrared (NIR) CMOS sensors. The optical information related to the SPR effect was extracted from images based on grayscale conversion and an edge detection algorithm. To achieve accurate monitoring of refractive index (RI) changes, the grayscale means of the VIS and NIR images and the RGB summation of the edge-detected images were used as training and test inputs for the BP neural network. We verified the effectiveness and superiority of this sensing system by experiments on sodium chloride solution identification and protein binding detection. This work is promising for practical applications in standardized biochemical sensing.
A Review of Recent Advances in Flexible Wearable Sensors for Wound Detection Based on Optical and Electrical Sensing
Authors: Sun Xianyou , Zhang Yanchi , Ma Chiyu , Yuan Qunchen , Wang Xinyi , Wan Hao , Wang Ping
Published: December 2021

Chronic wounds that are difficult to heal can cause persistent physical pain and significant medical costs for millions of patients each year. However, traditional wound care methods based on passive bandages cannot accurately assess the wound and may cause secondary damage during frequent replacement. With advances in materials science and smart sensing technology, flexible wearable sensors for wound condition assessment have been developed that can accurately detect physiological markers in wounds and provide the necessary information for treatment decisions. The sensors can implement the sensing of biochemical markers and physical parameters that can reflect the infection and healing process of the wound, as well as transmit vital physiological information to the mobile device through optical or electrical signals. Most reviews focused on the applicability of flexible composites in the wound environment or drug delivery devices. This paper summarizes typical biochemical markers and physical parameters in wounds and their physiological significance, reviews recent advances in flexible wearable sensors for wound detection based on optical and electrical sensing principles in the last 5 years, and discusses the challenges faced and future development. This paper provides a comprehensive overview for researchers in the development of flexible wearable sensors for wound detection.
Physical Forces and Transient Nuclear Envelope Rupture during Metastasis: The Key for Success?
Authors: Gauthier Benoit R. , Lorenzo Petra I. , Comaills Valentine
Published: December 2021

During metastasis, invading tumor cells and circulating tumor cells (CTC) face multiple mechanical challenges during migration through narrow pores and cell squeezing. However, little is known on the importance and consequences of mechanical stress for tumor progression and success in invading a new organ. Recently, several studies have shown that cell constriction can lead to nuclear envelope rupture (NER) during interphase. This loss of proper nuclear compartmentalization has a profound effect on the genome, being a key driver for the genome evolution needed for tumor progression. More than just being a source of genomic alterations, the transient nuclear envelope collapse can also support metastatic growth by several mechanisms involving the innate immune response cGAS/STING pathway. In this review we will describe the importance of the underestimated role of cellular squeezing in the progression of tumorigenesis. We will describe the complexity and difficulty for tumor cells to reach the metastatic site, detail the genomic aberration diversity due to NER, and highlight the importance of the activation of the innate immune pathway on cell survival. Cellular adaptation and nuclear deformation can be the key to the metastasis success in many unsuspected aspects.
Prognostic and Therapeutic Implications of Tumor Biology in Colorectal Liver Metastases
Authors: Kamphues Carsten , Beyer Katharina , Margonis Georgios Antonios
Published: December 2021

Prognostic models allow clinicians to predict survival outcomes, facilitate patient–physician discussions, and identify subgroups with potentially distinct prognoses [...]
Influence of the Metal Incorporation into Hydroxyapatites on the Deactivation Behavior of the Solids in the Esterification of Glycerol
Authors: Mota Gabriela , Carmo José Vitor C. do , Paz Camila B. , Saraiva Gilberto D. , Campos Adriana , Duarte Gian , Filho Edson C. da Silva , Oliveira Alcineia C. , Soares João M. , Rodríguez-Castellón Enrique , Rodríguez-Aguado Elena
Published: December 2021

The effects of the metal incorporation into hydroxyapatites on the deactivation behavior of the solids were examined in the esterification of glycerol (EG) reaction. The introduction of Cu, Co, or Ni ions by ion exchange in calcium-deficient hydroxyapatites resulted in active catalysts for the EG reaction. The metal contents were varied from 2.0 to 17.0%, providing better performances at rather high metal contents. Part of metal species existed in the hydroxyapatite lattice structure and also as isolated Cu2+, Ni2+, and Co2+ entities on the surface, as shown by XPS and EPR. The effects of the reaction temperature, reaction time, and glycerol to acetic acid molar ratios were deeply investigated. The spent solids used in this study were characterized by XRD, FTIR, SEM-EDS, chemical analyses, EPR, and XPS. The Cu2+–OH acid pairs could promote a superior catalytic performance of Cu-containing hydroxyapatites due to the resistance of these solids against leaching of the active species, which is even better than those of Co and Ni-containing counterparts with high metal contents. Cu into hydroxyapatite had a good reusability and long-term utilization for five consecutive cycles of 24 h under a glycerol to acetic acid molar ratio of 0.25 at 80 °C, and longer reaction times provide triacetin formation. This was due to the fact that Cu was stabilized by interacting with Ca, PO4, and OH sites into the hydroxyapatite lattice, being highly active for the EG reaction. The results also revealed that isolated Cu2+ sites played an important role in enhancing the glycerol conversion, intrinsically due to the Cu-containing hydroxyapatites ability to avoid strong adsorption of glycerol oligomers on the catalytic sites.
The Effects of Ce and W Promoters on the Performance of Alumina-Supported Nickel Catalysts in CO2 Methanation Reaction
Authors: Gac Wojciech , Zawadzki Witold , Greluk Magdalena , Słowik Grzegorz , Rotko Marek , Kuśmierz Marcin
Published: December 2021

The influence of Ce and W promoters on the performance of alumina-supported nickel catalysts in the CO2 methanation reaction was investigated. The catalysts were obtained by the co-impregnation method. Nitrogen low-temperature adsorption, temperature-programmed reduction, hydrogen desorption, transmission electron microscopy, X-ray diffraction, and photoelectron spectroscopy studies were used for catalyst characterization. An introduction of Ce and W promoters (1–5 wt %) led to the decrease in mean Ni crystallite size. Gradual increase in the active surface area was observed only for Ce-promoted catalysts. The increase in CO2 conversion in methanation reaction at low-reaction temperatures carried out over Ce-promoted catalysts was attributed to the increase in the active surface area and changes in the redox properties. The introduction of small amounts of tungsten led to an increase in the activity of catalysts, although a decrease in the active surface area was observed. Quasi in situ XPS studies revealed changes in the oxidation state of tungsten under CO2 methanation reaction conditions, indicating the participation of redox promoter changes in the course of surface reactions, leading to an improvement in the activity of the catalyst.
A Comparative Study of the Effect of Graphene Oxide, Graphitic Carbon Nitride, and Their Composite on the Photocatalytic Activity of Cu3SnS4
Authors: Olatunde Olalekan C. , Onwudiwe Damian C.
Published: December 2021

Photocatalysis has shown high potential in dealing with the ever-broadening problem of wastewater treatment, escalated by the increasing level of recalcitrant chemicals often referred to as emerging contaminants. In this study, the effect of support material on the photocatalytic activity of copper tin sulfide (Cu3SnS4) nanoparticles for the degradation of tetracycline as an emerging contaminant is presented. Graphene oxide, protonated graphitic carbon nitride, and a composite of graphitic carbon nitride and graphene oxide were explored as support materials for Cu3SnS4 nanoparticles. The nanoparticles were incorporated with the different carbonaceous substrates to afford graphene-supported Cu3SnS4 (GO-CTS), protonated graphitic carbon nitride-supported Cu3SnS4 (PCN-CTS), and graphene oxide/protonated graphitic carbon nitride-supported Cu3SnS4 (GO/PCN-CTS). Physicochemical, structural, and optical properties of the prepared nanocomposites were characterized using techniques such as Fourier transform infra-red spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-Vis near infrared, and fluorescence spectrophotometry. The compositing of the Cu3SnS4 nanoparticles on the support materials was confirmed by the characterization techniques, and the optical properties of the composites were found to be influenced by the nature of the support material. The incorporation of CTS into the support materials resulted in a reduction in band gap energy with evaluated band gaps of 1.65, 1.46, 1.43 eV, and 1.16 eV. The reduction in band gap energy suggests the potential of the composites for enhanced photocatalytic activity. From the photocatalytic study, the degradation efficiency of tetracycline by CTS, PCN-CTS, GO-CTS, and PC/GO-CTS was 74.1, 85.2, 90.9, and 96.5%, respectively. All the composites showed enhanced activity compared to pristine CTS, and the existence of a synergy between GO and PCN when both were employed as support materials was observed. Based on the charge carrier recombination characteristics and the band edge potential calculations from the composites, a possible mechanism of action of each composite was proposed. This study therefore confirms the possibility of modulating the mechanism of action and subsequently the efficiency of semiconductor materials by altering the nature of the support material.
Tailoring g-C3N4 with Lanthanum and Cobalt Oxides for Enhanced Photoelectrochemical and Photocatalytic Activity
Authors: Iqbal Naseer
Published: December 2021

Herein, the synthesis, characterization, and photoelectrochemical and photocatalytic characteristics of hydrothermally prepared La2O3–g-C3N4, CoO–g-C3N4, and La2O3–CoO–g-C3N4 are discussed. The XRD analysis and crystalline phases unveiled the impregnation of La2O3 and CoO into g-C3N4. The microscopic analysis supports the formation of g-C3N4 nanoflakes and La2O3 and CoO nanoparticles embedded homogeneously in the La2O3–CoO–g-C3N4 nanocomposite, whereas the EDX comprehended their respective elemental composition and ratios. A bandgap energy of 2.38 eV for La2O3–CoO–g-C3N4 was calculated using the Tauc plot method, complementing high visible-light activity. The solar-driven water-splitting reaction exhibited significant photocurrent efficiency (~3.75 mA/cm2), augmenting the hydrogen generation by La2O3–CoO–g-C3N4 compared to that by pure g-C3N4, La2O3–g-C3N4, and CoO–g-C3N4 in 0.5 M Na2SO4 electrolyte. The synergistic effect of La2O3 and CoO impregnation with g-C3N4 led to effective division of the photogenerated charge transporters, enhancing the photocatalytic hydrogen generation by the photocatalysts. Furthermore, photocatalytic pollutant removal, namely greater than 90% decomposition of methylene blue (MB) from water, was investigated with a pseudo-first-order reaction kinetics under 1 sun visible-light irradiation. Thus, La2O3–CoO–g-C3N4 nanocomposite was found to be a prospective material for harnessing solar energy.