bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of Roux-en-Y Gastric Bypass on Mitochondrial Biogenesis and Dynamics in Leukocytes of Obese Women
Authors: Abad-Jiménez Zaida , Vezza Teresa , López-Domènech Sandra , Fernández-Reyes Meylin , Canet Francisco , Morillas Carlos , Gómez-Abril Segundo Ángel , Bañuls Celia , Víctor Víctor M. , Rocha Milagros
Published: June 2022

The chronic low-grade inflammation widely associated with obesity can lead to a prooxidant status that triggers mitochondrial dysfunction. To date, Roux-en-Y gastric bypass (RYGB) is considered the most effective strategy for obese patients. However, little is known about its molecular mechanisms. This interventional study aimed to investigate whether RYGB modulates oxidative stress, inflammation and mitochondrial dynamics in the leukocytes of 47 obese women at one year follow-up. We evaluated biochemical parameters and serum inflammatory cytokines -TNFα, IL6 and IL1β- to assess systemic status. Total superoxide production -dHe-, mitochondrial membrane potential -TMRM-, leucocyte protein expression of inflammation mediators -MCP1 and NF-kB-, antioxidant defence -GPX1-, mitochondrial regulation—PGC1α, TFAM, OXPHOS and MIEAP- and dynamics -MFN2, MNF1, OPA1, FIS1 and p-DRP1- were also determined. After RYGB, a significant reduction in superoxide and mitochondrial membrane potential was evident, while GPX1 content was significantly increased. Likewise, a marked upregulation of the transcription factors PGC1α and TFAM, complexes of the oxidative phosphorylation chain (I–V) and MIEAP and MFN1 was observed. We conclude that women undergoing RYGB benefit from an amelioration of their prooxidant and inflammatory status and an improvement in mitochondrial dynamics of their leukocytes, which is likely to have a positive effect on clinical outcome.
Polish and New Zealand Propolis as Sources of Antioxidant Compounds Inhibit Glioblastoma (T98G, LN-18) Cell Lines and Astrocytoma Cells Derived from Patient
Authors: Moskwa Justyna , Naliwajko Sylwia Katarzyna , Markiewicz-Żukowska Renata , Gromkowska-Kępka Krystyna Joanna , Soroczyńska Jolanta , Puścion-Jakubik Anna , Borawska Maria Halina , Isidorov Valery , Socha Katarzyna
Published: June 2022

Gliomas, including glioblastoma multiforme and astrocytoma, are common brain cancers in adults. Propolis is a natural product containing many active ingredients. The aim of this study was to compare the chemical composition, total phenolic content and concentration of toxic elements as well as the anticancer potential of Polish (PPE) and New Zealand (Manuka—MPE) propolis extracts on diffuse astrocytoma derived from patient (DASC) and glioblastoma (T98G, LN-18) cell lines. The antioxidants such as flavonoids and chalcones (pinocembrin, pinobanksin, pinobanksin 3-acetate and chrysin) were the main components in both types of propolis. The content of arsenic (As) and lead (Pb) in MPE was higher than PPE. The anti-proliferative study showed strong activity of PPE and MPE propolis on DASC, T98G, and LN-18 cells by apoptosis induction, cell cycle arrest and attenuated migration. These findings suggest that despite their different geographic origins, Polish and New Zealand propolis are sources of antioxidant compounds and show similar activity and a promising anti-glioma potential in in vitro study. However, further in vivo studies are required in order to assess therapeutic potential of propolis.
How to Improve the Digital Competence for E-Learning?
Authors: Kallas Külli , Pedaste Margus
Published: June 2022

Digital competence for learning (skills, knowledge and attitudes needed for learning with digital devices) is a factor that affects the effectiveness of both the traditional and e-learning process. More specifically, technical competence is considered to be one of the four pillars of successful e-learning. Several studies show that in practice, digital technology has not always been used successfully, even in countries with very high digital readiness. Therefore, it is important to assess the different dimensions of digital competence for learning and analyse the interrelations between these dimensions in order to make suggestions for advancements. In our study, we applied a test with students from primary and lower secondary schools in Estonia to assess their digital competence for learning and used Structural Equation Modelling to understand how attitudes predict digital skills and knowledge that can be acquired in the individual and social settings. The findings confirm that only behavioural intention to use digital devices predicts the development of digital skills and knowledge. Moreover, some knowledge and skills acquired in the individual settings predict the development of knowledge and skills acquired in the social settings. The study provides researchers and practitioners with suggestions for improving the structure and quality of e-learning.
Galleria mellonella as a Novel In Vivo Model to Screen Natural Product-Derived Modulators of Innate Immunity
Authors: Wright Claire Louise , Kavanagh Owen
Published: June 2022

Immunomodulators are drugs that either stimulate or suppress the immune system in response to an immunopathological disease or cancer. The majority of clinically approved immunomodulators are either chemically synthesised (e.g., dexamethasone) or protein-based (e.g., monoclonal antibodies), whose uses are limited due to toxicity issues, poor bioavailability, or prohibitive cost. Nature is an excellent source of novel compounds, as it is estimated that almost half of all licenced medicines are derived from nature or inspired by natural product (NP) structures. The clinical success of the fungal-derived immunosuppressant cyclosporin A demonstrates the potential of natural products as immunomodulators. Conventionally, the screening of NP molecules for immunomodulation is performed in small animal models; however, there is a growing impetus to replace animal models with more ethical alternatives. One novel approach is the use of Galleria melonella larvae as an in vivo model of immunity. Despite lacking adaptive antigen-specific immunity, this insect possesses an innate immune system comparable to mammals. In this review, we will describe studies that have used this alternative in vivo model to assess the immunomodulating activity of synthetic and NP-derived compounds, outline the array of bioassays employed, and suggest strategies to enhance the use of this model in future research.
An Acoustic Feature-Based Deep Learning Model for Automatic Thai Vowel Pronunciation Recognition
Authors: Rukwong Niyada , Pongpinigpinyo Sunee
Published: June 2022

For Thai vowel pronunciation, it is very important to know that when mispronunciation occurs, the meanings of words change completely. Thus, effective and standardized practice is essential to pronouncing words correctly as a native speaker. Since the COVID-19 pandemic, online learning has become increasingly popular. For example, an online pronunciation application system was introduced that has virtual teachers and an intelligent process of evaluating students that is similar to standardized training by a teacher in a real classroom. This research presents an online automatic computer-assisted pronunciation training (CAPT) using deep learning to recognize Thai vowels in speech. The automatic CAPT is developed to solve the inadequacy of instruction specialists and the complex vowel teaching process. It is a unique system that develops computer techniques integrated with linguistic theory. The deep learning model is the most significant part of recognizing vowels pronounced for the automatic CAPT. The major challenge in Thai vowel recognition is the correct identification of Thai vowels when spoken in real-world situations. A convolutional neural network (CNN), a deep learning model, is applied and developed in the classification of pronounced Thai vowels. A new dataset for Thai vowels was designed, collected, and examined by linguists. The result of an optimal CNN model with Mel spectrogram (MS) achieves the highest accuracy of 98.61%, compared with Mel frequency cepstral coefficients (MFCC) with the baseline long short-term memory (LSTM) model and MS with the baseline LSTM model have an accuracy of 94.44% and 90.00% respectively.
Research on Adhesive Coefficient of Rubber Wheel Crawler on Wet Tilted Photovoltaic Panel
Authors: Nguyen Minh Tri , Truong Cong Toai , Nguyen Vu Thinh , Duong Van Tu , Nguyen Huy Hung , Nguyen Tan Tien
Published: June 2022

The demand for renewable energy sources is growing fast because of the negative impact of the utilization of fossil energy, nuclear energy, and hydroelectricity. One of the renewable energy sources, known as solar energy, which uses the photovoltaic panel (PV) to generate electricity from the sun, is a promising alternative that has great potential to deal with the power crisis. However, the power productivity and efficiency conversion are affected significantly by dust accumulation on PVs. Many researchers investigated PV panel dust cleaning methods to improve performance, yield, and profitability. Various dust cleaning and mitigation methods such as rainfall, labor-based, and mechanized cleaning are explored, and we demonstrated that dust removal could be automated with cleaning robots effectively. Due to the specified geographical site of PV panel installation, cleaning robots might work on the misalignment and uneven PV arrays, presenting huge challenges for an autonomous cleaning robot. Thus, a rubber wheel crawler robot with semi-autonomous handling provides a flexible motion that is a well-suited solution to clean rooftop PV arrays. Nevertheless, the rubber wheel crawler robot might suffer slippage on the wet glass of tilted PV arrays. This paper studies the anti-slip effect of the rubber wheel crawler equipped with a cleaning robot under the wet surface of tilted PV panels. First, a theoretical model consisting of several parameters is established to validate the slippage of the rubber wheel crawler on the wet tilted PV. Then, some parameters of the theoretical model are approximated through experimental tests. Finally, simulation results of the theoretical model are conducted to evaluate the accuracy of the proposed theoretical model in comparison to the experimental results under the same working conditions. The merits provide the efficient design of rubber wheel crawlers, enabling the anti-slip ability of robots.
Novel Hate Speech Detection Using Word Cloud Visualization and Ensemble Learning Coupled with Count Vectorizer
Authors: Turki Turki , Roy Sanjiban Sekhar
Published: June 2022

A plethora of negative behavioural activities have recently been found in social media. Incidents such as trolling and hate speech on social media, especially on Twitter, have grown considerably. Therefore, detection of hate speech on Twitter has become an area of interest among many researchers. In this paper, we present a computational framework to (1) examine out the computational challenges behind hate speech detection and (2) generate high performance results. First, we extract features from Twitter data by utilizing a count vectorizer technique. Then, we provide the labeled dataset of constructed features to adopted ensemble methods, including Bagging, AdaBoost, and Random Forest. After training, we classify new tweet examples into one of the two categories, hate speech or non-hate speech. Experimental results show (1) that Random Forest has surpassed other methods by generating 95% using accuracy performance results and (2) word cloud displays the most prominent tweets that are responsible for hateful sentiments.
Research on the Lightweight Deployment Method of Integration of Training and Inference in Artificial Intelligence
Authors: Zheng Yangyang , He Bin , Li Tianling
Published: June 2022

In recent years, the continuous development of artificial intelligence has largely been driven by algorithms and computing power. This paper mainly discusses the training and inference methods of artificial intelligence from the perspective of computing power. To address the issue of computing power, it is necessary to consider performance, cost, power consumption, flexibility, and robustness comprehensively. At present, the training of artificial intelligence models mostly are based on GPU platforms. Although GPUs offer high computing performance, their power consumption and cost are relatively high. It is not suitable to use GPUs as the implementation platform in certain application scenarios with demanding power consumption and cost. The emergence of high-performance heterogeneous architecture devices provides a new path for the integration of artificial intelligence training and inference. Typically, in Xilinx and Intel’s multi-core heterogeneous architecture, multiple high-performance processors and FPGAs are integrated into a single chip. When compared with the current separate training and inference method, heterogeneous architectures leverage a single chip to realize the integration of AI training and inference, providing a good balance of training and inference of different targets, further reducing the cost of training and implementation of AI inference and power consumption, so as to achieve the lightweight goals of computation, and to improve the flexibility and robustness of the system. In this paper, based on the LeNet-5 network structure, we first introduced the process of network training using a multi-core CPU in Xilinx’s latest multi-core heterogeneous architecture device, MPSoC. Then, the method of converting the network model into hardware logic implementation was studied, and the model parameters were transferred from the processing system of the device to the hardware accelerator structure, composed of programmable logic through the bus interface AXI provided on the chip. Finally, the integrated implementation method was tested and verified in Xilinx MPSoC. According to the test results, the recognition accuracy of this lightweight deployment scheme on MNIST dataset and CIFAR-10 dataset reached 99.5 and 75.4% respectively, while the average processing time of the single frame was only 2.2 ms. In addition, the power consumption of the network within the SoC hardware accelerator is only 1.363 W at 100 MHz.
Investigation of Meat from Ostriches Raised and Slaughtered in Bavaria, Germany: Microbiological Quality and Antimicrobial Resistance
Authors: Beindorf Philipp-Michael , Kovalenko Oksana , Ulrich Sebastian , Geißler Hanna , Korbel Rüdiger , Schwaiger Karin , Dorn-In Samart , Esteban-Cuesta Irene
Published: June 2022

Ostrich meat is characterized by high nutritional value; however, it remains an exotic product in most countries worldwide. In Europe, only few data are available regarding its microbial contamination, prevalence of antimicrobial-resistant bacteria, and safety. Therefore, this study aimed to investigate the microbiological quality and safety of ostrich meat samples (n = 55), each from one animal, produced in Bavaria, Germany. The provided microbiological status of ostrich meat included mesophilic aerobic bacteria, Enterobacteria, and mesophilic yeast and molds. In terms of food safety, all meat samples were negative for Salmonella spp. and Trichinella spp. Additionally, meat samples and a further 30 stool samples from 30 individuals were investigated for Shiga toxin-producing Escherichia coli genes, with two meat samples that were qPCR-positive. Antimicrobial-resistant Enterobacteriaceae, Enterococcus faecalis, and Enterococcus faecium strains were from meat and stool samples also analyzed; 13 potentially resistant Enterobacteriaceae (meat samples) and 4 Enterococcus faecium (stool samples) were isolated, and their susceptibility against 29 and 14 antimicrobials, respectively, was characterized. The results of this study provide an overview of microbial loads and food safety aspects that may be used as baseline data for the ostrich meat industry to improve their hygienic quality. However, the implementation of monitoring programs is recommended, and microbiological standards for ostrich meat production should be established.
Neuronal Depolarization Induced RNA m5C Methylation Changes in Mouse Cortical Neurons
Authors: Xu Xiguang , Johnson Zachary , Xie Hehuang
Published: June 2022

Neuronal activity is accomplished via substantial changes in gene expression, which may be accompanied by post-transcriptional modifications including RNA cytosine-5 methylation (m5C). Despite several reports on the transcriptome profiling of activated neurons, the dynamics of neuronal mRNA m5C modification in response to environmental stimuli has not been explored. Here, we provide transcriptome-wide maps of m5C modification, together with gene expression profiles, for mouse cortical neurons at 0 h, 2 h, and 6 h upon membrane depolarization. Thousands of differentially expressed genes (DEGs) were identified during the neuronal depolarization process. In stimulated neurons, the majority of early response genes were found to serve as expression regulators of late response genes, which are involved in signaling pathways and diverse synaptic functions. With RNA bisulfite sequencing data, a union set of 439 m5C sites was identified with high confidence, and approximately 30% of them were shared by neurons at all three time points. Interestingly, over 41% of the m5C sites showed increased methylation upon neuronal activation and were enriched in transcripts coding for proteins with synaptic functions. In addition, a modest negative correlation was observed between RNA expression and methylation. In summary, our study provided dynamic transcriptome-wide landscapes of RNA m5C methylation in neurons, and revealed that mRNA m5C methylation is associated with the regulation of gene expression.
Does the Actin Network Architecture Leverage Myosin-I Functions?
Authors: Pernier Julien , Schauer Kristine
Published: June 2022

The actin cytoskeleton plays crucial roles in cell morphogenesis and functions. The main partners of cortical actin are molecular motors of the myosin superfamily. Although our understanding of myosin functions is heavily based on myosin-II and its ability to dimerize, the largest and most ancient class is represented by myosin-I. Class 1 myosins are monomeric, actin-based motors that regulate a wide spectrum of functions, and whose dysregulation mediates multiple human diseases. We highlight the current challenges in identifying the “pantograph” for myosin-I motors: we need to reveal how conformational changes of myosin-I motors lead to diverse cellular as well as multicellular phenotypes. We review several mechanisms for scaling, and focus on the (re-) emerging function of class 1 myosins to remodel the actin network architecture, a higher-order dynamic scaffold that has potential to leverage molecular myosin-I functions. Undoubtfully, understanding the molecular functions of myosin-I motors will reveal unexpected stories about its big partner, the dynamic actin cytoskeleton.
Commercial Vaccines Do Not Confer Protection against Two Genogroups of Piscirickettsia salmonis, LF-89 and EM-90, in Atlantic Salmon
Authors: Figueroa Carolina , Torrealba Débora , Morales-Lange Byron , Mercado Luis , Dixon Brian , Conejeros Pablo , Silva Gabriela , Soto Carlos , Gallardo José A.
Published: June 2022

In Atlantic salmon, vaccines have failed to control and prevent Piscirickettsiosis, for reasons that remain elusive. In this study, we report the efficacy of two commercial vaccines developed with the Piscirickettsia salmonis isolates AL100005 and AL 20542 against another two genogroups which are considered highly and ubiquitously prevalent in Chile: LF-89 and EM-90. Two cohabitation trials were performed to mimic field conditions and vaccine performance: (1) post-smolt fish were challenged with a single infection of LF-89, (2) adults were coinfected with EM-90, and a low level coinfection of sea lice. In the first trial, the vaccine delayed smolt mortalities by two days; however, unvaccinated and vaccinated fish did not show significant differences in survival (unvaccinated: 60.3%, vaccinated: 56.7%; p = 0.28). In the second trial, mortality started three days later for vaccinated fish than unvaccinated fish. However, unvaccinated and vaccinated fish did not show significant differences in survival (unvaccinated: 64.6%, vaccinated: 60.2%, p = 0.58). Thus, we found no evidence that the evaluated vaccines confer effective protection against the genogroups LF-89 and EM-90 of P. salmonis with estimated relative survival proportions (RPSs) of −9% and −12%, respectively. More studies are necessary to evaluate whether pathogen heterogeneity is a key determinant of the lack of vaccine efficacy against P. salmonis.
Expression of a PCSK9 Gain-of-Function Mutation in C57BL/6J Mice to Facilitate Angiotensin II-Induced AAAs
Authors: Sawada Hisashi , Daugherty Alan , Lu Hong S.
Published: June 2022

Angiotensin II (AngII) infusion in mice has been used widely to investigate mechanisms of abdominal aortic aneurysms (AAAs). To achieve a high incidence of AngII-induced AAAs, mice should be hypercholesterolemic. Therefore, either low-density lipoprotein receptor (LDLR) or apolipoprotein E deficiency have been used as a hypercholesterolemic background. However, it is a time-consuming and expensive process to generate compound deficient strains that have either an LDLR or apolipoprotein E deficient background. Proprotein convertase subtilisin/kexin type 9 (PCSK9) facilitates the degradation of LDL receptors. Previous studies demonstrated profound increases of plasma cholesterol concentrations after a single intraperitoneal injection of adeno-associated viruses (AAV) expressing a gain-of-function mutation of mouse PCSK9 (AAV.mPCSK9D377Y) in C57BL/6J mice fed a Western diet. Of note, injection of AAV.mPCSK9D377Y augmented AngII-induced AAA formation in C57BL/6J mice that had comparable severity of AAAs to LDLR deficient mice. Thus, AAV.mPCSK9D377Y infection greatly expedites studies on a gene of interest using AngII-induced AAAs. This commentary provides a brief technical guide of this approach and discusses the pros and cons of its use in AAA research.
Combined Analysis of BSA-Seq Based Mapping, RNA-Seq, and Metabolomic Unraveled Candidate Genes Associated with Panicle Grain Number in Rice (Oryza sativa L.)
Authors: Ma Yafei , Mackon Enerand , Jeazet Dongho Epse Mackon Guibeline Charlie , Zhao Yitong , Li Qiufeng , Dai Xianggui , Yao Yuhang , Xia Xiuzhong , Nong Baoxuan , Liu Piqing
Published: June 2022

Rice grain yield is a complex and highly variable quantitative trait consisting of several key components, including the grain weight, the effective panicles per unit area, and the grain number per panicle (GNPP). The GNPP is a significant contributor to grain yield controlled by multiple genes (QTL) and is crucial for improvement. Attempts have been made to find genes for this trait, which has always been a challenging and arduous task through conventional methods. We combined a BSA analysis, RNA profiling, and a metabolome analysis in the present study to identify new candidate genes involved in the GNPP. The F2 population from crossing R4233 (high GNPP) and Ce679 (low GNPP) revealed a frequency distribution fitting two segregated genes. Three pools, including low, middle, and high GNPP, were constructed and a BSA analysis revealed six candidate regions spanning 5.38 Mb, containing 739 annotated genes. Further, a conjunctive analysis of BSA-Seq and RNA-Seq showed 31 differentially expressed genes (DEGs) in the candidate intervals. Subsequently, a metabolome analysis showed 1024 metabolites, with 71 significantly enriched, including 44 up and 27 downregulated in Ce679 vs. R4233. A KEGG enrichment analysis of these 31 DEGs and 71 differentially enriched metabolites (DEMs) showed two genes, Os12g0102100 and Os01g0580500, significantly enriched in the metabolic pathways’ biosynthesis of secondary metabolites, cysteine and methionine metabolism, and fatty acid biosynthesis. Os12g0102100, which encodes for the alcohol dehydrogenase superfamily and a zinc-containing protein, is a novel gene whose contribution to the GNPP is not yet elucidated. This gene coding for mitochondrial trans-2-enoyl-CoA reductase is involved in the biosynthesis of myristic acid, also known as tetradecanoic acid. The Os01g0580500 coding for the enzyme 1-aminoclopropane-1-carboxylate oxidase (OsACO7) is responsible for the final step of the ethylene biosynthesis pathway through the conversion of 1-aminocyclopropane-1-carboxylic acid (ACC) into ethylene. Unlike Os12g0102100, this gene was significantly upregulated in R4233, downregulated in Ce679, and significantly enriched in two of the three metabolite pathways. This result pointed out that these two genes are responsible for the difference in the GNPP in the two cultivars, which has never been identified. Further validation studies may disclose the physiological mechanisms through which they regulate the GNPP in rice.
Screening and Characterization of Streptomyces spp. Isolated from Three Moroccan Ecosystems Producing a Potential Inhibitor of the Drug Efflux Pump AcrAB-TolC
Authors: Azmani Asma , Lemriss Sanaa , Barakate Mustapha , Souiri Amal , Dhiba Driss , Hassani Lahcen , Hamdali Hanane
Published: June 2022

Traditional antimicrobial antibiotics are increasingly suffering from the emergence of multidrug resistance among pathogenic microorganisms. The antibiotic era is threatened by the ruthless rise of resistance in bacterial infections. A significant role in these resistance profiles is attributed to multidrug efflux pumps. Hence, much effort is being directed towards developing new compounds to overcome this problem. During our screening program of efflux pumps inhibitors (EPI) produced by bioactive Moroccan Actinobacteria, 210 isolates were screened for their antibacterial activities against Escherichia coli strains containing a system of efflux pump AcrAB-TolC, fully functional, and its mutant, inactivated due to the insertion of transposon Tn903 in AcrAB operon, using the method of agar disc diffusion. The results showed that 14 isolates were able to produce EPI as they were active against the wild type strain but not against the mutant in comparison with the synthetic inhibitor L-Phe-L-Arg-β-naphthylamide (PaβN). We focused on the highest EPI activity produced by four strains (Z332, Z35/G, Z385/b and 136). Taxonomic studies and the 16S rDNA sequence indicated that these strains belonged to the Streptomyces species. This work could contribute to the discovery of a new class of antibacterial agents that could expand the therapeutic arsenal.
Machine Learning Predictor of Immune Checkpoint Blockade Response in Gastric Cancer
Authors: Sung Ji-Yong , Cheong Jae-Ho
Published: June 2022

Predicting responses to immune checkpoint blockade (ICB) lacks official standards despite the discovery of several markers. Expensive drugs and different reactivities for each patient are the main disadvantages of immunotherapy. Gastric cancer is refractory and stem-like in nature and does not respond to immunotherapy. In this study, we aimed to identify a characteristic gene that predicts ICB response in gastric cancer and discover a drug target for non-responders. We built and evaluated a model using four machine learning algorithms for two cohorts of bulk and single-cell RNA seq to predict ICB response in gastric cancer patients. Through the LASSO feature selection, we discovered a marker gene signature that distinguishes responders from non-responders. VCAN, a candidate characteristic gene selected by all four machine learning algorithms, had a significantly high prevalence in non-responders (p = 0.0019) and showed a poor prognosis (p = 0.0014) at high expression values. This is the first study to discover a signature gene for predicting ICB response in gastric cancer by molecular subtype and provides broad insights into the treatment of stem-like immuno-oncology through precision medicine.
Host HSPD1 Translocation from Mitochondria to the Cytoplasm Induced by Streptococcus suis Serovar 2 Enolase Mediates Apoptosis and Loss of Blood–Brain Barrier Integrity
Authors: Wu Tong , Jia Li , Lei Siyu , Jiang Hexiang , Liu Jianan , Li Na , Langford Paul R. , Liu Hongtao , Lei Liancheng
Published: June 2022

Streptococcus suis serovar 2 (S. suis serovar 2) is a zoonotic pathogen that causes meningitis in pigs and humans, and is a serious threat to the swine industry and public health. Understanding the mechanism(s) by which S. suis serovar 2 penetrates the blood–brain barrier (BBB) is crucial to elucidating the pathogenesis of meningitis. In a previous study, we found that expression of the virulence factor enolase (Eno) by S. suis serovar 2 promotes the expression of host heat shock protein family D member 1 (HSPD1) in brain tissue, which leads to the apoptosis of porcine brain microvascular endothelial cells (PBMECs) and increased BBB permeability, which in turn promotes bacterial translocation across the BBB. However, the mechanism by which HSPD1 mediates Eno-induced apoptosis remains unclear. In this study, we demonstrate that Eno promotes the translocation of HSPD1 from mitochondria to the cytoplasm, where HSPD1 binds to β-actin (ACTB), the translocated HSPD1, and its interaction with ACTB led to adverse changes in cell morphology and promoted the expression of apoptosis-related proteins, second mitochondria-derived activator of caspases (Smac), and cleaved caspase-3; inhibited the expression of X-linked inhibitor of apoptosis protein (XIAP); and finally promoted cell apoptosis. These results further elucidate the role of HSPD1 in the process of Eno-induced apoptosis and increased BBB permeability, increasing our understanding of the pathogenic mechanisms of meningitis, and providing a framework for novel therapeutic strategies.
Circadian Volume Changes in Hippocampal Glia Studied by Label-Free Interferometric Imaging
Authors: Naseri Kouzehgarani Ghazal , Kandel Mikhail E. , Sakakura Masayoshi , Dupaty Joshua S. , Popescu Gabriel , Gillette Martha U.
Published: June 2022

Complex brain functions, including learning and memory, arise in part from the modulatory role of astrocytes on neuronal circuits. Functionally, the dentate gyrus (DG) exhibits differences in the acquisition of long-term potentiation (LTP) between day and night. We hypothesize that the dynamic nature of astrocyte morphology plays an important role in the functional circuitry of hippocampal learning and memory, specifically in the DG. Standard microscopy techniques, such as differential interference contrast (DIC), present insufficient contrast for detecting changes in astrocyte structure and function and are unable to inform on the intrinsic structure of the sample in a quantitative manner. Recently, gradient light interference microscopy (GLIM) has been developed to upgrade a DIC microscope with quantitative capabilities such as single-cell dry mass and volume characterization. Here, we present a methodology for combining GLIM and electrophysiology to quantify the astrocyte morphological behavior over the day-night cycle. Colocalized measurements of GLIM and fluorescence allowed us to quantify the dry masses and volumes of hundreds of astrocytes. Our results indicate that, on average, there is a 25% cell volume reduction during the nocturnal cycle. Remarkably, this cell volume change takes place at constant dry mass, which suggests that the volume regulation occurs primarily through aqueous medium exchange with the environment.
Molecularly Imprinted Polymer Functionalized Bi2S3/Ti3C2TX MXene Nanocomposites for Photoelectrochemical/Electrochemical Dual-Mode Sensing of Chlorogenic Acid
Authors: Qiu Zhenli , Fan Dechun , Xue Xianghang , Guo Shujun , Lin Youxiu , Chen Yiting , Tang Dianping
Published: June 2022

We report the proof-of-concept of molecularly imprinted polymer (MIP) functionalized Bi2S3/Ti3C2TX MXene nanocomposites for photoelectrochemical (PEC)/electrochemical (EC) dual-mode sensing of chlorogenic acid (CGA). Specifically, the in-situ growth of the Bi2S3/Ti3C2TX MXene served as a transducer substrate for molecularly imprinted polymers such as PEC and EC signal generators, due to its high surface area, suitable bandwidth and abundant active sites. In addition, the chitosan as a binder was encapsulated into MIP by means of phase inversion on a fluorine-doped tin dioxide (FTO) electrode. In the determination of CGA as an analytical model, the dual-mode sensor based on MIP functionalized Bi2S3/Ti3C2TX MXene nanocomposites had good selectivity, excellent stability and acceptable reproducibility, which displayed a linear concentration range from 0.0282 μM to 2824 μM for the PEC signal and 0.1412 μM to 22.59 μM for the EC signal with a low detection limit of 2.4 nM and 43.1 nM, respectively. Importantly, two dual-response mode with different transduction mechanisms could mutually conform to dramatically raise the reliability and accuracy of detection compared to single-mode detection. This work is a breakthrough for the design of dual-mode sensors and will provide a reasonable basis for the construction of dual-mode sensor platforms.
Amorphigenin from Amorpha fruticosa L. Root Extract Induces Autophagy-Mediated Melanosome Degradation in mTOR-Independent- and AMPK-Dependent Manner
Authors: Lee Ki Won , Nguyen Dang Thi , Kim Minju , Lee Si Hyeon , Lim Seyeon , Kim Jisu , Park Ki Hun , Kim Jeong Yoon , Yoo Jiyun , Hwangbo Cheol , Kim Kwang Dong
Published: June 2022

In this study, we investigated the depigmentation effect of Amorpha fruticosa L. root extract (RE), an herbal medicine. A. fruticosa RE significantly induced depigmentation in α-MSH-treated B16F10 cells at noncytotoxic concentrations. Further, the RE decreased the protein levels of the melanosomal proteins Tyr and Pmel without decreasing their transcript levels. We found that MG132, a proteasome complex inhibitor, was unable to rescue the protein levels, but PepA/E-64D (a lysosomal enzyme inhibitor), 3-MA (a representative autophagy inhibitor), and ATG5 knockdown effectively rescued the protein levels and inhibited the depigmentation effect following RE treatment. Among rotenoids, amorphigenin composed in the RE was identified as a functional chemical that could induce depigmentation; whereas rapamycin, an mTOR inhibitor and a nonselective autophagy inducer, could not induce depigmentation, and amorphigenin effectively induced depigmentation through the degradation of melanosomal proteins. Amorphigenin activated AMPK without affecting mTOR, and knockdown of AMPK offset the whitening effect through degradation of melanosome proteins by amorphigenin. Results from this study suggested that amorphigenin can induce degradation of the melanosome through an AMPK-dependent autophagy process, and has the potential to be used as a depigmentation agent for the treatment of hyperpigmentation.
Insights into the Uses of Traditional Plants for Diabetes Nephropathy: A Review
Authors: Shahin D. H. Haleema , Sultana Rokeya , Farooq Juveriya , Taj Tahreen , Khaiser Umaima Farheen , Alanazi Nader Sulaiman Ayyt , Alshammari Mohammed Kanan , Alshammari Mohammad Nazal , Alsubaie Firas Hamdan , Asdaq Syed Mohammed Basheeruddin , Alotaibi Abdulmueen A. , Alamir Abdulrhman ahmed , Imran Mohd. , Jomah Shahamah
Published: June 2022

Diabetic nephropathy (DN) is a serious kidney illness characterized by proteinuria, glomerular enlargement, reduced glomerular filtration, and renal fibrosis. DN is the most common cause of end-stage kidney disease, accounting for nearly one-third of all cases of diabetes worldwide. Hyperglycemia is a major factor in the onset and progression of diabetic nephropathy. Many contemporary medicines are derived from plants since they have therapeutic properties and are relatively free of adverse effects. Glycosides, alkaloids, terpenoids, and flavonoids are among the few chemical compounds found in plants that are utilized to treat diabetic nephropathy. The purpose of this review was to consolidate information on the clinical and pharmacological evidence supporting the use of a variety of medicinal plants to treat diabetic nephropathy.
COVID-19 Response in Zimbabwe: The Need for a Paradigm Shift?
Authors: Chitungo Itai , Dzinamarira Tafadzwa , Tungwarara Nigel , Chimene Munashe , Mukwenha Solomon , Kunonga Edward , Musuka Godfrey , Murewanhema Grant
Published: June 2022

Zimbabwe reported its first case of coronavirus disease 2019 (COVID-19) on 20 March 2020 and the country’s response has largely adhered to international protocols. From the outset of the pandemic, most control measures were premised upon knowledge of breaking infectious diseases’ chains of transmission gained from previous experiences with comparable pathogens. As relatively little was known about the novel virus, and the prospects of effective vaccines were not on the horizon, these tough control measures were deemed appropriate. Two years into the pandemic, a massive evolution of knowledge has transpired, and safe and effective vaccines against the virus are now available, are administered to billions of people, and can significantly reduce new infections, severe disease, hospitalisation, and death from the disease. Based on the understanding of the pandemic and the need to restore socio-economic activities, in this review we propose a paradigm shift in addressing the challenges of the COVID-19 pandemic. The COVID-19 response should take into consideration the local context and tailor-make a response that addresses local challenges.
Microparticle Production of Active Pharmaceutical Ingredient Using Supercritical Antisolvent Process: A Case Study of Allopurinol
Authors: Khudaida Salal , Wang Wei-Kai , Wu Wei-Yi , Su Chie-Shaan
Published: June 2022

Allopurinol is a relatively water-insoluble drug and, consequently, its efficacy was frequently limited by the dissolution or solubility phenomena. The purpose of this study was to improve the solid-state properties and dissolution behavior of allopurinol via a supercritical antisolvent (SAS) process using CO2 as an antisolvent. The effects of operating parameters: temperature (35–55 °C), pressure (80–100 bar), solution concentration (8–15 mg/mL), CO2 flow rate (2–4 L/min), and solution flow rate (0.25–0.50 mL/min) were studied. Moreover, the physical properties of unprocessed and SAS-processed allopurinol were analyzed by SEM, FTIR, DSC, TGA, and PXRD. The dissolution rate of unprocessed and SAS-processed allopurinol was also investigated and compared. In this case study, allopurinol was effectively micronized from 15.3 μm to 1.35 μm at the optimal operating condition. The results verify that the solid-state properties and dissolution rate of allopurinol can be controlled and improved via the micronization process by using SAS technology.
Role of Diffusion Tensor Imaging in the Diagnosis of Traumatic Axonal Injury in Individual Patients with a Concussion or Mild Traumatic Brain Injury: A Mini-Review
Authors: Jang Sung-Ho , Cho Min-Jye
Published: June 2022

Present review paper aims to understand role of diffusion tensor imaging (DTI) and diffusion tensor tractography (DTT) in diagnosis of traumatic axonal injury (TAI), induced by head trauma, in individual patients with a concussion or mild traumatic brain injury (mTBI). Precise information on presence and severity of TAI in brain is necessary for determining appropriate therapeutic strategies. Several hundred DTI-based studies have reported TAI in concussion or mTBI. Majority of these DTI-based studies have been performed in a group of patients, whereas case studies that have reported TAI in individual patients with a concussion or mTBI are fewer. Summary of these DTI-based studies for individual patients is as follows: DTI can be used as a non-invasive tool for determining presence and severity of TAI in individual patients with concussion or mTBI. However, for diagnosis of TAI in an individual patient, several conditions are required to be met: no past history of head trauma, presence of possible conditions for TAI occurrence during head trauma, development of new clinical features after head trauma, and DTI observed abnormality of a neural structure that coincides with a newly developed clinical feature. However, further studies for a more precise diagnosis of TAI in individual patients should be encouraged.
A Model of Interacting Navier–Stokes Singularities
Authors: Faller Hugues , Fery Lucas , Geneste Damien , Dubrulle Bérengère
Published: June 2022

We introduce a model of interacting singularities of Navier–Stokes equations, named pinçons. They follow non-equilibrium dynamics, obtained by the condition that the velocity field around these singularities obeys locally Navier–Stokes equations. This model can be seen as a generalization of the vorton model of Novikov that was derived for the Euler equations. When immersed in a regular field, the pinçons are further transported and sheared by the regular field, while applying a stress onto the regular field that becomes dominant at a scale that is smaller than the Kolmogorov length. We apply this model to compute the motion of a pair of pinçons. A pinçon dipole is intrinsically repelling and the pinçons generically run away from each other in the early stage of their interaction. At a late time, the dissipation takes over, and the dipole dies over a viscous time scale. In the presence of a stochastic forcing, the dipole tends to orientate itself so that its components are perpendicular to their separation, and it can then follow during a transient time a near out-of-equilibrium state, with forcing balancing dissipation. In the general case where the pinçons have arbitrary intensity and orientation, we observe three generic dynamics in the early stage: one collapse with infinite dissipation, and two expansion modes, the dipolar anti-aligned runaway and an anisotropic aligned runaway. The collapse of a pair of pinçons follows several characteristics of the reconnection between two vortex rings, including the scaling of the distance between the two components, following Leray scaling tc−t.
A NISQ Method to Simulate Hermitian Matrix Evolution
Authors: Li Keren , Gao Pan
Published: June 2022

As a universal quantum computer requires millions of error-corrected qubits, one of the current goals is to exploit the power of noisy intermediate-scale quantum (NISQ) devices. Based on a NISQ module–layered circuit, we propose a heuristic protocol to simulate Hermitian matrix evolution, which is widely applied as the core for many quantum algorithms. The two embedded methods, with their own advantages, only require shallow circuits and basic quantum gates. Capable to being deployed in near future quantum devices, we hope it provides an experiment-friendly way, contributing to the exploitation of power of current devices.
An Encryption Algorithm for Region of Interest in Medical DICOM Based on One-Dimensional eλ-cos-cot Map
Authors: Meng Xin , Li Jinqing , Di Xiaoqiang , Sheng Yaohui , Jiang Donghua
Published: June 2022

Today, with the rapid development of the Internet, improving image security becomes more and more important. To improve image encryption efficiency, a novel region of interest (ROI) encryption algorithm based on a chaotic system was proposed. First, a new 1D eλ-cos-cot (1D-ECC) with better chaotic performance than the traditional chaotic system is proposed. Second, the chaotic system is used to generate a plaintext-relate keystream based on the label information of a medical image DICOM (Digital Imaging and Communications in Medicine) file, the medical image is segmented using an adaptive threshold, and the segmented region of interest is encrypted. The encryption process is divided into two stages: scrambling and diffusion. In the scrambling stage, helical scanning and index scrambling are combined to scramble. In the diffusion stage, two-dimensional bi-directional diffusion is adopted, that is, the image is bi-directionally diffused row by column to make image security better. The algorithm offers good encryption speed and security performance, according to simulation results and security analysis.
Asymmetric Bipartite Consensus of Multi-Agent Systems under Periodic Detection Event-Triggered Mechanism
Authors: Wang Wenxin , Ye Hongtao , Luo Wenguang , Huang Dan
Published: June 2022

This paper investigates the periodic event-triggered asymmetric bipartite consensus problem of multi-agent systems (MASs) under structurally balanced undirected signed graphs. In order to reduce the consumption of communication resources and continuous detection in the control process of MASs, a novel periodic detection event-triggered asymmetric bipartite consensus control protocol is proposed. In particular, each agent samples only in a fixed period. For each agent, two event conditions are given, and only when state error satisfies this event condition can the event be triggered. A new type of Laplacian matrix is constructed to achieve asymmetric bipartite consensus. The control method can guarantee the performance of MASs and have less communication resources. Based on the Lyapunov stability theorem and algebraic graph theory, the proposed periodic event-triggered control strategy is able to implement the asymmetric bipartite consensus when the topology is structurally balanced undirected signed graphs. The proposed method in this paper can reduce the restriction on the sampling period and automatically exclude Zeno behavior. Finally, the validity of the conclusion is verified by numerical simulation.
Research on Cosine-Sum Windows with Maximum Side-Lobe Decay for High Precision ADC Spectral Testing
Authors: Fu Jiangduo , Yang Zhong , Song Jiayin , Zhan Yi , Qiao Shushan
Published: June 2022

Achieving coherent sampling has always been a major challenge in analog-to-digital converter (ADC) spectral testing. If the coherent sampling condition cannot be met, leakage appears in the spectrum, which results in inaccurate parameters. The windowing method is widely used to process ADC data to eliminate leakage. However, this method requires prior knowledge about the type of window, and some commonly used windows cannot provide accurate results for a high precision ADC. In this paper, some general principles for optimizing the cosine-sum window and some windows with maximum side-lobe decay have been presented. A test method for eliminating the leakage caused by non-coherent sampling is also proposed. The proposed method can accurately evaluate the dynamic parameters of an ADC with arbitrary non-coherency. Various simulation results and measurement data demonstrate the functionality and robustness of the proposed method. The proposed method significantly relaxes the condition of coherent sampling and decreases the test cost.
Optical Modelling of Planar and Fibre Perovskite Solar Cells
Authors: Moshonas Nikolaos , Stathopoulos Nikolaos A. , Pagiatakis Gerasimos
Published: June 2022

We present the optical modelling of a mesoporous fibre perovskite solar cell (PSC). It was conducted by means of the transmission line method (TLM), which was used to calculate the efficiency and short-circuit photo-current density of the cell. The TLM was first applied for a planar mesoporous PSC and verified with the experimental results from the literature. Numerical calculations for both planar and fibre PSC were conducted and analysed regarding their efficiency in terms of optical simulation. The importance of choosing the thin-film layers’ materials and thickness was demonstrated, and a potential improvement using anti-reflection coatings was also examined.
Extracting Prominent Aspects of Online Customer Reviews: A Data-Driven Approach to Big Data Analytics
Authors: Ali Noaman M. , Alshahrani Abdullah , Alghamdi Ahmed M. , Novikov Boris
Published: June 2022

Sentiment analysis on social media and e-markets has become an emerging trend. Extracting aspect terms for structure-free text is the primary task incorporated in the aspect-based sentiment analysis. This significance relies on the dependency of other tasks on the results it provides, which directly influences the accuracy of the final results of the sentiment analysis. In this work, we propose an aspect term extraction model to identify the prominent aspects. The model is based on clustering the word vectors generated using the pre-trained word embedding model. Dimensionality reduction was employed to improve the quality of word clusters obtained using the K-Means++ clustering algorithm. The proposed model was tested on the real datasets collected from online retailers’ websites and the SemEval-14 dataset. Results show that our model outperforms the baseline models.