bluuebunny/crossref_metadata_2025 huggingface dataset:
A Customer-Centric View of E-Commerce Security and Privacy
Authors: Saeed Saqib
Published: January 2023

Business organizations have huge potential to increase their customer base by offering e-commerce services, especially in the post-pandemic era. Ensuring secure e-commerce applications plays an important role in increasing customer base. To develop appropriate policies and secure technological infrastructures, business organizations first need to establish an understanding of the reservations of their customers toward e-commerce, as well as their perception of security and privacy of e-commerce applications. In this paper, we present the results of an empirical study of e-commerce customers conducted in Pakistan to gain an insight into their mindset on using e-commerce applications. An online questionnaire was set up to collect data, which were analyzed using the partial least squares method with SmartPLS software. The empirical findings highlight that customers’ concerns about credit card usage, concerns over information security, motivational factors for shopping offered by business organizations, customer trustworthiness, and user’s feelings about the reputation of e-commerce impact their perception of security of online data and trust in an e-commerce application. The results of this study can help organizations in Pakistan to develop policies and improve technological infrastructures by adopting emerging technologies and digital forensics.
Special Issue on Multi-Agent Systems
Authors: Julian Vicente , Botti Vicente
Published: January 2023

Multi-agent systems (MAS) are a class of systems in which multiple agents interact with each other and their environment to achieve a common or individual goal [...]
Viscoelasticity: Mathematical Modelling, Numerical Simulations, and Experimental Work
Authors: Ferrás Luís L. , Afonso Alexandre M.
Published: January 2023

Viscoelastic materials are abundant in nature and present in our daily lives [...]
Semi-Global Stereo Matching Algorithm Based on Multi-Scale Information Fusion
Authors: Deng Changgen , Liu Deyuan , Zhang Haodong , Li Jinrong , Shi Baojun
Published: January 2023

Semi-global matching (SGM) has been widely used in binocular vision. In spite of its good efficiency, SGM still has difficulties in dealing with low-texture regions. In this paper, an SGM algorithm based on multi-scale information fusion (MSIF), named SGM-MSIF, is proposed by combining multi-path cost aggregation and cross-scale cost aggregation (CSCA). Firstly, the stereo pairs at different scales are obtained by Gaussian pyramid down-sampling. The initial matching cost volumes at different scales are computed by combining census transform and color information. Then, the multi-path cost aggregation in SGM is introduced into the cost aggregation at each scale and the aggregated cost volumes are fused by CSCA. Thirdly, the disparity map is optimized by internal left-right consistency check and median filter. Finally, experiments are conducted on Middlebury datasets to evaluate the proposed algorithm. Experimental results show that the average error matching rate (EMR) of the proposed SGM-MSIF algorithm reduced by 1.96% compared with SGM. Compared with classical cross-scale stereo matching algorithm, the average EMR of SGM-MSIF algorithm reduced by 0.92%, while the processing efficiency increased by 58.7%. In terms of overall performance, the proposed algorithm outperforms the classic SGM and CSCA algorithms. It can achieve high matching accuracy and high processing efficiency for binocular vision applications, especially for those with low-texture regions.
3D-Printed Metal Surgical Guide for Endodontic Microsurgery (a Proof of Concept)
Authors: Cabezon Camille , Aubeux Davy , Pérez Fabienne , Gaudin Alexis
Published: January 2023

Thanks to recent advances, printed surgical guides are now fully integrated into digital workflows and are beneficial in terms of accuracy in endodontic microsurgery (EMS). The aim of this study was to evaluate the accuracy of new 3D-printed surgical metal guides (SMGs) with open-frame structures in an endodontic surgical simulation model ex vivo based on a pig jaw. Twenty-nine roots were included. SMGs were produced using 3D implant planning software and printed using cobalt-chrome and a laser sintering printer. The SMGs were designed to allow for surgical access at 3 mm from the apex of each root. Virtual planning and postoperative CBCT scans were compared by analysing the apical and angular deviations. To test for deviations equal to zero, a one-sample test was used. The differences between the virtually planned implant and the actual position of the drill path were statistically significant for five SMGs on the eight produced guides, whereas there were no differences for the three others. The mean apical deviation was 3.2 mm ± 1.7 using SMGs, and the angular deviation was measured at 3.10 degrees ± 2.37. Although deviations were observed, the results demonstrate the feasibility and the potential for such guides during EMS procedures.
A Semi-Parallel Active Learning Method Based on Kriging for Structural Reliability Analysis
Authors: Li Zhian , Li Xiao , Li Chen , Ge Jiangqin , Qiu Yi
Published: January 2023

The reliability analysis system is currently evolving, and reliability analysis efforts are also focusing more on correctness and efficiency. The effectiveness of the active learning Kriging metamodel for the investigation of structural system reliability has been demonstrated. In order to effectively predict failure probability, a semi-parallel active learning method based on Kriging (SPAK) is developed in this study. The process creates a novel learning function called UA, which takes the correlation between training points and samples into account. The UA function has been developed from the U function but is distinct from it. The UA function improves the original U function, which pays too much attention to the area near the threshold and the accuracy of the surrogate model is improved. The semi-parallel learning method is then put forth, and it works since UA and U functions are correlated. One or two training points will be added sparingly during the model learning iteration. It effectively lowers the required training points and iteration durations and increases the effectiveness of model building. Finally, three numerical examples and one engineering application are carried out to show the precision and effectiveness of the suggested method. In application, evaluation efficiency is increased by at least 14.5% and iteration efficiency increased by 35.7%. It can be found that the proposed algorithm is valuable for engineering applications.
Analysis of Elastoplastic Mechanical Properties of Non-Uniform Frozen Wall Considering Frost Heave
Authors: Wang Bin , Liang Shenwei , Cao Yi , Rong Chuanxin , Yu Shengmin
Published: January 2023

The aim of this study was to analyze the force and deformation law of an artificial frozen wall. Thus, the frost heave coefficient was introduced to describe the frost heave characteristics, and the frozen wall was regarded as a heterogeneous material whose material properties changed in a parabolic pattern with the radius. The elastoplastic stress and displacement formulas of a non-uniform frozen wall considering frost heave characteristics were derived according to different strength criteria. Consequently, the derived formulas were used to calculate and analyze the mechanical characteristics of the artificial frozen wall. The results showed that the radial stress of the frozen wall changed linearly, whereas the circumferential stress change followed a parabolic pattern after considering the non-uniform characteristics. Moreover, the displacement of the outer edge of the frozen wall was always greater than that of the inner edge, and the displacement of the inner edge changed with the increasing temperature, significantly greater than that of the outer edge. When the frozen wall was in the elastic state, its displacement caused by frost heave was constant. When the frozen wall entered the elastic–plastic state, the displacement of its inner edge caused by frost heave increased with the increase in the radius of the plastic zone, whereas the displacement of the outer edge caused by frost heave decreased with the increase in the radius of the plastic zone.
Bacterial, Archaeal, and Eukaryote Diversity in Planktonic and Sessile Communities Inside an Abandoned and Flooded Iron Mine (Quebec, Canada)
Authors: Lhoste Elise , Comte Francis , Brown Kevin , Delisle Alain , Jaclin David , Ponsin Violaine , Rosabal Maikel , Lazar Cassandre Sara
Published: January 2023

Abandoned and flooded ore mines are examples of hostile environments (cold, dark, oligotrophic, trace metal) with a potential vast diversity of microbial communities rarely characterized. This study aimed to understand the effects of depth, the source of water (surface or groundwater), and abiotic factors on the communities present in the old Forsyth iron mine in Quebec (Canada). Water and biofilm samples from the mine were sampled by a team of technical divers who followed a depth gradient (0 to 183 m deep) to study the planktonic and sessile communities’ diversity and structure. We used 16S/18S rRNA amplicon to characterize the taxonomic diversity of Bacteria, Archaea, and Eukaryotes. Our results show that depth was not a significant factor explaining the difference in community composition observed, but lifestyle (planktonic/sessile) was. We discovered a vast diversity of microbial taxa, with taxa involved in carbon- and sulfur-cycling. Sessile communities seem to be centered on C1-cycling with fungi and heterotrophs likely adapted to heavy-metal stress. Planktonic communities were dominated by ultra-small archaeal and bacterial taxa, highlighting harsh conditions in the mine waters. Microbial source tracking indicated sources of communities from surface to deeper layers and vice versa, suggesting the dispersion of organisms in the mine, although water connectivity remains unknown.
Overview of PM10, PM2.5 and BC and Their Dependent Relationships with Meteorological Variables in an Urban Area in Northwestern Morocco
Authors: Bounakhla Youssef , Benchrif Abdelfettah , Costabile Francesca , Tahri Mounia , El Gourch Bassma , El Hassan El Kafssaoui , Zahry Fatiha , Bounakhla Moussa
Published: January 2023

At an urban site in Kenitra, Morocco, two aerosol size fractions (PM2.5 and PM10) were sampled for four seasons to characterize the seasonal trends of particulate (PM) and carbonaceous (BC) aerosols. An in-depth statistical analysis of the lag-effects of meteorology on collected data was investigated using uni- and multivariate linear regression analyses. The results revealed significant seasonal trends for PM10, PM2.5, and BC. PM concentrations showed the maximum values in autumn (61.4 ± 24.5 µg/m3 for PM10 and 21.2 ± 8.2 µg/m3 for PM2.5), while the minimum was observed in winter (40.2 ± 17.1 µg/m3) for PM10 and in summer (14.3 ± 3.3 µg/m3) for PM2.5. High BC concentrations were recorded in summer (6.3 ± 4.2 μg/m3, on average). The relative humidity 1–2 days earlier showed a higher negative correlation with the PM concentrations (except in winter), and the temperature 1–3 days earlier showed a negative correlation with the PM2.5 in winter and summer and a positive one with the PM10 in autumn. Wind speed was negatively associated with PM10 on the current day in winter and 3 days earlier in summer. However, diverse effects of wind speed on PM2.5 were observed (negative in summer and positive in spring). These results confirm the important role of meteorology in the formation of urban air pollution with pronounced variations in different seasons.
Spatio-Temporal Variation of Carbon Emission Intensity and Spatial Heterogeneity of Influencing Factors in the Yangtze River Delta
Authors: Xu Jianhui , Li Yuanyuan , Hu Feng , Wang Li , Wang Kai , Ma Wenhao , Ruan Ning , Jiang Weizong
Published: January 2023

The Yangtze River Delta plays an important strategic role in China’s economic development pattern, and its carbon emission intensity, which reflects the development of a low-carbon economy, has attracted much attention. From the perspective of the city-level, this study uses the coefficient of variation, spatial autocorrelation and the Multi-scale Geographically Weighted Regression (MGWR) model to study the spatio-temporal characteristics of carbon emission intensity in the Yangtze River Delta from 1997 to 2017 and the spatial heterogeneity of its influencing factors. The results indicated that: (1) the carbon emission intensity in the Yangtze River Delta increased first and then decreased during the sample period, and the number of low-carbon emission intensity zones decreased first and then increased. (2) Through the coefficient of variation analysis, it is known that the ratio of nugget value to base value is much less than 25%, indicating that the correlation between the cities in the Yangtze River Delta is becoming more and more obvious, the spatial difference is becoming smaller, and the integration level is growing higher and higher. (3) The carbon emission intensity of the Yangtze River Delta has a strong positive spatial correlation, and the carbon emission intensity of the Yangtze River Delta decreases from the north to the south. (4) The effect of population size on carbon emission intensity is bidirectional, but the inhibition effect is greater than the promotion effect, and the average regression coefficient is −0.0796; the average regression coefficient of economic development level is 0.3674, and the average regression coefficient of industrial structure is 0.1702, both of which have a positive impact on carbon emission intensity. The degree of urbanization has a bidirectional effect, and the regression coefficient ranges from −0.920 to 0.091, and the negative effect is quite strong. Additionally, each factor has spatial heterogeneity.
Does Public Participation Reduce Regional Carbon Emission?
Authors: Zhang Xin , Yang Yongliang , Li Yi
Published: January 2023

Public participation is playing an increasingly important role in environmental governance. This paper uses panel data from Chinese cities to evaluate the causal relationship between public participation, regional carbon emissions, and regional carbon intensity. We obtain the following conclusions: (1) Public participation significantly reduces regional carbon emissions and regional carbon intensity, which remains robust after a series of robustness and endogeneity discussions. (2) The carbon reduction effect of public participation performs better in eastern regions, regions with higher per capita income, and regions with a concentration of tertiary industries and talents. (3) We divided the public participation into resident participation and environment non-governmental organizations (ENGOs) participation. We found an excellent interactive emission reduction effect with resident participation and a good interaction between resident participation and government and environmental organizations. (4) This paper finds that promoting regional green technology innovation is a significant mechanism for public participation in achieving carbon emission reduction. (5) Finally, this paper found an “inverted U-shaped” non-linear relationship between public participation and regional carbon emissions. The results reveal the importance of public participation in regional carbon emissions and provide an empirical basis for promoting informal environmental regulation.
EEG-Based Person Identification and Authentication Using Deep Convolutional Neural Network
Authors: Alsumari Walaa , Hussain Muhammad , Alshehri Laila , Aboalsamh Hatim A.
Published: January 2023

Using biometric modalities for person recognition is crucial to guard against impostor attacks. Commonly used biometric modalities, such as fingerprint scanners and facial recognition, are effective but can easily be tampered with and deceived. These drawbacks have recently motivated the use of electroencephalography (EEG) as a biometric modality for developing a recognition system with a high level of security. The majority of existing EEG-based recognition methods leverage EEG signals measured either from many channels or over a long temporal window. Both set limits on their usability as part of real-life security systems. Moreover, nearly all available methods use hand-engineered techniques and do not generalize well to unknown data. The few EEG-based recognition methods based on deep learning suffer from an overfitting problem, and a large number of model parameters must be learned from only a small amount of available EEG data. Leveraging recent developments in deep learning, this study addresses these issues and introduces a lightweight convolutional neural network (CNN) model consisting of a small number of learnable parameters that enable the training and evaluation of the CNN model on a small amount of available EEG data. We present a robust and efficient EEG-based recognition system using this CNN model. The system was validated on a public domain benchmark dataset and achieved a rank-1 identification result of 99% and an equal error rate of authentication performance of 0.187%. The system requires only two EEG channels and a signal measured over a short temporal window of 5 s. Consequently, this method can be used in real-life settings to identify or authenticate biometric security systems.
The SQEIRP Mathematical Model for the COVID-19 Epidemic in Thailand
Authors: Jitsinchayakul Sowwanee , Humphries Usa Wannasingha , Khan Amir
Published: January 2023

The spread of COVID-19 started in late December 2019 and is still ongoing. Many countries around the world have faced an outbreak of COVID-19, including Thailand, which must keep an eye on the spread and find a way to deal with this extreme outbreak. Of course, we are unable to determine the number of people who will contract this disease in the future. Therefore, if there is a tool that helps to predict the outbreak and the number of people infected, it will be able to find preventive measures in time. This paper aims to develop a mathematical model suitable for the lifestyle of the Thai population facing the COVID-19 situation. It has been established that after close contact with an infected person, a group of individuals will be quarantined and non-quarantined. If they contract COVID-19, they will enter the incubation period of the infection. The incubation period is divided into the quarantine class and the exposed class. Afterwards, both classes will move to the hospitalized infected class and the infected class, wherein the infected class is able to spread the disease to the surrounding environment. This study describes both classes in the SQEIRP model based on the population segmentation that was previously discussed. After that, the positive and bounded solutions of the model are examined, and we consider the equilibrium point, as well as the global stability of the disease-free point according to the Castillo-Chavez method. The SQEIRP model is then numerically analyzed using MATLAB software version R2022a. The cumulative percentage of hospitalized and non-hospitalized infections after 7 days after the commencement of the infection was determined to be 11 and 34 percent of the entire population, respectively. The Next-Generation Matrix approach was used to calculate the Basic Reproduction Numbers (R0). The SQEIRP model’s R0 was 3.78, indicating that one infected individual can result in approximately three additional infections. The results of this SQEIRP model provide a preliminary guide to identifying trends in population dynamics in each class.
Efficient Battery Models for Performance Studies-Lithium Ion and Nickel Metal Hydride Battery
Authors: Krishnamoorthy Umapathi , Gandhi Ayyavu Parimala , Panchal Hitesh , Shanmugam Dayana , Balasubramani Sukanya , Al-rubaie Ali Jawad , Al-khaykan Ameer , Oza Ankit D. , Hembrom Sagram , Patel Tvarit , Vizureanu Petrica , Burduhos-Nergis Diana-Petronela
Published: January 2023

Apart from being emission-free, electric vehicles enjoy benefits such as low maintenance and operating costs, noise-free, easy to drive, and the convenience of charging at home. All these benefits are directly dependent on the performance of the battery used in the vehicle. In this paper, one-dimensional modeling of Li-ion and NiMH batteries was developed, and their performances were studied. The performance characteristics of the batteries, such as the charging and discharging characteristics, the constituent losses of over-potential voltage, and the electrolyte concentration profile at various stages of charge and discharge cycles, were also studied. It is found that the electrolyte concentration profiles of Li-ion batteries show a drooping behavior at the start of the discharge cycle and a rising behavior at the end of discharge because of the concentration polarization due to the low diffusion coefficient. The electrolyte concentration profiles of NiMH batteries show rising behavior throughout the discharge cycle without any deviations. The reason behind this even behavior throughout the discharge cycle is attributed to the reduced concentration polarization due to electrolyte transport limitations. It is found that the losses associated with the NiMH battery are larger and almost constant throughout the battery’s operation. Whereas for the Li-ion batteries, the losses are less variable. The electrolyte concentration directly affects the overpotential losses incurred during the charging and discharging phases.
Advances in Vanadium-Redoxed Polyanions for High-Voltage Sodium-Ion Batteries
Authors: Wu Honglun , Chen Yiqing , Wen Tianzhuo , Chen Long , Pu Xiangjun , Chen Zhongxue
Published: January 2023

Large-scale energy storage using sodium ion batteries (SIBs) as a hub for the conversion of renewable energy has become a topic of great importance. However, the application of SIBs is hindered by low energy density arising from inferior capacity and operation voltage. In this regard, vanadium-based phosphate polyanions with multiple valence changes (III–V), high redox potential, abundant resources, spacious frame structure, and remarkable thermal stability are promising avenues to address this dilemma. In this review, following the principle of electronic structure and function relationship, we summarize the recent progress in phosphates, pyrophosphates, fluorophosphates, and mixed polyanions of vanadium-centered polyanionic materials for SIBs. This review may provide comprehensive understanding and guidelines to further construct high performance, low-cost sodium-ion batteries.
Emotional State Classification from MUSIC-Based Features of Multichannel EEG Signals
Authors: Hossain Sakib Abrar , Rahman Md. Asadur , Chakrabarty Amitabha , Rashid Mohd Abdur , Kuwana Anna , Kobayashi Haruo
Published: January 2023

Electroencephalogram (EEG)-based emotion recognition is a computationally challenging issue in the field of medical data science that has interesting applications in cognitive state disclosure. Generally, EEG signals are classified from frequency-based features that are often extracted using non-parametric models such as Welch’s power spectral density (PSD). These non-parametric methods are not computationally sound due to having complexity and extended run time. The main purpose of this work is to apply the multiple signal classification (MUSIC) model, a parametric-based frequency-spectrum-estimation technique to extract features from multichannel EEG signals for emotional state classification from the SEED dataset. The main challenge of using MUSIC in EEG feature extraction is to tune its parameters for getting the discriminative features from different classes, which is a significant contribution of this work. Another contribution is to show some flaws of this dataset for the first time that contributed to achieving high classification accuracy in previous research works. This work used MUSIC features to classify three emotional states and achieve 97% accuracy on average using an artificial neural network. The proposed MUSIC model optimizes a 95–96% run time compared with the conventional classical non-parametric technique (Welch’s PSD) for feature extraction.
A Two-Compartment Fermentation System to Quantify Strain-Specific Interactions in Microbial Co-Cultures
Authors: Ulmer Andreas , Veit Stefan , Erdemann Florian , Freund Andreas , Loesch Maren , Teleki Attila , Zeidan Ahmad A. , Takors Ralf
Published: January 2023

To fulfil the growing interest in investigating microbial interactions in co-cultures, a novel two-compartment bioreactor system was developed, characterised, and implemented. The system allowed for the exchange of amino acids and peptides via a polyethersulfone membrane that retained biomass. Further system characterisation revealed a Bodenstein number of 18, which hints at backmixing. Together with other physical settings, the existence of unwanted inner-compartment substrate gradients could be ruled out. Furthermore, the study of Damkoehler numbers indicated that a proper metabolite supply between compartments was enabled. Implementing the two-compartment system (2cs) for growing Streptococcus thermophilus and Lactobacillus delbrueckii subs. bulgaricus, which are microorganisms commonly used in yogurt starter cultures, revealed only a small variance between the one-compartment and two-compartment approaches. The 2cs enabled the quantification of the strain-specific production and consumption rates of amino acids in an interacting S. thermophilus–L. bulgaricus co-culture. Therefore, comparisons between mono- and co-culture performance could be achieved. Both species produce and release amino acids. Only alanine was produced de novo from glucose through potential transaminase activity by L. bulgaricus and consumed by S. thermophilus. Arginine availability in peptides was limited to S. thermophilus’ growth, indicating active biosynthesis and dependency on the proteolytic activity of L. bulgaricus. The application of the 2cs not only opens the door for the quantification of exchange fluxes between microbes but also enables continuous production modes, for example, for targeted evolution studies.
Plant Exosome-like Nanoparticles as Biological Shuttles for Transdermal Drug Delivery
Authors: Wang Ye , Wei Yongsheng , Liao Hui , Fu Hongwei , Yang Xiaobin , Xiang Qi , Zhang Shu
Published: January 2023

Exosomes act as emerging transdermal drug delivery vehicles with high deformability and excellent permeability, which can be used to deliver various small-molecule drugs and macromolecular drugs and increase the transdermal and dermal retention of drugs, improving the local efficacy and drug delivery compliance. At present, there are many studies on the use of plant exosome-like nanoparticles (PELNVs) as drug carriers. In this review, the source, extraction, isolation, and chemical composition of plant exosomes are reviewed, and the research progress on PELNVs as drug delivery systems in transdermal drug delivery systems in recent years has elucidated the broad application prospect of PELNVs.
Effects of Biological Age on Athletic Adaptations to Combined Plyometric and Sprint with Change of Direction with Ball Training in Youth Soccer Players
Authors: Marzouki Hamza , Sbai Samar , Ouergui Ibrahim , Selmi Okba , Andrade Marilia S. , Bouhlel Ezdine , Thuany Mabliny , Weiss Katja , Nikolaidis Pantelis T. , Knechtle Beat
Published: January 2023

There is evidence for the effectiveness of youth combined plyometric and sprint with change of direction (COD) training. However, the evidence is not well-known regarding the in-season effects of biological age (peak height velocity—PHV) on the motor adaptive processes following combined plyometric and COD with ball training (P-CODBT) in youth soccer players. This study aimed to examine the in-season effects of P-CODBT (8 weeks and twice a week) on the athletic performances of male youth soccer players, circa- and post-PHV. In a randomized controlled training study with pre-to-post measurements, forty-eight male players were assigned into two experimental (performing P-CODBT; n = 12 × circa-PHV and n = 12 × post-PHV) and two control groups (CONG; n = 12 × circa-PHV and n = 12 × post-PHV). The pre- and post-training participants were assessed for their anthropometric, linear sprinting with and without a ball, COD speed with and without a ball, vertical jump, dynamic balance, and endurance-intensive performances. After the intervention, the experimental condition induced significant (all p < 0.0001) and small to large effect size (ES = 0.263–3.471) additional gains only on explosive measures compared to CONG. Both the experimental (all p < 0.0001; ES = 0.338–1.908) and control (p = 0.011–0.0001; ES = 0.2–1.8) groups improved their athletic performances over the training period. The improvements generated by p-CODBT were not affected by biological age. In-season short-term P-CODBT (twice a week) could be safe way to generate benefits in explosive performances in youth soccer players, which are relevant components of match-winning actions in soccer.
FK506-Binding Protein 2 Participates in Proinsulin Folding
Authors: Hoefner Carolin , Bryde Tenna Holgersen , Pihl Celina , Tiedemann Sylvia Naiga , Bresson Sophie Emilie , Hotiana Hajira Ahmed , Khilji Muhammad Saad , Santos Theodore Dos , Puglia Michele , Pisano Paola , Majewska Mariola , Durzynska Julia , Klindt Kristian , Klusek Justyna , Perone Marcelo J. , Bucki Robert , Hägglund Per Mårten , Gourdon Pontus Emanuel , Gotfryd Kamil , Urbaniak Edyta , Borowiak Malgorzata , Wierer Michael , MacDonald Patrick Edward , Mandrup-Poulsen Thomas , Marzec Michal Tomasz
Published: January 2023

Apart from chaperoning, disulfide bond formation, and downstream processing, the molecular sequence of proinsulin folding is not completely understood. Proinsulin requires proline isomerization for correct folding. Since FK506-binding protein 2 (FKBP2) is an ER-resident proline isomerase, we hypothesized that FKBP2 contributes to proinsulin folding. We found that FKBP2 co-immunoprecipitated with proinsulin and its chaperone GRP94 and that inhibition of FKBP2 expression increased proinsulin turnover with reduced intracellular proinsulin and insulin levels. This phenotype was accompanied by an increased proinsulin secretion and the formation of proinsulin high-molecular-weight complexes, a sign of proinsulin misfolding. FKBP2 knockout in pancreatic β-cells increased apoptosis without detectable up-regulation of ER stress response genes. Interestingly, FKBP2 mRNA was overexpressed in β-cells from pancreatic islets of T2D patients. Based on molecular modeling and an in vitro enzymatic assay, we suggest that proline at position 28 of the proinsulin B-chain (P28) is the substrate of FKBP2’s isomerization activity. We propose that this isomerization step catalyzed by FKBP2 is an essential sequence required for correct proinsulin folding.
Effect of Hydrogen Oxide-Induced Oxidative Stress on Bone Formation in the Early Embryonic Development Stage of Chicken
Authors: Tompkins Yuguo , Liu Guanchen , Marshall Brett , Sharma Milan Kumar , Kim Woo Kyun
Published: January 2023

The current study aimed to monitor the impact of H2O2-induced oxidative stress on avian bone formation during the early stage of embryonic development. Fertilized Cobb broiler eggs were divided into five treatment groups and micro-injected with varying concentrations of H2O2, i.e., control (PBS; 0 nM), 10 nM, 30 nM, 100 nM, and 300 nM, on embryonic day 3, with continued incubation thereafter. The treatment concentrations were selected based on the level of lipid peroxidation and the survival rate of embryo. Embryos were collected at 6 h, 24 h, 48 h, and 72 h post-injection. The mRNA expression levels of apoptotic markers, antioxidant enzymes, and early bone formation gene markers were measured. The results showed that the microinjection of H2O2 altered the expression pattern of antioxidant enzymes’ mRNA during early embryogenesis and decreased the expression of COL1A2 and COL2A1 at 6 h and 24 h post-injection. Decreased expression of BMP, BGLAP, and RUNX2 was observed 48 h post-injection. Additionally, a shorter embryo length was observed in the 100 nM and 300 nM H2O2 treatment groups 72 h post-injection. In conclusion, H2O2-induced oxidative stress suppressed the expression of bone formation gene markers, with chronic effects on avian embryonic development.
Advances and Challenges in Spatial Transcriptomics for Developmental Biology
Authors: Choe Kyongho , Pak Unil , Pang Yu , Hao Wanjun , Yang Xiuqin
Published: January 2023

Development from single cells to multicellular tissues and organs involves more than just the exact replication of cells, which is known as differentiation. The primary focus of research into the mechanism of differentiation has been differences in gene expression profiles between individual cells. However, it has predominantly been conducted at low throughput and bulk levels, challenging the efforts to understand molecular mechanisms of differentiation during the developmental process in animals and humans. During the last decades, rapid methodological advancements in genomics facilitated the ability to study developmental processes at a genome-wide level and finer resolution. Particularly, sequencing transcriptomes at single-cell resolution, enabled by single-cell RNA-sequencing (scRNA-seq), was a breath-taking innovation, allowing scientists to gain a better understanding of differentiation and cell lineage during the developmental process. However, single-cell isolation during scRNA-seq results in the loss of the spatial information of individual cells and consequently limits our understanding of the specific functions of the cells performed by different spatial regions of tissues or organs. This greatly encourages the emergence of the spatial transcriptomic discipline and tools. Here, we summarize the recent application of scRNA-seq and spatial transcriptomic tools for developmental biology. We also discuss the limitations of current spatial transcriptomic tools and approaches, as well as possible solutions and future prospects.
Pollen Coat Proteomes of Arabidopsis thaliana, Arabidopsis lyrata, and Brassica oleracea Reveal Remarkable Diversity of Small Cysteine-Rich Proteins at the Pollen-Stigma Interface
Authors: Wang Ludi , Lau Yui-Leung , Fan Lian , Bosch Maurice , Doughty James
Published: January 2023

The pollen coat is the outermost domain of the pollen grain and is largely derived from the anther tapetum, which is a secretory tissue that degenerates late in pollen development. By being localised at the interface of the pollen–stigma interaction, the pollen coat plays a central role in mediating early pollination events, including molecular recognition. Amongst species of the Brassicaceae, a growing body of data has revealed that the pollen coat carries a range of proteins, with a number of small cysteine-rich proteins (CRPs) being identified as important regulators of the pollen–stigma interaction. By utilising a state-of-the-art liquid chromatography/tandem mass spectrometry (LC-MS/MS) approach, rich pollen coat proteomic profiles were obtained for Arabidopsis thaliana, Arabidopsis lyrata, and Brassica oleracea, which greatly extended previous datasets. All three proteomes revealed a strikingly large number of small CRPs that were not previously reported as pollen coat components. The profiling also uncovered a wide range of other protein families, many of which were enriched in the pollen coat proteomes and had functions associated with signal transduction, cell walls, lipid metabolism and defence. These proteomes provide an excellent source of molecular targets for future investigations into the pollen–stigma interaction and its potential evolutionary links to plant–pathogen interactions.
Isolation and Characterization of the Arapaima gigas Growth Hormone (ag-GH) cDNA and Three-Dimensional Modeling of This Hormone in Comparison with the Human Hormone (hGH)
Authors: Lima Eliana Rosa , Freire Renan Passos , Suzuki Miriam Fussae , Oliveira João Ezequiel , Yosidaki Vanessa Luna , Peroni Cibele Nunes , Sevilhano Thaís , Zorzeto Moisés , Torati Lucas Simon , Soares Carlos Roberto Jorge , Lima Igor Daniel de Miranda , Kronenberger Thales , Maltarollo Vinicius Gonçalves , Bartolini Paolo
Published: January 2023

In a previous work, the common gonadotrophic hormone α-subunit (ag-GTHα), the ag-FSH β- and ag-LH β-subunit cDNAs, were isolated and characterized by our research group from A. gigas pituitaries, while a preliminary synthesis of ag-FSH was also carried out in human embryonic kidney 293 (HEK293) cells. In the present work, the cDNA sequence encoding the ag-growth hormone (ag-GH) has also been isolated from the same giant Arapaimidae Amazonian fish. The ag-GH consists of 208 amino acids with a putative 23 amino acid signal peptide and a 185 amino acid mature peptide. The highest identity, based on the amino acid sequences, was found with the Elopiformes (82.0%), followed by Anguilliformes (79.7%) and Acipenseriformes (74.5%). The identity with the corresponding human GH (hGH) amino acid sequence is remarkable (44.8%), and the two disulfide bonds present in both sequences were perfectly conserved. Three-dimensional (3D) models of ag-GH, in comparison with hGH, were generated using the threading modeling method followed by molecular dynamics. Our simulations suggest that the two proteins have similar structural properties without major conformational changes under the simulated conditions, even though they are separated from each other by a >100 Myr evolutionary period (1 Myr = 1 million years). The sequence found will be used for the biotechnological synthesis of ag-GH while the ag-GH cDNA obtained will be utilized for preliminary Gene Therapy studies.
The Challenges and Prospects of p53-Based Therapies in Ovarian Cancer
Authors: Wallis Bryce , Bowman Katherine Redd , Lu Phong , Lim Carol S.
Published: January 2023

It has been well established that mutations in the tumor suppressor gene, p53, occur readily in a vast majority of cancer tumors, including ovarian cancer. Typically diagnosed in stages three or four, ovarian cancer is the fifth leading cause of death in women, despite accounting for only 2.5% of all female malignancies. The overall 5-year survival rate for ovarian cancer is around 47%; however, this drops to an abysmal 29% for the most common type of ovarian cancer, high-grade serous ovarian carcinoma (HGSOC). HGSOC has upwards of 96% of cases expressing mutations in p53. Therefore, wild-type (WT) p53 and p53-based therapies have been explored as treatment options via a plethora of drug delivery vehicles including nanoparticles, viruses, polymers, and liposomes. However, previous p53 therapeutics have faced many challenges, which have resulted in their limited translational success to date. This review highlights a selection of these historical p53-targeted therapeutics for ovarian cancer, why they failed, and what the future could hold for a new generation of this class of therapies.
Inflammation Regulation by Bacterial Molecular Patterns
Authors: Guryanova Svetlana V. , Kataeva Anastasiya
Published: January 2023

Stimulation of innate immunity by bacterial molecular patterns can induce an enhanced cellular immune response to pathogens that are associated with innate immune memory shaped by epigenetic changes. Immunological memory can be expressed in the acceleration/intensification of inflammation, as well as in the exact opposite—to maintain tolerance and non-response to a repeated stimulus. Tolerance is one of the central concepts of immunity and is ensured by the consistency of all parts of the immune response. The severe consequences of inflammation force researchers to study in detail all stages of the downstream pathways that are activated after exposure to a stimulus, while the formation of non-response to a pro-inflammatory stimulus has not yet received a detailed description. Elucidation of the mechanism of tolerance is an urgent task for the prevention and treatment of inflammatory diseases. The aim of this investigation was to study the dynamic changes in the gene expression of A20 and ATF3, the inflammation suppressors, against the background of the expression of the genes of the innate immunity receptors TLR4 and NOD2 and the pro-inflammatory cytokine TNF-α under the influence of TLR4 and NOD2 agonists, lipopolysaccharide (LPS) and glucosaminylmuramyl dipeptide (GMDP). The mechanism of inflammation regulation by bioregulators of bacterial origin—LPS and GMDP—was evaluated in vitro in human peripheral blood mononuclear cells and in vivo after i.p. administration of LPS and GMDP to mice. Gene expression was assessed by RT-PCR. Innate immune receptors and the pro-inflammatory cytokine TNF-α were found to develop early in response to LPS and GMDP, both in vitro and in vivo. Genes of cytosolic proteins controlling inflammation (A20 and ATF3) were expressed later. Prior exposure of the innate immune system to LPS and muramyl peptides may modulate host defense against acute inflammation. As a result of the study, new data were obtained on dynamic changes in deubiquitinase A20 and the transcription factor ATF3, which are involved in the limitation and suppression of inflammatory reactions caused by fragments of bacterial cell walls—LPS and GMDP. Thus, bioregulators of bacterial origin LPS and GMDP, along with pro-inflammatory factors, activate the expression of genes that suppress inflammation, which should be considered when analyzing data from studies of the pro-inflammatory properties of LPS and GMDP and when developing drugs based on them.
Computer-Aided Early Melanoma Brain-Tumor Detection Using Deep-Learning Approach
Authors: Asad Rimsha , Rehman Saif ur , Imran Azhar , Li Jianqiang , Almuhaimeed Abdullah , Alzahrani Abdulkareem
Published: January 2023

Brain tumors affect the normal functioning of the brain and if not treated in time these cancerous cells may affect the other tissues, blood vessels, and nerves surrounding these cells. Today, a large population worldwide is affected by the precarious disease of the brain tumor. Healthy tissues of the brain are suspected to be damaged because of tumors that become the most significant reason for a large number of deaths nowadays. Therefore, their early detection is necessary to prevent patients from unfortunate mishaps resulting in loss of lives. The manual detection of brain tumors is a challenging task due to discrepancies in appearance in terms of shape, size, nucleus, etc. As a result, an automatic system is required for the early detection of brain tumors. In this paper, the detection of tumors in brain cells is carried out using a deep convolutional neural network with stochastic gradient descent (SGD) optimization algorithm. The multi-classification of brain tumors is performed using the ResNet-50 model and evaluated on the public Kaggle brain-tumor dataset. The method achieved 99.82% and 99.5% training and testing accuracy, respectively. The experimental result indicates that the proposed model outperformed baseline methods, and provides a compelling reason to be applied to other diseases.
A Mitochondrion-Targeting Protein (B2) Primes ROS/Nrf2-Mediated Stress Signals, Triggering Apoptosis and Necroptosis in Lung Cancer
Authors: Chiu Hsuan-Wen , Hung Shao-Wen , Chiu Ching-Feng , Hong Jiann-Ruey
Published: January 2023

The betanodavirus B2 protein targets mitochondria and triggers mitochondrion-mediated cell death signaling in lung cancer cells; however, its molecular mechanism remains unknown. In this study, we observed that B2 triggers hydrogen peroxide/Nrf2-involved stress signals in the dynamic regulation of non-small lung cancer cell (NSCLC)-programmed cell death. Here, the B2 protein works as a necrotic inducer that triggers lung cancer death via p53 upregulation and RIP3 expression, suggesting a new perspective on lung cancer therapy. We employed the B2 protein to target A549 lung cancer cells and solid tumors in NOD/SCID mice. Tumors were collected and processed for the hematoxylin and eosin staining of tissue and cell sections, and their sera were used for blood biochemistry analysis. We observed that B2 killed an A549 cell-induced solid tumor in NOD/SCID mice; however, the mutant ΔB2 did not. In NOD/SCID mice, B2 (but not ΔB2) induced both p53/Bax-mediated apoptosis and RIPK3-mediated necroptosis. Finally, immunochemistry analysis showed hydrogen peroxide /p38/Nrf2 stress strongly inhibited the production of tumor markers CD133, Thy1, and napsin, which correlate with migration and invasion in cancer cells. This B2-triggered, ROS/Nrf2-mediated stress signal triggered multiple signals via pathways that killed A549 lung cancer tumor cells in vivo. Our results provide novel insight into lung cancer management and drug therapy.
Sesamin Attenuates VEGFA-Induced Angiogenesis via Inhibition of Src and FAK Signaling in Chick Chorioallantoic Membrane Model and Human Endothelial EA.hy926 Cells
Authors: Keratibumrungpong Tanyaporn , Srisuthtayanont Warunee , Wanachewin Orawan , Klangjorhor Jeerawan , Phitak Thanyaluck , Pothacharoen Peraphan , Shwe Thuzar Hla , Kongtawelert Prachya
Published: January 2023

Sesamin, a major phytochemical in sesame seeds and oil, has been reported to have effects on physiological and pathological angiogenesis in several studies. Nevertheless, the underlying mechanisms of sesamin’s effect on angiogenesis are not understood well enough. This study aimed to investigate its effect on both physiological and pathological angiogenesis using the in vivo chick chorioallantoic membrane (CAM) model and the in vitro human endothelial cell line, EA.hy926, model. Sesamin inhibited the VEGFA-induced pathological angiogenesis significantly, although no effect was seen on angiogenesis without induction. It reduced the formation of vascular branches in the VEGFA-treated CAMs and also the proliferation and migration of EA.hy926 endothelial cells induced by VEGFA. Sesamin impeded the VEGF-mediated activation of Src and FAK signaling proteins, which may be responsible for sesamin-mediated reduction of pathological angiogenesis. Moreover, the effect of sesamin on the expressions of angiogenesis-related genes was then investigated and it was found that both mRNA and protein expressions of Notch1, the key pathway in vascular development, induced by VEGFA, were significantly reduced by sesamin. Our results altogether suggested that sesamin, by inhibiting pathological angiogenesis, has the potential to be employed in the prevention or treatment of diseases with over-angiogenesis, such as cancers.
Cancer Stem Cell Relationship with Pro-Tumoral Inflammatory Microenvironment
Authors: Sipos Ferenc , Műzes Györgyi
Published: January 2023

Inflammatory processes and cancer stem cells (CSCs) are increasingly recognized as factors in the development of tumors. Emerging evidence indicates that CSCs are associated with cancer properties such as metastasis, treatment resistance, and disease recurrence. However, the precise interaction between CSCs and the immune microenvironment remains unexplored. Although evasion of the immune system by CSCs has been extensively studied, new research demonstrates that CSCs can also control and even profit from the immune response. This review provides an overview of the reciprocal interplay between CSCs and tumor-infiltrating immune cells, collecting pertinent data about how CSCs stimulate leukocyte reprogramming, resulting in pro-tumor immune cells that promote metastasis, chemoresistance, tumorigenicity, and even a rise in the number of CSCs. Tumor-associated macrophages, neutrophils, Th17 and regulatory T cells, mesenchymal stem cells, and cancer-associated fibroblasts, as well as the signaling pathways involved in these pro-tumor activities, are among the immune cells studied. Although cytotoxic leukocytes have the potential to eliminate CSCs, immune evasion mechanisms in CSCs and their clinical implications are also known. We intended to compile experimental findings that provide direct evidence of interactions between CSCs and the immune system and CSCs and the inflammatory milieu. In addition, we aimed to summarize key concepts in order to comprehend the cross-talk between CSCs and the tumor microenvironment as a crucial process for the effective design of anti-CSC therapies.