bluuebunny/crossref_metadata_2025 huggingface dataset:
Differences Evaluation of Pavement Roughness Distribution Based on Light Detection and Ranging Data
Authors: Gao Qian , Fan Lei , Wei Siyu , Li Yishun , Du Yuchuan , Liu Chenglong
Published: July 2023

Pavement roughness serves as a crucial indicator for evaluating road performance. However, traditional measurement methods, such as laser detection vehicles, are limited to providing roughness values for a single profile, failing to capture the overall pavement condition comprehensively. To address this limitation, this study utilized high-precision light detection and ranging technology (LiDAR) to acquire three-dimensional point cloud data for a 25 km road section in Shanghai. Road elevations were extracted from different lateral survey lines. Subsequently, variance analysis and the Kruskal–Wallis non-parametric test were conducted to evaluate the differences in the lateral distribution and longitudinal variability of the pavement roughness. The findings revealed significant differences in the international roughness index (IRI) among the survey lines within the road section. Moreover, the observed variations in the lateral distribution of pavement roughness were influenced by the characteristics of the road section itself. Roads exhibiting discrete roughness patterns displayed a higher likelihood of significant detection disparities. Additionally, it was discovered that the discrepancy between the detection length and the actual road length introduced volatility in repeated detection results, necessitating a limitation of this discrepancy to 30 m. Consequently, it has been recommended to consider the lateral distribution of pavement roughness and to regulate the detection length in road performance evaluations to enhance reliability and facilitate more accurate maintenance decision making. The study highlights the importance of incorporating comprehensive assessment approaches for pavement roughness in road management practices.
C-MWCAR: Classification Based on Multiple Weighted Class Association Rules
Authors: Li Gui , Liu Fan , Wu Cheng , Yao Yuan , Wu Guangxin , Wang Zhu , Zhang Yanchun
Published: July 2023

Classification is a very important task in data mining and pattern analysis, which have been widely used to solve various real-world problems. To obtain better classification performance, in this paper, we propose a novel classification framework based on multiple weighted class association rules (C-MWCAR), whose key idea is to transform the association among features into a set of class association rules (CARs), then classify unknown instances based on the CARs obtained. Concretely, C-MWCAR consists of a dictionary order-based CAR mining algorithm (DOCMA), a branch-based CAR selection algorithm (BCSA), and a multiple weighted CARs-based classifier (MWCC). Specifically, DOCMA mines the complete set of CARs, from which BCSA further selects a representative and concise set of CARs based on the distribution, coverage, and redundancy of the mined CARs. When classifying an unknown instance, MWCC picks out a set of CARs that are most similar to the given instance and computes the weighted importance of those CARs. Finally, the class label of the given instance will be determined by the similarities between the instance and the CARs and the weighted importance of the CARs. Furthermore, we apply the proposed C-MWCAR to a real-world classification task, i.e., hypertension diagnosis, based on a real dataset of 128 subjects. Experimental results indicate that C-MWCAR outperforms four baseline methods and achieves 93.3%, 93.8%, and 92.7% in terms of accuracy, sensitivity, and specificity, respectively.
Dental Surface Conditioning Techniques to Increase the Micromechanical Retention to Fiberglass Posts: A Literature Review
Authors: Moreno-Sánchez Paulina Leticia , Ramírez-Álvarez Maricela , Ayala-Ham Alfredo del Rosario , Silva-Benítez Erika de Lourdes , Casillas-Santana Miguel Ángel , Leyva del Rio Diana , Espinosa-Cristóbal León Francisco , Lizárraga-Verdugo Erik , Avendaño-Félix Mariana Melisa , Soto-Sainz Jesús Eduardo
Published: July 2023

Glass fiber posts (GFP) have an elastic modulus that shares structural characteristics with dentin. Ineffective removal of the smear layer (SL) in the root canal after post space preparation reduces resin tag formation, compromising an efficient hybrid layer formation leading to a subsequent debonding. In this sense, this review article focuses on the published literature related to dentin conditioning for GFP placement with the use of acidic solutions such as EDTA, citric and maleic acid or prefabricated conditioning solutions such as MTAD and QMix, both with/without activation by sonic or laser devices, analyzed by scanning electron microscopy (SEM) and/or push- out bond strength (POBS) test. The collected information suggested that the conditioning agent that showed better results for dentin conditioning increasing the bond strength of the GFP to the root canal is 17% EDTA without activation.
An Evolutionary Neural Network Approach for Slopes Stability Assessment
Authors: Tinoco Joaquim , Gomes Correia António , Cortez Paulo , Toll David
Published: July 2023

A current big challenge for developed or developing countries is how to keep large-scale transportation infrastructure networks operational under all conditions. Network extensions and budgetary constraints for maintenance purposes are among the main factors that make transportation network management a non-trivial task. On the other hand, the high number of parameters affecting the stability condition of engineered slopes makes their assessment even more complex and difficult to accomplish. Aiming to help achieve the more efficient management of such an important element of modern society, a first attempt at the development of a classification system for rock and soil cuttings, as well as embankments based on visual features, was made in this paper using soft computing algorithms. The achieved results, although interesting, nevertheless have some important limitations to their successful use as auxiliary tools for transportation network management tasks. Accordingly, we carried out new experiments through the combination of modern optimization and soft computing algorithms. Thus, one of the main challenges to overcome is related to the selection of the best set of input features for a feedforward neural network for earthwork hazard category (EHC) identification. We applied a genetic algorithm (GA) for this purpose. Another challenging task is related to the asymmetric distribution of the data (since typically good conditions are much more common than bad ones). To address this question, three training sampling approaches were explored: no resampling, the synthetic minority oversampling technique (SMOTE), and oversampling. Some relevant observations were taken from the optimization process, namely, the identification of which variables are more frequently selected for EHC identification. After finding the most efficient models, a detailed sensitivity analysis was applied over the selected models, allowing us to measure the relative importance of each attribute in EHC identification.
Application of Digital Twin in the Industry of Axial Hollow-Wall Pipes
Authors: Guo Zeyuan , Hu Shaowei , Jin Wencan , Ye Yuxiao , Shan Changxi
Published: July 2023

With the increasing demand for automation in agriculture, more and more researchers are exploring the application of digital twin in agricultural production. However, existing studies have predominantly focused on enhancing resource utilization efficiency and improving irrigation control systems in agricultural production through the implementation of digital twins. Unfortunately, there is a noticeable research gap when it comes to applying digital twins specifically to buried water conveyance pipelines within an agricultural irrigation infrastructure. Focusing on the long-term performance requirements of buried pipelines in agricultural irrigation and drainage, this study established a digital twin system for the industry of axial hollow-wall pipes with an outer diameter of 200 mm, specifically designed for this field of operation. The system was used to optimize the end-forming process of axial hollow-wall pipes, resulting in improved leak tightness under internal pressure and angular deflection of the pipes. The study suggests that the most effective method for the end-forming process of axial hollow-wall pipes is to heat the pipe for 60 s at the ambient temperature of 15 °C, with heating temperatures of 225 °C on both the inner and outer sides. Additionally, preheating the stamping equipment to 70 °C and controlling the cooling temperature, during pipe detachment, to between 35 °C and 45 °C is recommended. In terms of the leak tightness under internal pressure and angular deviation, the study found that increasing the thickness of the protruding end of the sealing ring to 16 mm, and shortening the chamfer length to 20 mm, while maintaining the same slope, can enhance the sealing effectiveness of the pipeline interface. The implementation of the digital twin system improves the production efficiency of the hollow pipe production line during the end-forming process, resulting in a yield rate of the pipe of up to 95% for qualified products. Moreover, the system provides intelligent closed-loop feedback which ensures the long-term operation and maintenance of the pipelines, making it easier to identify problems and implement design improvements. By doing so, it contributes to ensuring the long-term stability of related agricultural production.
A Reuse-Oriented Visual Smart Contract Code Generator for Efficient Development of Complex Multi-Party Interaction Scenarios
Authors: Shen Xinzhe , Li Wenyu , Xu Hanchuan , Wang Xiao , Wang Zhongjie
Published: July 2023

Multi-party interaction scenarios usually involve interaction and collaboration between multiple participants, such as business negotiation, teamwork, etc. In multi-party interaction scenarios, trust mechanisms are needed to ensure the use of rights and the fulfillment of obligations. The use of blockchain and smart contracts to establish a decentralized trust mechanism is a solution. The development process of smart contracts may require experts in different fields to design them together, and it is difficult for non-experts to understand smart contract code. The traditional method of smart contract development is for the developer to manually write the smart contract code, which may lead to low development efficiency and the inability of the scene participants to understand the smart contract code. To address this challenge, we propose a reuse-oriented visual smart contract generator to efficiently develop complex multi-party interaction scenarios. This paper proposes a model based on BPMN that uses smart contracts to express the process of multi-party interaction so that the parties in various domains understand the business requirements. Then, a multi-layer reusable library is proposed and used to generate a visual solidity code. We also integrate code compilation, security checking, and deployment into the target blockchain environment for testing. The function of the tool is verified in the case of flight delay insurance, which shows that it can aid the automated development of smart contracts for multi-party interaction scenarios. At the same time, the feasibility of the tool is verified by five cases selected from the literature, which shows that it can aid the development of smart contracts to achieve a high degree of reusability.
Analysis of Selected Production Parameters for the Quality of Pressure Castings as a Tool to Increase Competitiveness
Authors: Ružbarský Juraj , Gašpár Štefan
Published: July 2023

The research conducted in the paper highlights the importance of pressure or holding pressure in the mold cavity as a critical production parameter in the high-pressure die casting process for Al-Si alloys. The experiments revealed a direct correlation between the pressure or holding pressure in the mold cavity and the mechanical properties of the castings, including ultimate tensile strength, percentage share of porosity, and the structure of the alloys. The results of the experiments showed that increasing the pressure or holding pressure in the mold cavity led to an increase in ultimate tensile strength and a reduction in the porosity of the castings. The higher pressure or holding pressure also resulted in the elimination of pores in the casting, which further improved its mechanical properties. The increase in ultimate tensile strength and reduction in porosity can be attributed to the better filling of the mold cavity, leading to reduced air entrapment and porosity in the castings. Overall, this paper emphasizes the need for optimizing the technological parameters of the die casting process to ensure the high-quality and efficient production of castings with reduced defects. The results of this study suggest that controlling the pressure or holding pressure in the mold cavity can significantly improve the mechanical properties of the castings, which is essential for achieving the desired quality standards.
Forgery Detection for Anti-Counterfeiting Patterns Using Deep Single Classifier
Authors: Zheng Hong , Zhou Chengzhuo , Li Xi , Wang Tianyu , You Changhui
Published: July 2023

At present, anti-counterfeiting schemes based on the combination of anti-counterfeiting patterns and two-dimensional codes is a research hotspot in digital anti-counterfeiting technology. However, many existing identification schemes rely on special equipment such as scanners and microscopes; there are few methods for authentication that use smartphones. In particular, the ability to classify blurry pattern images is weak, leading to a low recognition rate when using mobile terminals. In addition, the existing methods need a sufficient number of counterfeit patterns for model training, which is difficult to acquire in practical scenarios. Therefore, an authentication scheme for an anti-counterfeiting pattern captured by smartphones is proposed in this paper, featuring a single classifier consisting of two modules. A feature extraction module based on U-Net extracts the features of the input images; then, the extracted feature is input to a one-class classification module. The second stage features a boundary-optimized OCSVM classification method. The classifier only needs to learn positive samples to achieve effective identification. The experimental results show that the proposed approach has a better ability to distinguish the genuine and counterfeit anti-counterfeiting pattern images. The precision and recall rate of the approach reach 100%, and the recognition rate for the blurry images of the genuine anti-counterfeiting patterns is significantly improved.
Monitoring Hygienic Measures for Decreasing Salmonella Occurrence in Scalding Tank Water of a Turkey Slaughterhouse
Authors: Arispón Francisco , Cano Nazaret , Jordano Rafael , Medina Luis M.
Published: July 2023

The objective of this work was to test different treatments based on the temperature and acidification of scalding tank water throughout the day in a turkey slaughterhouse under industrial conditions in order to decrease the occurrence of Salmonella. After controlling the scalding tank water under usual conditions, the following measures were taken: (a) the temperature was increased to 60 °C and 70 °C for 15 min at the halfway point of the day; (b) the scalding water was acidified and six different initial pH levels were tested. Both measures which were tested (heating and acidification of scalding water) showed efficiency in reducing the occurrence of Salmonella during the scalding step. In order to prevent the disadvantages associated with the hardest measures in each case, we propose that scalding water be heated to 70 °C for 15 min without carcasses, which can be repeated if the disadvantages of the exposed costs and resources of processing are acceptable. Regarding acidification, a suitable measure would be an initial pH of 4.0 or any treatment that keeps the pH of the scalding water below 4.5, using acid that does not affect the final quality of the products and/or the elements involved.
Epidemiology of Injury Complaints in Elite Sprinting Athletes in Athletics (Track and Field)
Authors: Edouard Pascal , Caumeil Benjamin , Giroux Caroline , Bruneau Antoine , Tondut Jeanne , Navarro Laurent , Hanon Christine , Guilhem Gaël , Ruffault Alexis
Published: July 2023

Objective: To describe the epidemiology of injury complaints related to the athletics activity in elite athletics (track and field) athletes practicing disciplines with sprints (i.e., sprints, hurdles, combined events, long jump, and triple jump). Methods: We conducted a cross-sectional study on elite sprinting athletes licensed with the French Federation of Athletics with retrospective data collection of injury complaints related to the athletics activity that occurred during their lifetime athletics activity, allowing the reporting of the injury complaints during the one-year period before the survey and at the time of the survey, using a self-reported online survey system. We calculated the (i) lifetime, (ii) 1 year, and (iii) point (at the time of the survey) prevalence proportion, and we descriptively analyzed the injury complaint characteristics. Results: A total of 302 injury complaints related to the athletics activity were reported by 64 athletes of the 68 included athletes. The lifetime prevalence proportion was 95.6% (95% CI: 90.7 to 100.5%). The 1-year prevalence proportion was 61.8% (95% CI: 50.2 to 73.3%). The point prevalence proportion (at the time of the survey) was 16.2% (95% CI: 7.4 to 24.9%). Almost all injury complaints were located in the lower limb (92.7%) and especially involved the hamstrings (33.4%); the main type involved was the muscle (49.0%), and injury complaints mainly occurred during training and with a sudden mode of onset. The most frequent diagnosis was hamstring muscle injury (31.1%). Conclusions: This study provides new insights specifically in elite sprinting athletes, confirming the injury risk in this population and that the main injury diagnosis was the hamstring muscle injury. Efforts should thus continue to monitor injuries in this population and to develop athletics- and sprinting-specific injury risk reduction strategies.
Atmospheric Pollution in Port Cities
Authors: Owusu-Mfum Shnelle , Hudson Malcolm D. , Osborne Patrick E. , Roberts Toby J. , Zapata-Restrepo Lina M. , Williams Ian D.
Published: July 2023

Authoritative, trustworthy, continual, automatic hourly air quality monitoring is a relatively recent innovation. The task of reliably identifying long-term trends in air quality is therefore very challenging, as well as complex. Ports are major sources of atmospheric pollution, which is linked to marine traffic and increased road traffic congestion. This study investigated the long-term trends and drivers of atmospheric pollution in the port cities of Houston, London, and Southampton in 2000–2019. Authoritative air quality and meteorological data for seven sites at these three locations were meticulously selected alongside available traffic count data. Data were acquired for sites close to the port and sites that were near the city centre to determine whether the port emissions were influencing different parts of the city. Openair software was used for plots and statistical analyses. Pollutant concentrations at Houston, Southampton and Thurrock (London) slowly reduced over time and did not exceed national limits, in contrast to NO2 and PM10 concentrations at London Marylebone Road. Drivers of atmospheric pollution include meteorology, geographical and temporal variation, and traffic flow. Statistically significant relationships (p < 0.001) between atmospheric pollution concentration and meteorology across most sites were found, but this was not seen with traffic flows in London and Southampton. However, port emissions and the other drivers of atmospheric pollution act together to govern the air quality in the city.
Segregation of Fast-Reactive Species in Atmospheric Turbulent Flow
Authors: Brasseur Guy P. , Barth Mary , Kazil Jan , Patton Edward G. , Wang Yuting
Published: July 2023

Atmospheric turbulence, which produces chaotic motions in the planetary boundary layer, can inhibit mixing between fast-reacting species produced or released at different locations. This segregation process modifies the effective rate at which reactions occur between these species and is not appropriately accounted for in coarse-resolution models, since these models assume complete mixing of tracers within each grid box. Here, we present a few examples of large-eddy simulations (LES) applied to chemically reactive species in a forested area with high emissions of biogenic hydrocarbons, an urban area rich in anthropogenic emissions, and a maritime area with high emissions of reduced sulfur species.
Existence, Uniqueness and the Multi-Stability Results for a W-Hilfer Fractional Differential Equation
Authors: Aderyani Safoura Rezaei , Saadati Reza , Rassias Themistocles M. , Srivastava Hari M.
Published: July 2023

In this paper, we apply the well-known aggregation mappings on Mittag-Leffler-type functions to investigating new approximation error estimates of a W-Hilfer fractional differential equation, by a different concept of Ulam-type stability in both bounded and unbounded domains.
Economic and Environmental Viability of Lithium-Ion Battery Recycling—Case Study in Two Canadian Regions with Different Energy Mixes
Authors: Gonzales-Calienes Giovanna , Kannangara Miyuru , Bensebaa Farid
Published: July 2023

Lithium-ion battery (LIB) pack is the core component of electric vehicles (EVs). As the demand is continuously increasing, it puts a lot of strain on the battery raw material supply chains. Likewise, the large quantity of spent LIBs from different sources will add to the complexity of end-of-life (EoL) management. Battery recycling processing is a potential source of critical cathode precursor materials as an alternative to virgin raw material sourcing. Indeed, metal sulfates (nickel, cobalt, and manganese) and lithium carbonate could be recovered through EoL processing. This study aims to provide an economic and environmental life cycle sustainability assessment of recycled battery materials. This assessment is based on a bottom-up approach considering geographical boundaries and process data inputs. The two sources of critical cathode battery materials, virgin and recycled battery materials, are compared based on economic and environmental indicators. This study identified the province of Quebec in Canada as the geographical boundary where several battery processing plants have been recently announced. The best available recycling process (hydrometallurgy) was selected. For the virgin materials, this study considers the option of importing from other jurisdictions by using global average supply chain values. Furthermore, a comparison of alternative supply chain configurations was performed using a spatially differentiated approach. The main findings of this study are as follows: (i) the environmental credit of recycled cathode active materials (CAMs) is estimated as −6.46 kg CO2e/kg CAM, and (ii) the overall cost and environmental impacts of producing LIB cathode active material from recycled battery materials can be 48% and 54% lower than production from virgin materials, respectively, considering the upstream, midstream, and downstream stages of the CAM supply chain. The main drivers for the reduction in these financial costs and emissions are the local transportation and the hydrometallurgical process. The assessment results provide insights to support the development of appropriate policies and R&D solutions adapted to local considerations as well as offer additional possibilities to improve the design of sustainable supply chains for LIB recycling.
Predicting Recurrence in Pancreatic Ductal Adenocarcinoma after Radical Surgery Using an AX-Unet Pancreas Segmentation Model and Dynamic Nomogram
Authors: Ni Haixu , Zhou Gonghai , Chen Xinlong , Ren Jing , Yang Minqiang , Zhang Yuhong , Zhang Qiyu , Zhang Lei , Mao Chengsheng , Li Xun
Published: July 2023

This study aims to investigate the reliability of radiomic features extracted from contrast-enhanced computer tomography (CT) by AX-Unet, a pancreas segmentation model, to analyse the recurrence of pancreatic ductal adenocarcinoma (PDAC) after radical surgery. In this study, we trained an AX-Unet model to extract the radiomic features from preoperative contrast-enhanced CT images on a training set of 205 PDAC patients. Then we evaluated the segmentation ability of AX-Unet and the relationship between radiomic features and clinical characteristics on an independent testing set of 64 patients with clear prognoses. The lasso regression analysis was used to screen for variables of interest affecting patients’ post-operative recurrence, and the Cox proportional risk model regression analysis was used to screen for risk factors and create a nomogram prediction model. The proposed model achieved an accuracy of 85.9% for pancreas segmentation, meeting the requirements of most clinical applications. Radiomic features were found to be significantly correlated with clinical characteristics such as lymph node metastasis, resectability status, and abnormally elevated serum carbohydrate antigen 19-9 (CA 19-9) levels. Specifically, variance and entropy were associated with the recurrence rate (p < 0.05). The AUC for the nomogram predicting whether the patient recurred after surgery was 0.92 (95% CI: 0.78–0.99) and the C index was 0.62 (95% CI: 0.48–0.78). The AX-Unet pancreas segmentation model shows promise in analysing recurrence risk factors after radical surgery for PDAC. Additionally, our findings suggest that a dynamic nomogram model based on AX-Unet can provide pancreatic oncologists with more accurate prognostic assessments for their patients.
Exploring the Impact of Herbal Therapies on COVID-19 and Influenza: Investigating Novel Delivery Mechanisms for Emerging Interventions
Authors: Fornari Laurindo Lucas , Taynara Marton Ledyane , Minniti Giulia , Dogani Rodrigues Victória , Buzinaro Suzuki Rodrigo , Maria Cavallari Strozze Catharin Virgínia , Joshi Rakesh Kumar , Barbalho Sandra Maria
Published: July 2023

Synthetic antivirals and corticosteroids have been used to treat both influenza and the SARS-CoV-2 disease named COVID-19. However, these medications are not always effective, produce several adverse effects, and are associated with high costs. Medicinal plants and their constituents act on several different targets and signaling pathways involved in the pathophysiology of influenza and COVID-19. This study aimed to perform a review to evaluate the effects of medicinal plants on influenza and COVID-19, and to investigate the potential delivery systems for new antiviral therapies. EMBASE, PubMed, GOOGLE SCHOLAR, and COCHRANE databases were searched. The studies included in this review showed that medicinal plants, in different formulations, can help to decrease viral spread and the time until full recovery. Plants reduced the incidence of acute respiratory syndromes and the symptom scores of the illnesses. Moreover, plants are related to few adverse effects and have low costs. In addition to their significance as natural antiviral agents, medicinal plants and their bioactive compounds may exhibit low bioavailability. This highlights the need for alternative delivery systems, such as metal nanoparticles, which can effectively transport these compounds to infected tissues.
Vaccination against Epstein–Barr Latent Membrane Protein 1 Protects against an Epstein–Barr Virus-Associated B Cell Model of Lymphoma
Authors: Soo Hoo Wesley I. , Higa Kaylie , McCormick Alison A.
Published: July 2023

In this study, we demonstrate that expression of viral latent membrane protein 1 (LMP1) in a mouse B cell line renders the animals responsive to protection from a 38C13-LMP1 tumor challenge with a novel vaccine. The Epstein–Barr virus (EBV) preferentially infects circulating B lymphocytes, has oncogenic potential, and is associated with a wide variety of B cell lymphomas. EBV is ectotrophic to human cells, and currently there are no B cell animal models of EBV-associated lymphoma that can be used to investigate vaccine immunotherapy. Since most EBV-infected human tumor cells express latent membrane protein 1 (LMP1) on their surface, this viral antigen was tested as a potential target for an anticancer vaccine in a mouse model. Here, we describe a new mouse model of LMP1-expressing B cell lymphoma produced with plasmid transduction of 38C13 into mouse B cells. The expression of LMP-1 was confirmed with a western blot analysis and immunocytochemistry. We then designed a novel LMP1 vaccine, by fusing viral antigen LMP1 surface loop epitopes to the surface of a viral antigen carrier, the Tobacco Mosaic virus (TMV). Vaccinated mice produced high titer antibodies against the TMV-LMP1 vaccine; however, cellular responses were at the baseline, as measured with IFNγ ELISpot. Despite this, the vaccine showed significant protection from a 38C13-LMP1 tumor challenge. To provide additional immune targets, we compared TMV-LMP1 peptide immunization with DNA immunization with the full-length LMP1 gene. Anti-LMP1 antibodies were significantly higher in TMV-LMP1-vaccinated mice compared to the DNA-immunized mice, but, as predicted, DNA-vaccinated mice had improved cellular responses using IFNγ ELISpot. Surprisingly, the TMV-LMP1 vaccine provided protection from a 38C13-LMP1 tumor challenge, while the DNA vaccine did not. Thus, we demonstrated that LMP1 expression in a mouse B cell line is responsive to antibody immunotherapy that may be applied to EBV-associated disease.
Gender Differences in the Pathogenesis and Risk Factors of Hepatocellular Carcinoma
Authors: Nevola Riccardo , Tortorella Giovanni , Rosato Valerio , Rinaldi Luca , Imbriani Simona , Perillo Pasquale , Mastrocinque Davide , La Montagna Marco , Russo Antonio , Di Lorenzo Giovanni , Alfano Maria , Rocco Maria , Ricozzi Carmen , Gjeloshi Klodian , Sasso Ferdinando Carlo , Marfella Raffaele , Marrone Aldo , Kondili Loreta Anesti , Esposito Nicolino , Claar Ernesto , Cozzolino Domenico
Published: July 2023

Several chronic liver diseases are characterized by a clear gender disparity. Among them, hepatocellular carcinoma (HCC) shows significantly higher incidence rates in men than in women. The different epidemiological distribution of risk factors for liver disease and HCC only partially accounts for these gender differences. In fact, the liver is an organ with recognized sexual dysmorphism and is extremely sensitive to the action of androgens and estrogens. Sex hormones act by modulating the risk of developing HCC and influencing its aggressiveness, response to treatments, and prognosis. Furthermore, androgens and estrogens are able to modulate the action of other factors and cofactors of liver damage (e.g., chronic HBV infection, obesity), significantly influencing their carcinogenic power. The purpose of this review is to examine the factors related to the different gender distribution in the incidence of HCC as well as the pathophysiological mechanisms involved, with particular reference to the central role played by sex hormones.
Comparative Methods for Quantification of Sulfate-Reducing Bacteria in Environmental and Engineered Sludge Samples
Authors: Zambrano-Romero Aracely , Ramirez-Villacis Dario X. , Barriga-Medina Noelia , Sierra-Alvarez Reyes , Trueba Gabriel , Ochoa-Herrera Valeria , Leon-Reyes Antonio
Published: July 2023

This study aimed to compare microscopic counting, culture, and quantitative or real-time PCR (qPCR) to quantify sulfate-reducing bacteria in environmental and engineered sludge samples. Four sets of primers that amplified the dsrA and apsA gene encoding the two key enzymes of the sulfate-reduction pathway were initially tested. qPCR standard curves were constructed using genomic DNA from an SRB suspension and dilutions of an enriched sulfate-reducing sludge. According to specificity and reproducibility, the DSR1F/RH3-dsr-R primer set ensured a good quantification based on dsrA gene amplification; however, it exhibited inconsistencies at low and high levels of SRB concentrations in environmental and sulfate-reducing sludge samples. Ultimately, we conducted a qPCR method normalized to dsrA gene copies, using a synthetic double-stranded DNA fragment as a calibrator. This method fulfilled all validation criteria and proved to be specific, accurate, and precise. The enumeration of metabolically active SRB populations through culture methods differed from dsrA gene copies but showed a plausible positive correlation. Conversely, microscopic counting had limitations due to distinguishing densely clustered organisms, impacting precision. Hence, this study proves that a qPCR-based method optimized with dsrA gene copies as a calibrator is a sensitive molecular tool for the absolute enumeration of SRB populations in engineered and environmental sludge samples.
Biodiversity of Endophytic Microbes in Diverse Tea Chrysanthemum Cultivars and Their Potential Promoting Effects on Plant Growth and Quality
Authors: Sun Tong , Yang Yanrong , Duan Kuolin , Liao Yuan , Zhang Zhi , Guan Zhiyong , Chen Sumei , Fang Weimin , Chen Fadi , Zhao Shuang
Published: July 2023

The endophytic microbiomes significantly differed across tea chrysanthemum cultivars and organs (stems and leaves). The most abundant endophytic bacterial genera were Pseudomonas, Masillia, and Enterobacter in the leaves and Sphingomonas and Curtobacterium in the stems of the five cultivars. Meanwhile, the most abundant endophytic fungal genera in the leaves and stems of the five tea chrysanthemums were Alternaria, Cladosporium, and Sporobolomyces. Specifically, Rhodotorula was dominant in the leaves of ‘Jinsi huangjv’ and Paraphoma was dominant in the stems of ‘Jinsi huangjv’. In all cultivars, the diversity and richness of endophytic bacteria were higher in leaves than in stems (p < 0.05). The highest diversity and richness of endophytic bacteria were recorded in ‘Chujv’, followed by ‘Jinsi huangjv’, ‘Fubai jv’, ‘Nannong jinjv’, and ‘Hangbai jv’. Meanwhile, endophytic fungi were less pronounced. Twenty-seven and 15 cultivable endophytic bacteria and fungi were isolated, four isolated endophytic bacteria, namely, CJY1 (Bacillus oryzaecorticis), CY2 (Pseudomonas psychrotolerans), JSJ7, and JSJ17 (Enterobacter cloacae) showed higher indole acetic acid production ability. Further field studies indicated that inoculation of these four endophytic bacteria not only promoted plant growth and yield but also increased total flavonoids, chlorogenic acid, luteolin, and 3,5-dicoffeylquinic acid levels in the dry flowers of tea chrysanthemums.
An Insight into Occurrence, Biology, and Pathogenesis of Rice Root-Knot Nematode Meloidogyne graminicola
Authors: Arun Arunachalam , Shanthi Annaiyan , Raveendran Muthurajan , Seenivasan Nagachandrabose , Pushpam Ramamoorthy , Shandeep Ganeshan
Published: July 2023

Rice (Oryza sativa L.) is one of the most widely grown crops in the world, and is a staple food for more than half of the global total population. Root-knot nematodes (RKNs), Meloidogyne spp., and especially M. graminicola, seem to be significant rice pests, which makes them the most economically important plant-parasitic nematode in this crop. RKNs develop a feeding site in galls by causing host cells to differentiate into hypertrophied, multinucleate, metabolically active cells known as giant cells. This grazing framework gives the nematode a constant food source, permitting it to develop into a fecund female and complete its life cycle inside the host root. M. graminicola effector proteins involved in nematode parasitism, including pioneer genes, were functionally characterized in earlier studies. Molecular modelling and docking studies were performed on Meloidogyne graminicola protein targets, such as β-1,4-endoglucanase, pectate lyase, phospholipase B-like protein, and G protein-coupled receptor kinase, to understand the binding affinity of Beta-D-Galacturonic Acid, 2,6,10,15,19,23-hexamethyltetracosane, (2S)-2-amino-3-phenylpropanoic acid, and 4-O-Beta-D-Galactopyranosyl-Alpha-D-Glucopyranose against ligand molecules of rice. This study discovered important molecular aspects of plant–nematode interaction and candidate effector proteins that were regulated by M. graminicola-infected rice plants. To the best of our knowledge, this is the first study to describe M. graminicola’s molecular adaptation to host parasitism.
Gene Expression and Drug Sensitivity Analysis of Mitochondrial Chaperones Reveals That HSPD1 and TRAP1 Expression Correlates with Sensitivity to Inhibitors of DNA Replication and Mitosis
Authors: Badarni Mai , Gabbay Shani , Elkabets Moshe , Rotblat Barak
Published: July 2023

Mitochondria—critical metabolic hubs in eukaryotic cells—are involved in a wide range of cellular functions, including differentiation, proliferation, and death. Mitochondria import most of their proteins from the cytosol in a linear form, after which they are folded by mitochondrial chaperones. However, despite extensive research, the extent to which the function of particular chaperones is essential for maintaining specific mitochondrial and cellular functions remains unknown. In particular, it is not known whether mitochondrial chaperones influence the sensitivity to drugs used in the treatment of cancers. By mining gene expression and drug sensitivity data for cancer cell lines from publicly available databases, we identified mitochondrial chaperones whose expression is associated with sensitivity to oncology drugs targeting particular cellular pathways in a cancer-type-dependent manner. Importantly, we found the expression of TRAP1 and HSPD1 to be associated with sensitivity to inhibitors of DNA replication and mitosis. We confirmed experimentally that the expression of HSPD1 is associated with an increased sensitivity of ovarian cancer cells to drugs targeting mitosis and a reduced sensitivity to drugs promoting apoptosis. Taken together, our results support a model in which particular mitochondrial pathways hinge upon specific mitochondrial chaperones and provide the basis for understanding selectivity in mitochondrial chaperone-substrate specificity.
The Ins and Outs of Endosteal Niche Disruption in the Bone Marrow: Relevance for Myeloma Oncogenesis
Authors: Capp Jean-Pascal , Bataille Régis
Published: July 2023

Multiple Myeloma (MM) and its preexisting stage, termed Monoclonal Gammopathy of Undetermined Significance (MGUS), have long been considered mainly as genomic diseases. However, the bone changes observed in both conditions have led to a reassessment of the role of the bone microenvironment, mainly the endosteal niche in their genesis. Here, we consider the disruption of the endosteal niche in the bone marrow, that is, the shift of the endosteal niche from an osteoblastic to an osteoclastic profile produced by bone senescence and inflammaging, as the key element. Thus, this disrupted endosteal niche is proposed to represent the permissive microenvironment necessary not only for the emergence of MM from MGUS but also for the emergence and maintenance of MGUS. Moreover, the excess of osteoclasts would favor the presentation of antigens (Ag) into the endosteal niche because osteoclasts are Ag-presenting cells. As such, they could significantly stimulate the presentation of some specific Ag and the clonal expansion of the stimulated cells as well as favor the expansion of such selected clones because osteoclasts are immunosuppressive. We also discuss this scenario in the Gaucher disease, in which the high incidence of MGUS and MM makes it a good model both at the bone level and the immunological level. Finally, we envisage that this endosteal niche disruption would increase the stochasticity (epigenetic and genetic instability) in the selected clones, according to our Tissue Disruption-induced cell Stochasticity (TiDiS) theory.
Circular RNA as a Novel Regulator and Promising Biomarker in Polycystic Ovary Syndrome
Authors: Jing Tianrui , Wu Yifan , Wan Anran , Ge Chengmin , Chen Zi-Jiang , Du Yanzhi
Published: July 2023

Polycystic ovary syndrome (PCOS) is a prevalent metabolic and reproductive disorder that causes low fertility in females. Despite its detrimental effects on women’s health, care for PCOS has been impeded by its undefined pathogenesis. Thus, there is an urgent need to explore novel biomarkers and therapeutic targets for the diagnosis and treatment of PCOS. Circular RNAs (circRNAs) are a class of noncoding RNAs with covalently closed cyclic structures, present in high abundance, and show development-stage specific expression patterns. Recent studies have demonstrated that circRNAs participate in PCOS progression by modulating various biological functions, including cell proliferation, apoptosis, and steroidogenesis. In addition, circRNAs are widely present in the follicular fluid of women with PCOS, indicating their potential as diagnostic biomarkers and therapeutic targets for PCOS. This review provides the current knowledge of circRNAs in PCOS, including their regulatory functions and molecular mechanisms, and explores their potential as diagnostic biomarkers and therapeutic targets.
Omics Overview of the SPARC Gene in Mesothelioma
Authors: Wu Licun , de Perrot Marc
Published: July 2023

The SPARC gene plays multiple roles in extracellular matrix synthesis and cell shaping, associated with tumor cell migration, invasion, and metastasis. The SPARC gene is also involved in the epithelial-mesenchymal transition (EMT) process, which is a critical phenomenon leading to a more aggressive cancer cell phenotype. SPARC gene overexpression has shown to be associated with poor survival in the mesothelioma (MESO) cohort from the TCGA database, indicating that this gene may be a powerful prognostic factor in MESO. Its overexpression is correlated with the immunosuppressive tumor microenvironment. Here, we summarize the omics advances of the SPARC gene, including the summary of SPARC gene expression associated with prognosis in pancancer and MESO, the immunosuppressive microenvironment, and cancer cell stemness. In addition, SPARC might be targeted by microRNAs. Notably, despite the controversial functions on angiogenesis, SPARC may directly or indirectly contribute to tumor angiogenesis in MESO. In conclusion, SPARC is involved in tumor invasion, metastasis, immunosuppression, cancer cell stemness, and tumor angiogenesis, eventually impacting patient survival. Strategies targeting this gene may provide novel therapeutic approaches to the treatment of MESO.
Maize Internode Autofluorescence at the Macroscopic Scale: Image Representation and Principal Component Analysis of a Series of Large Multispectral Images
Authors: Devaux Marie-Françoise , Corcel Mathias , Guillon Fabienne , Barron Cécile
Published: July 2023

A quantitative histology of maize stems is needed to study the role of tissue and of their chemical composition in plant development and in their end-use quality. In the present work, a new methodology is proposed to show and quantify the spatial variability of tissue composition in plant organs and to statistically compare different samples accounting for biological variability. Multispectral UV/visible autofluorescence imaging was used to acquire a macroscale image series based on the fluorescence of phenolic compounds in the cell wall. A series of 40 multispectral large images of a whole internode section taken from four maize inbred lines were compared. The series consisted of more than 1 billion pixels and 11 autofluorescence channels. Principal Component Analysis was adapted and named large PCA and score image montages at different scales were built. Large PCA score distributions were proposed as quantitative features to compare the inbred lines. Variations in the tissue fluorescence were clearly displayed in the score images. General intensity variations were identified. Rind vascular bundles were differentiated from other tissues due to their lignin fluorescence after visible excitation, while variations within the pith parenchyma were shown via UV fluorescence. They depended on the inbred line, as revealed by the first four large PCA score distributions. Autofluorescence macroscopy combined with an adapted analysis of a series of large images is promising for the investigation of the spatial heterogeneity of tissue composition between and within organ sections. The method is easy to implement and can be easily extended to other multi–hyperspectral imaging techniques. The score distributions enable a global comparison of the images and an analysis of the inbred lines’ effect. The interpretation of the tissue autofluorescence needs to be further investigated by using complementary spatially resolved techniques.
Pharmacological Potential of Betulin as a Multitarget Compound
Authors: Adepoju Feyisayo O. , Duru Kingsley C. , Li Erguang , Kovaleva Elena G. , Tsurkan Mikhail V.
Published: July 2023

Betulin is a natural triterpene, usually from birch bark, known for its potential wound-healing properties. Despite having a wide range of pharmacological targets, no studies have proposed betulin as a multitarget compound. Betulin has protective effects against cardiovascular and liver diseases, cancer, diabetes, oxidative stress, and inflammation. It reduces postprandial hyperglycemia by inhibiting α-amylase and α-glucosidase activity, combats tumor cells by inducing apoptosis and inhibiting metastatic proteins, and modulates chronic inflammation by blocking the expression of proinflammatory cytokines via modulation of the NFκB and MAPKs pathways. Given its potential to influence diverse biological networks with high target specificity, it can be hypothesized that betulin may eventually become a new lead for drug development because it can modify a variety of pharmacological targets. The summarized research revealed that the diverse beneficial effects of betulin in various diseases can be attributed, at least in part, to its multitarget anti-inflammatory activity. This review focuses on the natural sources, pharmacokinetics, pharmacological activity of betulin, and the multi-target effects of betulin on signaling pathways such as MAPK, NF-κB, and Nrf2, which are important regulators of the response to oxidative stress and inflammation in the body.
The Extent and Impact of COVID-19 Infection among Family and Friends: A Scoping Review
Authors: Wiblishauser Michael , Chapa Tori , Ellis K’Ondria
Published: July 2023

There exist a plethora of studies examining the psychological and physical impacts of COVID-19 on infected victims. Fewer studies have been published assessing the different types of impacts that an individual’s COVID-19 infection has on close friends and family members. This is the first scoping review to gauge the reported psychosocial issues and daily hassles that impact the relatives and friends of infected individuals. This study was conducted by inputting key terms/MeSH terms into selected internet databases to locate prospective studies. The frameworks of scoping reviews by Arksey et al. and the preferred reporting items for systematic review and meta-analyses (PRISMA) were utilized in the methodology for identifying and selecting the studies. After data extraction, 37 studies were deemed suitable for analysis. The findings generated from each study were placed into combined categories. A total of 16 combined categories were generated from the amalgamation of the findings. The results show that psychosocial feelings (e.g., anxiety, stress, and depression) were the category with the highest prevalence of grouped findings. The results from this study may serve as the impetus for future interventions targeting the alleviation of psychosocial feelings or day-to-day hassles associated with having a loved one inflicted with a severe illness.