Botanical and Genetic Identification Followed by Investigation of Chemical Composition and Biological Activities on the Scabiosa atropurpurea L. Stem from Tunisian Flora

Dipsacus and Scabiosa Species-The Source of Specialized Metabolites with High Biological Relevance: A Review

The genera Dipsacus L. and Scabiosa L. of the Caprifoliaceae family are widely distributed in Europe, Asia, and Africa. This work reviews the available literature on the phytochemical profiles, ethnomedicinal uses, and biological activities of the most popular species. These plants are rich sources of many valuable specialized metabolites with beneficial medicinal properties, such as triterpenoid derivatives, iridoids, phenolic acids, and flavonoids. They are also sources of essential oils. The genus Dipsacus has been used for centuries in Chinese and Korean folk medicines to treat bone (osteoporosis) and joint problems (rheumatic arthritis). The Korean Herbal Pharmacopoeia and Chinese Pharmacopoeia include Dipsaci radix, the dried roots of D. asperoides C.Y.Cheng & T.M.Ai. In addition, S. comosa Fisch. ex Roem & Schult. and S. tschiliiensis Grunning are used in traditional Mongolian medicine to treat liver diseases. The current scientific literature data indicate that these plants and their constituents have various biological properties, including inter alia antiarthritic, anti-neurodegenerative, anti-inflammatory, antioxidant, anticancer, and antimicrobial activities; they have also been found to strengthen tendon and bone tissue and protect the liver, heart, and kidney. The essential oils possess antibacterial, antifungal, and insecticidal properties. This paper reviews the key biological values of Dipsacus and Scabiosa species, as identified by in vitro and in vivo studies, and presents their potential pharmacological applications.

Biosynthesis and Characterization of Silver Nanoparticles from the Extremophile Plant Aeonium haworthii and Their Antioxidant, Antimicrobial and Anti-Diabetic Capacities

The present paper described the first green synthesis of silver nanoparticles (AgNPs) from the extremophile plant Aeonium haworthii. The characterization of the biosynthesized silver nanoparticles was carried out by using UV-Vis, FTIR and STM analysis. The antioxidant, antidiabetic and antimicrobial properties were also reported. The newly described AgNPs were spherical in shape and had a size of 35-55 nm. The lowest IC50 values measured by the DPPH assay indicate the superior antioxidant behavior of our AgNPs as opposed to ascorbic acid. The silver nanoparticles show high antidiabetic activity determined by the inhibitory effect of α amylase as compared to the standard Acarbose. Moreover, the AgNPs inhibit bacterial growth owing to a bactericidal effect with the MIC values varying from 0.017 to 1.7 µg/mL. The antifungal action was evaluated against Candida albicans, Candida tropicalis, Candida glabrata, Candida sake and non-dermatophytic onychomycosis fungi. A strong inhibitory effect on Candida factors' virulence was observed as proteinase and phospholipase limitations. In addition, the microscopic observations show that the silver nanoparticles cause the eradication of blastospores and block filamentous morphogenesis. The combination of the antioxidant, antimicrobial and antidiabetic behaviors of the new biosynthesized silver nanoparticles highlights their promising use as natural phytomedicine agents.

Chemical Composition, Antifungal and Anti-Biofilm Activities of Volatile Fractions of Convolvulus althaeoides L. Roots from Tunisia

The antifungal drugs currently available and mostly used for the treatment of candidiasis exhibit the phenomena of toxicity and increasing resistance. In this context, plant materials might represent promising sources of antifungal agents. The aim of this study is to evaluate for the first time the chemical content of the volatile fractions (VFs) along with the antifungal and anti-biofilm of Convolvulus althaeoides L. roots. The chemical composition was determined by gas chromatography coupled to a flame ionization detector and mass spectrometry. In total, 73 and 86 chemical compounds were detected in the n-hexane (VF1) and chloroform (VF2) fractions, respectively. Analysis revealed the presence of four main compounds: n-hexadecenoic acid (29.77%), 4-vinyl guaiacol (12.2%), bis(2-ethylhexyl)-adipate (9.69%) and eicosane (3.98%) in the VF extracted by hexane (VF1). n-hexadecenoic acid (34.04%), benzyl alcohol (7.86%) and linoleic acid (7.30%) were the main compounds found in the VF extracted with chloroform (VF2). The antifungal minimum inhibitory concentrations (MICs) of the obtained fractions against Candida albicans, Candida glabrata and Candida tropicalis were determined by the micro-dilution technique and values against Candida spp. ranged from 0.87 to 3.5 mg/mL. The biofilm inhibitory concentrations (IBF) and sustained inhibition (BSI) assays on C. albicans, C. glabrata and C. tropicalis were also investigated. The VFs inhibited biofilm formation up to 0.87 mg/mL for C. albicans, up to 1.75 mg/mL against C. glabrata and up to 0.87 mg/mL against C. tropicalis. The obtained results highlighted the synergistic mechanism of the detected molecules in the prevention of candidosic biofilm formation.

Petrogenesis and Tectonic Implications of Early Paleozoic Magmatism in Awen Gold District, South Section of the Truong Son Orogenic Belt, Laos

The Truong Son orogenic belt (TSOB) is one of the most important orogenic belts in the Indochina block. There are numerous mafic to felsic intrusions in the Early Paleozoic caused by the Tethyan orogeny. However, the tectono-magmatic evolution of the TSOB in the Early Paleozoic is still unclear. In this paper, zircon U-Pb dating, whole-rock geochemistry, and the Sr-Nd isotopic data of the Early Paleozoic magmatic rocks have been systematically investigated to explore the petrogenesis and tectonic significance of these rocks in the TSOB. Based on our new results integrated with previous geological data, four major tectono-magmatic episodes are identified. (1) The Middle Cambrian (~507 Ma) is the early stage of northward subduction of the Tamky-Phuoc Son Ocean. (2) The Early Ordovician to Middle Ordovician (483–461 Ma) is the main subduction stage of the Tamky-Phuoc Son Ocean. The intrusive rock associations imply the closure of the Tamky-Phuoc Son Ocean. (3) The Late Ordovician to Early Silurian (461–438 Ma) is the collision stage of the Kontum massif and Truong Son terrane. (4) The Early Silurian to Late Silurian (438–410 Ma) is the late stage of collision accompanied by slab roll-back.

The Moderator Effect of Communicative Rational Action in the Relationship between Emotional Labor and Job Satisfaction

The aim of this study was to determine whether emotional labor behavior has an effect on job satisfaction, and if there is an effect, to reveal whether communicative rational action has a moderator effect. This research was carried out in the banking sector. The sample group consisted of administrators of foreign capital bank managers (427) at all levels in Turkey. The collected data were analyzed with the IBM SPSS 21 program. Multiple regression analysis and SPSS PROCESS v3.5 (model1) methods were used in the analysis. According to the analysis, the three sub-dimensions of communicative rational action (practical-rational action, rational communication, and rational action) have a moderator role in the effect of emotional labor and job satisfaction. The other two sub dimensions (value–rational–action and firm family) do not have a moderator role in this effect. In the analysis made according to the total score of communicative rational action, the moderator role of communicative rational action in the effect of emotional labor and job satisfaction was determined. As a result of the research and analysis, it was determined that emotional labor has a positive effect on the phenomenon of job satisfaction.

Integration of Stress–Strain Maps in Mineral Systems Targeting for IOCG Mineralisation within the Mt. Woods Inlier, Gawler Craton, South Australia

The application of finite element analysis is used to simulate the relative distribution and magnitude of stress–strain conditions during a geologically brief, NNW-SSE-oriented, extensional event (1595 Ma to 1590 Ma), co-incident with IOCG-hydrothermal fluid flow and mineralisation across the Mt Woods Inlier, Gawler Craton, South Australia. Differential stress and shear strain maps across the modelled terrane highlight regions that were predisposed to strain localization, extensional failure and fluid throughput during the simulated mineralisation event. These maps are integrated with other datasets and interpretation layers, one of which is a proposed structural–geometrical relationship apparent in many world-class IOCG deposits, including Prominent Hill, Olympic Dam, Sossego, Salobo, Cristalino and Candelaria. These deposits occur at steeply plunging, pipe-like intersections of conjugate extensional systems of faults, shears and/or contacts, wherein the obtuse angle may have been bisected by the maximum principal extensional axis (viz., σ3) during mineralisation. Several other layers are also used for the generation of targets, such as distance from major shear zones, favourable host lithologies, and proximity to tectonostratigraphic contacts of markedly contrasting competency. The result is an integrated target index or heat map for IOCG prospectively across the Mt. Woods Inlier.

Blockchain Technology in Operations & Supply Chain Management: A Content Analysis

Scholars are increasingly examining how the distributed blockchain technology can counter specific supply chain and operations management challenges. Various research approaches emerge from different scholarly backgrounds, but the interrelation of research areas and current trends has not been adequately considered in a systematic review. We employ a data-driven content analysis approach to examine previous research on blockchain technology in operations management and supply chain management. We investigate the extent to which blockchain technology was considered in scholarly works, structure the research efforts, and identify trends, interrelated themes, and promising research opportunities. Quantitative and qualitative content analysis is conducted on an extensive literature sample of 410 articles. Results indicate an optimistic attitude due to potentials such as tracking and tracing abilities, efficiency increases, and trust-building. Conceptual studies dominate the literature set, with increasing qualitative research efforts. Grand theories are seldomly addressed in the studies. Blockchain technology is outlined as particularly useful when combined with other technologies like IoT. We also identified sustainability implications of the technology, such as enabling transparency for SC stakeholders. Cryptocurrencies can facilitate further efficiency gains if legal uncertainties are reduced. The study is concluded with managerial and theoretical implications and future research opportunities.

Understanding the Mechanisms That Drive Phage Resistance in Staphylococci to Prevent Phage Therapy Failure

Despite occurring at the microscopic scale, the armed race between phages and their bacterial hosts involves multiple mechanisms, some of which are just starting to be understood. On the one hand, bacteria have evolved strategies that can stop the viral infection at different stages (adsorption, DNA injection and replication, biosynthesis and assembly of the viral progeny and/or release of the newly formed virions); on the other, phages have gradually evolved counterattack strategies that allow them to continue infecting their prey. This co-evolutionary process has played a major role in the development of microbial populations in both natural and man-made environments. Notably, understanding the parameters of this microscopic war will be paramount to fully benefit from the application of phage therapy against dangerous, antibiotic-resistant human pathogens. This review gathers the current knowledge regarding the mechanisms of phage resistance in the Staphylococcus genus, which includes Staphylococcus aureus, one of the most concerning microorganisms in terms of antibiotic resistance acquisition. Some of these strategies involve permanent changes to the bacterial cell via mutations, while others are transient, adaptive changes whose expression depends on certain environmental cues or the growth phase. Finally, we discuss the most plausible strategies to limit the impact of phage resistance on therapy, with a special emphasis on the importance of a rational design of phage cocktails in order to thwart therapeutic failure.

First Report of the Biosynthesis and Characterization of Silver Nanoparticles Using Scabiosa atropurpurea subsp. maritima Fruit Extracts and Their Antioxidant, Antimicrobial and Cytotoxic Properties

Candida and dermatophyte infections are difficult to treat due to increasing antifungal drugs resistance such as fluconazole, as well as the emergence of multi-resistance in clinical bacteria. Here, we first synthesized silver nanoparticles using aqueous fruit extracts from Scabiosa atropurpurea subsp. maritima (L.). The characterization of the AgNPs by means of UV, XRD, FTIR, and TEM showed that the AgNPs had a uniform spherical shape with average sizes of 40–50 nm. The biosynthesized AgNPs showed high antioxidant activity when investigated using 1,1-diphenyl-2-picryl-hydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays. The AgNPs displayed strong antibacterial potential expressed by the maximum zone inhibition and the lowest MIC and MBC values. The AgNPs revealed a significant antifungal effect against the growth and biofilm of Candida species. In fact, the AgNPs were efficient against Trichophyton rubrum, Trichophyton interdigitale, and Microsporum canis. The antifungal mechanisms of action of the AgNPs seem to be due to the disruption of membrane integrity and a reduction in virulence factors (biofilm and hyphae formation and a reduction in germination). Finally, the silver nanoparticles also showed important cytotoxic activity against the human multiple myeloma U266 cell line and the human breast cancer cell line MDA-MB-231. Therefore, we describe new silver nanoparticles with promising biomedical application in the development of novel antimicrobial and anticancer agents.

The Sustainable Efficiency Improvement of Internet Companies under the Background of Digital Transformation

The digital economy is a driving force for economic growth in various countries. When the digital economy is deeply integrated with Internet companies, it also brings about great challenges to corporate innovation. This paper used the DEA-Malmquist model to measure the efficiency of the science and technology investment of 30 Internet-listed companies in China from 2011 to 2019, constructing a long-distance function and displaying the dynamic changes in the comparative efficiency of time and space. This research evaluated the digital maturity and digital experience of Internet companies under the continuous investment of science and technology, concluding that the investment in science and technology under the digital economy can improve the innovation efficiency of China’s Internet companies. Research shows that technology investment has a significant positive impact on the digitalization of Internet companies, but there is heterogeneity among different companies. Based on the theoretical research in this article and the empirical experience of in-depth digitalization, it also provides path suggestions for the in-depth development of digitalization of Internet companies. This research has important theoretical significance and practical value for further promoting the development of Internet companies and promoting the application of the digital economy.

Malignant Bone Tumors Diagnosis Using Magnetic Resonance Imaging Based on Deep Learning Algorithms

Background and Objectives: Malignant bone tumors represent a major problem due to their aggressiveness and low survival rate. One of the determining factors for improving vital and functional prognosis is the shortening of the time between the onset of symptoms and the moment when treatment starts. The objective of the study is to predict the malignancy of a bone tumor from magnetic resonance imaging (MRI) using deep learning algorithms. Materials and Methods: The cohort contained 23 patients in the study (14 women and 9 men with ages between 15 and 80). Two pretrained ResNet50 image classifiers are used to classify T1 and T2 weighted MRI scans. To predict the malignancy of a tumor, a clinical model is used. The model is a feed forward neural network whose inputs are patient clinical data and the output values of T1 and T2 classifiers. Results: For the training step, the accuracies of 93.67% for the T1 classifier and 86.67% for the T2 classifier were obtained. In validation, both classifiers obtained 95.00% accuracy. The clinical model had an accuracy of 80.84% for training phase and 80.56% for validation. The receiver operating characteristic curve (ROC) of the clinical model shows that the algorithm can perform class separation. Conclusions: The proposed method is based on pretrained deep learning classifiers which do not require a manual segmentation of the MRI images. These algorithms can be used to predict the malignancy of a tumor and on the other hand can shorten the time of their diagnosis and treatment process. While the proposed method requires minimal intervention from an imagist, it needs to be tested on a larger cohort of patients.

Origin of Baseline Drift in Metal Oxide Gas Sensors: Effects of Bulk Equilibration

Metal oxide (MOX) gas sensors and gas sensor arrays are widely used to detect toxic, combustible, and corrosive gases and gas mixtures inside ambient air. Important but poorly researched effects counteracting reliable detection are the phenomena of sensor baseline drift and changes in gas response upon long-term operation of MOX gas sensors. In this paper, it is shown that baseline drift is not limited to materials with poor crystallinity, but that this phenomenon principally also occurs in materials with almost perfect crystalline order. Building on this result, a theoretical framework for the analysis of such phenomena is developed. This analysis indicates that sensor drift is caused by the slow annealing of quenched-in non-equilibrium oxygen-vacancy donors as MOX gas sensors are operated at moderate temperatures for prolonged periods of time. Most interestingly, our analysis predicts that sensor drift in n-type MOX materials can potentially be mitigated or even suppressed by doping with metal impurities with chemical valences higher than those of the core metal constituents of the host crystals.