1,720,966 research outputs found
Cheminformatic approaches to hit-prioritization and target prediction of potential anti-mrsa natural products
No full textMagister Pharmaceuticae - MPharmThe growing resistance of Methicillin-Resistant Staphylococcus aureus (MRSA) to currently prescribed drugs has resulted in the failure of prevention and treatment of different infections caused by the superbug. Therefore, to keep pace with the resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have displayed varying in vitro activities against the pathogen but few of these natural compounds have been studied for their prospects to be potential antimicrobial drug candidates. This may be due to the high cost, tedious, and time-consuming process of conducting the important preclinical tests on these compounds. Hence, there is a need for cost-effective strategies for mining the available data on these natural compounds. This would help to get the knowledge that may guide rational prioritization of “likely to succeed” natural compounds to be developed into potential antimicrobial drug candidates
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Cheminformatic Approaches to Hit-Prioritization and Target Prediction of Potential Anti-MRSA Natural Products
No full text>Magister Scientiae - MScThe growing resistance of Methicillin-Resistant Staphylococcus aureus (MRSA) to currently prescribed drugs has resulted in the failure of prevention and treatment of different infections caused by the superbug. Therefore, to keep pace with the resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have displayed varying in vitro activities against the pathogen but few of these natural compounds have been studied for their prospects to be potential antimicrobial drug candidates. This may be due to the high cost, tedious, and time-consuming process of conducting the important preclinical tests on these compounds. Hence, there is a need for cost-effective strategies for mining the available data on these natural compounds. This would help to get the knowledge that may guide rational prioritization of “likely to succeed” natural compounds to be developed into potential antimicrobial drug candidates. Cheminformatic approaches in drug discovery enable chemical data mining, in conjunction with unsupervised and supervised learning from available bioactivity data that may unlock the full potential of NPs in antimicrobial drug discovery. Therefore, taking advantage of the available NPs with their known in vitro activity against MRSA, this study conducted cheminformatic and data mining analysis towards hit profiling, hit-prioritization, hit-optimization, and target prediction of anti-MRSA NPs. Cheminformatic profiling was conducted on the 111 anti-MRSA NPs (AMNPs) retrieved from literature. About 20 current drugs for MRSA (CDs) were used as a reference to identify AMNPs with promising prospects to become drug candidates
Cheminformatic approaches to hit-prioritization and target prediction of potential anti-mrsa natural products
Full text linkMagister Pharmaceuticae - MPharmThe growing resistance of Methicillin-Resistant Staphylococcus aureus (MRSA) to currently prescribed drugs has resulted in the failure of prevention and treatment of different infections caused by the superbug. Therefore, to keep pace with the resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have displayed varying in vitro activities against the pathogen but few of these natural compounds have been studied for their prospects to be potential antimicrobial drug candidates. This may be due to the high cost, tedious, and time-consuming process of conducting the important preclinical tests on these compounds. Hence, there is a need for cost-effective strategies for mining the available data on these natural compounds. This would help to get the knowledge that may guide rational prioritization of “likely to succeed” natural compounds to be developed into potential antimicrobial drug candidates
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Evaluation of the Antimicrobial and Wound Healing efficacy of Extracts from Ehretia species and their Silver Nanoparticles.
No full textThe rise of antimicrobial-resistant pathogens and the increasing prevalence of chronic wounds pose serious threats to public health and the global economy. Chronic wounds become difficult to treat, especially when they harbor polymicrobial infections, as these complex infections often encourage the development of drug resistance. Many existing conventional treatments are associated with constraints, such as limited efficacy, high costs, and adverse side effects on surrounding healthy tissues. These factors necessitate a paradigm shift. In recent years, extracts from medicinal plants and their chemical derivatives have attracted significant attention as promising alternative therapeutic agents. This is primarily attributed to their cost-effectiveness, widespread accessibility, and fewer side effects. Ehretia species, widely distributed medicinal plants across southern Africa and other parts of the world, have been traditionally used to treat various ailments, including respiratory disorders, gastrointestinal disorders, skin conditions, and inflammatory and pain-related ailments. In addition to their medicinal properties, plant extracts are increasingly valuable in green nanotechnology, offering a cost–effective, sustainable, and environmentally friendly method for fabricating nanoparticles (NPs). Silver nanoparticles (AgNPs) hold significant potential in wound healing by reducing inflammation and preventing infections. In this respect, the combination of nanotechnology and medicinal plant extracts offers an innovative green approach to enhancing wound treatment. The current study aimed to investigate the efficacy of Ehretia rigida (Er) leaf aqueous extract and its AgNPs as potential antimicrobial and wound healing agents. A multifaceted methodology combining in silico and in vitro approaches was used to achieve this goal. Initially, a literature search was conducted to retrieve and generate a library of phytoconstituents from Ehretia species. A key protein structure in the selected multidrug-resistant bacterium Klebsiella pneumoniae, specifically the carbapenemase-2 (KPC-2), was identified from freely available databases, such as https://www.uniprot.org/ and https://www.rcsb.org/. These datasets were used in protein–ligand simulations to investigate the interactions and potential mechanisms of action of the phytoconstituents. Thereafter, Er leaf aqueous extraction was performed and used for the synthesis of Er-AgNPs, followed by optimization of the synthesis conditions. The synthesized Er-AgNPs were characterized via various physicochemical techniques, such as ultraviolet–visible (UV–vis) spectrophotometry, dynamic light scattering (DLS), Fourier transform infrared (FTIR) spectroscopy, and high-resolution transmission electron microscopy (HR-TEM). Phytochemical screening was performed to quantify the total phenolic and flavonoid contents in the Er leaf extract and Er-AgNPs
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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