scholarly journals Taxonomy, Diversity and Cultivation of the Oudemansielloid/Xeruloid Taxa Hymenopellis, Mucidula, Oudemansiella, and Xerula with Respect to Their Bioactivities: A Review

2021 ◽  
Vol 7 (1) ◽  
pp. 51
Author(s):  
Allen Grace Niego ◽  
Olivier Raspé ◽  
Naritsada Thongklang ◽  
Rawiwan Charoensup ◽  
Saisamorn Lumyong ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Bioactive Compounds ◽  
State Of The Art ◽  
Bioactive Metabolites ◽  
High Quality ◽  
Important Resource ◽  
Molecular Weights ◽  
Anti Cancer ◽  
Potential Applications ◽  
Commercial Applications

The oudemansielloid/xeruloid taxa Hymenopellis, Mucidula, Oudemansiella, and Xerula are genera of Basidiomycota that constitute an important resource of bioactive compounds. Numerous studies have shown antimicrobial, anti-oxidative, anti-cancer, anti-inflammatory and other bioactivities of their extracts. The bioactive principles can be divided into two major groups: (a) hydrophilic polysaccharides with relatively high molecular weights and (b) low molecular medium polar secondary metabolites, such as the antifungal strobilurins. In this review, we summarize the state of the art on biodiversity, cultivation of the fungi and bioactivities of their secondary metabolites and discuss future applications. Although the strobilurins are well-documented, with commercial applications as agrochemical fungicides, there are also other known compounds from this group that have not yet been well-studied. Polysaccharides, dihydro-citrinone phenol A acid, scalusamides, and acetylenic lactones such as xerulin, also have potential applications in the nutraceutical, pharmaceutical and medicinal market and should be further explored. Further studies are recommended to isolate high quality bioactive compounds and fully understand their modes of action. Given that only few species of oudemansielloid/xeruloid mushrooms have been explored for their production of secondary metabolites, these taxa represent unexplored sources of potentially useful and novel bioactive metabolites.

scholarly journals Biodiversity of Secondary Metabolites Compounds Isolated from Phylum Actinobacteria and Its Therapeutic Applications

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4504
Author(s):  
Muhanna Al-shaibani ◽  
Radin Maya Saphira Radin Mohamed ◽  
Nik Sidik ◽  
Hesham Enshasy ◽  
Adel Al-Gheethi ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Bioactive Compounds ◽  
Extreme Environments ◽  
Software Tool ◽  
Gene Clusters ◽  
Well Being ◽  
Bioactive Substances ◽  
Diverse Range ◽  
Wide Range ◽  
Potential Applications

The current review aims to summarise the biodiversity and biosynthesis of novel secondary metabolites compounds, of the phylum Actinobacteria and the diverse range of secondary metabolites produced that vary depending on its ecological environments they inhabit. Actinobacteria creates a wide range of bioactive substances that can be of great value to public health and the pharmaceutical industry. The literature analysis process for this review was conducted using the VOSviewer software tool to visualise the bibliometric networks of the most relevant databases from the Scopus database in the period between 2010 and 22 March 2021. Screening and exploring the available literature relating to the extreme environments and ecosystems that Actinobacteria inhabit aims to identify new strains of this major microorganism class, producing unique novel bioactive compounds. The knowledge gained from these studies is intended to encourage scientists in the natural product discovery field to identify and characterise novel strains containing various bioactive gene clusters with potential clinical applications. It is evident that Actinobacteria adapted to survive in extreme environments represent an important source of a wide range of bioactive compounds. Actinobacteria have a large number of secondary metabolite biosynthetic gene clusters. They can synthesise thousands of subordinate metabolites with different biological actions such as anti-bacterial, anti-parasitic, anti-fungal, anti-virus, anti-cancer and growth-promoting compounds. These are highly significant economically due to their potential applications in the food, nutrition and health industries and thus support our communities’ well-being.

scholarly journals Isolation and optimized production of putative antimicrobial compounds from Egyptian soil isolate Streptomyces sp. MS. 10

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mohamed Sebak ◽  
Amal E. Saafan ◽  
Sameh Abdelghani ◽  
Walid Bakeer ◽  
Abeer S. Moawad ◽  
...  
Keyword(s):  
Natural Products ◽  
Secondary Metabolites ◽  
Bioactive Compounds ◽  
Mass Spectrometry Analysis ◽  
Proton Nuclear Magnetic Resonance ◽  
Bioactive Metabolites ◽  
Resonance Spectroscopy ◽  
Type I ◽  
Antimicrobial Compounds ◽  
Egyptian Soil

Abstract Background The rapid spread of antibiotic resistance has increased research interest in the discovery of natural products, mainly from actinomycetes, which have been the primary source of antimicrobial compounds. This study aimed to isolate, characterize, and optimize the production of some of the bioactive compounds from bioactive soil actinomycetes. Results One promising soil actinomycete, which was molecularly identified as Streptomyces sp. and designated as Streptomyces sp. MS. 10, showed broad-spectrum antimicrobial activity, including activity against methicillin-resistant Staphylococcus aureus. Thus, it was selected for isolation of its major bioactive compounds. Polymerase chain reaction amplification of the genes responsible for antibiotic biosynthesis showed the presence of genes encoding type I and type II polyketide synthase. Liquid chromatography-mass spectrometry analysis found that the major antimicrobial compounds produced by Streptomyces sp. MS. 10 were weakly ionized bioactive secondary metabolites. A large-scale fermentation experiment of Streptomyces sp. MS. 10 using pre-optimized culture conditions followed by bioassay-guided chromatographic separation of its secondary metabolites resulted in the isolation of putative bioactive compounds that were identified as fatty acids using proton nuclear magnetic resonance spectroscopy. Conclusions Egyptian soil is still a good source for exploring bioactive actinomycetes. Additionally, this study highlighted the importance of combining both physicochemical and genotypic characterization with spectroscopic analysis of the major natural products when isolating bioactive metabolites.

In vitro antibacterial and antibiotic-potentiation activities of five edible plant extracts and mode of action against several MDR Gram-negative phenotypes

2020 ◽  
Vol 4 (1) ◽  
pp. 1-14
Author(s):  
Carine M.N. Ngaffo ◽  
Simplice B. Tankeo ◽  
Michel-Gael F. Guefack ◽  
Brice E. N. Wamba ◽  
Paul Nayim ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Bioactive Compounds ◽  
Plant Extracts ◽  
Theobroma Cacao ◽  
Efflux Pumps ◽  
Phoenix Dactylifera ◽  
Food Plants ◽  
Proton Pumps ◽  
Gram Negative ◽  
E Coli

Abstract Background: Bacterial infections involving the multidrug resistant (MDR) strains are among the top leading causes of death throughout the world. Healthcare system across the globe has been suffering from an extra-ordinary burden in terms of looking for the new and more potent antimicrobial compounds. The aim of the present study was to determine the antibacterial activity of some Cameroonian edible plants (Garcinia lucida bark, Phoenix dactylifera pericarps, Theobroma cacao pod, Solanum macrocarpon leaves and Termitomyces titanicus whole plant) and their antibiotics-potentiation effects against some MDR Gram-negative bacteria phenotypes expressing efflux pumps (Escherichia coli, Enterobacter aerogenes, Klebsiella pneumoniae, Pseudomonas aeruginosa and Providencia stuartii strains). Methods: The antibacterial activities of plant extract alone and in combination with usual antibiotics were carried out using the micro-dilution method. The effects of the most active plant extract (Garcinia lucida bark) on H+-ATPase-mediated proton pumps and on bacterial growth kinetic were performed using experimental protocols, while qualitative reference methods were used to highligh the major groups of secondary metabolites present in the extracts. Results: Qualitative phytochemical screening of plant extracts indicated that all analysed secondary metabolites were present in Theobroma cacao and Termitomyces titanicus while one (saponins) of them was absent in Garcinia lucida and Solanum macrocarpon. Only three of them (polyphenols, flavonoids and saponins) were detected in Phoenix dactylifera. Antibacterial essays showed that G. lucida was the most active plant as it inhibited the growth of all studied bacteria with strong activity (MIC<100 µg/mL) against E. coli ATCC8739, significant activity (100≤MIC≤512 µg/mL) against 80% of bacteria and moderate activity (512<MIC≤2048 µg/mL) against E. coli AG100A and E. aerogenes (EA289 and CM64). It was followed by T. cacao and S. macrocarpon extracts which exhibited an antibacterial potential against 95% and 80% of bacterial strains, respectively. These three extracts exhibited a bactericidal effect on a few bacteria. Extracts from T. titanicus and P. dactylifera were less active as they moderately (512<MIC≤2048 µg/mL) inhibited the growth of 35% and 10% of bacteria. All extracts selectively potentiated the activities of all antibiotics with improvement activity factors (IAF) ranging from 2 to 256. G. lucida, T. cacao and S. macrocarpon potentiated the activities of 100%, 89% and 67% of antibiotics respectively against more than 70%, suggesting that they contain bioactive compounds which could be considered as efflux pumps inhibitors. Whereas T. titanicus and P. dactylifera improved the activities of almost 40% and 20% of antibiotics, respectively. This increase of activities also characterizes synergistic effects between antibiotics and these bioactive compounds. G. lucida extract at all tested concentrations, strongly inhibited the growth of bacterial strain E. coli ATCC8739 and exhibited an inhibitory effect on this bacterial H+-ATPase-mediated proton pumps increasing the pH of the medium. Conclusion: The overall results indicated that food plants among which G. lucida, T. cacao and S. macrocarpon could have a benefit interest in combatting resistant types of bacteria. Keywords: Food plants; infectious diseases; MDR bacteria; efflux pumps; antibiotics; secondary metabolites.

Flavonoids and other Non-Alkaloidal Constituents of Genus Erythrina: A Detailed Account of Phytochemical Review

2019 ◽  
Vol 23 ◽  
Author(s):  
Ninh The Son ◽  
Abdelsamed I. Elshamymistry
Keyword(s):  
Secondary Metabolites ◽  
Web Of Science ◽  
Herbal Medicines ◽  
Original Research ◽  
Chemical Structures ◽  
Fatty Acid Derivatives ◽  
Material Sources ◽  
Anti Cancer ◽  
Alkaloidal Constituents ◽  
The Web

: Genus Erythrina belongs to family Fabaceae, which widely distributed in tropical and subtropical areas, and has been applied in both traditional herbal medicines, and pharmacological uses. Original research articles and publications on overview of alkaloids related to this genus are available, but a supportive systematic review account highlighted phytochemical aspects of other types of secondary metabolites is now insufficient. Utilizing data information from SCI-Finder, Google Scholar, the Web of Science, Scopus, Science Direct, PubMed, Chemical Abstracts, ACS journals, Springer, Taylor Francis, Bentham Science and IOP Science, the reliable material sources of this systematic manuscript paper were obtained from the literature published from 1980s to now. A vast amount of data showed that the non-alkaloidal secondary metabolites obtained from genus Erythrina with various classes of chemical structures. Herein, approximately five hundred constituents were isolated comprising of flavonoids, terpenoids, saponins, phytosterols, phenols, arylbenzofurans, coumarins, alcohols, ceramides, mono-sugars and fatty acid derivatives. It resembles the previously phytochemical reports on the plants of differential genus of family Fabaceae, flavonoids reached to the high amount in plants of genus Erythrina. Numerous biological researches such as anti-microbacteria, anti-cancer, anti-virus using isolated compounds from Erythrina species suggested that secondary metabolites of Erythrina plants are now becoming promising agents for drug developments.

UBAR

2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
State Of The Art ◽  
State Of Charge ◽  
User Preference ◽  
Management Approach ◽  
High Quality ◽  
Trade Off ◽  
Run Time

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.

scholarly journals Global optimization of an encapsulated Si/SiO$$_2$$ L3 cavity with a 43 million quality factor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
J. P. Vasco ◽  
V. Savona
Keyword(s):  
Global Optimization ◽  
Photonic Crystal ◽  
Quality Factor ◽  
State Of The Art ◽  
Optimization Strategy ◽  
High Quality ◽  
Optimal Value ◽  
Out Of Plane ◽  
Fabrication Tolerances ◽  
Structural Imperfections

AbstractWe optimize a silica-encapsulated silicon L3 photonic crystal cavity for ultra-high quality factor by means of a global optimization strategy, where the closest holes surrounding the cavity are varied to minimize out-of-plane losses. We find an optimal value of $$Q_c=4.33\times 10^7$$ Q c = 4.33 × 10 7 , which is predicted to be in the 2 million regime in presence of structural imperfections compatible with state-of-the-art silicon fabrication tolerances.

scholarly journals Performance vs. hardware requirements in state-of-the-art automatic speech recognition

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Alexandru-Lucian Georgescu ◽  
Alessandro Pappalardo ◽  
Horia Cucu ◽  
Michaela Blott
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
State Of The Art ◽  
Decision Makers ◽  
Computing Power ◽  
Trade Off ◽  
Speech Features ◽  
Commercial Applications ◽  
Guided Tour ◽  
Embedded Applications

AbstractThe last decade brought significant advances in automatic speech recognition (ASR) thanks to the evolution of deep learning methods. ASR systems evolved from pipeline-based systems, that modeled hand-crafted speech features with probabilistic frameworks and generated phone posteriors, to end-to-end (E2E) systems, that translate the raw waveform directly into words using one deep neural network (DNN). The transcription accuracy greatly increased, leading to ASR technology being integrated into many commercial applications. However, few of the existing ASR technologies are suitable for integration in embedded applications, due to their hard constrains related to computing power and memory usage. This overview paper serves as a guided tour through the recent literature on speech recognition and compares the most popular ASR implementations. The comparison emphasizes the trade-off between ASR performance and hardware requirements, to further serve decision makers in choosing the system which fits best their embedded application. To the best of our knowledge, this is the first study to provide this kind of trade-off analysis for state-of-the-art ASR systems.

scholarly journals In vivo interactome profiling by enzyme‐catalyzed proximity labeling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yangfan Xu ◽  
Xianqun Fan ◽  
Yang Hu
Keyword(s):  
State Of The Art ◽  
Catalytic Efficiency ◽  
Biological Processes ◽  
Protein Protein Interaction ◽  
Current State ◽  
Protein Interactome ◽  
Potential Applications ◽  
Protein Protein Interaction Networks ◽  
Temporal And Spatial

AbstractEnzyme-catalyzed proximity labeling (PL) combined with mass spectrometry (MS) has emerged as a revolutionary approach to reveal the protein-protein interaction networks, dissect complex biological processes, and characterize the subcellular proteome in a more physiological setting than before. The enzymatic tags are being upgraded to improve temporal and spatial resolution and obtain faster catalytic dynamics and higher catalytic efficiency. In vivo application of PL integrated with other state of the art techniques has recently been adapted in live animals and plants, allowing questions to be addressed that were previously inaccessible. It is timely to summarize the current state of PL-dependent interactome studies and their potential applications. We will focus on in vivo uses of newer versions of PL and highlight critical considerations for successful in vivo PL experiments that will provide novel insights into the protein interactome in the context of human diseases.

scholarly journals An All-Batch Loss for Constructing Prediction Intervals

2021 ◽  
Vol 11 (4) ◽  
pp. 1728
Author(s):  
Hua Zhong ◽  
Li Xu
Keyword(s):  
Gradient Descent ◽  
State Of The Art ◽  
Prediction Interval ◽  
Feedforward Neural Networks ◽  
Important Research ◽  
Likelihood Principle ◽  
High Quality ◽  
Construction Methods ◽  
Important Research Topic ◽  
Benchmark Datasets

The prediction interval (PI) is an important research topic in reliability analyses and decision support systems. Data size and computation costs are two of the issues which may hamper the construction of PIs. This paper proposes an all-batch (AB) loss function for constructing high quality PIs. Taking the full advantage of the likelihood principle, the proposed loss makes it possible to train PI generation models using the gradient descent (GD) method for both small and large batches of samples. With the structure of dual feedforward neural networks (FNNs), a high-quality PI generation framework is introduced, which can be adapted to a variety of problems including regression analysis. Numerical experiments were conducted on the benchmark datasets; the results show that higher-quality PIs were achieved using the proposed scheme. Its reliability and stability were also verified in comparison with various state-of-the-art PI construction methods.

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