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  • 1
    In: BMC Genomics, Springer Science and Business Media LLC, Vol. 17, No. S6 ( 2016-7)
    Type of Medium: Online Resource
    ISSN: 1471-2164
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
    detail.hit.zdb_id: 2041499-7
    SSG: 12
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  • 2
    In: Pharmaceutics, MDPI AG, Vol. 12, No. 7 ( 2020-07-09), p. 652-
    Abstract: This study aimed at improving the targeting and cytotoxic effect of ellagic acid (EA) on colon cancer cells. EA was encapsulated in chitosan (CHIT) polymers then coated by eudragit S100 (ES100) microparticles. The release of EA double-coated microparticles (MPs) was tested at simulative pH values. Maximum release was observed at 24 h and pH 7.4. The cytotoxicity of EA MPs on HCT 116 colon cancer cells was synergistically improved as compared with raw EA. Cell-cycle analysis by flow cytometry suggested enhanced G2-M phase colon cancer cell accumulation. In addition, a significantly higher cell fraction was observed in the pre-G phase, which highlighted the enhancement of the proapoptotic activity of EA formulated in the double-coat mixture. Annexin-V staining was used for substantiation of the observed cell-death-inducing activity. Cell fractions were significantly increased in early, late, and total cell death. This was backed by high elevation in cellular content of caspase 3. Effectiveness of the double-coated EA to target colonic tissues was confirmed using real-time iohexol dye X-ray radiography. In conclusion, CHIT loaded with EA and coated with ES100 formula exhibits improved colon targeting as well as enhanced cytotoxic and proapoptotic activity against HCT 116 colon cancer when compared with the administration of raw EA.
    Type of Medium: Online Resource
    ISSN: 1999-4923
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2527217-2
    SSG: 15,3
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  • 3
    In: Marine Drugs, MDPI AG, Vol. 19, No. 2 ( 2021-02-12), p. 109-
    Abstract: Coculture is a productive technique to trigger microbes’ biosynthetic capacity by mimicking the natural habitats’ features principally by competition for food and space and interspecies cross-talks. Mixed cultivation of two Red Sea-derived actinobacteria, Actinokineospora spheciospongiae strain EG49 and Rhodococcus sp. UR59, resulted in the induction of several non-traced metabolites in their axenic cultures, which were detected using LC–HRMS metabolomics analysis. Antimalarial guided isolation of the cocultured fermentation led to the isolation of the angucyclines actinosporins E (1), H (2), G (3), tetragulol (5) and the anthraquinone capillasterquinone B (6), which were not reported under axenic conditions. Interestingly, actinosporins were previously induced when the axenic culture of the Actinokineospora spheciospongiae strain EG49 was treated with signalling molecule N-acetyl-d-glucosamine (GluNAc); this finding confirmed the effectiveness of coculture in the discovery of microbial metabolites yet to be discovered in the axenic fermentation with the potential that could be comparable to adding chemical signalling molecules in the fermentation flask. The isolated angucycline and anthraquinone compounds exhibited in vitro antimalarial activity and good biding affinity against lysyl-tRNA synthetase (PfKRS1), highlighting their potential developability as new antimalarial structural motif.
    Type of Medium: Online Resource
    ISSN: 1660-3397
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2175190-0
    SSG: 15,3
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  • 4
    In: Biology, MDPI AG, Vol. 11, No. 1 ( 2021-12-29), p. 43-
    Abstract: Coronavirus disease 2019 (COVID-19) has spread worldwide, and medicinal resources have become inadequate in several regions. Computed tomography (CT) scans are capable of achieving precise and rapid COVID-19 diagnosis compared to the RT-PCR test. At the same time, artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL), find it useful to design COVID-19 diagnoses using chest CT scans. In this aspect, this study concentrates on the design of an artificial intelligence-based ensemble model for the detection and classification (AIEM-DC) of COVID-19. The AIEM-DC technique aims to accurately detect and classify the COVID-19 using an ensemble of DL models. In addition, Gaussian filtering (GF)-based preprocessing technique is applied for the removal of noise and improve image quality. Moreover, a shark optimization algorithm (SOA) with an ensemble of DL models, namely recurrent neural networks (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU), is employed for feature extraction. Furthermore, an improved bat algorithm with a multiclass support vector machine (IBA-MSVM) model is applied for the classification of CT scans. The design of the ensemble model with optimal parameter tuning of the MSVM model for COVID-19 classification shows the novelty of the work. The effectiveness of the AIEM-DC technique take place on benchmark CT image data set, and the results reported the promising classification performance of the AIEM-DC technique over the recent state-of-the-art approaches.
    Type of Medium: Online Resource
    ISSN: 2079-7737
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2661517-4
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  • 5
    In: Journal of Healthcare Engineering, Hindawi Limited, Vol. 2022 ( 2022-3-30), p. 1-13
    Abstract: Early and accurate detection of COVID-19 is an essential process to curb the spread of this deadly disease and its mortality rate. Chest radiology scan is a significant tool for early management and diagnosis of COVID-19 since the virus targets the respiratory system. Chest X-ray (CXR) images are highly useful in the effective detection of COVID-19, thanks to its availability, cost-effective means, and rapid outcomes. In addition, Artificial Intelligence (AI) techniques such as deep learning (DL) models play a significant role in designing automated diagnostic processes using CXR images. With this motivation, the current study presents a new Quantum Seagull Optimization Algorithm with DL-based COVID-19 diagnosis model, named QSGOA-DL technique. The proposed QSGOA-DL technique intends to detect and classify COVID-19 with the help of CXR images. In this regard, the QSGOA-DL technique involves the design of EfficientNet-B4 as a feature extractor, whereas hyperparameter optimization is carried out with the help of QSGOA technique. Moreover, the classification process is performed by a multilayer extreme learning machine (MELM) model. The novelty of the study lies in the designing of QSGOA for hyperparameter optimization of the EfficientNet-B4 model. An extensive series of simulations was carried out on the benchmark test CXR dataset, and the results were assessed under different aspects. The simulation results demonstrate the promising performance of the proposed QSGOA-DL technique compared to recent approaches.
    Type of Medium: Online Resource
    ISSN: 2040-2309 , 2040-2295
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2545054-2
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  • 6
    Online Resource
    Online Resource
    MDPI AG ; 2021
    In:  Micromachines Vol. 12, No. 5 ( 2021-05-05), p. 519-
    In: Micromachines, MDPI AG, Vol. 12, No. 5 ( 2021-05-05), p. 519-
    Abstract: Sickle cell disease (SCD) is a widespread disease caused by a mutation in the beta-globin gene that leads to the production of abnormal hemoglobin called hemoglobin S. The inheritance of the mutation could be homozygous or heterozygous combined with another hemoglobin mutation. SCD can be characterized by the presence of dense, sickled cells that causes hemolysis of blood cells, anemia, painful episodes, organ damage, and in some cases death. Early detection of SCD can help to reduce the mortality and manage the disease effectively. Therefore, different techniques have been developed to detect the sickle cell disease and the carrier states with high sensitivity and specificity. These techniques can be screening tests such as complete blood count, peripheral blood smears, and sickling test; confirmatory tests such as hemoglobin separation techniques; and genetic tests, which are more expensive and need to be done in centralized labs by highly skilled personnel. However, advanced portable point of care techniques have been developed to provide a low-cost, simple, and user-friendly device for detecting SCD, for instance coupling solubility tests with portable devices, using smartphone microscopic classifications, image processing techniques, rapid immunoassays, and sensor-based platforms. This review provides an overview of the current and emerging techniques for sickle cell disease detection and highlights the different potential methods that could be applied to help the early diagnosis of SCD.
    Type of Medium: Online Resource
    ISSN: 2072-666X
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2620864-7
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  • 7
    In: Metabolites, MDPI AG, Vol. 10, No. 1 ( 2020-01-11), p. 31-
    Abstract: Many routes have been explored to search for effective, safe, and affordable alternatives to hazardous female contraceptives. Herbal extracts and their secondary metabolites are some of the interesting research areas to address this growing issue. This study aims to investigate the effects of ten different plant extracts on testicular spermatogenesis. The correlation between the chemical profile of these extracts and their in vivo effect on male reproductive system was evaluated using various techniques. Approximately 10% of LD50 of hydro-methanolic extracts were orally administrated to rats for 60 days. Semen parameters, sexual organ weights, and serum levels of male sex hormones in addition to testes histopathology, were evaluated. Moreover, metabolomic analysis using (LC-HRESIMS), multivariate analysis (PCA), immunohistochemistry (caspase-3 and β-catenin), and a docking study were performed. Results indicated that three plant extracts significantly decreased epididymal sperm density and motility. Moreover, their effects on testicular cells were also assured by histopathological evaluations. Metabolomic profiling of the bioactive plant extracts showed the presence of diverse phytochemicals, mostly oleanane saponins, phenolic diterpenes, and lupane triterpenes. A docking study on caspase-3 enzyme showed that oleanane saponins possessed the highest binding affinity. An immunohistochemistry assay on β-catenin and caspase-3 indicated that Albizzia lebbeck was the most active extract for decreasing immunoexpression of β-catenin, while Rosmarinus officinalis showed the highest activity for increasing immunoexpression of caspase-3. The spermatogenesis decreasing the activity of A. lebbeck, Anagallis arvensis, and R. officinalis can be mediated via up-regulation of caspase-3 and down-regulation of β-catenin existing in testis cells.
    Type of Medium: Online Resource
    ISSN: 2218-1989
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2662251-8
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  • 8
    In: Analytical Chemistry, American Chemical Society (ACS), Vol. 88, No. 20 ( 2016-10-18), p. 10019-10027
    Type of Medium: Online Resource
    ISSN: 0003-2700 , 1520-6882
    Language: English
    Publisher: American Chemical Society (ACS)
    Publication Date: 2016
    detail.hit.zdb_id: 1483443-1
    detail.hit.zdb_id: 1508-8
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  • 9
    In: Pharmaceuticals, MDPI AG, Vol. 14, No. 6 ( 2021-06-05), p. 541-
    Abstract: The COVID-19 pandemic is still active around the globe despite the newly introduced vaccines. Hence, finding effective medications or repurposing available ones could offer great help during this serious situation. During our anti-COVID-19 investigation of microbial natural products (MNPs), we came across α-rubromycin, an antibiotic derived from Streptomyces collinus ATCC19743, which was able to suppress the catalytic activity (IC50 = 5.4 µM and Ki = 3.22 µM) of one of the viral key enzymes (i.e., MPro). However, it showed high cytotoxicity toward normal human fibroblasts (CC50 = 16.7 µM). To reduce the cytotoxicity of this microbial metabolite, we utilized a number of in silico tools (ensemble docking, molecular dynamics simulation, binding free energy calculation) to propose a novel scaffold having the main pharmacophoric features to inhibit MPro with better drug-like properties and reduced/minimal toxicity. Nevertheless, reaching this novel scaffold synthetically is a time-consuming process, particularly at this critical time. Instead, this scaffold was used as a template to explore similar molecules among the FDA-approved medications that share its main pharmacophoric features with the aid of pharmacophore-based virtual screening software. As a result, cromoglicic acid (aka cromolyn) was found to be the best hit, which, upon in vitro MPro testing, was 4.5 times more potent (IC50 = 1.1 µM and Ki = 0.68 µM) than α-rubromycin, with minimal cytotoxicity toward normal human fibroblasts (CC50 〉 100 µM). This report highlights the potential of MNPs in providing unprecedented scaffolds with a wide range of therapeutic efficacy. It also revealed the importance of cheminformatics tools in speeding up the drug discovery process, which is extremely important in such a critical situation.
    Type of Medium: Online Resource
    ISSN: 1424-8247
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2193542-7
    SSG: 15,3
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  • 10
    In: Marine Drugs, MDPI AG, Vol. 18, No. 5 ( 2020-05-05), p. 243-
    Abstract: Liquid chromatography coupled with high resolution mass spectrometry (LC-HRESMS)-assisted metabolomic profiling of two sponge-associated actinomycetes, Micromonospora sp. UR56 and Actinokineospora sp. EG49, revealed that the co-culture of these two actinomycetes induced the accumulation of metabolites that were not traced in their axenic cultures. Dereplication suggested that phenazine-derived compounds were the main induced metabolites. Hence, following large-scale co-fermentation, the major induced metabolites were isolated and structurally characterized as the already known dimethyl phenazine-1,6-dicarboxylate (1), phenazine-1,6-dicarboxylic acid mono methyl ester (phencomycin; 2), phenazine-1-carboxylic acid (tubermycin; 3), N-(2-hydroxyphenyl)-acetamide (9), and p-anisamide (10). Subsequently, the antibacterial, antibiofilm, and cytotoxic properties of these metabolites (1–3, 9, and 10) were determined in vitro. All the tested compounds except 9 showed high to moderate antibacterial and antibiofilm activities, whereas their cytotoxic effects were modest. Testing against Staphylococcus DNA gyrase-B and pyruvate kinase as possible molecular targets together with binding mode studies showed that compounds 1–3 could exert their bacterial inhibitory activities through the inhibition of both enzymes. Moreover, their structural differences, particularly the substitution at C-1 and C-6, played a crucial role in the determination of their inhibitory spectra and potency. In conclusion, the present study highlighted that microbial co-cultivation is an efficient tool for the discovery of new antimicrobial candidates and indicated phenazines as potential lead compounds for further development as antibiotic scaffold.
    Type of Medium: Online Resource
    ISSN: 1660-3397
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2175190-0
    SSG: 15,3
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