Repurposing Approach IdentifiesPitavastatin as a Potent AzoleChemosensitizing Agent EffectiveAgainst Azole-Resistant CandidaSpecies

The limited number of antifungals and the rising frequency of azole-resistant Candida species are growing challenges to human medicine. Drug repurposing signifies an appealing approach to enhance the activity of current antifungal drugs. Here, we evaluated the ability of Pharmakon 1600 drug library to sensitize an azole-resistant Candida albicans to the effect of fluconazole. The primary screen revealed 44 non-antifungal hits were able to act synergistically with fluconazole against the test strain. Of note, 21 compounds, showed aptness for systemic administration and limited toxic effects, were considered as potential fluconazole adjuvants and thus were termed as “repositionable hits”. A follow-up analysis revealed pitavastatin displaying the most potent fluconazole chemosensitizing activity against the test strain (ΣFICI 0.05) and thus was further evaluated against 18 isolates of C. albicans (n = 9), C. glabrata (n = 4), and C. auris (n = 5). Pitavastatin displayed broad-spectrum synergistic interactions with both fluconazole and voriconazole against ~89% of the tested strains (ΣFICI 0.05–0.5). Additionally, the pitavastatin-fluconazole combination significantly reduced the biofilm-forming abilities of the tested Candida species by up to 73%, and successfully reduced the fungal burdens in a Caenorhabditis elegans infection model by up to 96%. This study presents pitavastatin as a potent azole chemosensitizing agent that warrant further investigation

Ospemifene Displays Broad-Spectrum Synergistic Interactions with Itraconazole Through Potent Interference with Fungal Efflux Activities

Azole antifungals are vital therapeutic options for treating invasive mycotic infections. However, the emergence of azole-resistant isolates combined with limited therapeutic options presents a growing challenge in medical mycology. To address this issue, we utilized microdilution checkerboard assays to evaluate nine stilbene compounds for their ability to interact synergistically with azole drugs, particularly against azole-resistant fungal isolates. Ospemifene displayed the most potent azole chemosensitizing activity, and its combination with itraconazole displayed broad-spectrum synergistic interactions against Candida albicans, Candida auris, Cryptococcus neoformans, and Aspergillus fumigatus (ΣFICI = 0.05–0.50). Additionally, in a Caenorhabditis elegans infection model, the ospemifene-itraconazole combination significantly reduced fungal CFU burdens in infected nematodes by ~75–96%. Nile Red efflux assays and RT-qPCR analysis suggest ospemifene interferes directly with fungal efflux systems, thus permitting entry of azole drugs into fungal cells. This study identifies ospemifene as a novel antifungal adjuvant that augments the antifungal activity of itraconazole against a broad range of fungal pathogens

Identification and characterization of antibacterial compound(s) of cockroaches (Periplaneta americana)

Infectious diseases remain a significant threat to human health, contributing to more than 17 million deaths, annually. With the worsening trends of drug resistance, there is a need for newer and more powerful antimicrobial agents. We hypothesized that animals living in polluted environments are potential source of antimicrobials. Under polluted milieus, organisms such as cockroaches encounter different types of microbes, including superbugs. Such creatures survive the onslaught of superbugs and are able to ward off disease by producing antimicrobial substances. Here, we characterized antibacterial properties in extracts of various body organs of cockroaches (Periplaneta americana) and showed potent antibacterial activity in crude brain extract against methicillin-resistant Staphylococcus aureus and neuropathogenic E. coli K1. The size-exclusion spin columns revealed that the active compound(s) are less than 10 kDa in molecular mass. Using cytotoxicity assays, it was observed that pre-treatment of bacteria with lysates inhibited bacteria-mediated host cell cytotoxicity. Using spectra obtained with LC-MS on Agilent 1290 infinity liquid chromatograph, coupled with an Agilent 6460 triple quadruple mass spectrometer, tissues lysates were analyzed. Among hundreds of compounds, only a few homologous compounds were identified that contained isoquinoline group, chromene derivatives, thiazine groups, imidazoles, pyrrole containing analogs, sulfonamides, furanones, flavanones, and known to possess broad-spectrum antimicrobial properties, and possess anti-inflammatory, anti-tumour, and analgesic properties. Further identification, characterization and functional studies using individual compounds can act as a breakthrough in developing novel therapeutics against various pathogens including superbugs

Illustrating and homology modeling the proteins of the Zika virus

The Zika virus (ZIKV) is a flavivirus of the family Flaviviridae, which is similar to dengue virus, yellow fever and West Nile virus. Recent outbreaks in South America, Latin America, the Caribbean and in particular Brazil have led to concern for the spread of the disease and potential to cause Guillain-Barré syndrome and microcephaly. Although ZIKV has been known of for over 60 years there is very little in the way of knowledge of the virus with few publications and no crystal structures. No antivirals have been tested against it either in vitro or in vivo. ZIKV therefore epitomizes a neglected disease. Several suggested steps have been proposed which could be taken to initiate ZIKV antiviral drug discovery using both high throughput screens as well as structure-based design based on homology models for the key proteins. We now describe preliminary homology models created for NS5, FtsJ, NS4B, NS4A, HELICc, DEXDc, peptidase S7, NS2B, NS2A, NS1, E stem, glycoprotein M, propeptide, capsid and glycoprotein E using SWISS-MODEL. Eleven out of 15 models pass our model quality criteria for their further use. While a ZIKV glycoprotein E homology model was initially described in the immature conformation as a trimer, we now describe the mature dimer conformer which allowed the construction of an illustration of the complete virion. By comparing illustrations of ZIKV based on this new homology model and the dengue virus crystal structure we propose potential differences that could be exploited for antiviral and vaccine design. The prediction of sites for glycosylation on this protein may also be useful in this regard. While we await a cryo-EM structure of ZIKV and eventual crystal structures of the individual proteins, these homology models provide the community with a starting point for structure-based design of drugs and vaccines as well as a for computational virtual screening

Effect of Polymers on Behavior of Ultra-High-Strength Concrete

The development of ultra-high-performance concrete (UHPC) is still practically limited due to the scarcity of robust mixture designs and sustainable sources of local constituent materials. This study investigates the engineering characteristics of Styrene Butadiene Rubber (SBR) polymeric fiber-reinforced UHPC with partial substitution of cement at 0, 5 and 20 wt.% with latex polymer under steam and air curing techniques. The compressive and tensile strengths along with capillary water absorption and sulfate resistance were measured to evaluate the mechanical and durability properties. Scanning Electron Microscopy (SEM) was carried out to explore the microstructure development and hydration products in the designed mixtures under different curing regimes. The results indicated that the mixtures incorporating 20 wt.% SBR polymer achieved superior compressive strength at later ages. Additionally, the tensile strength of the polymeric UHPC without steel fibers and with 20% polymers was enhanced by 50%, which promotes the development of novel UHPC mixtures in which steel fibers could be partially replaced by polymer, while enhancing the tensile properties

Photoneutrons and Gamma Capture Dose Rates at the Maze Entrance of Varian TrueBeam and Elekta Versa HD Medical Linear Accelerators

Herein, we evaluated the neutron and gamma capture dose equivalent rates at the maze entrance of Varian TrueBeam and Elekta Versa HD™ medical linear accelerators (linacs) using experimental measurements as well as empirical calculations. Dose rates were measured using calibrated neutron and gamma area survey meters placed side-by-side at the measurement point of interest. Measurements were performed at a source-to-detector distance of 100 cm, with a 10 × 10 cm2 field size therapeutic X-ray beam, and a 30 × 30 × 15 cm3 solid water patient equivalent phantom, with a linac operating at 15, 10 MV, and 10 MV flattened filter-free (FFF). Dose rates were also measured at different points at the centerline along the maze towards the maze entrance. The measured dose equivalent rates at the maze entrance were comparable to those reported in the literature. The dose rates along the maze decreased exponentially towards the maze entrance and were significant for short maze lengths. The evaluated empirical methods for estimating neutron dose rates at the maze entrance of a linac proposed by Kersey, the modified Kersey method and Falcão method, agree by a factor of two from the experimental measurements. The results revealed vital radiation protection considerations owing to neutron contamination in external beam therapy

Smart Detection of Tomato Leaf Diseases Using Transfer Learning-Based Convolutional Neural Networks

Plant diseases affect the availability and safety of plants for human and animal consumption and threaten food safety, thus reducing food availability and access, as well as reducing crop yield and quality. There is a need for novel disease detection methods that can be used to reduce plant losses due to disease. Thus, this study aims to diagnose tomato leaf diseases by classifying healthy and unhealthy tomato leaf images using two pre-trained convolutional neural networks (CNNs): Inception V3 and Inception ResNet V2. The two models were trained using an open-source database (PlantVillage) and field-recorded images with a total of 5225 images. The models were investigated with dropout rates of 5%, 10%, 15%, 20%, 25%, 30%, 40%, and 50%. The most important results showed that the Inception V3 model with a 50% dropout rate and the Inception ResNet V2 model with a 15% dropout rate, as they gave the best performance with an accuracy of 99.22% and a loss of 0.03. The high-performance rate shows the possibility of utilizing CNNs models for diagnosing tomato diseases under field and laboratory conditions. It is also an approach that can be expanded to support an integrated system for diagnosing various plant diseases