A novel derivative of thioridazine shows low toxicity and efficient activity against gram‐positive pathogens

Thioridazine hydrochloride (HCl) has been suggested as a promising antimicrobial helper compound for the treatment of infections with antimicrobial-resistant bacteria. Unfortunately, the therapeutic concentration of thioridazine HCl is generally higher than what can be tolerated clinically, in part due to its toxic side effects on the central nervous system. Therefore, we aimed to synthesize a less toxic thioridazine derivative that would still retain its properties as a helper compound. This resulted in a compound designated 1-methyl-2-(2-(2-(methylthio)-10H-phenothiazin-10-yl)ethyl)-1-pentylpiperidin-1-ium bromide (abbreviated T5), which exhibited low blood–brain barrier permeability. The lowest minimal inhibitory concentration (MIC) against Staphylococcus aureus exposed to the novel compound was reduced 32-fold compared to thioridazine HCl (from 32 µg/mL to 1 µg/mL). The MIC values for T5 against five Gram-positive pathogens ranged from 1 µg/mL to 8 µg/mL. In contrast to thioridazine HCl, T5 does not act synergistically with oxacillin. In silico predictive structure analysis of T5 suggests that an acceptably low toxicity and lack of induced cytotoxicity was demonstrated by a lactate dehydrogenase assay. Conclusively, T5 is suggested as a novel antimicrobial agent against Gram-positive bacteria. However, future pharmacokinetic and pharmacodynamic studies are needed to clarify the clinical potential of this novel discovery

Insight Into the Anti-staphylococcal Activity of JBC 1847 at Sub-Inhibitory Concentration

Multidrug-resistant pathogens constitute a serious global issue and, therefore, novel antimicrobials with new modes of action are urgently needed. Here, we investigated the effect of a phenothiazine derivative (JBC 1847) with high antimicrobial activity on Staphylococcus aureus, using a wide range of in vitro assays, flow cytometry, and RNA transcriptomics. The flow cytometry results showed that JBC 1847 rapidly caused depolarization of the cell membrane, while the macromolecule synthesis inhibition assay showed that the synthesis rates of DNA, RNA, cell wall, and proteins, respectively, were strongly decreased. Transcriptome analysis of S. aureus exposed to sub-inhibitory concentrations of JBC 1847 identified a total of 78 downregulated genes, whereas not a single gene was found to be significantly upregulated. Most importantly, there was downregulation of genes involved in adenosintrifosfat (ATP)-dependent pathways, including histidine biosynthesis, which is likely to correlate with the observed lower level of intracellular ATP in JBC 1847–treated cells. Furthermore, we showed that JBC 1847 is bactericidal against both exponentially growing cells and cells in a stationary growth phase. In conclusion, our results showed that the antimicrobial properties of JBC 1847 were primarily caused by depolarization of the cell membrane resulting in dissipation of the proton motive force (PMF), whereby many essential bacterial processes are affected. JBC 1847 resulted in lowered intracellular levels of ATP followed by decreased macromolecule synthesis rate and downregulation of genes essential for the amino acid metabolism in S. aureus. Bacterial compensatory mechanisms for this proposed multi-target activity of JBC 1847 seem to be limited based on the observed very low frequency of resistance toward the compound

Surrogate model uncertainty in wind turbine reliability assessment

Lowering the cost of wind energy entails the optimization of wind turbine material consumption without compromising structural safety. Traditionally, wind turbines are designed by the partial safety factor method, which is calibrated by probabilistic models and presented in the IEC 61400-1 design standard. This approach significantly reduces the amount of aero-elastic simulations required to assess the fatigue limit state of wind turbines, but it may lead to inconsistent reliability levels across wind farm projects. To avoid this, wind turbines may be designed by probabilistic methods using surrogate models to approximate fatigue load effects. In this approach, it is important to quantify and model all relevant uncertainties including that of the surrogate model itself. Here we quantify this uncertainty according to Eurocode 1990 for polynomial chaos expansion (PCE) and Kriging using wind data from 99 real sites and the 5 MW reference turbine designed by NREL. We investigate a wide range of simulation efforts to train the surrogate models. Our results show that Kriging yields a higher accuracy per invested simulation compared to PCE. This improved understanding of utilizing PCE and Kriging in fatigue reliability assessment may significantly benefit decision support in probabilistic design of wind turbines.ISSN:0960-1481ISSN:1879-068