Combinatorial activity of flavonoids with antibiotics against drug resistant Staphylococcus aureus

The use of resistance-modifying agents is a potential strategy that is used to prolong the effective life of antibiotics in the face of increasing antibiotic resistance. Since certain flavonoids are potent bacterial efflux pump inhibitors, we assessed morin, rutin, quercetin, hesperidin, and (+)-catechin for their combined activity with the antibiotics ciprofloxacin, tetracycline, erythromycin, oxacillin, and ampicillin against drug-resistant strains of Staphylococcus aureus, including methicillin-resistant S. aureus. Four established methods were used to determine the combined efficacy of each combination: microdilution checkerboard assays, time-kill determinations, the Etest, and dual disc-diffusion methods. The cytotoxicity of the flavonoids was additionally evaluated in a mouse fibroblast cell line. Quercetin and its isomer morin decreased by 3- to 16-fold the minimal inhibitory concentration of ciprofloxacin, tetracycline, and erythromycin against some S. aureus strains. Rutin, hesperidin, and (+)-catechin did not promote any potentiation of antibiotics. Despite the potential cytotoxicity of these phytochemicals at a high concentration (fibroblast IC50 of 41.8 and 67.5mg/L, respectively), quercetin is commonly used as a supplement for several therapeutic purposes. All the methods, with exception of the time-kill assay, presented a high degree of congruence without any apparent strain specificity.This work was supported by Operational Program for Competitiveness Factors—COMPETE, FCT/MEC (PIDDAC), and FEDER through Projects Bioresist—PTDC/EBB-EBI/ 105085/2008; Phytodisinfectants—PTDC/DTP-SAP/1078/ 2012 (COMPETE: FCOMP-01-0124-FEDER-028765) and the PhD grants awarded to Ana Abreu (SFRH/BD/84393/ 2012) and Anabela Borges (SFRH/BD/63398/2009). The authors are very grateful to Professor Simon Gibbons (De- partment of Pharmaceutical and Biological Chemistry, The School of Pharmacy, UCL School of Pharmacy, London) for providing the bacterial strains.info:eu-repo/semantics/publishedVersio

The K-theoretic Farrell-Jones Conjecture for hyperbolic groups

We prove the K-theoretic Farrell-Jones Conjecture for hyperbolic groups with (twisted) coefficients in any associative ring with unit.Comment: 33 pages; final version; to appear in Invent. Mat

Design of a 6 MeV Electron Cooling System for the SSC Medium Energy Booster

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Feasibility of therapeutic drug monitoring of sorafenib in patients with liver or thyroid cancer

Introduction: Sorafenib is a tyrosine-kinase inhibitor approved for the treatment of renal cell carcinoma, hepatocellular carcinoma, thyroid carcinoma, and desmoid fibromatosis. As high inter-individual variability exists in exposure, there is a scientific rationale to pursue therapeutic drug monitoring (TDM). We investigated the feasibility of TDM in patients on sorafenib and tried to identify sub-groups in whom pharmacokinetically (PK) guided-dosing might be of added value. Methods: We included patients who started on sorafenib (between October 2017 and June 2020) at the recommended dose of 400 mg BID or with a step-up dosing schedule. Plasma trough levels (Ctrough) were measured at pre-specified time-points. Increasing the dose was advised if Ctrough was below the target of 3750 ng/mL and toxicity was manageable. Results: A total of 150 samples from 36 patients were collected. Thirty patients (83 %) had a Ctrough below the prespecified target concentration at a certain time point during treatment. Toxicity from sorafenib hampered dosing according to target Ctrough in almost half of the patients. In 11 patients, dosing was adjusted based on Ctrough. In three patients, this resulted in an adequate Ctrough without additional toxicity four weeks after the dose increase. In the remaining eight patients, dose adjustment based on Ctrough did not result in a Ctrough above the target or caused excessive toxicity. Conclusions: TDM for sorafenib is not of added value in daily clinical practice. In most cases, toxicity restricts the possibility of dose escalations.</p

Aflatoxin-Exposure of Vibrio gazogenes as a Novel System for the Generation of Aflatoxin Synthesis Inhibitors

Aflatoxin is a mycotoxin and a secondary metabolite, and the most potent known liver carcinogen that contaminates several important crops, and represents a significant threat to public health and the economy. Available approaches reported thus far have been insufficient to eliminate this threat, and therefore provide the rational to explore novel methods for preventing aflatoxin accumulation in the environment. Many terrestrial plants and microbes that share ecological niches and encounter the aflatoxin producers have the ability to synthesize compounds that inhibit aflatoxin synthesis. However, reports of natural aflatoxin inhibitors from marine ecosystem components that do not share ecological niches with the aflatoxin producers are rare. Here, we show that a non-pathogenic marine bacterium, Vibrio gazogenes, when exposed to low non-toxic doses of aflatoxin B1, demonstrates a shift in its metabolic output and synthesizes a metabolite fraction that inhibits aflatoxin synthesis without affecting hyphal growth in the model aflatoxin producer, Aspergillus parasiticus. The molecular mass of the predominant metabolite in this fraction was also different from the known prodigiosins, which are the known antifungal secondary metabolites synthesized by this Vibrio. Gene expression analyses using RT-PCR demonstrate that this metabolite fraction inhibits aflatoxin synthesis by down-regulating the expression of early-, middle-, and late- growth stage aflatoxin genes, the aflatoxin pathway regulator, aflR and one global regulator of secondary metabolism, laeA. Our study establishes a novel system for generation of aflatoxin synthesis inhibitors, and emphasizes the potential of the under-explored Vibrio’s silent genome for generating new modulators of fungal secondary metabolism

Expression of Plet1 controls interstitial migration of murine small intestinal dendritic cells

Under homeostatic conditions, dendritic cells (DCs) continuously patrol the intestinal lamina propria. Upon antigen encounter, DCs ini

The James Webb Space Telescope mission

Instrumentatio

Spatial and temporal evaluations of the liquid argon purity in ProtoDUNE-SP

Liquid argon time projection chambers (LArTPCs) rely on highly pure argon to ensure that ionization electrons produced by charged particles reach readout arrays. ProtoDUNE Single-Phase (ProtoDUNE-SP) was an approximately 700-ton liquid argon detector intended to prototype the Deep Underground Neutrino Experiment (DUNE) Far Detector Horizontal Drift module. It contains two drift volumes bisected by the cathode plane assembly, which is biased to create an almost uniform electric field in both volumes. The DUNE Far Detector modules must have robust cryogenic systems capable of filtering argon and supplying the TPC with clean liquid. This paper will explore comparisons of the argon purity measured by the purity monitors with those measured using muons in the TPC from October 2018 to November 2018. A new method is introduced to measure the liquid argon purity in the TPC using muons crossing both drift volumes of ProtoDUNE-SP. For extended periods on the timescale of weeks, the drift electron lifetime was measured to be above 30 ms using both systems. A particular focus will be placed on the measured purity of argon as a function of position in the detector

Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours