Comprehensive analysis of naturally occurring radionuclides in well water: Isotopic ratios, mitigation, and dose assessment.

In Sweden, around 20 % of the potable water comes from groundwater sources and about one million people drink water from their private wells. In areas with moderate or high abundance of naturally occurring radionuclides in the bedrock, the groundwater could be enhanced with radio and chemically toxic elements such as uranium, radium, lead and polonium. Therefore, this study aims to carry out a comprehensive analysis of the behaviour and radiological impact of naturally occurring radionuclides in well water.

Usefulness and limitations of various detector systems for estimation ofI thyroid activity following an RN event.

Following a radiological or nuclear (RN) event, rapid measurement ofI in members of the public is of utmost importance, and much equipment is needed for a high throughput. In this study, three gamma cameras (GCs), two thyroid uptake meters (TUMs) and one whole-body counter (WBC) were calibrated for activity measurements ofI in the thyroid. Minimum detectable activity was derived for the GCs, the TUMs and the WBC giving that a committed effective dose (CED) in the interval 2.

Nonparametric distributions of tensor-valued Lorentzian diffusion spectra for model-free data inversion in multidimensional diffusion MRI.

Magnetic resonance imaging (MRI) is the method of choice for noninvasive studies of micrometer-scale structures in biological tissues via their effects on the time- and frequency-dependent (restricted) and anisotropic self-diffusion of water. While new designs of time-dependent magnetic field gradient waveforms have enabled disambiguation between different aspects of translational motion that are convolved in traditional MRI methods relying on single pairs of field gradient pulses, data analysis for complex heterogeneous materials remains a challenge. Here, we propose and demonstrate nonparametric distributions of tensor-valued Lorentzian diffusion spectra, or "D(ω) distributions," as a general representation with sufficient flexibility to describe the MRI signal response from a wide range of model systems and biological tissues investigated with modulated gradient waveforms separating and correlating the effects of restricted and anisotropic diffusion.

Integrated transcriptomics- and structure-based drug repositioning identifies drugs with proteasome inhibitor properties.

Computational pharmacogenomics can potentially identify new indications for already approved drugs and pinpoint compounds with similar mechanism-of-action. Here, we used an integrated drug repositioning approach based on transcriptomics data and structure-based virtual screening to identify compounds with gene signatures similar to three known proteasome inhibitors (PIs; bortezomib, MG-132, and MLN-2238). In vitro validation of candidate compounds was then performed to assess proteasomal proteolytic activity, accumulation of ubiquitinated proteins, cell viability, and drug-induced expression in A375 melanoma and MCF7 breast cancer cells.

Multi-omics analysis identifies repurposing bortezomib in the treatment of kidney-, nervous system-, and hematological cancers.

Repurposing of FDA-approved drugs is a quick and cost-effective alternative to de novo drug development. Here, we identify genes involved in bortezomib sensitivity, predict cancer types that may benefit from treatment with bortezomib, and evaluate the mechanism-of-action of bortezomib in breast cancer (BT-474 and ZR-75-30), melanoma (A-375), and glioblastoma (A-172) cells in vitro. Cancer cell lines derived from cancers of the blood, kidney, nervous system, and skin were found to be significantly more sensitive to bortezomib than other organ systems.