© 2020 IOP Publishing Ltd.The Respiration Collector for In Vitro Analysis (ReCIVA) sampler, marketed by Owlstone Medical, provides a step forward in exhaled breath sampling through active sampling directly onto thermal desorption (TD) tubes. Although an improvement to the issues surrounding breath bag sampling, the ReCIVA device, first released in 2015, is a relatively new research and clinical tool that requires further exploration. Here, data are presented comparing two distinct ReCIVA devices. The results, comparing ReCIVA serial numbers #33 and #65, demonstrate that overall statistically insignificant results are obtained via targeted isoprene quantitation (p>0.05). However, when the data are parsed by the TD tube type used to capture breath volatiles, either Tenax TA or the dual bed Tenax/Carbograph 5TD (5TD), a statistical difference (p0.05). Global metabolomics analysis of the guided breathing rate data show more than 87% of the z-scores, comparing high and low breathing rates using both the Tenax and the 5TD tubes, are below the level for significance. Finally, data are provided from a single participant who displayed background levels of isoprene while illustrating levels of acetone consistent with the remaining participants. Collectively, these data support the use of multiple ReCIVA devices for exhaled breath collection and provide evidence for an instance where exhaled isoprene is consistent with background levels. Creative Commons Attribution license.We provide spectroscopic evidence for the charge density wave (CDW) phason mode at ≈ 0.93 THz in the two-leg, spin-1/2 ladders of Sr14Cu24O41using terahertz time-domain spectroscopy. We find that annealing in an oxygen atmosphere or doping with a low concentration of Co (≾1%) does not affect the CDW phason mode. However, Co doping at higher concentrations (10%), wherein the Co enters the ladder layers, destabilizes the CDW. We believe that the suppression of the CDW phase is due to an increase in intraladder overlap integrals through the shrinkage of interplane distance upon Co doping. © 2020 IOP Publishing Ltd.Fibroglandular tissue (FGT) segmentation is a crucial step for quantitative analysis of background parenchymal enhancement (BPE) in MRI, which is useful for breast cancer risk assessment. In this study, we develop an automated deep learning method based on a generative adversarial network (GAN) to identify the FGT region in MRI volumes and evaluate its impact on a specific clinical application. The GAN consists of an improved U-Net as a generator to generate FGT candidate areas and a patch deep convolutional neural network (DCNN) as discriminator to evaluate the authenticity of the synthetic FGT region. The proposed method has two improvements compared to the classical U-Net 1) the improved U-Net is designed to extract more features of the FGT region for a more accurate description of the FGT region; 2) a patch DCNN is designed for discriminating the authenticity of the FGT region generated by the improved U-Net, which makes the segmentation result more stable and accurate. A dataset of 100 three-dimensional radiologist were 0.46±0.15 (best 0.63) based on GAN segmented FGT areas, while the corresponding correlation coefficients were 0.41±0.16 (best 0.60) based on baseline U-Net segmented FGT areas. BPE can be quantified better using the FGT areas segmented by the proposed GAN model than using the FGT areas segmented by the baseline U-Net. © 2020 Institute of Physics and Engineering in Medicine.We report the elongation of embedded Au nanoparticles (NPs) in three different matrices, i.e., amorphous carbon (a-C), indium tin oxide (In1-xSnxOz; ITO) crystal and calcium fluoride (CaF2) crystal, under irradiations of 4 MeV C60+cluster ions and 200 MeV Xe ions. Under 4 MeV C60cluster irradiation, strong sputtering is induced in CaF2layer so that whole the layer was completely lost at a fluence of 5 × 1013ions/cm2.  https://www.selleckchem.com/products/Y-27632.html  Even though, Au NPs were partly observed in the SiO2, probably due to the recoil implantation. Amorphous carbon (a-C) layer exhibits low sputtering loss even under 4 MeV C60irradiation. However, the elongation in a-C layer was low. While ITO layer shows certain decrease in thickness under 4 MeV C60irradiation, large elongation of Au NPs was observed under both 4 MeV C60and 200 MeV Xe irradiation. The ITO layer preserved the crystallinity even after the large elongation was induced. This is the first report of the elongation of metal NPs in a crystalline matrix. © 2020 IOP Publishing Ltd.Inspired by stimuli-tailored dynamic processes that spatiotemporally create structure and function diversity in biology, a new hierarchical patterning strategy is proposed to induce the emergence of complex multidimensional structures via dynamic sacrificial printing of stimuli-responsive hydrogels. Using thermally-responsive gelatin (Gel) and pH-responsive chitosan (Chit) as proof-of-concept materials, we demonstrate that the initially printed sacrificial material (Gel/Chit-H+ hydrogel with a single gelatin network) can be converted dynamically into non-sacrificial material (Gel/Chit-H+-Citr hydrogel with gelatin and electrostatic citrate-chitosan dual-network) under the cues of stimuli (citrate ion). Complex hierarchical structures and functions can be created by controlling either the printing patterns of citrate ink or diffusion time of citrate ion into the Gel/Chit-H+ hydrogel. Specifically, mechanically-anisotropic hydrogel film and cell patterning can be achieved via 2D patterning, complex external and internal 3D structures can be fabricated in stimuli-responsive hydrogel and other hydrogel that is not stimuli-responsive under experimental conditions (also owing to erasable properties of Gel/Chit-H+-Citr hydrogel) via 3D patterning, interconnected or segregated fluidic network can be constructed from the same initial 3D grid structure via 4D patterning. Our method is very simple, safe and generally reagentless, and the products/structures are often erasable, compatible and digestible, which enables advanced fabrication technologies (e.g., additive manufacturing) to be applied to a sustainable materials platform. © 2020 IOP Publishing Ltd.