bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy of chemical and biological slug control measures in response to watering and earthworms
Authors: Dörler Daniel , Scheucher Agnes , Zaller Johann G. 
Published: February 2019

AbstractThe Spanish Slug (Arion vulgaris, formerly known as Arion lusitanicus) is an invasive agricultural and horticultural pest species that causes great damages all over Europe. Numerous options to control this slug are on the market; among the most commonly used are slug pellets containing the active ingredients metaldehyde or iron-III-phosphate and the application of parasitic nematodes (Phasmarhabditis hermaphrodita). These control measures potentially also affect non-target organisms like earthworms (Lumbricidae), which themselves can directly and/or indirectly alter a plant’s susceptibility against slug herbivory. Also, the efficacy of slug control treatments is expected to be influenced by watering. In a greenhouse experiment we investigated the influence of daily watering vs. every third day watering on slug control efficacy and potential interactions with earthworms. We found significant interactions between watering and slug control efficacy. Slug herbivory and biomass decreased after application of slug pellets; metaldehyde was more effective under less frequent watering while iron-III-phosphate was unaffected by watering. Parasitic nematodes had no effect on slug herbivory and biomass production. Earthworm activity was reduced with less frequent watering but did not interact with slug control. We conclude that watering patterns should be considered when choosing slug control measures.
Electron spin relaxations of phosphorus donors in bulk silicon under large electric field
Authors: Park Daniel K. , Park Sejun , Jee Hyejung , Lee Soonchil 
Published: February 2019

AbstractModulation of donor electron wavefunction via electric fields is vital to quantum computing architectures based on donor spins in silicon. For practical and scalable applications, the donor-based qubits must retain sufficiently long coherence times in any realistic experimental conditions. Here, we present pulsed electron spin resonance studies on the longitudinal (T1) and transverse (T2) relaxation times of phosphorus donors in bulk silicon with various electric field strengths up to near avalanche breakdown in high magnetic fields of about 1.2 T and low temperatures of about 8 K. We find that the T1 relaxation time is significantly reduced under large electric fields due to electric current, and T2 is affected as the T1 process can dominate decoherence. Furthermore, we show that the magnetoresistance effect in silicon can be exploited as a means to combat the reduction in the coherence times. While qubit coherence times must be much longer than quantum gate times, electrically accelerated T1 can be found useful when qubit state initialization relies on thermal equilibration.
Quantitative assessment of regional variation in tissue clearing efficiency using optical coherence tomography (OCT) and magnetic resonance imaging (MRI): A feasibility study
Authors: Baek Kwangyeol , Jung Sunwoo , Lee Junwon , Min Eunjung , Jung Woonggyu , Cho Hyungjoon 
Published: February 2019

AbstractTissue clearing has gained attention as a pioneering research tool for imaging of large tissue samples. This technique improves light transmission by reducing light scattering within tissues, either by removing lipids or by replacing water with a high refractive index solution. Although various clearing techniques have been developed, quantitative assessments on clearing efficacy depending on tissue properties are rare. In this study, we developed the quantitative mapping of regional clearing efficacy using mean free path in optical coherence tomography (OCT) and proton density in magnetic resonance imaging (MRI), and demonstrated its feasibility in the brain sample with four representative clearing techniques (benzyl alcohol and benzyl benzoate [BABB], ClearT, Scale, and passive CLARITY technique [PACT]). BABB (solvent-based clearing), involving both refractive index matching and lipid removal, exhibited best optical clearing performance with the highest proton density reduction both in gray and white matter. Lipid-removing techniques such as Scale (aqueous hyperhydration) and PACT (hydrogel embedding) showed higher clearing efficiency in white matter than gray matter in accordance with larger proton density increase in white matter. For ClearT (aqueous-based simple immersion), we observed lowest clearing efficiency in the white matter as well as poor lipid removal reflected in low proton density reduction. Our results showed the feasibility of the regional mapping of clearing efficacy and correlating optical transparency and proton density changes using OCT and MRI from existing tissue clearing techniques. This novel quantitative mapping of clearing efficacy depending on tissue types and clearing methods may be helpful in the development of optimized clearing methods for different biological samples.
Protein SUMOylation regulates insulin secretion at multiple stages
Authors: Davey Jeffrey S. , Carmichael Ruth E. , Craig Tim J. 
Published: February 2019

AbstractType-II Diabetes Mellitus (T2DM) is one of the fastest growing public health issues of modern times, consuming 12% of worldwide health budgets and affecting an estimated 400 million people. A key pathological trait associated with this disease is the failure of normal glucose-stimulated insulin secretion (GSIS) from pancreatic beta cells. Several lines of evidence suggest that vesicle trafficking events such as insulin secretion are regulated by the post-translational modification, SUMOylation, and indeed SUMOylation has been proposed to act as a ‘brake’ on insulin exocytosis. Here, we show that diabetic stimuli which inhibit GSIS are correlated with an increase in cellular protein SUMOylation, and that inhibition of deSUMOylation reduces GSIS. We demonstrate that manipulation of cellular protein SUMOylation levels, by overexpression of several different components of the SUMOylation pathway, have varied and complex effects on GSIS, indicating that SUMOylation regulates this process at multiple stages. We further demonstrate that inhibition of syntaxin1A SUMOylation, via a knockdown-rescue strategy, greatly enhances GSIS. Our data are therefore consistent with the model that SUMOylation acts as a brake on GSIS, and we have identified SUMOylation of syntaxin 1 A as a potential component of this brake. However, our data also demonstrate that the role of SUMOylation in GSIS is complex and may involve many substrates.
Superconducting Diamond on Silicon Nitride for Device Applications
Authors: Bland Henry A. , Thomas Evan L. H. , Klemencic Georgina M. , Mandal Soumen , Morgan David J. , Papageorgiou Andreas , Jones Tyrone G. , Williams Oliver A. 
Published: February 2019

AbstractChemical vapour deposition (CVD) grown nanocrystalline diamond is an attractive material for the fabrication of devices. For some device architectures, optimisation of its growth on silicon nitride is essential. Here, the effects of three pre-growth surface treatments, often employed as cleaning methods, were investigated. Such treatments provide control over the surface charge of the silicon nitride substrate through modification of the surface functionality, allowing for the optimisation of electrostatic diamond seeding densities. Zeta potential measurements and X-ray photoelectron spectroscopy (XPS) were used to analyse the silicon nitride surface following each treatment. Exposing silicon nitride to an oxygen plasma offered optimal surface conditions for the electrostatic self-assembly of a hydrogen-terminated diamond nanoparticle monolayer. The subsequent growth of boron-doped nanocrystalline diamond thin films on modified silicon nitride, under CVD conditions, produced coalesced films for oxygen plasma and solvent treatments, whilst pin-holing of the diamond film was observed following RCA-1 treatment. The sharpest superconducting transition was observed for diamond grown on oxygen plasma treated silicon nitride, demonstrating it to be of the least structural disorder. Modifications to the substrate surface optimise the seeding and growth processes for the fabrication of diamond on silicon nitride devices.
A ferroptosis–based panel of prognostic biomarkers for Amyotrophic Lateral Sclerosis
Authors: Devos David , Moreau Caroline , Kyheng Maeva , Garçon Guillaume , Rolland Anne Sophie , Blasco Hélène , Gelé Patrick , Timothée Lenglet T. , Veyrat-Durebex C. , Corcia Philippe , Dutheil Mary , Bede Peter , Jeromin Andreas , Oeckl Patrick , Otto Markus , Meininger Vincent , Danel-Brunaud Véronique , Devedjian Jean-christophe , Duce James A. , Pradat Pierre François 
Published: February 2019

AbstractAccurate patient stratification into prognostic categories and targeting Amyotrophic Lateral Sclerosis (ALS)-associated pathways may pave the way for promising trials. We evaluated blood-based prognostic indicators using an array of pathological markers. Plasma samples were collected as part of a large, phase III clinical trial (Mitotarget/TRO19622) at months 1, 6, 12 and 18. The ALSFRS-r score was used as a proxy of disease progression to assess the predictive value of candidate biological indicators. First, established clinical predictors were evaluated in all 512 patients. Subsequently, pathologic markers, such as proxies of neuronal integrity (Neurofilament light chain and phosphorylated heavy chain), DNA oxidation (8-oxo-2′-desoxyguanosine), lipid peroxidation (4-hydroxy-2-nonenal, isoprostane), inflammation (interleukin-6) and iron status (ferritin, hepcidin, transferrin) were assessed in a subset of 109 patients that represented the whole cohort. Markers of neuronal integrity, DNA and lipid oxidation, as well as iron status at baseline are accurate predictors of disability at 18-month follow-up. The composite scores of these markers in association with established clinical predictors enable the accurate forecasting of functional decline. The identified four biomarkers are all closely associated with ‘ferroptosis’, a recently discovered form of programmed cell death with promising therapeutic targets. The predictive potential of these pathophysiology-based indicators may offer superior patient stratification for future trials, individualised patient care and resource allocation.
Wavelength-dependent Optical Instability Mechanisms and Decay Kinetics in Amorphous Oxide Thin-Film Devices
Authors: Bae Junyoung , Jeong Inkyung , Lee Sungsik 
Published: February 2019

AbstractWe present a study on decay kinetics for a recovery process depending on the light wavelength selected in optical instability measurements against amorphous In-Ga-Zn-O (a-IGZO) thin-film devices. To quantitatively analyze optically-induced instability behaviors, a stretched exponential function (SEF) and its inverse Laplace transform are employed for a time- and energy-dependent analysis, respectively. The analyzed results indicate that a shorter wavelength light activates electrons largely from the valence band while metastable states are deionized with the respective photon energy (hv). In contrast, a longer wavelength illumination is mainly activating trapped electrons at metastable states, e.g. oxygen defects. In particular, at 500 nm wavelength (hv ~ 2.5 eV), it shows an early persistency with a much higher activation energy. This also implies that the majority of metastable states remain ionized, thus the deionization energy >2.5 eV. However, the decay trend at 600 nm wavelength (hv ~ 2 eV) is found to be less persistent and lower current level compared to the case at 500 nm wavelength, suggesting the ionization energy of metastable states >2 eV. Finally, it is deduced that majority of oxygen defects before the illumination reside within the energy range between 2 eV and 2.5 eV from the conduction band edge.
Machine Learning Methods for Control of Fibre Lasers with Double Gain Nonlinear Loop Mirror
Authors: Kokhanovskiy Alexey , Ivanenko Aleksey , Kobtsev Sergey , Smirnov Sergey , Turitsyn Sergey 
Published: February 2019

AbstractMany types of modern lasers feature nonlinear properties, which makes controlling their operation a challenging engineering problem. In particular, fibre lasers present both high-performance devices that are already used for diverse industrial applications, but also interesting and not yet fully understood nonlinear systems. Fibre laser systems operating at high power often have multiple equilibrium states, and this produces complications with the reproducibility and management of such devices. Self-tuning and feedback-enabled machine learning approaches might define a new era in laser science and technology. The present study is the first to demonstrate experimentally the application of machine learning algorithms for control of the pulsed regimes in an all-normal dispersion, figure-eight fibre laser with two independent amplifying fibre loops. The ability to control the laser operation state by electronically varying two drive currents makes this scheme particularly attractive for implementing machine learning approaches. The self-tuning adjustment of two independent gain levels in the laser cavity enables generation-on-demand pulses with different duration, energy, spectral characteristics and time coherence. We introduce and evaluate the application of several objective functions related to selection of the pulse duration, energy and degree of temporal coherence of the radiation. Our results open up the possibility for new designs of pulsed fibre lasers with robust electronics-managed control.
Dynamic heterogeneity in complex interfaces of soft interface-dominated materials
Authors: Sagis Leonard M. C. , Liu Bingxue , Li Yuan , Essers Jeffrey , Yang Jack , Moghimikheirabadi Ahmad , Hinderink Emma , Berton-Carabin Claire , Schroen Karin 
Published: February 2019

AbstractComplex interfaces stabilized by proteins, polymers or nanoparticles, have a much richer dynamics than those stabilized by simple surfactants. By subjecting fluid-fluid interfaces to step extension-compression deformations, we show that in general these complex interfaces have dynamic heterogeneity in their relaxation response that is well described by a Kohlrausch-Williams-Watts function, with stretch exponent β between 0.4–0.6 for extension, and 0.6–1.0 for compression. The difference in β between expansion and compression points to an asymmetry in the dynamics. Using atomic force microscopy and simulations we prove that the dynamic heterogeneity is intimately related to interfacial structural heterogeneity and show that the dominant mode for stretched exponential relaxation is momentum transfer between bulk and interface, a mechanism which has so far largely been ignored in experimental surface rheology. We describe how its rate constant can be determined using molecular dynamics simulations. These interfaces clearly behave like disordered viscoelastic solids and need to be described substantially different from the 2d homogeneous viscoelastic fluids typically formed by simple surfactants.
Fibroblast origin shapes tissue homeostasis, epidermal differentiation, and drug uptake
Authors: Hausmann Christian , Zoschke Christian , Wolff Christopher , Darvin Maxim E. , Sochorová Michaela , Kováčik Andrej , Wanjiku Barbara , Schumacher Fabian , Tigges Julia , Kleuser Burkhard , Lademann Jürgen , Fritsche Ellen , Vávrová Kateřina , Ma Nan , Schäfer-Korting Monika 
Published: February 2019

AbstractPreclinical studies frequently lack predictive value for human conditions. Human cell-based disease models that reflect patient heterogeneity may reduce the high failure rates of preclinical research. Herein, we investigated the impact of primary cell age and body region on skin homeostasis, epidermal differentiation, and drug uptake. Fibroblasts derived from the breast skin of female 20- to 30-year-olds or 60- to 70-year-olds and fibroblasts from juvenile foreskin (<10 years old) were compared in cell monolayers and in reconstructed human skin (RHS). RHS containing aged fibroblasts differed from its juvenile and adult counterparts, especially in terms of the dermal extracellular matrix composition and interleukin-6 levels. The site from which the fibroblasts were derived appeared to alter fibroblast-keratinocyte crosstalk by affecting, among other things, the levels of granulocyte-macrophage colony-stimulating factor. Consequently, the epidermal expression of filaggrin and e-cadherin was increased in RHS containing breast skin fibroblasts, as were lipid levels in the stratum corneum. In conclusion, the region of the body from which fibroblasts are derived appears to affect the epidermal differentiation of RHS, while the age of the fibroblast donors determines the expression of proteins involved in wound healing. Emulating patient heterogeneity in preclinical studies might improve the treatment of age-related skin conditions.
Quantification of hepatic steatosis in chronic liver disease using novel automated method of second harmonic generation and two-photon excited fluorescence
Authors: Goh George Boon-Bee , Leow Wei Qiang , Liang Shen , Wan Wei Keat , Lim Tony Kiat Hon , Tan Chee Kiat , Chang Pik Eu 
Published: February 2019

AbstractThe presence of hepatic steatosis (HS) is an important histological feature in a variety of liver disease. It is critical to assess HS accurately, particularly where it plays an integral part in defining the disease. Conventional methods of quantifying HS remain semi-quantitative, with potential limitations in precision, accuracy and subjectivity. Second Harmonic Generation (SHG) microscopy is a novel technology using multiphoton imaging techniques with applicability in histological tissue assessment. Using an automated algorithm based on signature SHG parameters, we explored the utility and application of SHG for the diagnosis and quantification of HS. SHG microscopy analysis using GENESIS (HistoIndex, Singapore) was applied on 86 archived liver biopsy samples. Reliability was correlated with 3 liver histopathologists. Data analysis was performed using SPSS. There was minimal inter-observer variability between the 3 liver histopathologists, with an intraclass correlation of 0.92 (95% CI 0.89–0.95; p < 0.001). Good correlation was observed between the histopathologists and automated SHG microscopy assessment of HS with Pearson correlation of 0.93: p < 0.001. SHG microscopy provides a valuable tool for objective, more precise measure of HS using an automated approach. Our study reflects proof of concept evidence for potential future refinement to current conventional histological assessment.
Antitumoral effect of maintained neutrophilia induced by rhG-CSF in a murine model of pancreatic cancer
Authors: Brú A. , Bosch R. , Céspedes M. V. , Carmona-Güedes S. , Pascual E. , Brú I. , Souto J. C. 
Published: February 2019

AbstractAlthough the protumoral functions of polymorphonuclear neutrophils are well known, some now-forgotten studies report antitumoral roles for these cells. The present work examines the antitumoral effect of maintained neutrophilia induced via the injection of recombinant human granulocyte colony stimulating factor (rhG-CSF, 100 μg/kg/day) in a Panc-1 subcutaneous xenograft murine model of pancreatic cancer. This treatment was compared with gemcitabine administration (120 mg/kg every two days) and a saline control (n = 6–7 mice per group). Compared to the controls, both the rhG-CSF- and gemcitabine-treated mice showed significantly suppressed tumor growth by day 4 (p < 0.001 and p = 0.013 respectively). From a mean starting volume of 106.9 ± 3.1 mm3 for all treatment groups, the final mean tumor volumes reached were 282.0 ± 30.7 mm3 for the rhG-CSF-treated mice, 202.6 ± 18.1 mm3 for the gemcitabine-treated mice and 519.4 ± 62.9 mm3 for the control mice (p < 0.004 and p < 0.01, respectively, vs. control). The rhG-CSF-treated tumors showed higher percentage necrosis than those treated with gemcitabine (37.4 ± 4.6 vs. 7.5 ± 3.0; p < 0.001). This is the first report of a clear anti-tumoral effect of rhG-CSF when used in monotherapy against pancreatic cancer. Since rhG-CSF administration is known to be associated with very few adverse events, it may offer an attractive alternative in the clinical treatment of pancreatic cancer.
The impact of fasting on resting state brain networks in mice
Authors: Tsurugizawa Tomokazu , Djemai Boucif , Zalesky Andrew 
Published: February 2019

AbstractFasting is known to influence learning and memory in mice and alter the neural networks that subserve these cognitive functions. We used high-resolution functional MRI to study the impact of fasting on resting-state functional connectivity in mice following 12 h of fasting. The cortex and subcortex were parcellated into 52 subregions and functional connectivity was measured between each pair of subregions in groups of fasted and non-fasted mice. Functional connectivity was globally increased in the fasted group compared to the non-fasted group, with the most significant increases evident between the hippocampus (bilateral), retrosplenial cortex (left), visual cortex (left) and auditory cortex (left). Functional brain networks in the non-fasted group comprised five segregated modules of strongly interconnected subregions, whereas the fasted group comprised only three modules. The amplitude of low frequency fluctuations (ALFF) was decreased in the ventromedial hypothalamus in the fasted group. Correlation in gamma oscillations derived from local field potentials was increased between the left visual and retrosplenial cortices in the fasted group and the power of gamma oscillations was reduced in the ventromedial hypothalamus. These results indicate that fasting induces profound changes in functional connectivity, most likely resulting from altered coupling of neuronal gamma oscillations.
Random-Reaction-Seed Method for Automated Identification of Neurite Elongation and Branching
Authors: Li Alvason Zhenhua , Corey Lawrence , Zhu Jia 
Published: February 2019

AbstractConventional deterministic algorithms (i.e., skeletonization and edge-detection) lack robustness and sensitivity to reliably detect the neurite elongation and branching of low signal-to-noise-ratio microscopy images. Neurite outgrowth experiments produce an enormous number of images that require automated measurement; however, the tracking of neurites is easily lost in the automated process due to the intrinsic variability of neurites (either axon or dendrite) under stimuli. We have developed a stochastic random-reaction-seed (RRS) method to identify neurite elongation and branching accurately and automatically. The random-seeding algorithm of RRS is based on the hidden-Markov-model (HMM) to offer a robust enough way for tracing arbitrary neurite structures, while the reaction-seeding algorithm of RRS secures the efficiency of random seeding. It is noteworthy that RRS is capable of tracing a whole neurite branch by only one initial seed, so that RRS is proficient at quantifying extensive amounts of neurite outgrowth images with noisy background in microfluidic devices of biomedical engineering fields. The method also showed notable performance for reconstructing of net-like structures, and thus is expected to be proficient for biomedical feature extractions in a wide range of applications, such as retinal vessel segmentation and cell membrane profiling in spurious-edge-tissues.