5,445 research outputs found
The Dormancy Dilemma: Quiescence versus Balanced Proliferation
Metastatic dissemination with subsequent clinical outgrowth leads to the greatest part of morbidity and mortality from most solid tumors. Even more daunting is that many of these metastatic deposits silently lie undetected, recurring years to decades after primary tumor extirpation by surgery or radiation (termed metastatic dormancy). As primary tumors are frequently curable, a critical focus now turns to preventing the lethal emergence from metastatic dormancy. Current carcinoma treatments include adjuvant therapy intended to kill the cryptic metastatic tumor cells. Because such standard therapies mainly kill cycling cells, this approach carries an implicit assumption that metastatic cells are in the mitogenic cycle. Thus, the pivotal question arises as to whether clinically occult micrometastases survive in a state of balanced proliferation and death, or whether these cells undergo at least long periods of quiescence marked by cell-cycle arrest. The treatment implications are thus obvious—if the carcinoma cells are cycling then therapies should target cycling cells, whereas if cells are quiescent then therapies should either maintain dormancy or be toxic to dormant cells. Because this distinction is paramount to rational therapeutic development and administration, we investigated whether quiescence or balanced proliferation is the most likely etiology underlying metastatic dormancy. We recently published a computer simulation study that determined that balanced proliferation is not the likely driving force and that quiescence most likely participates in metastatic dormancy. As such, a greater emphasis on developing diagnostics and therapeutics for quiescent carcinomas is needed.National Institutes of Health (U.S.). National Center for Advancing Translational Sciences (Grant UH2TR000496
Enhanced efficiency of solid-state NMR investigations of energy materials using an external automatic tuning/matching (eATM) robot.
We have developed and explored an external automatic tuning/matching (eATM) robot that can be attached to commercial and/or home-built magic angle spinning (MAS) or static nuclear magnetic resonance (NMR) probeheads. Complete synchronization and automation with Bruker and Tecmag spectrometers is ensured via transistor-transistor-logic (TTL) signals. The eATM robot enables an automated "on-the-fly" re-calibration of the radio frequency (rf) carrier frequency, which is beneficial whenever tuning/matching of the resonance circuit is required, e.g. variable temperature (VT) NMR, spin-echo mapping (variable offset cumulative spectroscopy, VOCS) and/or in situ NMR experiments of batteries. This allows a significant increase in efficiency for NMR experiments outside regular working hours (e.g. overnight) and, furthermore, enables measurements of quadrupolar nuclei which would not be possible in reasonable timeframes due to excessively large spectral widths. Additionally, different tuning/matching capacitor (and/or coil) settings for desired frequencies (e.g. Li and P at 117 and 122MHz, respectively, at 7.05 T) can be saved and made directly accessible before automatic tuning/matching, thus enabling automated measurements of multiple nuclei for one sample with no manual adjustment required by the user. We have applied this new eATM approach in static and MAS spin-echo mapping NMR experiments in different magnetic fields on four energy storage materials, namely: (1) paramagnetic Li and P MAS NMR (without manual recalibration) of the Li-ion battery cathode material LiFePO; (2) paramagnetic O VT-NMR of the solid oxide fuel cell cathode material LaNiO; (3) broadband Nb static NMR of the Li-ion battery material BNbO; and (4) broadband static I NMR of a potential Li-air battery product LiIO. In each case, insight into local atomic structure and dynamics arises primarily from the highly broadened (1-25MHz) NMR lineshapes that the eATM robot is uniquely suited to collect. These new developments in automation of NMR experiments are likely to advance the application of in and ex situ NMR investigations to an ever-increasing range of energy storage materials and systems.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 655444 (O.P.). D.M.H. acknowledges funding from the Cambridge Commonwealth Trusts. J.L. gratefully acknowledges Trinity College, Cambridge (UK) for funding. K.J.G. gratefully acknowledges funding from the Winston Churchill Foundation of the United States and the Herchel Smith Scholarship. M.B. is the CEO of NMR Service GmbH (Erfurt, Germany), which manufactures the eATM device; M.B. acknowledges funding of the Central Innovation Programme for small and medium-sized enterprises (SMEs; Zentrales Innovationsprogramm Mittelstand, ZIM) of the German Federal Ministry of Economic Affairs and Energy (Bundesministerium für Wirtschaft und Energie, BMWi) under the Grant No. KF 2845501UWF. DFT calculations were performed on (1) the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council and (2) the Center for Functional Nanomaterials cluster, Brookhaven National Laboratory, which is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, under Contract No. DE-AC02-98CH10886
Monocyte-mediated Tumoricidal Activity via the Tumor Necrosis Factor–related Cytokine, TRAIL
TRAIL (tumor necrosis factor [TNF]-related apoptosis-inducing ligand) is a molecule that displays potent antitumor activity against selected targets. The results presented here demonstrate that human monocytes rapidly express TRAIL, but not Fas ligand or TNF, after activation with interferon (IFN)-γ or -α and acquire the ability to kill tumor cells. Monocyte-mediated tumor cell apoptosis was TRAIL specific, as it could be inhibited with soluble TRAIL receptor. Moreover, IFN stimulation caused a concomitant loss of TRAIL receptor 2 expression, which coincides with monocyte acquisition of resistance to TRAIL-mediated apoptosis. These results define a novel mechanism of monocyte-induced cell cytotoxicity that requires TRAIL, and suggest that TRAIL is a key effector molecule in antitumor activity in vivo
Spatial variability of precipitation regimes over Turkey
Turkish annual precipitation regimes are analysed to provide large-scale perspective and redefine precipitation regions. Monthly total precipitation data are employed for 107 stations (1963–2002). Precipitation regime shape (seasonality) and magnitude (size) are classified using a novel multivariate methodology. Six shape and five magnitude classes are identified, which exhibit clear spatial structure. A composite (shape and magnitude) regime classification reveals dominant controls on spatial variability of precipitation. Intra-annual timing and magnitude of precipitation is highly variable due to seasonal shifts in Polar and Subtropical zones and physiographic factors. Nonetheless, the classification methodology is shown to be a powerful tool that identifies physically-interpretable precipitation regions: (1) coastal regimes for Marmara, coastal Aegean, Mediterranean and Black Sea; (2) transitional regimes in continental Aegean and Southeast Anatolia; and (3) inland regimes across central and Eastern Anatolia. This research has practical implications for understanding water resources, which are under ever growing pressure in Turkey
Random field Ising systems on a general hierarchical lattice: Rigorous inequalities
Random Ising systems on a general hierarchical lattice with both, random
fields and random bonds, are considered. Rigorous inequalities between
eigenvalues of the Jacobian renormalization matrix at the pure fixed point are
obtained. These inequalities lead to upper bounds on the crossover exponents
.Comment: LaTeX, 13 pages, figs. 1a,1b,2. To be published in PR
Role of live microbial feed supplements with reference to anaerobic fungi in ruminant productivity: A review
To keep the concept of a safe food supply to the consumers, animal feed industries world over are showing an increasing
interest in the direct-fed microbials (DFM) for improved animal performance in terms of growth or productivity. This becomes
all the more essential in a situation, where a number of the residues of antibiotics and/or other growth stimulants reach in
milk and meat with a number of associated potential risks for the consumers. Hence, in the absence of growth stimulants,
a positive manipulation of the rumen microbial ecosystem to enhance the feedstuff utilization for improved production efficiency
by ruminants has become of much interest to the researchers and entrepreneurs. A few genera of live microbes
(i.e., bacteria, fungi and yeasts in different types of formulations from paste to powder) are infrequently used as DFM for the
domestic ruminants. These DFM products are live microbial feed supplements containing naturally occurring microbes in
the rumen. Among different DFM possibilities, anaerobic rumen fungi (ARF) based additives have been found to improve
ruminant productivity consistently during feeding trials. Administration of ARF during the few trials conducted, led to the
increased weight gain, milk production, and total tract digestibility of feed components in ruminants. Anaerobic fungi in the
rumen display very strong cell-wall degrading cellulolytic and xylanolytic activities through rhizoid development, resulting in
the physical disruption of feed structure paving the way for bacterial action. Significant improvements in the fiber digestibility
were found to coincide with increases in ARF in the rumen indicating their role. Most of the researches based on DFM
have indicated a positive response in nutrient digestion and methane reducing potential during in vivo and/or in vitro supplementation
of ARF as DFM. Therefore, DFM especially ARF will gain popularity but it is necessary that all the strain
Standard operating procedure for curation and clinical interpretation of variants in cancer
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the complexity of the models used to capture clinical knowledge. CIViC (Clinical Interpretation of Variants in Cancer - www.civicdb.org) is a fully open, free-to-use cancer variant interpretation knowledgebase that incorporates highly detailed curation of evidence obtained from peer-reviewed publications and meeting abstracts, and currently holds over 6300 Evidence Items for over 2300 variants derived from over 400 genes. CIViC has seen increased adoption by, and also undertaken collaboration with, a wide range of users and organizations involved in research. To enhance CIViC\u27s clinical value, regular submission to the ClinVar database and pursuit of other regulatory approvals is necessary. For this reason, a formal peer reviewed curation guideline and discussion of the underlying principles of curation is needed. We present here the CIViC knowledge model, standard operating procedures (SOP) for variant curation, and detailed examples to support community-driven curation of cancer variants
SDWFS-MT-1: A Self-Obscured Luminous Supernova at z~0.2
We report the discovery of a six-month-long mid-infrared transient,
SDWFS-MT-1 (aka SN 2007va), in the Spitzer Deep, Wide-Field Survey of the NOAO
Deep Wide-Field Survey Bootes field. The transient, located in a z=0.19 low
luminosity (M_[4.5]~-18.6 mag, L/L_MilkyWay~0.01) metal-poor (12+log(O/H)~7.8)
irregular galaxy, peaked at a mid-infrared absolute magnitude of M_[4.5]~-24.2
in the 4.5 micron Spitzer/IRAC band and emitted a total energy of at least
10^51 ergs. The optical emission was likely fainter than the mid-infrared,
although our constraints on the optical emission are poor because the transient
peaked when the source was "behind" the Sun. The Spitzer data are consistent
with emission by a modified black body with a temperature of ~1350 K. We rule
out a number of scenarios for the origin of the transient such as a Galactic
star, AGN activity, GRB, tidal disruption of a star by a black hole and
gravitational lensing. The most plausible scenario is a supernova exploding
inside a massive, optically thick circumstellar medium, composed of multiple
shells of previously ejected material. If the proposed scenario is correct,
then a significant fraction (~10%) of the most luminous supernova may be
self-enshrouded by dust not only before but also after the supernova occurs.
The spectral energy distribution of the progenitor of such a supernova would be
a slightly cooler version of eta Carina, peaking at 20-30 microns.Comment: 26 pages, 5 figures, 1 table, accepted for publication in Ap
Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions
In any economic analysis, regions or municipalities should not be regarded as isolated spatial units, but rather as highly interrelated small open economies. These spatial interrelations must be considered also when the aim is to forecast economic variables. For example, policy makers need accurate forecasts of the unemployment evolution in order to design short- or long-run local welfare policies. These predictions should then consider the spatial interrelations and dynamics of regional unemployment. In addition, a number of papers have demonstrated the improvement in the reliability of long-run forecasts when spatial dependence is accounted for. We estimate a heterogeneouscoefficients dynamic panel model employing a spatial filter in order to account for spatial heterogeneity and/or spatial autocorrelation in both the levels and the dynamics of unemployment, as well as a spatial vector-autoregressive (SVAR) model. We compare the short-run forecasting performance of these methods, and in particular, we carry out a sensitivity analysis in order to investigate if different number and size of the administrative regions influence their relative forecasting performance. We compute short-run unemployment forecasts in two countries with different administrative territorial divisions and data frequency: Switzerland (26 regions, monthly data for 34 years) and Spain (47 regions, quarterly data for 32 years)
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