Magnetic fields are ubiquitous in the Universe. The energy density of these fields is typically comparable to the energy density of the fluid motions of the plasma in which they are embedded, making ...magnetic fields essential players in the dynamics of the luminous matter. The standard theoretical model for the origin of these strong magnetic fields is through the amplification of tiny seed fields via turbulent dynamo to the level consistent with current observations. However, experimental demonstration of the turbulent dynamo mechanism has remained elusive, since it requires plasma conditions that are extremely hard to re-create in terrestrial laboratories. Here we demonstrate, using laser-produced colliding plasma flows, that turbulence is indeed capable of rapidly amplifying seed fields to near equipartition with the turbulent fluid motions. These results support the notion that turbulent dynamo is a viable mechanism responsible for the observed present-day magnetization.
The usefulness of pharmacokinetic parameters for glioma grading has been reported based on the perfusion data from parts of entire-tumor volumes. However, the perfusion values may not reflect the ...entire-tumor characteristics. Our aim was to investigate the feasibility of glioma grading by using histogram analyses of pharmacokinetic parameters including the volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue from T1-weighted dynamic contrast-enhanced perfusion MR imaging.
Twenty-eight patients (14 men, 14 women; mean age, 49.75 years; age range, 25-72 years) with histopathologically confirmed gliomas (World Health Organization grade II, n = 7; grade III, n = 8; grade IV, n = 13) were examined before surgery or biopsy with conventional MR imaging and T1-weighted dynamic contrast-enhanced perfusion MR imaging at 3T. Volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue were calculated from the entire-tumor volume. Histogram analyses from these parameters were correlated with glioma grades. The parameters with the best percentile from cumulative histograms were identified by analysis of the area under the curve of the receiver operating characteristic analysis and were compared by using multivariable stepwise logistic regression analysis for distinguishing high- from low-grade gliomas.
All parametric values increased with increasing glioma grade. There were significant differences among the 3 grades in all parameters (P < .01). For the differentiation of high- and low-grade gliomas, the highest area under the curve values were found at the 98th percentile of the volume transfer constant (area under the curve, 0.912; cutoff value, 0.277), the 90th percentile of extravascular extracellular space volume per unit volume of tissue (area under the curve, 0.939; cutoff value, 19.70), and the 84th percentile of blood plasma volume per unit volume of tissue (area under the curve, 0.769; cutoff value, 11.71). The 98th percentile volume transfer constant value was the only variable that could be used to independently differentiate high- and low-grade gliomas in multivariable stepwise logistic regression analysis.
Histogram analysis of pharmacokinetic parameters from whole-tumor volume data can be a useful method for glioma grading. The 98th percentile value of the volume transfer constant was the most significant measure.
We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980-2004) retrospective forecasts performed by 14 climate model systems ...(7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models' MME for the period of 1981-2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial-temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80-90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model's slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.
Aims
For the effective production of 146S particles, which determines foot‐and‐mouth disease (FMD) vaccine efficacy, we aimed to identify the optimal medium that is easy‐to‐use, productive and ...economically affordable for the large‐scale production of FMD vaccine.
Methods and Results
Nine combinations of cell growth media and replacement media were tested for virus propagation. Apart from the replacement strategy, we tested a simple addition strategy involving the addition of 30% v/v of fresh medium to the total spent medium using the Cellvento BHK‐200 (Vento). Unlike other tested media that produced poor yields of 146S particles when the spent media were not eliminated, Vento exhibited high productivity with the 30% addition strategy.
Conclusions
Considering its lower price and media consumption compared to those of other media that require media replacement, the 30% addition strategy of Vento is highly effective. Furthermore, owing to its simple application strategy, it makes the scale‐up process easy and helps in saving the time and labour involved in spent media removal.
Significance and Impact of the Study
Through the first comparative assessment of commercial media for the 146S particle recovery, this study suggests the best practical medium for the industrial‐scale production of FMD vaccines.
The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for ...four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.
Background: This study was to devise a prognostic model for metastatic gastric cancer patients undergoing first-line chemotherapy. Patients and methods: A retrospective analysis was carried out on ...1455 gastric cancer patients, who received first-line chemotherapy from September 1994 to February 2005. Results: At multivariate level, poor prognostic factors were no previous gastrectomy P = 0.003; relative risk (RR), 1.191; 95% confidence interval (CI) 1.061–1.338, albumin <3.6 g/dl (P = <0.001; RR, 1.245; 95% CI 1.106–1.402), alkaline phosphatase >85 U/l (P = <0.001; RR, 1.224; 95% CI 1.092–1.371), Eastern Cooperative Oncology Group performance status of two or more (P = <0.001; RR, 1.690; 95% CI 1.458–1.959), the presence of bone metastases (P = 0.001; RR, 1.460; 95% CI 1.616–1.836), and the presence of ascites (P = <0.001; RR, 1.452; 95% CI 1.295–1.628). Of 1434 patients, 489 patients (34.1%) were categorized as low-risk group (zero to one factors), 889 patients (62.0%) as intermediate-risk group (two to four factors), and 56 patients (3.9%) as high-risk group (five to six factors). Median survival durations for low, intermediate, and high-risk groups were 12.5 months, 7.0 months, and 2.7 months, respectively. Conclusions: This model should facilitate the individual patient risk stratification and thus, more appropriate therapies for each metastatic gastric cancer patient.
A UV‐light‐emitting homojunction ZnO LED is grown by radiofrequency sputtering at high temperature, improving the structural, electrical, and optical properties of the n‐ and p‐type ZnO layers. The ...figure shows a comparison of the electroluminescence spectra of A) a p–n homojunction ZnO LED and B) a ZnO LED with Mg0.1Zn0.9O layers used as energy barrier layers. Such materials are of interest for their potential use in long‐lifetime solid‐state lighting, high‐density information storage, secure communication, and chemical/biological‐agent monitoring.
Nuclear fusion is one of the most attractive alternatives to carbon-dependent energy sources1. Harnessing energy from nuclear fusion in a large reactor scale, however, still presents many scientific ...challenges despite the many years of research and steady advances in magnetic confinement approaches. State-of-the-art magnetic fusion devices cannot yet achieve a sustainable fusion performance, which requires a high temperature above 100 million kelvin and sufficient control of instabilities to ensure steady-state operation on the order oftens of seconds2,3. Here we report experiments at the Korea Superconducting Tokamak Advanced Research4 device producing a plasma fusion regime that satisfies most ofthe above requirements: thanks to abundant fast ions stabilizing the core plasma turbulence, we generate plasmas at a temperature of 100 million kelvin lasting up to 20 seconds without plasma edge instabilities or impurity accumulation. A low plasma density combined with a moderate input power for operation is key to establishing this regime by preserving a high fraction of fast ions. This regime is rarely subject to disruption and can be sustained reliably even without a sophisticated control, and thus represents a promising path towards commercial fusion reactors.
Collisionless shocks can be produced as a result of strong magnetic fields in a plasma flow, and therefore are common in many astrophysical systems. The Weibel instability is one candidate mechanism ...for the generation of sufficiently strong fields to create a collisionless shock. Despite their crucial role in astrophysical systems, observation of the magnetic fields produced by Weibel instabilities in experiments has been challenging. Using a proton probe to directly image electromagnetic fields, we present evidence of Weibel-generated magnetic fields that grow in opposing, initially unmagnetized plasma flows from laser-driven laboratory experiments. Three-dimensional particle-in-cell simulations reveal that the instability efficiently extracts energy from the plasma flows, and that the self-generated magnetic energy reaches a few percent of the total energy in the system. This result demonstrates an experimental platform suitable for the investigation of a wide range of astrophysical phenomena, including collisionless shock formation in supernova remnants, large-scale magnetic field amplification, and the radiation signature from gamma-ray bursts.
Aims
The purpose of this study was to isolate, identify and characterize an antifungal compound from Lactobacillus plantarum KCC‐10 from forage silage with potential beneficial properties.
Methods ...and Results
The 16S rRNA gene‐based phylogenetic affiliation was determined using bioinformatic tools and identified as Lactobacillus sp. KCC‐10 with 100% sequence similarity to L. plantarum. The antifungal substances were extracted with ethyl acetate from spent medium in which Lactobacillus sp. KCC‐10 was cultivated. Antifungal activity was assessed using the broth microdilution technique. The compounds were obtained by eluting the crude extract with various concentrations of solvents followed by chromatographic purification. Based on the infrared, 13C nuclear magnetic resonance (NMR) and 1H NMR spectral data, the compound was identified as a phenolic‐related antibiotic. The minimum inhibitory concentration of the compound against Aspergillus clavatus, A. oryzae, Botrytis elliptica and Scytalidium vaccinii was 2·5 mg ml−1 and that against A. fumigatus, A. niger and S. fusca was 5·0 mg ml−1, respectively. In addition, Lactobacillus sp. KCC‐10 was highly sensitive towards oxgall (0·3%) but grew well in the presence of sodium taurocholate (0·3%). An antimicrobial susceptibility pattern was an intrinsic feature of this strain; thus, consumption does not represent a health risk to humans or animals.
Conclusion
Novel L. plantarum KCC‐10 with antifungal and potential probiotic properties was characterized for use in animal food.
Significance and Impact of the Study
This study revealed that L. plantarum KCC‐10 exhibited good antifungal activity similar to that of probiotic Lactobacillus strains.
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