The energetic consequence of specific dynamic action in southern bluefin tuna Thunnus maccoyii

Copyright © 2007 The Company of BiologistsThe effect of feeding on the rate of oxygen consumption (O2) of four groups of three southern bluefin tuna Thunnus maccoyii (SBT) was examined in a large static respirometer at water temperatures of 18.2-20.3°C. Six feeding events of rations between 2.1-8.5% body mass (%Mb) of Australian sardines (Sardinops neopilchardus) were recorded (two of the groups were fed twice). Before feeding, fish swam between 0.71 and 1.4 body lengths s-1 (BL s-1) and the routine metabolic rate (RMR) was 366±32.5 mg kg-1 h-1 (mean ± s.e.m.). For all trials, O2 was elevated post feeding, presumably as a result of specific dynamic action (SDA). Swimming velocity was also elevated post feeding for periods similar to that of O2 (between 20-45 h, longest for the largest rations). Post feeding swimming velocity increased to between 0.87-2.6 BL s-1 and was also dependent on ration consumed. It is suggested that the purpose of increased post-feeding swimming velocity was to increase ventilation volume as a response to the enhanced metabolic demand associated with SDA. Peak post-prandial O2 increased linearly with ration size to a maximum of 1290 mg kg-1 h-1, corresponding to 2.8 times the RMR. When converted to its energy equivalent, total magnitude of SDA was linearly correlated with ration size to a maximum of 192 kJ kg-1 h-1, and as a proportion of gross energy ingested (SDA coefficient), it averaged 35±2.2%. These results demonstrate that, although the factorial increase of SDA in SBT is similar to that of other fish species, the absolute energetic cost of SDA is much higher. These results support the contention that tuna are energy speculators, gambling high rates of energy expenditure for potentially higher rates of energy returns. The ration that southern bluefin tuna require to equal the combined metabolic costs of SDA and RMR is estimated in this study to be 3.5%Mb of Australian sardines per day.Q. P. Fitzgibbon, R. S. Seymour, D. Ellis and J. Buchana

New results on GP Com

We present high resolution optical and UV spectra of the 46 min orbital period, helium binary, GP Com. Our data contains simultaneous photometric correction which confirms the flaring behaviour observed in previous optical and UV data. In this system all lines show a triple peaked structure where the outer two peaks are associated with the accretion disc around the compact object. The main aim of this paper is to constrain the origin of the central peak, also called ``central spike''. We find that the central spike contributes to the flare spectra indicating that its origin is probably the compact object. We also detect that the central spike moves with orbital phase following an S-wave pattern. The radial velocity semiamplitude of the S-wave is ~10 km/s indicating that its origin is near the centre of mass of the system, which in this case lies very close to the white dwarf. Our resolution is higher than that of previous data which allows us to resolve structure in the central peak of the line. The central spike in three of the HeI lines shows another peak blueshifted with respect to the main peak. We propose that one of the peaks is a neutral helium forbidden transition excited in a high electron density region. This forbidden transition is associated with the permitted one (the stronger peak in two of the lines). The presence of a high electron density region again favours the white dwarf as their origin.Comment: 14 pages, 16 figures. Accepted for publication in A&

Water Vapor Measurements by Howard University Raman Lidar during the WAVES 2006 Campaign

Retrieval of water vapor mixing ratio using the Howard University Raman Lidar is presented with emphasis on three aspects: i) performance of the lidar against collocated radiosondes and Raman lidar, ii) investigation of the atmospheric state variables when poor agreement between lidar and radiosondes values occurred and iii) a comparison with satellite-based measurements. The measurements were acquired during the Water Vapor Validation Experiment Sondes/Satellites 2006 field campaign. Ensemble averaging of water vapor mixing ratio data from ten night-time comparisons with Vaisala RS92 radiosondes shows on average an agreement within 10 % up to approx. 8 km. A similar analysis of lidar-to-lidar data of over 700 profiles revealed an agreement to within 20 % over the first 7 km (10 % below 4 km). A grid analysis, defined in the temperature - relative humidity space, was developed to characterize the lidar - radiosonde agreement and quantitatively localizes regions of strong and weak correlations as a function of altitude, temperature or relative humidity. Three main regions of weak correlation emerge: i) regions of low relative humidity and low temperature, ii) moderate relative humidity at low temperatures and iii) low relative humidity at moderate temperatures. Comparison of Atmospheric InfraRed Sounder and Tropospheric Emission Sounder satellites retrievals of moisture with that of Howard University Raman Lidar showed a general agreement in the trend but the formers miss a lot of the details in atmospheric structure due to their low resolution. A relative difference of about 20 % is usually found between lidar and satellites measurements

Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs

Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to treat individual patients. Here, we present an approach, named Drug Ranking Using ML (DRUML), which uses omics data to produce ordered lists of >400 drugs based on their anti-proliferative efficacy in cancer cells. To reduce noise and increase predictive robustness, instead of individual features, DRUML uses internally normalized distance metrics of drug response as features for ML model generation. DRUML is trained using in-house proteomics and phosphoproteomics data derived from 48 cell lines, and it is verified with data comprised of 53 cellular models from 12 independent laboratories. We show that DRUML predicts drug responses in independent verification datasets with low error (mean squared error < 0.1 and mean Spearman’s rank 0.7). In addition, we demonstrate that DRUML predictions of cytarabine sensitivity in clinical leukemia samples are prognostic of patient survival (Log rank p < 0.005). Our results indicate that DRUML accurately ranks anti-cancer drugs by their efficacy across a wide range of pathologies

Enhancing the early student experience

This paper is concerned with identifying how the early student experience can be enhanced in order to improve levels of student retention and achievement. The early student experience is the focus of this project as the literature has consistently declared the first year to be the most critical in shaping persistence decisions. Programme managers of courses with high and low retention rates have been interviewed to identify activities that appear to be associated with good retention rates. The results show that there are similarities in the way programmes with high retention are run, with these features not being prevalent on programmes with low retention. Recommendations of activities that appear likely to enhance the early student experience are provided

Co-activation of NF-κB and MYC renders cancer cells addicted to IL6 for survival and phenotypic stability

NF-κB and MYC are found co-deregulated in human B and plasma-cell cancers. In physiology, NF-κB is necessary for terminal B-to-plasma cell differentiation, whereas MYC repression is required. It is thus unclear if NF-κB/MYC co-deregulation is developmentally compatible in carcinogenesis and/or impacts cancer cell differentiation state, possibly uncovering unique sensitivities. Using a mouse system to trace cell lineage and oncogene activation we found that NF-κB/MYC co-deregulation originated cancers with a plasmablast-like phenotype, alike human plasmablastic-lymphoma and was linked to t(8;14)[MYC-IGH] multiple myeloma. Notably, in contrast to NF-κB or MYC activation alone, co-deregulation rendered cells addicted to IL6 for survival and phenotypic stability. We propose that conflicting oncogene-driven differentiation pressures can be accommodated at a cost in poorly-differentiated cancers. SIGNIFICANCE: Our studies improve the understanding of cancer pathogenesis by demonstrating that co-deregulation of NF-κB and MYC synergize in forming a cancer with a poorly-differentiated state. The cancers in the mouse system share features with human Plasmablastic lymphoma that has a dismal prognosis and no standard of care, and with t(8;14)[MYC-IGH] Multiple myeloma, which is in overall resistant to standard therapy. Notably, we found that NF-κB and MYC co-deregulation uniquely render cells sensitive to IL6 deprivation, providing a road-map for patient selection. Because of the similarity of the cancers arising in the compound mutant mouse model with that of human Plasmablastic lymphoma and t(8;14)[MYC-IGH] Multiple myeloma, this model could serve in preclinical testing to investigate novel therapies for these hard-to-treat diseases

A multi-gene signature predicts outcome in patients with pancreatic ductal adenocarcinoma.

© 2014 Haider et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Improved usage of the repertoires of pancreatic ductal adenocarcinoma (PDAC) profiles is crucially needed to guide the development of predictive and prognostic tools that could inform the selection of treatment options