Dynamical ocean forcing of the Madden-Julian Oscillation at lead times of up to five months

We show that a simple three-dimensional ocean model linearised about a resting basic state can accurately simulate the dynamical ocean response to wind forcing by the Madden-Julian Oscillation (MJO). This includes the propagation of equatorial waves in the Indian Ocean, from the generation of oceanic equatorial Kelvin waves to the arrival of downwelling oceanic equatorial Rossby waves in the western Indian Ocean, where they have been shown to trigger MJO convective activity. Simulations with idealised wind forcing suggest that the latitudinal width of this forcing plays a crucial role in determining the potential for such feedbacks. Forcing the model with composite MJO winds accurately captures the global ocean response, demonstrating that the observed ocean dynamical response to the MJO can be interpreted as a linear response to surface wind forcing. The model is then applied to study “primary” Madden-Julian events, which are not immediately preceded by any MJO activity nor by any apparent atmospheric triggers, but have been shown to coincide with the arrival of downwelling oceanic equatorial Rossby waves. Case study simulations show how this oceanic equatorial Rossby wave activity is partly forced by reflection of an oceanic equatorial Kelvin wave triggered by a westerly wind burst 140 days previously, and partly directly forced by easterly wind stress anomalies around 40 days prior to the event. This suggests predictability for primary Madden-Julian events on times scales of up to five months, following the re-emergence of oceanic anomalies forced by winds almost half a year earlier

Experiences following cataract surgery - patient perspectives

PURPOSE: Most patients report being highly satisfied with the outcome of cataract surgery but there are variable reports regarding the impact of cataract surgery on some real-world activities, such as fall rates. We hypothesised that adaptations to changed refractive correction and visual function may cause difficulties in undertaking everyday activities for some patients and used a series of focus groups to explore this issue. METHOD: Qualitative methods were used to explore patients' experiences of their vision following cataract surgery, including adaptation to vision changes and their post-surgical spectacle prescription. Twenty-six participants took part in five focus groups (Mean age = 68.2 ± 11.4 years), and the data were analysed using thematic analysis. RESULTS: We identified three themes. 'Changes to Vision' explores participants' adaptation following cataract surgery. While several had problems with tasks relying on binocular vision, few found them bothersome and they resolved following second eye surgery. Participants described a trial and error approach to solving these problems rather than applying solutions suggested by their eyecare professionals. 'Prescription Restrictions' describes the long-term vision problems that pre-surgery myopic patients experienced as a consequence of becoming emmetropic following surgery and thus needing spectacles for reading and other close work activities, which they did not need before surgery. Very few reported that they had the information or time to make a decision regarding their post-operative correction. 'Information Needs' describes participant's responses to the post-surgical information they were given, and the unmet information need regarding when they can drive following surgery. CONCLUSION: The findings highlight the need for clinicians to provide information on adaptation effects, assist patients to select the refractive outcome that best suits their lifestyle, and provide clear advice about when patients can start driving again. Patients need to be provided with better guidance from clinicians and prescribing guidelines for clinicians would be beneficial, particularly for the period between first- and second-eye surgery

Two real parton contributions to non-singlet kernels for exclusive QCD DGLAP evolution

Results for the two real parton differential distributions needed for implementing a next-to-leading order (NLO) parton shower Monte Carlo are presented. They are also integrated over the phase space in order to provide solid numerical control of the MC codes and for the discussion of the differences between the standard $\bar{MS}$ factorization and Monte Carlo implementation at the level of inclusive NLO evolution kernels. Presented results cover the class of non-singlet diagrams entering into NLO kernels. The classic work of Curci-Furmanski-Pertonzio was used as a guide in the calculations.Comment: 34 pages, 3 figure

VaxiJen: a server for prediction of protective antigens, tumour antigens and subunit vaccines

BACKGROUND: Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach – such as speed and cost efficiency – its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties. RESULTS: Bacterial, viral and tumour protein datasets were used to derive models for prediction of whole protein antigenicity. Every set consisted of 100 known antigens and 100 non-antigens. The derived models were tested by internal leave-one-out cross-validation and external validation using test sets. An additional five training sets for each class of antigens were used to test the stability of the discrimination between antigens and non-antigens. The models performed well in both validations showing prediction accuracy of 70% to 89%. The models were implemented in a server, which we call VaxiJen. CONCLUSION: VaxiJen is the first server for alignment-independent prediction of protective antigens. It was developed to allow antigen classification solely based on the physicochemical properties of proteins without recourse to sequence alignment. The server can be used on its own or in combination with alignment-based prediction methods. It is freely-available online at the URL:

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer

From student to graduate: Four learners’ perspectives of the professional doctorate journey

This paper presents a consideration of the experiences and perspectives of four female academics who are the first graduates of a new Professional Doctorate programme at a university in the South West of England. The authors position themselves simultaneously as researchers and research participants, engaging in collaborative autoethnography to reflect critically on their experiences. Key issues are identified, including the need to navigate some significant shifts in identity throughout the doctorate, and how the course structure and peer relationships supported each of the authors to reach their end goal – the successful completion of their studies. The paper concludes with a discussion of the potential implications of the authors’ experiences for leaders of professional doctorates. These include student/lecturer contracts and actively facilitating opportunities for students to establish relationships for peer support

Spike pattern recognition by supervised classification in low dimensional embedding space

© The Author(s) 2016. This article is published with open access at Springerlink.com under the terms of the Creative Commons Attribution License 4.0, (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Epileptiform discharges in interictal electroencephalography (EEG) form the mainstay of epilepsy diagnosis and localization of seizure onset. Visual analysis is rater-dependent and time consuming, especially for long-term recordings, while computerized methods can provide efficiency in reviewing long EEG recordings. This paper presents a machine learning approach for automated detection of epileptiform discharges (spikes). The proposed method first detects spike patterns by calculating similarity to a coarse shape model of a spike waveform and then refines the results by identifying subtle differences between actual spikes and false detections. Pattern classification is performed using support vector machines in a low dimensional space on which the original waveforms are embedded by locality preserving projections. The automatic detection results are compared to experts’ manual annotations (101 spikes) on a whole-night sleep EEG recording. The high sensitivity (97 %) and the low false positive rate (0.1 min−1), calculated by intra-patient cross-validation, highlight the potential of the method for automated interictal EEG assessment.Peer reviewedFinal Published versio

Evidence of an active volcanic heat source beneath the Pine Island Glacier

Tectonic landforms reveal that the West Antarctic Ice Sheet (WAIS) lies atop a major volcanic rift system. However, identifying subglacial volcanism is challenging. Here we show geochemical evidence of a volcanic heat source upstream of the fast-melting Pine Island Ice Shelf, documented by seawater helium isotope ratios at the front of the Ice Shelf cavity. The localization of mantle helium to glacial meltwater reveals that volcanic heat induces melt beneath the grounded glacier and feeds the subglacial hydrological network crossing the grounding line. The observed transport of mantle helium out of the Ice Shelf cavity indicates that volcanic heat is supplied to the grounded glacier at a rate of ~ 2500 ± 1700 MW, which is ca. half as large as the active Grimsvötn volcano on Iceland. Our finding of a substantial volcanic heat source beneath a major WAIS glacier highlights the need to understand subglacial volcanism, its hydrologic interaction with the marine margins, and its potential role in the future stability of the WAIS