1,032 research outputs found
Private Schools and Queue‐jumping: A reply to White
John White (2016) defends the UK private school system from the accusation that it allows an unfair form of ‘queue jumping’ in university admissions. He offers two responses to this accusation, one based on considerations of harm, and one based on meritocratic distribution of university places. We will argue that neither response succeeds: the queue-jumping argument remains a powerful case against the private school system in the UK. We begin by briefly outlining the queue-jumping argument (§1), before evaluating White’s no-harm (§2) and meritocracy (§3) arguments
A hot cocoon in the ultralong GRB 130925A: hints of a PopIII-like progenitor in a low density wind environment
GRB 130925A is a peculiar event characterized by an extremely long gamma-ray
duration (7 ks), as well as dramatic flaring in the X-rays for
20 ks. After this period, its X-ray afterglow shows an atypical soft
spectrum with photon index 4, as observed by Swift and Chandra,
until s, when XMM-Newton observations uncover a harder spectral
shape with 2.5, commonly observed in GRB afterglows. We find that
two distinct emission components are needed to explain the X-ray observations:
a thermal component, which dominates the X-ray emission for several weeks, and
a non-thermal component, consistent with a typical afterglow. A forward shock
model well describes the broadband (from radio to X-rays) afterglow spectrum at
various epochs. It requires an ambient medium with a very low density wind
profile, consistent with that expected from a low-metallicity blue supergiant
(BSG). The thermal component has a remarkably constant size and a total energy
consistent with those expected by a hot cocoon surrounding the relativistic
jet. We argue that the features observed in this GRB (its ultralong duration,
the thermal cocoon, and the low density wind environment) are associated with a
low metallicity BSG progenitor and, thus, should characterize the class of
ultralong GRBs.Comment: 6 pgs, 3 figs, fig1 revised, ApJL in pres
Gene Network Inference and Biochemical Assessment Delineates GPCR Pathways and CREB Targets in Small Intestinal Neuroendocrine Neoplasia
Small intestinal (SI) neuroendocrine tumors (NET) are increasing in incidence, however little is known about their biology. High throughput techniques such as inference of gene regulatory networks from microarray experiments can objectively define signaling machinery in this disease. Genome-wide co-expression analysis was used to infer gene relevance network in SI-NETs. The network was confirmed to be non-random, scale-free, and highly modular. Functional analysis of gene co-expression modules revealed processes including ‘Nervous system development’, ‘Immune response’, and ‘Cell-cycle’. Importantly, gene network topology and differential expression analysis identified over-expression of the GPCR signaling regulators, the cAMP synthetase, ADCY2, and the protein kinase A, PRKAR1A. Seven CREB response element (CRE) transcripts associated with proliferation and secretion: BEX1, BICD1, CHGB, CPE, GABRB3, SCG2 and SCG3 as well as ADCY2 and PRKAR1A were measured in an independent SI dataset (n = 10 NETs; n = 8 normal preparations). All were up-regulated (p<0.035) with the exception of SCG3 which was not differently expressed. Forskolin (a direct cAMP activator, 10−5 M) significantly stimulated transcription of pCREB and 3/7 CREB targets, isoproterenol (a selective ß-adrenergic receptor agonist and cAMP activator, 10−5 M) stimulated pCREB and 4/7 targets while BIM-53061 (a dopamine D2 and Serotonin [5-HT2] receptor agonist, 10−6 M) stimulated 100% of targets as well as pCREB; CRE transcription correlated with the levels of cAMP accumulation and PKA activity; BIM-53061 stimulated the highest levels of cAMP and PKA (2.8-fold and 2.5-fold vs. 1.8–2-fold for isoproterenol and forskolin). Gene network inference and graph topology analysis in SI NETs suggests that SI NETs express neural GPCRs that activate different CRE targets associated with proliferation and secretion. In vitro studies, in a model NET cell system, confirmed that transcriptional effects are signaled through the cAMP/PKA/pCREB signaling pathway and that a SI NET cell line was most sensitive to a D2 and 5-HT2 receptor agonist BIM-53061.© 2011 Drozdov et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Population-level susceptibility, severity and spread of pandemic influenza: design of, and initial results from, a pre-pandemic and hibernating pandemic phase study using cross-sectional data from the Health Survey for England (HSE)
Background
Assessing severity and spread of a novel influenza strain at the start of a pandemic is critical for informing a targeted and proportional response. It requires community-level studies to estimate the burden of infection and disease. Rapidly initiating such studies in a pandemic is difficult. The study aims to establish an efficient system allowing real-time assessment of population susceptibility, spread of infection and clinical attack rates in the event of a pandemic.
Methods
We developed and appended additional survey questions and specimen collection to the Health Survey for England (HSE) – a large, annual, rolling nationally representative general population survey recruiting throughout the year – to enable rapid population-based surveys of influenza infection and disease during a pandemic. Using these surveys we can assess the spread of the virus geographically, by age and through time. The data generated can also provide denominators for national estimates of case fatality and hospitalisation rates.Phase 1: we compared retrospectively collected HSE illness rates during the first two infection waves of the 2009 pandemic with the Flu Watch study (a prospective community cohort). Monthly and seasonal age-specific rates of illness and proportion vaccinated were compared.Phase 2: we piloted blood specimen and data collection alongside the 2012–13 HSE. We are developing laboratory methods and protocols for real-time serological assays of a novel pandemic influenza virus using these specimens, and automated programmes for analysing and reporting illness and infection rates.Phase 3: during inter-pandemic years, the study enters a holding phase, where it is included in the yearly HSE ethics application and planning procedures, allowing rapid triggering in a pandemic.Phase 4: once retriggered, the study will utilise the methods developed in phase 2 to monitor the severity and spread of the pandemic in real time.
Results
Phase 1: the rates of reported illness during the first two waves in the HSE underestimated the community burden as measured by Flu Watch, but the patterns of illness by age and time were broadly comparable. The extent of underestimation was greatest for HSE participants interviewed later in the year compared with those interviewed closer to the pandemic. Vaccine uptake in the HSE study was comparable to independent national estimates and the Flu Watch study.Phases 2 and 3: illness data and serological samples from 2018 participants were collected in the 2012–13 HSE and transferred to the University College London Hospital. In the 2013 HSE and onwards, this project was included in the annual HSE ethics and planning rounds.
Conclusions
The HSE’s underestimation of illness rates during the first two waves of the pandemic is probably due to recall bias and the limitation of being able to report only one illness when multiple illnesses per season can occur. Changes to the illness questions (reporting only recent illnesses) should help minimise these issues. Additional prospective follow-up could improve measurement of disease incidence. The representative nature of the HSE allows accurate measurements of vaccine uptake.
Study registration
This study is registered as ISRCTN80214280.
Funding
This project was funded by the NIHR Public Health Research programme and will be published in full inPublic Health Research; Vol. 3, No. 6. See the NIHR Journals Library website for further project information
imaging and biomarkers in gastroenteropancreatic neuroendocrine tumor disease management
The complexity of the clinical management of neuroendocrine neoplasia (NEN) is
exacerbated by limitations in imaging modalities and a paucity of clinically
useful biomarkers. Limitations in currently available imaging modalities
reflect difficulties in measuring an intrinsically indolent disease,
resolution inadequacies and inter-/intra-facility device variability and that
RECIST (Response Evaluation Criteria in Solid Tumors) criteria are not optimal
for NEN. Limitations of currently used biomarkers are that they are secretory
biomarkers (chromogranin A, serotonin, neuron-specific enolase and
pancreastatin); monoanalyte measurements; and lack sensitivity, specificity
and predictive capacity. None of them meet the NIH metrics for clinical usage.
A multinational, multidisciplinary Delphi consensus meeting of NEN experts (n
= 33) assessed current imaging strategies and biomarkers in NEN management.
Consensus (>75%) was achieved for 78% of the 142 questions. The panel
concluded that morphological imaging has a diagnostic value. However, both
imaging and current single-analyte biomarkers exhibit substantial limitations
in measuring the disease status and predicting the therapeutic efficacy.
RECIST remains suboptimal as a metric. A critical unmet need is the
development of a clinico-biological tool to provide enhanced information
regarding precise disease status and treatment response. The group considered
that circulating RNA was better than current general NEN biomarkers and
preliminary clinical data were considered promising. It was resolved that
circulating multianalyte mRNA (NETest) had clinical utility in both diagnosis
and monitoring disease status and therapeutic efficacy. Overall, it was
concluded that a combination of tumor spatial and functional imaging with
circulating transcripts (mRNA) would represent the future strategy for real-
time monitoring of disease progress and therapeutic efficacy
Dedicated workspaces: Faster resumption times and reduced cognitive load in sequential multitasking
Studies show that virtual desktops have become a widespread approach to window management within desktop environments. However, despite their success, there is no experimental evidence of their effect on multitasking. In this paper, we present an experimental study incorporating 16 participants in which a traditional Windows 7 environment is compared to one augmented by virtual desktops. Within the experimental condition, each virtual desktop acts as a dedicated workspace devoted to an independent goal-oriented task, as opposed to the control condition where only one single workspace is available to perform the same tasks. Results show that adopting virtual desktops as dedicated workspaces allows for faster task resumption (10 s faster on average) and reduced cognitive load during sequential multitasking. Within our experiment the majority of users already benefited from using dedicated workspaces after three switches to a previously suspended task, as the time lost on setting up workspaces was compensated for by faster subsequent task resumption. These results provide a strong argument for supporting goal-oriented dedicated workspaces within desktop environments
Recommended from our members
Challenges in quantifying changes in the global water cycle
Human influences have likely already impacted the large-scale water cycle but natural variability and observational uncertainty are substantial. It is essential to maintain and improve observational capabilities to better characterize changes. Understanding observed changes to the global water cycle is key to predicting future climate changes and their impacts. While many datasets document crucial variables such as precipitation, ocean salinity, runoff, and humidity, most are uncertain for determining long-term changes. In situ networks provide long time-series over land but are sparse in many regions, particularly the tropics. Satellite and reanalysis datasets provide global coverage, but their long-term stability is lacking. However, comparisons of changes among related variables can give insights into the robustness of observed changes. For example, ocean salinity, interpreted with an understanding of ocean processes, can help cross-validate precipitation. Observational evidence for human influences on the water cycle is emerging, but uncertainties resulting from internal variability and observational errors are too large to determine whether the observed and simulated changes are consistent. Improvements to the in situ and satellite observing networks that monitor the changing water cycle are required, yet continued data coverage is threatened by funding reductions. Uncertainty both in the role of anthropogenic aerosols, and due to large climate variability presently limits confidence in attribution of observed changes
- …
