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Background: Most people with common mental health problems do not seek evidence-based psychological interventions. Aims: The aim of this study was to investigate whether monitoring symptoms of depression and anxiety using an app increased treatment-seeking. Method: Three hundred and six people with significant levels of anxiety and depression, none of whom were currently receiving treatment, were randomly allocated to receive either (a) information about local psychological services only, (b) information plus regular symptom monitoring (every 6 days), or (c) information plus open symptom monitoring (monitoring when they felt like it). An app was used to provide information and monitor mood. Results: The proportion of participants who reported receiving treatment after starting the study was 7.2% (10/138) in the information only group, 8.1% (9/111) in the information plus regular monitoring group and 15.8% (9/57) in the information plus open monitoring group. There was a trend for participants who were able to monitor whenever they wished to be more likely to report receiving treatment than people who were only given information about their local treatment services. The impact of the intervention was greatest among participants who intended to seek treatment before taking part. Limitations were that only a small minority of those who downloaded the app completed the study and that the study relied on self-reported measures of treatment-seeking. Conclusions: Symptom monitoring can increase actual treatment-seeking in those with an intention to seek treatment.
During the 2009 influenza pandemic, a rapid assessment of disease severity was a challenge as a significant proportion of cases did not seek medical care; care-seeking behaviour changed and the proportion asymptomatic was unknown. A random-digit-dialling telephone survey was undertaken during the 2011/12 winter season in England and Wales to address the feasibility of answering these questions. A proportional quota sampling strategy was employed based on gender, age group, geographical location, employment status and level of education. Households were recruited pre-season and re-contacted immediately following peak seasonal influenza activity. The pre-peak survey was undertaken in October 2011 with 1061 individuals recruited and the post-peak telephone survey in March 2012. Eight hundred and thirty-four of the 1061 (78.6%) participants were successfully re-contacted. Their demographic characteristics compared well to national census data. In total, 8.4% of participants self-reported an influenza-like illness (ILI) in the previous 2 weeks, with 3.2% conforming to the World Health Organization (WHO) ILI case definition. In total, 29.6% of the cases reported consulting their general practitioner. 54.1% of the 1061 participants agreed to be re-contacted about providing biological samples. A population-based cohort was successfully recruited and followed up. Longitudinal survey methodology provides a practical tool to assess disease severity during future pandemics.
The Pueblo population of Chaco Canyon during the Bonito Phase (AD 800–1130) employed agricultural strategies and water-management systems to enhance food cultivation in this unpredictable environment. Scepticism concerning the timing and effectiveness of this system, however, remains common. Using optically stimulated luminescence dating of sediments and LiDAR imaging, the authors located Bonito Phase canal features at the far west end of the canyon. Additional ED-XRF and strontium isotope (87Sr/86Sr) analyses confirm the diversion of waters from multiple sources during Chaco’s occupation. The extent of this water-management system raises new questions about social organisation and the role of ritual in facilitating responses to environmental unpredictability.
Standards for organic pig production recommend that growing pigs are maintained on pasture. There is currently no information on the nutritional implications of such a system, since grazing intakes have not been recorded in pigs of this production stage. This study used n-alkane methodology previously validated in sows (Wilson et al., 1999) to measure the herbage intakes of individual pigs under such conditions.
The Taipan galaxy survey (hereafter simply ‘Taipan’) is a multi-object spectroscopic survey starting in 2017 that will cover 2π steradians over the southern sky (δ ≲ 10°, |b| ≳ 10°), and obtain optical spectra for about two million galaxies out to z < 0.4. Taipan will use the newly refurbished 1.2-m UK Schmidt Telescope at Siding Spring Observatory with the new TAIPAN instrument, which includes an innovative ‘Starbugs’ positioning system capable of rapidly and simultaneously deploying up to 150 spectroscopic fibres (and up to 300 with a proposed upgrade) over the 6° diameter focal plane, and a purpose-built spectrograph operating in the range from 370 to 870 nm with resolving power R ≳ 2000. The main scientific goals of Taipan are (i) to measure the distance scale of the Universe (primarily governed by the local expansion rate, H0) to 1% precision, and the growth rate of structure to 5%; (ii) to make the most extensive map yet constructed of the total mass distribution and motions in the local Universe, using peculiar velocities based on improved Fundamental Plane distances, which will enable sensitive tests of gravitational physics; and (iii) to deliver a legacy sample of low-redshift galaxies as a unique laboratory for studying galaxy evolution as a function of dark matter halo and stellar mass and environment. The final survey, which will be completed within 5 yrs, will consist of a complete magnitude-limited sample (i ⩽ 17) of about 1.2 × 106 galaxies supplemented by an extension to higher redshifts and fainter magnitudes (i ⩽ 18.1) of a luminous red galaxy sample of about 0.8 × 106 galaxies. Observations and data processing will be carried out remotely and in a fully automated way, using a purpose-built automated ‘virtual observer’ software and an automated data reduction pipeline. The Taipan survey is deliberately designed to maximise its legacy value by complementing and enhancing current and planned surveys of the southern sky at wavelengths from the optical to the radio; it will become the primary redshift and optical spectroscopic reference catalogue for the local extragalactic Universe in the southern sky for the coming decade.
Due to their extremely small luminosity compared to the stars they orbit, planets outside our own Solar System are extraordinarily difficult to detect directly in optical light. Careful photometric monitoring of distant stars, however, can reveal the presence of exoplanets via the microlensing or eclipsing effects they induce. The international PLANET collaboration is performing such monitoring using a cadre of semi-dedicated telescopes around the world. Their results constrain the number of gas giants orbiting 1–7 AU from the most typical stars in the Galaxy. Upgrades in the program are opening regions of “exoplanet discovery space” – toward smaller masses and larger orbital radii – that are inaccessible to the Doppler velocity technique.
Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster.
We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties.
The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature.
The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127–137)
Temperature fluctuations in the CMB (Cosmic Microwave Background) are a key prediction of cosmological models of structure formation in the early Universe. Observations at the Teide Observatory, Tenerife using radiometers operating at 10, 15 and 33 GHz have revealed individual hot and cold features in the microwave sky at high Galactic latitudes. These well-defined features are not atmospheric or Galactic in origin; they represent the first detection of individual primordial fluctuations in the CMB. Their intensity is defined by an intrinsic rms amplitude of 54−10+14 μK for a model with a coherence angle of 4°. The expected quadrupole term for a Harrison-Zel'dovich spectrum is QRMS–PS = 26 ± 6 μK. When our data at Dec=+40° are compared with the COBE DMR two-year data, the presence of individual features is confirmed. New experiments to detect structure on smaller scales are described.
Beamswitching has been used at 10, 15 and 33 GHz to map the microwave background over the Declination range 30° to 45°, covering more than one steradian of the sky. The beamwidth is 5° and the beam-throw is ±8° at each frequency. The three data sets are used to separate Galactic emission from intrinsic CMB emission. For the scan at Dec = 40° the intrinsic fluctuation level is ΔTrms = 48+21−15 μK on a coherence scale of 4°; the equivalent analysis for a Harrison-Zeldovich model gives a power spectrum normalisation of Qrms = 22+10−6 μK. The value of the fluctuation amplitude calculated from the likelihood analysis of the two-dimensional data set is ΔTrms = 54 ± 13 μK at 10 GHz and 39+8−7 μK at 15 GHz.
This is the official guideline endorsed by the specialty associations involved in the care of head and neck cancer patients in the UK. It discusses the evidence base pertaining to the management of metastatic neck disease in the setting of an unknown primary and provides recommendations on the work up and management for this group of patients receiving cancer care.
•All patients presenting with confirmed cervical lymph node metastatic squamous cell carcinoma and no apparent primary site should undergo:
The ZZ Ceti stars form a class of variable white dwarfs: the hydrogen dominated atmosphere ones, which do pulsate in an instability strip in the effective temperature range 13000K-11500K. We know 22 such ZZ Ceti white dwarfs. Their variations are caused by nonradial g-mode pulsations with periods are in the range 100-1000 seconds.
A subsample of the ZZ Ceti stars shows amplitude variations on time scales of the order of one month. These variations could be driven by nonlinear phenomena.
We review the current status and future prospects of the PLANET collaboration, an international team of astronomers performing high-precision photometric monitoring of microlensing events. Our photometric precision and sampling is characterised and the suitability of the database for variable star studies is discussed. Preliminary results on K-giant stability are presented.
The variability of CD-24 7599 (V=11.48 mag) was discovered by JCC during observing run XCOV7 of the Whole Earth Telescope (WET, Nather et al. 1990) network in February, 1992. The star was observed as an additional target and 117 hours of high-quality temporal spectroscopic observations were obtained.
Our analysis of these data revealed the presence of 7 independent pulsation modes between 27.0 and 38.1 cycles per day (313 – 441 μHz) with semiamplitudes of 2.1 – 10.2 milli-modulation amplitudes (mma). We showed that peaks at linear combination frequencies detected in the power spectra were not due to eigenmodes excited to visible amplitude by resonant mode coupling.
Inverse associations between dairy consumption and CVD have been reported in several epidemiological studies. Our objective was to conduct a meta-analysis of prospective cohort studies of dairy intake and CVD. A comprehensive literature search was conducted to identify studies that reported risk estimates for total dairy intake, individual dairy products, low/full-fat dairy intake, Ca from dairy sources and CVD, CHD and stroke. Random-effects meta-analyses were used to generate summary relative risk estimates (SRRE) for high v. low intake and stratified intake dose–response analyses. Additional dose–response analyses were performed. Heterogeneity was examined in sub-group and sensitivity analyses. In total, thirty-one unique cohort studies were identified and included in the meta-analysis. Several statistically significant SRRE below 1.0 were observed, namely for total dairy intake and stroke (SRRE=0·91; 95 % CI 0·83, 0·99), cheese intake and CHD (SRRE=0·82; 95 % CI 0·72, 0·93) and stroke (SRRE=0·87; 95 % CI 0·77, 0·99), and Ca from dairy sources and stroke (SRRE=0·69; 95 % CI 0·60, 0·81). However, there was little evidence for inverse dose–response relationships between the dairy variables and CHD and stroke after adjusting for within-study covariance. The results of this meta-analysis of prospective cohort studies have shown that dairy consumption may be associated with reduced risks of CVD, although additional data are needed to more comprehensively examine potential dose–response patterns.
Hopes to identify genetic susceptibility loci accounting for the heritability seen in unipolar depression have not been fully realized. Family history remains the ‘gold standard’ for both risk stratification and prognosis in complex phenotypes such as depression. Meanwhile, the physiological mechanisms underlying life-event triggers for depression remain opaque. Epigenetics, comprising heritable changes in gene expression other than alterations of the nucleotide sequence, may offer a way to deepen our understanding of the aetiology and pathophysiology of unipolar depression and optimize treatments. A heuristic target for exploring the relevance of epigenetic changes in unipolar depression is the hypothalamic–pituitary–adrenal (HPA) axis. The glucocorticoid receptor (GR) gene (NR3C1) has been found to be susceptible to epigenetic modification, specifically DNA methylation, in the context of environmental stress such as early life trauma, which is an established risk for depression later in life.
In this paper we discuss the progress that has been made by studies that have investigated the relationship between depression, early trauma, the HPA axis and the NR3C1 gene. Difficulties with the design of these studies are also explored.
Future efforts will need to comprehensively address epigenetic natural histories at the population, tissue, cell and gene levels. The complex interactions between the epigenome, genome and environment, as well as ongoing nosological difficulties, also pose significant challenges.
The work that has been done so far is nevertheless encouraging and suggests potential mechanistic and biomarker roles for differential DNA methylation patterns in NR3C1 as well as novel therapeutic targets.
Gamma-ray burst host galaxies are deficient in molecular gas, and show anomalous metal-poor regions close to GRB positions. Using recent Australia Telescope Compact Array (ATCA) Hi observations we show that they have substantial atomic gas reservoirs. This suggests that star formation in these galaxies may be fuelled by recent inflow of metal-poor atomic gas. While this process is debated, it can happen in low-metallicity gas near the onset of star formation because gas cooling (necessary for star formation) is faster than the Hi-to-H2 conversion.
Attentional impairment is a core cognitive feature of major depressive disorder (MDD) and bipolar disorder (BD). However, little is known of the characteristics of response time (RT) distributions from attentional tasks. This is crucial to furthering our understanding of the profile and extent of cognitive intra-individual variability (IIV) in mood disorders.
A computerized sustained attention task was administered to 138 healthy controls and 158 patients with a mood disorder: 86 euthymic BD, 33 depressed BD and 39 medication-free MDD patients. Measures of IIV, including individual standard deviation (iSD) and coefficient of variation (CoV), were derived for each participant. Ex-Gaussian (and Vincentile) analyses were used to characterize the RT distributions into three components: mu and sigma (mean and standard deviation of the Gaussian portion of the distribution) and tau (the ‘slow tail’ of the distribution).
Compared with healthy controls, iSD was increased significantly in all patient samples. Due to minimal changes in average RT, CoV was only increased significantly in BD depressed patients. Ex-Gaussian modelling indicated a significant increase in tau in euthymic BD [Cohen's d = 0.39, 95% confidence interval (CI) 0.09–0.69, p = 0.011], and both sigma (d = 0.57, 95% CI 0.07–1.05, p = 0.025) and tau (d = 1.14, 95% CI 0.60–1.64, p < 0.0001) in depressed BD. The mu parameter did not differ from controls.
Increased cognitive variability may be a core feature of mood disorders. This is the first demonstration of differences in attentional RT distribution parameters between MDD and BD, and BD depression and euthymia. These data highlight the utility of applying measures of IIV to characterize neurocognitive variability and the great potential for future application.