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Conservation of animal genetic resources requires regular monitoring and interventions to maintain population size and manage genetic variability. This study uses genealogical information to evaluate the impact of conservation measures in Europe, using (i) data from the Domestic Animal Diversity Information System (DAD-IS) and (ii) a posteriori assessment of the impact of various conservation measures on the genetic variability of 17 at-risk breeds with a wide range of interventions. Analysis of data from DAD-IS showed that 68% of national breed populations reported to receive financial support showed increasing demographic trends, v. 51% for those that did not. The majority of the 17 at-risk breeds have increased their numbers of registered animals over the last 20 years, but the changes in genetic variability per breed have not always matched the trend in population size. These differences in trends observed in the different metrics might be explained by the tensions between interventions to maintain genetic variability, and development initiatives which lead to intensification of selection.
We present very detailed images of the photosphere of an AGB star obtained with the PIONIER instrument, installed at the Very Large Telescope Interferometer (VLTI). The images show a well defined stellar disc populated by a few convective patterns. Thanks to the high precision of the observations we are able to derive the contrast and granulation horizontal scale of the convective pattern for the first time in a direct way. Such quantities are then compared with scaling relations between granule size, effective temperature, and surface gravity that are predicted by simulations of stellar surface convection.
Little is known about potential harmful effects as a consequence of self-guided internet-based cognitive behaviour therapy (iCBT), such as symptom deterioration rates. Thus, safety concerns remain and hamper the implementation of self-guided iCBT into clinical practice. We aimed to conduct an individual participant data (IPD) meta-analysis to determine the prevalence of clinically significant deterioration (symptom worsening) in adults with depressive symptoms who received self-guided iCBT compared with control conditions. Several socio-demographic, clinical and study-level variables were tested as potential moderators of deterioration.
Randomised controlled trials that reported results of self-guided iCBT compared with control conditions in adults with symptoms of depression were selected. Mixed effects models with participants nested within studies were used to examine possible clinically significant deterioration rates.
Thirteen out of 16 eligible trials were included in the present IPD meta-analysis. Of the 3805 participants analysed, 7.2% showed clinically significant deterioration (5.8% and 9.1% of participants in the intervention and control groups, respectively). Participants in self-guided iCBT were less likely to deteriorate (OR 0.62, p < 0.001) compared with control conditions. None of the examined participant- and study-level moderators were significantly associated with deterioration rates.
Self-guided iCBT has a lower rate of negative outcomes on symptoms than control conditions and could be a first step treatment approach for adult depression as well as an alternative to watchful waiting in general practice.
Almost nothing is known about the potential negative effects of Internet-based psychological treatments for depression. This study aims at investigating deterioration and its moderators within randomized trials on Internet-based guided self-help for adult depression, using an individual patient data meta-analyses (IPDMA) approach.
Studies were identified through systematic searches (PubMed, PsycINFO, EMBASE, Cochrane Library). Deterioration in participants was defined as a significant symptom increase according to the reliable change index (i.e. 7.68 points in the CES-D; 7.63 points in the BDI). Two-step IPDMA procedures, with a random-effects model were used to pool data.
A total of 18 studies (21 comparisons, 2079 participants) contributed data to the analysis. The risk for a reliable deterioration from baseline to post-treatment was significantly lower in the intervention v. control conditions (3.36 v. 7.60; relative risk 0.47, 95% confidence interval 0.29–0.75). Education moderated effects on deterioration, with patients with low education displaying a higher risk for deterioration than patients with higher education. Deterioration rates for patients with low education did not differ statistically significantly between intervention and control groups. The benefit–risk ratio for patients with low education indicated that 9.38 patients achieve a treatment response for each patient experiencing a symptom deterioration.
Internet-based guided self-help is associated with a mean reduced risk for a symptom deterioration compared to controls. Treatment and symptom progress of patients with low education should be closely monitored, as some patients might face an increased risk for symptom deterioration. Future studies should examine predictors of deterioration in patients with low education.
Major depressive disorder (MDD) is moderately heritable, however genome-wide association studies (GWAS) for MDD, as well as for related continuous outcomes, have not shown consistent results. Attempts to elucidate the genetic basis of MDD may be hindered by heterogeneity in diagnosis. The Center for Epidemiological Studies Depression (CES-D) scale provides a widely used tool for measuring depressive symptoms clustered in four different domains which can be combined together into a total score but also can be analysed as separate symptom domains.
We performed a meta-analysis of GWAS of the CES-D symptom clusters. We recruited 12 cohorts with the 20- or 10-item CES-D scale (32 528 persons).
One single nucleotide polymorphism (SNP), rs713224, located near the brain-expressed melatonin receptor (MTNR1A) gene, was associated with the somatic complaints domain of depression symptoms, with borderline genome-wide significance (pdiscovery = 3.82 × 10−8). The SNP was analysed in an additional five cohorts comprising the replication sample (6813 persons). However, the association was not consistent among the replication sample (pdiscovery+replication = 1.10 × 10−6) with evidence of heterogeneity.
Despite the effort to harmonize the phenotypes across cohorts and participants, our study is still underpowered to detect consistent association for depression, even by means of symptom classification. On the contrary, the SNP-based heritability and co-heritability estimation results suggest that a very minor part of the variation could be captured by GWAS, explaining the reason of sparse findings.
It is well known that web-based interventions can be effective treatments for depression. However, dropout rates in web-based interventions are typically high, especially in self-guided web-based interventions. Rigorous empirical evidence regarding factors influencing dropout in self-guided web-based interventions is lacking due to small study sample sizes. In this paper we examined predictors of dropout in an individual patient data meta-analysis to gain a better understanding of who may benefit from these interventions.
A comprehensive literature search for all randomized controlled trials (RCTs) of psychotherapy for adults with depression from 2006 to January 2013 was conducted. Next, we approached authors to collect the primary data of the selected studies. Predictors of dropout, such as socio-demographic, clinical, and intervention characteristics were examined.
Data from 2705 participants across ten RCTs of self-guided web-based interventions for depression were analysed. The multivariate analysis indicated that male gender [relative risk (RR) 1.08], lower educational level (primary education, RR 1.26) and co-morbid anxiety symptoms (RR 1.18) significantly increased the risk of dropping out, while for every additional 4 years of age, the risk of dropping out significantly decreased (RR 0.94).
Dropout can be predicted by several variables and is not randomly distributed. This knowledge may inform tailoring of online self-help interventions to prevent dropout in identified groups at risk.
We present in this chapter a description of optical interferometry combining instruments. For that purpose we describe the role of different key functions and give examples of the choice made in current and future instruments in particular at VLTI.
Studying the inner regions of protoplanetary disks (1-10 AU) is of importance to understand the formation of planets and the accretion process feeding the forming central star. Herbig AeBe stars are bright enough to be routinely observed by Near IR interferometers. The data for the fainter T Tauri stars is much more sparse. In this contribution we present the results of our ongoing survey at the VLTI. We used the PIONIER combiner that allows the simultaneous use of 4 telescopes, yielding 6 baselines and 3 independent closure phases at once. PIONIER's integrated optics technology makes it a sensitive instrument. We have observed 22 T Tauri stars so far, the largest survey for T Tauri stars to this date.
Our results demonstrate the very significant contribution of an extended component to the interferometric signal. The extended component is different from source to source and the data, with several baselines, offer a way to improve our knowledge of the disk geometry and/or composition. These results validate an earlier study by Pinte et al. 2008 and show that the dust inner radii of T Tauri disks now appear to be in better agreement with the expected position of the dust sublimation radius, contrary to previous claims.
The close environment of Herbig stars starts to be revealed step by step and it appears to be quite complex. Many physical phenomena interplay: the dust sublimation causing a puffed-up inner rim, a dusty halo, a dusty wind or an inner gaseous component. To investigate more deeply these regions, getting images at the first Astronomical Unit scale is necessary. This has become possible with near infrared instruments on the VLTI. We have developed a new imaging method adapted to young stellar objects where we process separately the stellar component from the rest of the image to reveal the environment by using the spectral differences between these two components. We present the result of this method on the first imaging survey of Herbig stars carried out by PIONIER on the VLTI.
In the course of our VLTI young stellar object PIONIER imaging program, we have identified a strong visibility chromatic dependency that appeared in certain sources. This effect, rising value of visibilities with decreasing wavelengths over one base, is also present in previous published and archival AMBER data. For Herbig AeBe stars, the H band is generally located at the transition between the star and the disk predominance in flux for Herbig AeBe stars. We believe that this phenomenon is responsible for the visibility rise effect. We present a method to correct the visibilities from this effect in order to allow “gray” image reconstruction software, like Mira, to be used. In parallel we probe the interest of carrying an image reconstruction in each spectral channel and then combine them to obtain the final broadband one. As an illustration we apply these imaging methods to MWC158, a (possibly Herbig) B[e] star intensively observed with PIONIER. Finally, we compare our result with a parametric model fitted onto the data.
Resonant coupling of an optical mode confined within a microcavity and an emitter is the basic prerequisite for the observation of Bose-Einstein condensation phenomena and the development of novel optical devices based on cavity polaritons.
We demonstrate highly spatially resolved 2” wafer characterization of the reflectivity and emission properties of a nitride based multi quantum well semi microcavity (i.e. structure without top Bragg reflector) to verify resonant regions. Photoluminescence and reflectivity spectra recorded at the same positions on the wafer exhibit a strong spatial dependence of the multi quantum well emission and the center wavelength of the stop band of the bottom Bragg reflector across the sample. Resonance, i.e., matching of the emission and the center wavelength of the stop band, is found in a region 8 mm off the center of the wafer.
The thickness profile across the AlInN/GaN Bragg reflector and multi quantum well layers was obtained by x-ray mappings over the full wafer. A perfect correlation between the local optical properties and the x-ray thickness distribution is found. Additional transmission electron microscopy investigations indicate a complete crack free structure and smooth interfaces between the layers within the Bragg reflector making the structure appropriate for strong coupling applications.
The use of nanotechnology based materials for chemical sensing has been of great interest since nanocrystalline materials have been shown to offer improved sensor sensitivity, stability, and response time. Several groups are successfully integrating nanostructures such as nanowires into operational sensors. The typical procedure may include random placement (e.g., dispersion, with fine-line patterning techniques used to create functional sensors) or time consuming precise fabrication (e.g., mechanical placement using an atomic force microscope or laser tweezer techniques). Dielectrophoresis has also been utilized, however it can be challenging to achieve good electrical contact of the nanostructures to the underlying electrodes. In this paper we report on a sensor platform that incorporates nanorods in a controlled, efficient, and effective manner. Semiconducting SnO2 nanorods are used as the sensing element for detection of hydrogen (H2) and propylene (C3H6) up to 600oC. Using a novel approach of combining dielectrophoresis with standard microfabrication processing techniques, we have achieved reproducible, time-efficient fabrication of gas sensors with reliable contacts to the SnO2 nanorods used for the detection of gases. The sensor layout is designed to assist in the alignment of the nanorods by selectively enhancing the electric field strength and allowing for the quick production of sensor arrays. The SnO2 nanorods are produced using a thermal evaporation-condensation approach. After growth, nanorods are separated from the resulting material using gravimetric separation. The rods vary in length from 3μm to greater than 10μm, with diameters ranging from 50 to 300nm. Dielectrophoresis is used to align multiple nanorods between electrodes. A second layer of metal is incorporated using standard microfabrication methods immediately after alignment to bury the ends of the rods making contact with the underlying electrodes within another layer of metal. Electrical contact was verified during testing by the response to H2 and C3H6 gases at a range of temperatures. Testing was performed on a stage with temperature control and probes were used for electrical contact. Gas flows into the testing chamber at a flow rate of 4000sccm. Sensor response of normalized current shift, |Igas-Iair|/Iair, was measured at a constant voltage bias. Sensors showed response to both H2 and C3H6. Detection of H2 was achieved at 100oC and response levels improved approximately 12000-fold at 600oC. Detection of C3H6 started at 100oC and improved approximately 10000-fold at 600oC. Detection of at least 200ppm for both gases was achieved at 600oC. Using this novel microfabrication approach, semiconducting SnO2 nanorods integrated into a microsensor platform have been demonstrated and sensing response showed dramatic increases at higher temperatures.