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Microlensing towards M31 with MDM data

We report the final analysis of a search for microlensing events in the direction of the Andromeda galaxy, which aimed to probe the MACHO composition of the M31 halo using data collected during the 1998-99 observational campaign at the MDM observatory. In a previous paper, we discussed the results from a first set of observations. Here, we deal with the complete data set, and we take advantage of some INT observations in the 1999-2000 seasons. This merging of data sets taken by different instruments turns out to be very useful, the study of the longer baseline available allowing us to test the uniqueness characteristic of microlensing events. As a result, all the candidate microlensing events previously reported turn out to be variable stars. We further discuss a selection based on different criteria, aimed at the detection of short--duration events. We find three candidates whose positions are consistent with self--lensing events, although the available data do not allow us to conclude unambiguously that they are due to microlensing.Comment: Accepted for publication in Astronomy and Astrophysic

The POINT-AGAPE survey II: An Unrestricted Search for Microlensing Events towards M31

An automated search is carried out for microlensing events using a catalogue of 44554 variable superpixel lightcurves derived from our three-year monitoring program of M31. Each step of our candidate selection is objective and reproducible by a computer. Our search is unrestricted, in the sense that it has no explicit timescale cut. So, it must overcome the awkward problem of distinguishing long-timescale microlensing events from long-period stellar variables. The basis of the selection algorithm is the fitting of the superpixel lightcurves to two different theoretical models, using variable star and blended microlensing templates. Only if microlensing is preferred is an event retained as a possible candidate. Further cuts are made with regard to (i) sampling, (ii) goodness of fit of the peak to a Paczynski curve, (iii) consistency of the microlensing hypothesis with the absence of a resolved source, (iv) achromaticity, (v) position in the colour-magnitude diagram and (vi) signal-to-noise ratio. Our results are reported in terms of first-level candidates, which are the most trustworthy, and second-level candidates, which are possible microlensing but have lower signal-to-noise and are more questionable. The pipeline leaves just 3 first-level candidates, all of which have very short full-width half-maximum timescale (<5 days) and 3 second-level candidates, which have timescales of 31, 36 and 51 days respectively. We also show 16 third-level lightcurves, as an illustration of the events that just fail the threshold for designation as microlensing candidates. They are almost certainly mainly variable stars. Two of the 3 first-level candidates correspond to known events (PA 00-S3 and PA 00-S4) already reported by the POINT-AGAPE project. The remaining first-level candidate is new.Comment: 22 pages, 18 figures, MNRAS, to appea

Early symptoms and sensations as predictors of lung cancer: a machine learning multivariate model.

The aim of this study was to identify a combination of early predictive symptoms/sensations attributable to primary lung cancer (LC). An interactive e-questionnaire comprised of pre-diagnostic descriptors of first symptoms/sensations was administered to patients referred for suspected LC. Respondents were included in the present analysis only if they later received a primary LC diagnosis or had no cancer; and inclusion of each descriptor required ≥4 observations. Fully-completed data from 506/670 individuals later diagnosed with primary LC (n = 311) or no cancer (n = 195) were modelled with orthogonal projections to latent structures (OPLS). After analysing 145/285 descriptors, meeting inclusion criteria, through randomised seven-fold cross-validation (six-fold training set: n = 433; test set: n = 73), 63 provided best LC prediction. The most-significant LC-positive descriptors included a cough that varied over the day, back pain/aches/discomfort, early satiety, appetite loss, and having less strength. Upon combining the descriptors with the background variables current smoking, a cold/flu or pneumonia within the past two years, female sex, older age, a history of COPD (positive LC-association); antibiotics within the past two years, and a history of pneumonia (negative LC-association); the resulting 70-variable model had accurate cross-validated test set performance: area under the ROC curve = 0.767 (descriptors only: 0.736/background predictors only: 0.652), sensitivity = 84.8% (73.9/76.1%, respectively), specificity = 55.6% (66.7/51.9%, respectively). In conclusion, accurate prediction of LC was found through 63 early symptoms/sensations and seven background factors. Further research and precision in this model may lead to a tool for referral and LC diagnostic decision-making

The POINT-AGAPE Survey: Comparing Automated Searches of Microlensing Events toward M31

Searching for microlensing in M31 using automated superpixel surveys raises a number of difficulties which are not present in more conventional techniques. Here we focus on the problem that the list of microlensing candidates is sensitive to the selection criteria or "cuts" imposed and some subjectivity is involved in this. Weakening the cuts will generate a longer list of microlensing candidates but with a greater fraction of spurious ones; strengthening the cuts will produce a shorter list but may exclude some genuine events. We illustrate this by comparing three analyses of the same data-set obtained from a 3-year observing run on the INT in La Palma. The results of two of these analyses have been already reported: Belokurov et al. (2005) obtained between 3 and 22 candidates, depending on the strength of their cuts, while Calchi Novati et al. (2005) obtained 6 candidates. The third analysis is presented here for the first time and reports 10 microlensing candidates, 7 of which are new. Only two of the candidates are common to all three analyses. In order to understand why these analyses produce different candidate lists, a comparison is made of the cuts used by the three groups...Comment: 28 pages, 24 figures, 9 table

Gene expression changes related to immune processes associate with cognitive endophenotypes of schizophrenia

Schizophrenia is a heterogeneous disorder characterized by a spectrum of symptoms and many different underlying causes. Thus, instead of using the broad diagnosis, intermediate phenotypes can be used to possibly decrease the underlying complexity of the disorder. Alongside the classical symptoms of delusions and hallucinations, cognitive deficits are a core feature of schizophrenia. To increase our understanding of the biological processes related to these cognitive deficits, we performed a genome-wide gene expression analysis. A battery of 14 neuropsychological tests was administered to 844 individuals from a Finnish familial schizophrenia cohort. We grouped the applied neuropsychological tests into five factors for further analysis. Cognitive endophenotypes, whole blood mRNA, genotype, and medication use data were studied from 47 individuals. Expression level of several RNA probes were significantly associated with cognitive performance. The factor representing Verbal Working Memory was associated with altered expression levels of 11 probes, of which one probe was also associated with a specific sub-measure of this factor (WMS-R Digit span backward). While, the factor Processing speed was related to one probe, which additionally associated among 55 probes with a specific sub-measure of this factor (WAIS-R Digit symbol). Two probes were associated with the measure recognition memory performance. Enrichment analysis of these differentially expressed probes highlighted immunological processes. Our findings are in line with genome-wide genetic discoveries made in schizophrenia, suggesting that immunological processes may be of biological interest for future drug design towards schizophrenia and the cognitive dysfunctions that underlie it.Peer reviewe

The importance of clinical and labour market histories in psychiatric disability retirement : analysis of the comprehensive Finnish national-level RETIRE data

Objectives Despite the stable incidence of mental disorders in Finland and Europe, mental health-related occupational disability has been increasing. We unveiled the paths to permanent psychiatric disability, recovery, or death, by analysing sequences of labour market participation. Methods The RETIRE register database includes information regarding all persons (n = 42,170) awarded an ICD-10 psychiatric disability pension between 2010 and 2015 in Finland. We identified clusters of typical paths of pre-retirement labour market history. Controlling for major mental disorders, age, and sex, we evaluated factors associated with returning to work (RTW), or death, over a 5-year follow-up period. Results Only 10.5% of the disabled subjects returned to work within the follow-up. Half of them ended up with a permanent disability pension. Seven distinguishable paths to disability were identified. Subjects in the cluster characterized by steady employment were relatively often females, lost their work ability due to affective disorders, and had the highest rate of returning to work (16.3%). Mortality was highest (9%) among the cluster characterized by long-term unemployment. Distributions of major diagnostic groups, as well as age and sex, differed between clusters. After their adjustment in the analysis of RTW or death, the identified labour market history paths prior to losing work ability remained as important independent prognostic factors for both outcomes. Conclusions The complex retirement process involves identifiable clinical and contextual associating factors. Labour market history patterns associate with varying prognoses after psychiatric retirement. Prolonged unemployment appears as a predictor of relatively poor prognoses, whereas employment indicates the opposite.Peer reviewe

Cosmic shear requirements on the wavelength-dependence of telescope point spread functions

Cosmic shear requires high precision measurement of galaxy shapes in the presence of the observational Point Spread Function (PSF) that smears out the image. The PSF must therefore be known for each galaxy to a high accuracy. However, for several reasons, the PSF is usually wavelength dependent, therefore the differences between the spectral energy distribution of the observed objects introduces further complexity. In this paper we investigate the effect of the wavelength-dependence of the PSF, focusing on instruments in which the PSF size is dominated by the diffraction-limit of the telescope and which use broad-band filters for shape measurement. We first calculate biases on cosmological parameter estimation from cosmic shear when the stellar PSF is used uncorrected. Using realistic galaxy and star spectral energy distributions and populations and a simple three-component circular PSF we find that the colour-dependence must be taken into account for the next generation of telescopes. We then consider two different methods for removing the effect (i) the use of stars of the same colour as the galaxies and (ii) estimation of the galaxy spectral energy distribution using multiple colours and using a telescope model for the PSF. We find that both of these methods correct the effect to levels below the tolerances required for per-cent level measurements of dark energy parameters. Comparison of the two methods favours the template-fitting method because its efficiency is less dependent on galaxy redshift than the broad-band colour method and takes full advantage of deeper photometry.Comment: 10 pages, 8 figures, version accepted for publication in MNRA

Classical novae from the POINT-AGAPE microlensing survey of M31 -- I. The nova catalogue

The POINT-AGAPE survey is an optical search for gravitational microlensing events towards the Andromeda Galaxy (M31). As well as microlensing, the survey is sensitive to many different classes of variable stars and transients. Here we describe the automated detection and selection pipeline used to identify M31 classical novae (CNe) and we present the resulting catalogue of 20 CN candidates observed over three seasons. CNe are observed both in the bulge region as well as over a wide area of the M31 disk. Nine of the CNe are caught during the final rise phase and all are well sampled in at least two colours. The excellent light-curve coverage has allowed us to detect and classify CNe over a wide range of speed class, from very fast to very slow. Among the light-curves is a moderately fast CN exhibiting entry into a deep transition minimum, followed by its final decline. We have also observed in detail a very slow CN which faded by only 0.01 mag day$^{-1}$ over a 150 day period. We detect other interesting variable objects, including one of the longest period and most luminous Mira variables. The CN catalogue constitutes a uniquely well-sampled and objectively-selected data set with which to study the statistical properties of classical novae in M31, such as the global nova rate, the reliability of novae as standard-candle distance indicators and the dependence of the nova population on stellar environment. The findings of this statistical study will be reported in a follow-up paper.Comment: 21 pages, 13 figures, re-submitted for publication in MNRAS, typos corrected, references updated, figures 5-9 made cleare