The Spitzer Survey of Interstellar Clouds in the Gould Belt. VI. The Auriga-California Molecular Cloud observed with IRAC and MIPS

We present observations of the Auriga-California Molecular Cloud (AMC) at 3.6, 4.5, 5.8, 8.0, 24, 70 and 160 micron observed with the IRAC and MIPS detectors as part of the Spitzer Gould Belt Legacy Survey. The total mapped areas are 2.5 sq-deg with IRAC and 10.47 sq-deg with MIPS. This giant molecular cloud is one of two in the nearby Gould Belt of star-forming regions, the other being the Orion A Molecular Cloud (OMC). We compare source counts, colors and magnitudes in our observed region to a subset of the SWIRE data that was processed through our pipeline. Using color-magnitude and color-color diagrams, we find evidence for a substantial population of 166 young stellar objects (YSOs) in the cloud, many of which were previously unknown. Most of this population is concentrated around the LkHalpha 101 cluster and the filament extending from it. We present a quantitative description of the degree of clustering and discuss the fraction of YSOs in the region with disks relative to an estimate of the diskless YSO population. Although the AMC is similar in mass, size and distance to the OMC, it is forming about 15 - 20 times fewer stars.Comment: (30 pages, 17 figures (2 multipage figures), accepted for publication in ApJ

Sleep, circadian rhythm, and physical activity patterns in depressive and anxiety disorders:A 2-week ambulatory assessment study

BACKGROUND: Actigraphy may provide a more valid assessment of sleep, circadian rhythm (CR), and physical activity (PA) than self-reported questionnaires, but has not been used widely to study the association with depression/anxiety and their clinical characteristics. METHODS: Fourteen-day actigraphy data of 359 participants with current (n = 93), remitted (n = 176), or no (n = 90) composite international diagnostic interview depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Objective estimates included sleep duration (SD), sleep efficiency, relative amplitude (RA) between day-time and night-time activity, mid sleep on free days (MSF), gross motor activity (GMA), and moderate-to-vigorous PA (MVPA). Self-reported measures included insomnia rating scale, SD, MSF, metabolic equivalent total, and MVPA. RESULTS: Compared to controls, individuals with current depression/anxiety had a significantly different objective, but not self-reported, PA and CR: lower GMA (23.83 vs. 27.4 milli-gravity/day, p = .022), lower MVPA (35.32 vs. 47.64 min/day, p = .023), lower RA (0.82 vs. 0.83, p = .033). In contrast, self-reported, but not objective, sleep differed between people with current depression/anxiety compared to those without current disorders; people with current depression/anxiety reported both shorter and longer SD and more insomnia. More depressive/anxiety symptoms and number of depressive/anxiety diagnoses were associated with larger disturbances of the actigraphy measures. CONCLUSION: Actigraphy provides ecologically valid information on sleep, CR, and PA that enhances data from self-reported questionnaires. As those with more severe or comorbid forms showed the lowest PA and most CR disruptions, the potential for adjunctive behavioral and chronotherapy interventions should be explored, as well as the potential of actigraphy to monitor treatment response to such interventions

Sociodemographic, Health and Lifestyle, Sampling, and Mental Health Determinants of 24-Hour Motor Activity Patterns:Observational Study

Background: Analyzing actigraphy data using standard circadian parametric models and aggregated nonparametric indices may obscure temporal information that may be a hallmark of the circadian impairment in psychiatric disorders. Functional data analysis (FDA) may overcome such limitations by fully exploiting the richness of actigraphy data and revealing important relationships with mental health outcomes. To our knowledge, no studies have extensively used FDA to study the relationship between sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics and daily motor activity patterns assessed with actigraphy in a sample of individuals with and without depression/anxiety. Objective: We aimed to study the association between daily motor activity patterns assessed via actigraphy and (1) sociodemographic, health and lifestyle, and sampling factors, and (2) psychiatric clinical characteristics (ie, presence and severity of depression/anxiety disorders). Methods: We obtained 14-day continuous actigraphy data from 359 participants from the Netherlands Study of Depression and Anxiety with current (n=93), remitted (n=176), or no (n=90) depression/anxiety diagnosis, based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition. Associations between patterns of daily motor activity, quantified via functional principal component analysis (fPCA), and sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics were assessed using generalized estimating equation regressions. For exploratory purposes, function-on-scalar regression (FoSR) was applied to quantify the time-varying association of sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics on daily motor activity. Results: Four components of daily activity patterns captured 77.4% of the variability in the data: overall daily activity level (fPCA1, 34.3% variability), early versus late morning activity (fPCA2, 16.5% variability), biphasic versus monophasic activity (fPCA3, 14.8% variability), and early versus late biphasic activity (fPCA4, 11.8% variability). A low overall daily activity level was associated with a number of sociodemographic, health and lifestyle, and psychopathology variables: older age (P<.001), higher education level (P=.005), higher BMI (P=.009), greater number of chronic diseases (P=.02), greater number of cigarettes smoked per day (P=.02), current depressive and/or anxiety disorders (P=.05), and greater severity of depressive symptoms (P<.001). A high overall daily activity level was associated with work/school days (P=.02) and summer (reference: winter; P=.03). Earlier morning activity was associated with older age (P=.02), having a partner (P=.009), work/school days (P<.001), and autumn and spring (reference: winter; P=.02 and P<.001, respectively). Monophasic activity was associated with older age (P=.005). Biphasic activity was associated with work/school days (P<.001) and summer (reference: winter; P<.001). Earlier biphasic activity was associated with older age (P=.005), work/school days (P<.001), and spring and summer (reference: winter; P<.001 and P=.005, respectively). In FoSR analyses, age, work/school days, and season were the main determinants having a time-varying association with daily motor activity (all P<.05). Conclusions: Features of daily motor activity extracted with fPCA reflect commonly studied factors such as the intensity of daily activity and preference for morningness/eveningness. The presence and severity of depression/anxiety disorders were found to be associated mainly with a lower overall activity pattern but not with the time of the activity. Age, work/school days, and season were the variables most strongly associated with patterns and time of activity, and thus future epidemiological studies on motor activity in depression/anxiety should take these variables into account

The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases.

Model organisms are essential experimental platforms for discovering gene functions, defining protein and genetic networks, uncovering functional consequences of human genome variation, and for modeling human disease. For decades, researchers who use model organisms have relied on Model Organism Databases (MODs) and the Gene Ontology Consortium (GOC) for expertly curated annotations, and for access to integrated genomic and biological information obtained from the scientific literature and public data archives. Through the development and enforcement of data and semantic standards, these genome resources provide rapid access to the collected knowledge of model organisms in human readable and computation-ready formats that would otherwise require countless hours for individual researchers to assemble on their own. Since their inception, the MODs for the predominant biomedical model organisms [Mus sp (laboratory mouse), Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Danio rerio, and Rattus norvegicus] along with the GOC have operated as a network of independent, highly collaborative genome resources. In 2016, these six MODs and the GOC joined forces as the Alliance of Genome Resources (the Alliance). By implementing shared programmatic access methods and data-specific web pages with a unified look and feel, the Alliance is tackling barriers that have limited the ability of researchers to easily compare common data types and annotations across model organisms. To adapt to the rapidly changing landscape for evaluating and funding core data resources, the Alliance is building a modern, extensible, and operationally efficient knowledge commons for model organisms using shared, modular infrastructure

Thermostable DNA Polymerase from a Viral Metagenome Is a Potent RT-PCR Enzyme

Viral metagenomic libraries are a promising but previously untapped source of new reagent enzymes. Deep sequencing and functional screening of viral metagenomic DNA from a near-boiling thermal pool identified clones expressing thermostable DNA polymerase (Pol) activity. Among these, 3173 Pol demonstrated both high thermostability and innate reverse transcriptase (RT) activity. We describe the biochemistry of 3173 Pol and report its use in single-enzyme reverse transcription PCR (RT-PCR). Wild-type 3173 Pol contains a proofreading 3′-5′ exonuclease domain that confers high fidelity in PCR. An easier-to-use exonuclease-deficient derivative was incorporated into a PyroScript RT-PCR master mix and compared to one-enzyme (Tth) and two-enzyme (MMLV RT/Taq) RT-PCR systems for quantitative detection of MS2 RNA, influenza A RNA, and mRNA targets. Specificity and sensitivity of 3173 Pol-based RT-PCR were higher than Tth Pol and comparable to three common two-enzyme systems. The performance and simplified set-up make this enzyme a potential alternative for research and molecular diagnostics

The Design and Implementation of A5146, a Prospective Trial Assessing the Utility of Therapeutic Drug Monitoring Using an Inhibitory Quotient in Antiretroviral-Experienced HIV-Infected Patients

The AIDS Clinical Trials Group designed and implemented a prospective, randomized, strategy trial in antiretroviral-experienced, HIV-infected patients, to evaluate the virologic impact of protease inhibitor dose escalation in response to therapeutic drug monitoring (TDM) with an inhibitory quotient, which integrates both drug exposure and viral drug resistance. In the process of developing this clinical trial several unique challenges were identified that required innovative solutions. The major challenge was the need to integrate resistance testing, pharmacokinetic data, medication adherence, toxicity data, clinical assessments, randomization assignment, and protocol-specified clinical management in a way that could be utilized in real-time by the protocol team, communicated promptly to the clinical sites, and transmitted accurately to the study database. In addition, the protocol team had to address the relative lack of commercially available therapeutic drug monitoring laboratories in the US that were experienced in antiretroviral drug assays, and a lack of familiarity with the principles of pharmacokinetic monitoring at participating clinical sites. This manuscript outlines the rationale for the design of this strategy trial, specific barriers to implementation that were identified, and solutions that were developed, with the hope that these experiences will facilitate the design and conduct of future trials of TDM

Comparison of 3173 Pol to Tth Pol in single enzyme RT-PCR detection of MS2 RNA.

<p>3173 Pol, exonuclease minus (left, red) and <i>Tth</i> Pol (right, green) were used according to manufacturer recommendations to amplify a 10² to 10⁸-fold dilution series of MS2 RNA and a water no target control using primers targeting the 160 bp product from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038371#pone-0038371-g006" target="_blank">Figure 6</a>. <b>A.</b> Electrophoresis 2% agarose gel. Center lane is 100 bp DNA ladder. <b>B.</b> Top: Real-time PCR fluorescence in RFU (relative fluorescence units) vs. PCR cycles and Bottom: melt data in -dRFU/dTemperature vs. Temperature (°C). Blue region indicates melt curves for specific products.</p

Sociodemographic, Health and Lifestyle, Sampling, and Mental Health Determinants of 24-Hour Motor Activity Patterns: Observational Study

Background Analyzing actigraphy data using standard circadian parametric models and aggregated nonparametric indices may obscure temporal information that may be a hallmark of the circadian impairment in psychiatric disorders. Functional data analysis (FDA) may overcome such limitations by fully exploiting the richness of actigraphy data and revealing important relationships with mental health outcomes. To our knowledge, no studies have extensively used FDA to study the relationship between sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics and daily motor activity patterns assessed with actigraphy in a sample of individuals with and without depression/anxiety. Objective We aimed to study the association between daily motor activity patterns assessed via actigraphy and (1) sociodemographic, health and lifestyle, and sampling factors, and (2) psychiatric clinical characteristics (ie, presence and severity of depression/anxiety disorders). Methods We obtained 14-day continuous actigraphy data from 359 participants from the Netherlands Study of Depression and Anxiety with current (n=93), remitted (n=176), or no (n=90) depression/anxiety diagnosis, based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition. Associations between patterns of daily motor activity, quantified via functional principal component analysis (fPCA), and sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics were assessed using generalized estimating equation regressions. For exploratory purposes, function-on-scalar regression (FoSR) was applied to quantify the time-varying association of sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics on daily motor activity. Results Four components of daily activity patterns captured 77.4% of the variability in the data: overall daily activity level (fPCA1, 34.3% variability), early versus late morning activity (fPCA2, 16.5% variability), biphasic versus monophasic activity (fPCA3, 14.8% variability), and early versus late biphasic activity (fPCA4, 11.8% variability). A low overall daily activity level was associated with a number of sociodemographic, health and lifestyle, and psychopathology variables: older age (P&lt;.001), higher education level (P=.005), higher BMI (P=.009), greater number of chronic diseases (P=.02), greater number of cigarettes smoked per day (P=.02), current depressive and/or anxiety disorders (P=.05), and greater severity of depressive symptoms (P&lt;.001). A high overall daily activity level was associated with work/school days (P=.02) and summer (reference: winter; P=.03). Earlier morning activity was associated with older age (P=.02), having a partner (P=.009), work/school days (P&lt;.001), and autumn and spring (reference: winter; P=.02 and P&lt;.001, respectively). Monophasic activity was associated with older age (P=.005). Biphasic activity was associated with work/school days (P&lt;.001) and summer (reference: winter; P&lt;.001). Earlier biphasic activity was associated with older age (P=.005), work/school days (P&lt;.001), and spring and summer (reference: winter; P&lt;.001 and P=.005, respectively). In FoSR analyses, age, work/school days, and season were the main determinants having a time-varying association with daily motor activity (all P&lt;.05). Conclusions Features of daily motor activity extracted with fPCA reflect commonly studied factors such as the intensity of daily activity and preference for morningness/eveningness. The presence and severity of depression/anxiety disorders were found to be associated mainly with a lower overall activity pattern but not with the time of the activity. Age, work/school days, and season were the variables most strongly associated with patterns and time of activity, and thus future epidemiological studies on motor activity in depression/anxiety should take these variables into account. </jats:sec

Biochemical attributes of PyroPhage 3173 Pol.

<p>Biochemical attributes of PyroPhage 3173 Pol.</p