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The goal of pharmacological treatment is a desired response, known as the target effect (e.g. bispectral index of 50). An understanding of the concentration–response relationship (i.e. pharmacodynamics (PD)) can be used to predict the target concentration (e.g. propofol 4 mg/L) required to achieve this target effect in a typical individual . Pharmacokinetic (PK) knowledge (e.g. clearance, volume) then determines the dose that will achieve the target concentration. Each individual, however, is somewhat different and there is variability associated with all parameters used in PK and PD equations (known as models). Covariate information (e.g. weight, age, pathology, drug interactions, pharmacogenomics) can be used to help predict the dose in a specific patient. The Holy Grail of clinical pharmacology is prediction of drug PK and PD in the individual patient (Fig. 4.1) and this requires knowledge of the covariates that contribute to variability .
The Murchison Widefield Array (MWA) is an open access telescope dedicated to studying the low-frequency (80–300 MHz) southern sky. Since beginning operations in mid-2013, the MWA has opened a new observational window in the southern hemisphere enabling many science areas. The driving science objectives of the original design were to observe 21 cm radiation from the Epoch of Reionisation (EoR), explore the radio time domain, perform Galactic and extragalactic surveys, and monitor solar, heliospheric, and ionospheric phenomena. All together
programs recorded 20 000 h producing 146 papers to date. In 2016, the telescope underwent a major upgrade resulting in alternating compact and extended configurations. Other upgrades, including digital back-ends and a rapid-response triggering system, have been developed since the original array was commissioned. In this paper, we review the major results from the prior operation of the MWA and then discuss the new science paths enabled by the improved capabilities. We group these science opportunities by the four original science themes but also include ideas for directions outside these categories.
Perfectionism is a transdiagnostic risk factor across psychopathology. The Clinical Perfectionism Questionnaire (CPQ) was developed to assess change in order to provide clinical utility, but currently the psychometric properties of the CPQ with adolescents is unknown.
To assess the factor structure and construct validity of the CPQ in female adolescents.
The CPQ was administered to 267 females aged 14–19 years of age. Confirmatory factor analysis (CFA) was used to examine the validity of the two-factor model and a second-order factor model. Pearson correlations were used to evaluate the relationships between the CPQ and a wide range of measures of perfectionism, psychopathology and personality traits.
The study demonstrated internal consistency, construct validity and incremental validity of the CPQ in a sample of female adolescents. The CFA in the present study confirmed the two-factor model of the CPQ with Factor 1 relating to perfectionistic strivings and Factor 2 representing perfectionistic concerns. The second-order two factor model indicated no deterioration in fit.
The two-factor model of the CPQ fits with the theoretical definition of clinical perfectionism where the over-dependence of self-worth on achievement and concern over mistakes are key elements. The CPQ is suitable for use with female adolescents in future research that seeks to better understand the role of perfectionism in the range of mental illnesses that impact youth.
A higher incidence of psychotic disorders has been consistently reported among black and other minority ethnic groups, particularly in northern Europe. It is unclear whether these rates have changed over time.
We identified all individuals with a first episode psychosis who presented to adult mental health services between 1 May 2010 and 30 April 2012 and who were resident in London boroughs of Lambeth and Southwark. We estimated age-and-gender standardised incidence rates overall and by ethnic group, then compared our findings to those reported in the Aetiology and Ethnicity of Schizophrenia and Other Psychoses (ÆSOP) study that we carried out in the same catchment area around 10 years earlier.
From 9109 clinical records we identified 558 patients with first episode psychosis. Compared with ÆSOP, the overall incidence rates of psychotic disorder in southeast London have increased from 49.4 (95% confidence interval (CI) 43.6–55.3) to 63.1 (95% CI 57.3–69.0) per 100 000 person-years at risk. However, the overall incidence rate ratios (IRR) were reduced in some ethnic groups: for example, IRR (95% CI) for the black Caribbean group reduced from 6.7 (5.4–8.3) to 2.8 (2.1–3.6) and the ‘mixed’ group from 2.7 (1.8–4.2) to 1.4 (0.9–2.1). In the black African group, there was a negligible difference from 4.1 (3.2–5.3) to 3.5 (2.8–4.5).
We found that incidence rates of psychosis have increased over time, and the IRR varied by the ethnic group. Future studies are needed to investigate more changes over time and determinants of change.
The Murchison Widefield Array (MWA) is an electronically steered low-frequency (<300 MHz) radio interferometer, with a ‘slew’ time less than 8 s. Low-frequency (∼100 MHz) radio telescopes are ideally suited for rapid response follow-up of transients due to their large field of view, the inverted spectrum of coherent emission, and the fact that the dispersion delay between a 1 GHz and 100 MHz pulse is on the order of 1–10 min for dispersion measures of 100–2000 pc/cm3. The MWA has previously been used to provide fast follow-up for transient events including gamma-ray bursts (GRBs), fast radio bursts (FRBs), and gravitational waves, using systems that respond to gamma-ray coordinates network packet-based notifications. We describe a system for automatically triggering MWA observations of such events, based on Virtual Observatory Event standard triggers, which is more flexible, capable, and accurate than previous systems. The system can respond to external multi-messenger triggers, which makes it well-suited to searching for prompt coherent radio emission from GRBs, the study of FRBs and gravitational waves, single pulse studies of pulsars, and rapid follow-up of high-energy superflares from flare stars. The new triggering system has the capability to trigger observations in both the regular correlator mode (limited to ≥0.5 s integrations) and using the Voltage Capture System (VCS, 0.1 ms integration) of the MWA and represents a new mode of operation for the MWA. The upgraded standard correlator triggering capability has been in use since MWA observing semester 2018B (July–Dec 2018), and the VCS and buffered mode triggers will become available for observing in a future semester.
An antimicrobial screen was applied to the cell phones of 26 resident physicians to determine its effects on the phone microbiome and its potential to serve as a selective agent for antibiotic or silver resistance genes. No increase of these genes was observed now was there a shift in the overall microbial community.
Stellarator configurations with reactor relevant energetic particle losses are constructed by simultaneously optimizing for quasisymmetry and an analytically derived metric (
), which attempts to align contours of the second adiabatic invariant,
with magnetic surfaces. Results show that with this optimization scheme it is possible to generate quasihelically symmetric equilibria on the scale of ARIES-CS which completely eliminate all collisionless alpha particle losses within normalized radius
. We show that the best performance is obtained by reducing losses at the trapped–passing boundary. Energetic particle transport can be improved even when neoclassical transport, as calculated using the metric
, is degraded. Several quasihelically symmetric equilibria with different aspect ratios are presented, all with excellent energetic particle confinement.
This work established the feasibility of flexible solution-processed radiation sensors prepared from an organic scintillator (1-phenyl-3-mesityl-2-pyrazoline) and a biocompatible semiconducting polymer (violanthrone-79). Absorbance, steady-state, and time-resolved photoluminescence measurements demonstrated a high efficiency for the transfer of absorbed energy from the scintillator to the semiconductor. Blended nanoparticles containing both materials were fabricated in order to reduce the intermolecular distance between molecules, creating a highly efficient energy transfer pathway. Radiation-sensing devices were then constructed from the materials. These exhibited successful sensitivity for gamma radiation from a 137Cs source that was not present for the control semiconducting polymer alone.
Langmuir circulation, a key turbulent process in the upper ocean, is mechanistically driven and sustained by imposed atmospheric wind stress and surface wave drift. In addition, and specifically in coastal zones, the presence of a mean current – whether associated with tidal currents or large-scale eddies – generates bottom-boundary-layer shear, which further modulates the physical attributes of coastal-zone Langmuir turbulence. We show that the presence of bottom-boundary-layer shear generated by oblique forcing between the mean current, atmospheric drag, and monochromatic wave field direction changes the orientation of the resultant, large-scale Langmuir cells. A model to predict this resultant orientation, based on salient parameters defining the forcing obliquity, is proposed. We also perform a systematic parametric study to isolate the ‘turning’ influence of salient parameters, which reveals that the resultant Langmuir cell orientation is always intermediate to the imposed forces. In order to provide a rigorous basis for the results, we study terms responsible for sustenance of streamwise vorticity, and provide a theoretical justification for the observed results.
A novel disinfectant studied using an EPA protocol demonstrated sustained antimicrobial activity (ie, 3–5 log10 reduction) in 5 minutes after 24 hours for Staphylococcus aureus, vancomycin-resistant Enterococcus, Candida auris, carbapenem-resistant Escherichia coli and antibiotic-susceptible E. coli, and Enterobacter spp. Only ∼2 log10 reduction occurred with carbapenem-resistant Enterobacter spp and K. pneumoniae, and antibiotic-susceptible K. pneumoniae.
Ion-temperature-gradient-driven (ITG) turbulence is compared for two quasi-symmetric (QS) stellarator configurations to determine the relationship between linear growth rates and nonlinear heat fluxes. We focus on the quasi-helically symmetric (QHS) stellarator HSX and the quasi-axisymmetric (QAS) stellarator NCSX. In normalized units, HSX exhibits higher growth rates than NCSX, while heat fluxes in gyro-Bohm units are lower in HSX. These results hold for simulations made with both adiabatic and kinetic electrons. The results show that HSX has a larger number of subdominant modes than NCSX and that eigenmodes are more spatially extended in HSX. We conclude that the consideration of nonlinear physics is necessary to accurately assess the heat flux due to ITG turbulence when comparing QS stellarator equilibria.
The Rio Grande Cone is a major fanlike depositional feature in the continental slope of the Pelotas Basin, Southern Brazil. Two representative sediment cores collected in the Cone area were retrieved using a piston core device. In this work, the organic matter (OM) in the sediments was characterized for a continental vs. marine origin using chemical proxies to help constrain the origin of gas in hydrates. The main contribution of OM was from marine organic carbon based on the stable carbon isotope (δ13C-org) and total organic carbon/total nitrogen ratio (TOC:TN) analyses. In addition, the 14C data showed important information about the origin of the OM and we suggest some factors that could modify the original organic matter and therefore mask the “real” 14C ages: (1) biological activity that could modify the carbon isotopic composition of bulk terrestrial organic matter values, (2) the existence of younger sediments from mass wasting deposits unconformably overlying older sediments, and (3) the deep-sediment-sourced methane contribution due to the input of “old” (>50 ka) organic compounds from migrating fluids.
We analyzed antibiotic use data from 29 southeastern US hospitals over a 5-year period to determine changes in antibiotic use after the fluoroquinolone US Food and Drug Administration (FDA) advisory update in 2016. Fluoroquinolone use declined both before and after the FDA announcement, and the use of select, alternative antibiotics increased after the announcement.
Fluoroquinolones are among the 4 most commonly prescribed antibiotic classes.1,2 Postmarketing reports of serious adverse events linked to fluoroquinolones include tendonitis, neuropathy, hypoglycemia, psychiatric side effects, and possible aortic vessel rupture, leading to safety label changes in July 2008 and August 2013.3 In July 2016, the US Food and Drug Administration (FDA) strengthened the “black box” warning following an initial safety announcement in May 2016, recommending avoidance of fluoroquinolones for uncomplicated infections such as acute exacerbation of chronic bronchitis, uncomplicated urinary tract infections, and acute bacterial sinusitis.4 Concerns over safety and the association with Clostridiodes difficile infection have led inpatient antimicrobial stewardship programs (ASPs) to develop initiatives to promote avoidance of quinolones. The objective of this study was to quantify the effect of the 2016 FDA “black box” update on inpatient antibiotic use among a cohort of southeastern US hospitals.
Social anxiety lies on a continuum, and young adults with elevated symptoms are at risk for developing a range of psychiatric disorders. Yet relatively little is known about the factors that govern the hour-by-hour experience and expression of social anxiety in the real world.
Here we used smartphone-based ecological momentary assessment (EMA) to intensively sample emotional experience across different social contexts in the daily lives of 228 young adults selectively recruited to represent a broad spectrum of social anxiety symptoms.
Leveraging data from over 11 000 real-world assessments, our results highlight the central role of close friends, family members, and romantic partners. The presence of such close companions was associated with enhanced mood, yet socially anxious individuals had fewer confidants and spent less time with the close companions that they do have. Although higher levels of social anxiety were associated with a general worsening of mood, socially anxious individuals appear to derive larger benefits – lower levels of negative affect, anxiety, and depression – from their close companions. In contrast, variation in social anxiety was unrelated to the amount of time spent with strangers, co-workers, and acquaintances; and we uncovered no evidence of emotional hypersensitivity to these less-familiar individuals.
These findings provide a framework for understanding the deleterious consequences of social anxiety in emerging adulthood and set the stage for developing improved intervention strategies.
Recent years have seen an exponential increase in the variety of healthcare data captured across numerous sources. However, mechanisms to leverage these data sources to support scientific investigation have remained limited. In 2013 the Pediatric Heart Network (PHN), funded by the National Heart, Lung, and Blood Institute, developed the Integrated CARdiac Data and Outcomes (iCARD) Collaborative with the goals of leveraging available data sources to aid in efficiently planning and conducting PHN studies; supporting integration of PHN data with other sources to foster novel research otherwise not possible; and mentoring young investigators in these areas. This review describes lessons learned through the development of iCARD, initial efforts and scientific output, challenges, and future directions. This information can aid in the use and optimisation of data integration methodologies across other research networks and organisations.
Data mining is a process of finding correlations and collecting and analysing a huge amount of data in a database to discover patterns or relationships. Flight delay creates significant problems in the present aviation system. Data mining techniques are desired for analysing the performance in which micro-level causes propagate to make system-level patterns of delay. Analysing flight delays is very difficult – both when looking from a historical view as well as when estimating delays with forecast demand. This paper proposes using Decision Tree (DT), Support Vector Machine (SVM), Naive Bayesian (NB), K-nearest neighbour (KNN) and Artificial Neural Network (ANN) to study and analyse delays among aircrafts. The performance of different data mining methods is found in the different regions of the updated datasets on these classifiers. Finally, the result shows a significant variation in the performance of different data mining methods and feature selection for this problem. This paper aims to deal with how data mining techniques can be used to understand difficult aircraft system delays in aviation. Our aim is to develop a classification model for studying and reducing delay using different data mining methods and, in this manner, to show that DT has a greater classification accuracy. The different feature selectors are used in this study in order to reduce the number of initial attributes. Our results clearly demonstrate the value of DT for analysing and visualising how system-level effects happen from subsystem-level causes.