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Important concepts from the diverse fields of physics, mathematics, engineering and computer science coalesce in this foundational text on the cutting-edge field of quantum information. Designed for undergraduate and graduate students with any STEM background, and written by a highly experienced author team, this textbook draws on quantum mechanics, number theory, computer science technologies, and more, to delve deeply into learning about qubits, the building blocks of quantum information, and how they are used in quantum computing and quantum algorithms. The pedagogical structure of the chapters features exercises after each section as well as focus boxes, giving students the benefit of additional background and applications without losing sight of the big picture. Recommended further reading and answers to select exercises further support learning. Written in approachable and conversational prose, this text offers a comprehensive treatment of the exciting field of quantum information while remaining accessible to students and researchers within all STEM disciplines.
Functional impairment in daily activities, such as work and socializing, is part of the diagnostic criteria for major depressive disorder and most anxiety disorders. Despite evidence that symptom severity and functional impairment are partially distinct, functional impairment is often overlooked. To assess whether functional impairment captures diagnostically relevant genetic liability beyond that of symptoms, we aimed to estimate the heritability of, and genetic correlations between, key measures of current depression symptoms, anxiety symptoms, and functional impairment.
Methods
In 17,130 individuals with lifetime depression or anxiety from the Genetic Links to Anxiety and Depression (GLAD) Study, we analyzed total scores from the Patient Health Questionnaire-9 (depression symptoms), Generalized Anxiety Disorder-7 (anxiety symptoms), and Work and Social Adjustment Scale (functional impairment). Genome-wide association analyses were performed with REGENIE. Heritability was estimated using GCTA-GREML and genetic correlations with bivariate-GREML.
Results
The phenotypic correlations were moderate across the three measures (Pearson’s r = 0.50–0.69). All three scales were found to be under low but significant genetic influence (single-nucleotide polymorphism-based heritability [h2SNP] = 0.11–0.19) with high genetic correlations between them (rg = 0.79–0.87).
Conclusions
Among individuals with lifetime depression or anxiety from the GLAD Study, the genetic variants that underlie symptom severity largely overlap with those influencing functional impairment. This suggests that self-reported functional impairment, while clinically relevant for diagnosis and treatment outcomes, does not reflect substantial additional genetic liability beyond that captured by symptom-based measures of depression or anxiety.
Next-generation X-ray satellite telescopes such as XRISM, NewAthena and Lynx will enable observations of exotic astrophysical sources at unprecedented spectral and spatial resolution. Proper interpretation of these data demands that the accuracy of the models is at least within the uncertainty of the observations. One set of quantities that might not currently meet this requirement is transition energies of various astrophysically relevant ions. Current databases are populated with many untested theoretical calculations. Accurate laboratory benchmarks are required to better understand the coming data. We obtained laboratory spectra of X-ray lines from a silicon plasma at an average spectral resolving power of $\sim$7500 with a spherically bent crystal spectrometer on the Z facility at Sandia National Laboratories. Many of the lines in the data are measured here for the first time. We report measurements of 53 transitions originating from the K-shells of He-like to B-like silicon in the energy range between $\sim$1795 and 1880 eV (6.6–6.9 Å). The lines were identified by qualitative comparison against a full synthetic spectrum calculated with ATOMIC. The average fractional uncertainty (uncertainty/energy) for all reported lines is ${\sim}5.4 \times 10^{-5}$. We compare the measured quantities against transition energies calculated with RATS and FAC as well as those reported in the NIST ASD and XSTAR’s uaDB. Average absolute differences relative to experimentally measured values are 0.20, 0.32, 0.17 and 0.38 eV, respectively. All calculations/databases show good agreement with the experimental values; NIST ASD shows the closest match overall.
Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.
Methods
T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).
Results
PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).
Conclusions
PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.
We compare the Emory 10-item, 4-choice Rey Complex Figure (CF) Recognition task with the Meyers and Lange (M&L) 24-item yes/no CF Recognition task in a large cohort of healthy research participants and in patients with heterogeneous movement disorder diagnoses. While both tasks assess CF recognition, they differ in key aspects including the saliency of target and distractor responses, self-selection versus forced-choice formats, and the length of the item sets.
Participants and Methods:
There were 1056 participants from the Emory Healthy Brain Study (EHBS; average MoCA = 26.8, SD = 2.4) and 223 movement disorder patients undergoing neuropsychological evaluation (average MoCA = 24.3, SD = 4.0).
Results:
Both recognition tasks differentiated between healthy and clinical groups; however, the Emory task demonstrated a larger effect size (Cohen’s d = 1.02) compared to the M&L task (Cohen’s d = 0.79). d-prime scoring of M&L recognition showed comparable group discrimination (Cohen’s d = 0.81). Unidimensional two-parameter logistic item response theory analysis revealed that many M&L items had low discrimination values and extreme difficulty parameters, which contributed to the task’s reduced sensitivity, particularly at lower cognitive proficiency levels relevant to clinical diagnosis. Dimensionality analyses indicated the influence of response sets as a potential contributor to poor item performance.
Conclusions:
Emory CF Recognition task demonstrates superior psychometric properties and greater sensitivity to cognitive impairment compared to the M&L task. Its ability to more precisely measure lower levels of cognitive functioning, along with its brevity, suggests it may be more effective for diagnostic use, especially in clinical populations with cognitive decline.
For Stokes waves in finite depth within the neighbourhood of the Benjamin–Feir stability transition, there are two families of periodic waves, one modulationally unstable and the other stable. In this paper we show that these two families can be joined by a heteroclinic connection, which manifests in the fluid as a travelling front. By shifting the analysis to the setting of Whitham modulation theory, this front is in wavenumber and frequency space. An implication of this jump is that a permanent frequency downshift of the Stokes wave can occur in the absence of viscous effects. This argument, which is built on a sequence of asymptotic expansions of the phase dynamics, is confirmed via energetic arguments, with additional corroboration obtained by numerical simulations of a reduced model based on the Benney–Roskes equation.
Threat sensitivity, an individual difference construct reflecting variation in responsiveness to threats of various types, predicts physiological reactivity to aversive stimuli and shares heritable variance with anxiety disorders in adults. However, no research has been conducted yet with youth to examine the heritability of threat sensitivity or evaluate the role of genetic versus environmental influences in its relations with mental health problems. The current study addressed this gap by evaluating the psychometric properties of a measure of this construct, the 20-item Trait Fear scale (TF-20), and examining its phenotypic and genotypic correlations with different forms of psychopathology in a sample of 346 twin pairs (121 monozygotic), aged 9–14 years. Analyses revealed high internal consistency and test-retest reliability for the TF-20. Evidence was also found for its convergent and discriminant validity in terms of phenotypic and genotypic correlations with measures of fear-related psychopathology. By contrast, the TF-20’s associations with depressive conditions were largely attributable to environmental influences. Extending prior work with adults, current study findings provide support for threat sensitivity as a genetically-influenced liability for phobic fear disorders in youth.
Multicenter clinical trials are essential for evaluating interventions but often face significant challenges in study design, site coordination, participant recruitment, and regulatory compliance. To address these issues, the National Institutes of Health’s National Center for Advancing Translational Sciences established the Trial Innovation Network (TIN). The TIN offers a scientific consultation process, providing access to clinical trial and disease experts who provide input and recommendations throughout the trial’s duration, at no cost to investigators. This approach aims to improve trial design, accelerate implementation, foster interdisciplinary teamwork, and spur innovations that enhance multicenter trial quality and efficiency. The TIN leverages resources of the Clinical and Translational Science Awards (CTSA) program, complementing local capabilities at the investigator’s institution. The Initial Consultation process focuses on the study’s scientific premise, design, site development, recruitment and retention strategies, funding feasibility, and other support areas. As of 6/1/2024, the TIN has provided 431 Initial Consultations to increase efficiency and accelerate trial implementation by delivering customized support and tailored recommendations. Across a range of clinical trials, the TIN has developed standardized, streamlined, and adaptable processes. We describe these processes, provide operational metrics, and include a set of lessons learned for consideration by other trial support and innovation networks.
We present the Evolutionary Map of the Universe (EMU) survey conducted with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU aims to deliver the touchstone radio atlas of the southern hemisphere. We introduce EMU and review its science drivers and key science goals, updated and tailored to the current ASKAP five-year survey plan. The development of the survey strategy and planned sky coverage is presented, along with the operational aspects of the survey and associated data analysis, together with a selection of diagnostics demonstrating the imaging quality and data characteristics. We give a general description of the value-added data pipeline and data products before concluding with a discussion of links to other surveys and projects and an outline of EMU’s legacy value.
Pre-pregnancy obesity (ppOB) is linked to pregnancy complications and abnormal fetal growth through placental mechanisms, and long non-coding RNAs (lncRNAs) may play an epigenetic role in these processes. We investigated overall and sex-specific associations of pre-pregnancy body mass index (ppBMI), ppOB, and birthweight with placental lncRNA transcripts in two birth cohorts. Study participants were mother-child dyads recruited to the CANDLE (Memphis, TN)(n = 725) and GAPPS (Seattle and Yakima, WA)(n = 159) cohorts. Maternal ppBMI was assessed at enrollment using interviewer-administered questionnaires. LncRNAs (1,077 and 1,033 for CANDLE and GAPPS, respectively) were sequenced from placental samples collected at birth. Placental lncRNA was regressed on ppBMI, ppOB (ppBMI ≥30kg/m2), or continuous birthweight in cohort-specific weighted linear models controlling for a priori-specified confounders and experimental variables. Potential effect modification by infant-sex was examined in sex-stratified analyses and models including BMI-infant-sex interaction terms. No lncRNA transcripts were significantly associated with ppBMI, ppOB, or birthweight in primary models. Among male infants in CANDLE, expression of three lncRNA transcripts (ERVH48-1, AC139099.1, CEBPA-DT) was associated with ppBMI and one transcript (AC104083.1) with birthweight. In GAPPS, ppBMI was associated with two lncRNA transcripts (AP000879.1 and AL365203.2) among males, and birthweight was associated with 17 lncRNA transcripts (including LINC02709, KANSL1-AS1, DANCR, EPB41L4A-AS1, and GABPB1-AS1) among females. No BMI-infant-sex interactions were observed. Though many of these potential associations are for uncharacterized transcripts, several identified lncRNAs (e.g., ERVH48-1 and CEBPA-DT) have been linked to pathways controlling cancer or placental growth, trophoblast differentiation, and gene expression. These associations warrant validation in future studies.
Mood and anxiety disorders co-occur and share symptoms, treatments and genetic risk, but it is unclear whether combining them into a single phenotype would better capture genetic variation. The contribution of common genetic variation to these disorders has been investigated using a range of measures; however, the differences in their ability to capture variation remain unclear, while the impact of rare variation is mostly unexplored.
Aims
We aimed to explore the contributions of common genetic variation and copy number variations associated with risk of psychiatric morbidity (P-CNVs) to different measures of internalising disorders.
Method
We investigated eight definitions of mood and anxiety disorder, and a combined internalising disorder, derived from self-report questionnaires, diagnostic assessments and electronic healthcare records (EHRs). Association of these definitions with polygenic risk scores (PRSs) of major depressive disorder and anxiety disorder, as well as presence of a P-CNV, was assessed.
Results
The effect sizes of both PRSs and P-CNVs were similar for mood and anxiety disorder. Compared to mood and anxiety disorder, internalising disorder resulted in higher prediction accuracy for PRSs, and increased significance of associations with P-CNVs for most definitions. Comparison across the eight definitions showed that PRSs had higher prediction accuracy and effect sizes for stricter definitions, whereas P-CNVs were more strongly associated with EHR- and self-report-based definitions.
Conclusions
Future studies may benefit from using a combined internalising disorder phenotype, and may need to consider that different phenotype definitions may be more informative depending on whether common or rare variation is studied.
Surfactant transport is central to a diverse range of natural phenomena with numerous practical applications in physics and engineering. Surprisingly, this process remains relatively poorly understood at the molecular scale. Here, we use non-equilibrium molecular dynamics (NEMD) simulations to study the spreading of sodium dodecyl sulphate on a thin film of liquid water. The molecular form of the control volume is extended to a coordinate system moving with the liquid–vapour interface to track surfactant spreading. We use this to compare the NEMD results to the continuum description of surfactant transport on an interface. By including the molecular details in the continuum model, we establish that the transport equation preserves substantial accuracy in capturing the underlying physics. Moreover, the relative importance of the different mechanisms involved in the transport process is identified. Consequently, we derive a novel exact molecular equation for surfactant transport along a deforming surface. Close agreement between the two conceptually different approaches, i.e. NEMD simulations and the numerical solution of the continuum equation, is found as measured by the surfactant concentration profiles, and the time dependence of the so-called spreading length. The current study focuses on a relatively simple specific solvent–surfactant system, and the observed agreement with the continuum model may not arise for more complicated industrially relevant surfactants and anti-foaming agents. In such cases, the continuum approach may fail to predict accompanying phase transitions, which can still be captured through the NEMD framework.
Objectives/Goals: Accurately stratifying patients with clinically isolated syndrome by risk of developing multiple sclerosis is of great clinical importance. Though numerous prediction models attempt to achieve this goal, no systematic review exists to independently evaluate these models. We aim to systematically identify and assess the risk of bias in all such models. Methods/Study Population: Studies developing or validating prediction models to assess risk of developing MS in patients with CIS who are not receiving an MS-indicated disease-modifying therapeutic will be identified via a systematic literature search. Studies will be evaluated for overall risk of bias using PROBAST (Prediction model Risk Of Bias Assessment Tool). Briefly, data sources, predictor, and outcome definition and assessment, applicability, and analysis will be assessed for each model in each identified study, and an overall risk of biased judgment will be assigned. Identified studies, predictors incorporated, results, and risk of bias assessment with accompanying rationale will be summarized in the final report. Results/Anticipated Results: Based on an initial exploratory search, we anticipate that most, if not all, identified prediction models will have high risk of bias. We anticipate that many studies will have limited applicability due to the use of outdated diagnostic criteria for definition of outcomes, or high risk of bias concerns originating from their analysis due to insufficient volume of included participants or poor model validation practices. We further anticipate that most, if not all, of the identified prediction models will have limited potential to be translated to use in a clinical setting. Discussion/Significance of Impact: Understanding how to identify patients with high-risk CIS may inform and improve clinician treatment decisions, patient outcomes, and future research study design. This work may also reveal flaws in current prediction models for CIS, opening new avenues of research and prompting development of improved prognostic models for patients with CIS.
ConG is software for conducting economic experiments in continuous and discrete time. It allows experimenters with limited programming experience to create a variety of strategic environments featuring rich visual feedback in continuous time and over continuous action spaces, as well as in discrete time or over discrete action spaces. Simple, easily edited input files give the experimenter considerable flexibility in specifying the strategic environment and visual feedback. Source code is modular and allows researchers with programming skills to create novel strategic environments and displays.
Edited by
Dharti Patel, Mount Sinai West and Morningside Hospitals, New York,Sang J. Kim, Hospital for Special Surgery, New York,Himani V. Bhatt, Mount Sinai West and Morningside Hospitals, New York,Alopi M. Patel, Rutgers Robert Wood Johnson Medical School, New Jersey
Lower respiratory tract disorders, which include pulmonary disorders like asthma and chronic obstructive pulmonary disease (COPD), are prevalent. This chapter discusses the pharmacology of some of the important classes of drugs used to treat these conditions. Bronchodilators relax smooth muscles and expand airways. Beta-2 agonists and anticholinergics are the two most commonly used bronchodilators used for this purpose. They are available in both short-acting and long-acting formulations. Short-acting (e.g. albuterol) are used as required for sudden episodes of breathlessness, while long-acting may be added if symptoms are not controlled or progress. Bronchodilators help to improve a patient’s overall quality of life through improved lung function, a decrease in symptoms, and improved exercise capacity. Corticosteroids, leukotriene modifiers, mast cell stabilizers, and Immunoglobulin E (IgE) blockers are classes of anti-inflammatory medications that have been shown to be effective treatments in controlling asthma symptoms and attacks. Research and experience have shown that a combination of these medications may be required. This can particularly be true for patients with intermediate and severe symptoms where a single medication has been inadequate in controlling/preventing recurrent symptoms.
Stewardship processes were compared across 123 hospitals that differed on a risk-adjusted post-discharge antibiotic use metric. Low-performing hospitals were less likely than high-performing hospitals to report routine interactions between their stewardship physician and pharmacist(s) (OR 0.12, 95% CI 0.03–0.55) and to have local antibiotic-prescribing guidelines (OR 0.21, 95% CI 0.05–0.93)
Previous studies identified clusters of first-episode psychosis (FEP) patients based on cognition and premorbid adjustment. This study examined a range of socio-environmental risk factors associated with clusters of FEP, aiming a) to compare clusters of FEP and community controls using the Maudsley Environmental Risk Score for psychosis (ERS), a weighted sum of the following risks: paternal age, childhood adversities, cannabis use, and ethnic minority membership; b) to explore the putative differences in specific environmental risk factors in distinguishing within patient clusters and from controls.
Methods
A univariable general linear model (GLS) compared the ERS between 1,263 community controls and clusters derived from 802 FEP patients, namely, low (n = 223) and high-cognitive-functioning (n = 205), intermediate (n = 224) and deteriorating (n = 150), from the EU-GEI study. A multivariable GLS compared clusters and controls by different exposures included in the ERS.
Results
The ERS was higher in all clusters compared to controls, mostly in the deteriorating (β=2.8, 95% CI 2.3 3.4, η2 = 0.049) and the low-cognitive-functioning cluster (β=2.4, 95% CI 1.9 2.8, η2 = 0.049) and distinguished them from the cluster with high-cognitive-functioning. The deteriorating cluster had higher cannabis exposure (meandifference = 0.48, 95% CI 0.49 0.91) than the intermediate having identical IQ, and more people from an ethnic minority (meandifference = 0.77, 95% CI 0.24 1.29) compared to the high-cognitive-functioning cluster.
Conclusions
High exposure to environmental risk factors might result in cognitive impairment and lower-than-expected functioning in individuals at the onset of psychosis. Some patients’ trajectories involved risk factors that could be modified by tailored interventions.
Since Holt and Laury (Am Econ Rev 92(5):1644–1655, 2002), the multiple price list (MPL) procedure has widely been used to elicit individual risk preferences. We assess the impact of varying list order and spacing, and of presentation via text or graphs. Relative to the original MPL baseline, some non-linear transformations of lottery prices systematically increase elicited risk aversion, while some graphical displays tend to reduce it.