154 research outputs found
Social Aggregation in Pea Aphids: Experiment and Random Walk Modeling
From bird flocks to fish schools and ungulate herds to insect swarms, social biological aggregations are found across the natural world. An ongoing challenge in the mathematical modeling of aggregations is to strengthen the connection between models and biological data by quantifying the rules that individuals follow. We model aggregation of the pea aphid, Acyrthosiphon pisum. Specifically, we conduct experiments to track the motion of aphids walking in a featureless circular arena in order to deduce individual-level rules. We observe that each aphid transitions stochastically between a moving and a stationary state. Moving aphids follow a correlated random walk. The probabilities of motion state transitions, as well as the random walk parameters, depend strongly on distance to an aphid\u27s nearest neighbor. For large nearest neighbor distances, when an aphid is essentially isolated, its motion is ballistic with aphids moving faster, turning less, and being less likely to stop. In contrast, for short nearest neighbor distances, aphids move more slowly, turn more, and are more likely to become stationary; this behavior constitutes an aggregation mechanism. From the experimental data, we estimate the state transition probabilities and correlated random walk parameters as a function of nearest neighbor distance. With the individual-level model established, we assess whether it reproduces the macroscopic patterns of movement at the group level. To do so, we consider three distributions, namely distance to nearest neighbor, angle to nearest neighbor, and percentage of population moving at any given time. For each of these three distributions, we compare our experimental data to the output of numerical simulations of our nearest neighbor model, and of a control model in which aphids do not interact socially. Our stochastic, social nearest neighbor model reproduces salient features of the experimental data that are not captured by the control
Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial
Background
Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy
Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke
BACKGROUND: Post-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction. AIMS: To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline. METHODS: We pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI 24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site. RESULTS: We included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) 24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline. CONCLUSIONS: The network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/
Consensus standards for acquisition, measurement, and reporting of intravascular optical coherence tomography studies
Objectives: The purpose of this document is to make the output of the International Working Group for Intravascular Optical Coherence Tomography (IWG-IVOCT) Standardization and Validation available to medical and scientific communities, through a peer-reviewed publication, in the interest of improving the diagnosis and treatment of patients with atherosclerosis, including coronary artery disease. Background: Intravascular optical coherence tomography (IVOCT) is a catheter-based modality that acquires images at a resolution of ∼10 μm, enabling visualization of blood vessel wall microstructure in vivo at an unprecedented level of detail. IVOCT devices are now commercially available worldwide, there is an active user base, and the interest in using this technology is growing. Incorporation of IVOCT in research and daily clinical practice can be facilitated by the development of uniform terminology and consensus-based standards on use of the technology, interpretation of the images, and reporting of IVOCT results. Methods: The IWG-IVOCT, comprising more than 260 academic and industry members from Asia, Europe, and the United States, formed in 2008 and convened on the topic of IVOCT standardization through a series of 9 national and international meetings. Results: Knowledge and recommendations from this group on key areas within the IVOCT field were assembled to generate this consensus document, authored by the Writing Committee, composed of academicians who have participated in meetings and/or writing of the text. Conclusions: This document may be broadly used as a standard reference regarding the current state of the IVOCT imaging modality, intended for researchers and clinicians who use IVOCT and analyze IVOCT data
Retreatment for hepatitis C virus direct-acting antiviral therapy virological failure in primary and tertiary settings: The REACH-C cohort
Virological failure occurs in a small proportion of people treated for hepatitis C virus (HCV) with direct-acting antiviral (DAA) therapies. This study assessed retreatment for virological failure in a large real-world cohort. REACH-C is an Australian observational study (n = 10,843) evaluating treatment outcomes of sequential DAA initiations across 33 health services between March 2016 to June 2019. Virological failure retreatment data were collected until October 2020. Of 408 people with virological failure (81% male; median age 53; 38% cirrhosis; 56% genotype 3), 213 (54%) were retreated once; 15 were retreated twice. A range of genotype specific and pangenotypic DAAs were used to retreat virological failure in primary (n = 56) and tertiary (n = 157) settings. Following sofosbuvir/velpatasvir/voxilaprevir availability in 2019, the proportion retreated in primary care increased from 21% to 40% and median time to retreatment initiation declined from 294 to 152 days. Per protocol (PP) sustained virological response (SVR12) was similar for people retreated in primary and tertiary settings (80% vs 81%; p = 1.000). In regression analysis, sofosbuvir/velpatasvir/voxilaprevir (vs. other regimens) significantly decreased likelihood of second virological failure (PP SVR12 88% vs. 77%; adjusted odds ratio [AOR] 0.29; 95%CI 0.11–0.81); cirrhosis increased likelihood (PP SVR12 69% vs. 91%; AOR 4.26; 95%CI 1.64–11.09). Indigenous Australians had lower likelihood of retreatment initiation (AOR 0.36; 95%CI 0.15–0.81). Treatment setting and prescriber type were not associated with retreatment initiation or outcome. Virological failure can be effectively retreated in primary care. Expanded access to simplified retreatment regimens through decentralized models may increase retreatment uptake and reduce HCV-related mortality
The NANOGrav 15-year Data Set: Search for Anisotropy in the Gravitational-Wave Background
The North American Nanohertz Observatory for Gravitational Waves (NANOGrav)
has reported evidence for the presence of an isotropic nanohertz gravitational
wave background (GWB) in its 15 yr dataset. However, if the GWB is produced by
a population of inspiraling supermassive black hole binary (SMBHB) systems,
then the background is predicted to be anisotropic, depending on the
distribution of these systems in the local Universe and the statistical
properties of the SMBHB population. In this work, we search for anisotropy in
the GWB using multiple methods and bases to describe the distribution of the
GWB power on the sky. We do not find significant evidence of anisotropy, and
place a Bayesian upper limit on the level of broadband anisotropy such
that . We also derive conservative estimates on the
anisotropy expected from a random distribution of SMBHB systems using
astrophysical simulations conditioned on the isotropic GWB inferred in the
15-yr dataset, and show that this dataset has sufficient sensitivity to probe a
large fraction of the predicted level of anisotropy. We end by highlighting the
opportunities and challenges in searching for anisotropy in pulsar timing array
data.Comment: 19 pages, 11 figures; submitted to Astrophysical Journal Letters as
part of Focus on NANOGrav's 15-year Data Set and the Gravitational Wave
Background. For questions or comments, please email [email protected]
The NANOGrav 12.5 yr Data Set: Search for Gravitational Wave Memory
We present the results of a Bayesian search for gravitational wave (GW) memory in the NANOGrav 12.5 yr data set. We find no convincing evidence for any gravitational wave memory signals in this data set. We find a Bayes factor of 2.8 in favor of a model that includes a memory signal and common spatially uncorrelated red noise (CURN) compared to a model including only a CURN. However, further investigation shows that a disproportionate amount of support for the memory signal comes from three dubious pulsars. Using a more flexible red-noise model in these pulsars reduces the Bayes factor to 1.3. Having found no compelling evidence, we go on to place upper limits on the strain amplitude of GW memory events as a function of sky location and event epoch. These upper limits are computed using a signal model that assumes the existence of a common, spatially uncorrelated red noise in addition to a GW memory signal. The median strain upper limit as a function of sky position is approximately 3.3 × 10−14. We also find that there are some differences in the upper limits as a function of sky position centered around PSR J0613−0200. This suggests that this pulsar has some excess noise that can be confounded with GW memory. Finally, the upper limits as a function of burst epoch continue to improve at later epochs. This improvement is attributable to the continued growth of the pulsar timing array
The NANOGrav 15-Year Data Set: Detector Characterization and Noise Budget
Pulsar timing arrays (PTAs) are galactic-scale gravitational wave detectors.
Each individual arm, composed of a millisecond pulsar, a radio telescope, and a
kiloparsecs-long path, differs in its properties but, in aggregate, can be used
to extract low-frequency gravitational wave (GW) signals. We present a noise
and sensitivity analysis to accompany the NANOGrav 15-year data release and
associated papers, along with an in-depth introduction to PTA noise models. As
a first step in our analysis, we characterize each individual pulsar data set
with three types of white noise parameters and two red noise parameters. These
parameters, along with the timing model and, particularly, a piecewise-constant
model for the time-variable dispersion measure, determine the sensitivity curve
over the low-frequency GW band we are searching. We tabulate information for
all of the pulsars in this data release and present some representative
sensitivity curves. We then combine the individual pulsar sensitivities using a
signal-to-noise-ratio statistic to calculate the global sensitivity of the PTA
to a stochastic background of GWs, obtaining a minimum noise characteristic
strain of at 5 nHz. A power law-integrated analysis shows
rough agreement with the amplitudes recovered in NANOGrav's 15-year GW
background analysis. While our phenomenological noise model does not model all
known physical effects explicitly, it provides an accurate characterization of
the noise in the data while preserving sensitivity to multiple classes of GW
signals.Comment: 67 pages, 73 figures, 3 tables; published in Astrophysical Journal
Letters as part of Focus on NANOGrav's 15-year Data Set and the Gravitational
Wave Background. For questions or comments, please email
[email protected]
How to Detect an Astrophysical Nanohertz Gravitational-Wave Background
Analysis of pulsar timing data have provided evidence for a stochastic
gravitational wave background in the nHz frequency band. The most plausible
source of such a background is the superposition of signals from millions of
supermassive black hole binaries. The standard statistical techniques used to
search for such a background and assess its significance make several
simplifying assumptions, namely: i) Gaussianity; ii) isotropy; and most often
iii) a power-law spectrum. However, a stochastic background from a finite
collection of binaries does not exactly satisfy any of these assumptions. To
understand the effect of these assumptions, we test standard analysis
techniques on a large collection of realistic simulated datasets. The dataset
length, observing schedule, and noise levels were chosen to emulate the
NANOGrav 15-year dataset. Simulated signals from millions of binaries drawn
from models based on the Illustris cosmological hydrodynamical simulation were
added to the data. We find that the standard statistical methods perform
remarkably well on these simulated datasets, despite their fundamental
assumptions not being strictly met. They are able to achieve a confident
detection of the background. However, even for a fixed set of astrophysical
parameters, different realizations of the universe result in a large variance
in the significance and recovered parameters of the background. We also find
that the presence of loud individual binaries can bias the spectral recovery of
the background if we do not account for them.Comment: 14 pages, 8 figure
The NANOGrav 15-year Data Set: Bayesian Limits on Gravitational Waves from Individual Supermassive Black Hole Binaries
Evidence for a low-frequency stochastic gravitational wave background has
recently been reported based on analyses of pulsar timing array data. The most
likely source of such a background is a population of supermassive black hole
binaries, the loudest of which may be individually detected in these datasets.
Here we present the search for individual supermassive black hole binaries in
the NANOGrav 15-year dataset. We introduce several new techniques, which
enhance the efficiency and modeling accuracy of the analysis. The search
uncovered weak evidence for two candidate signals, one with a
gravitational-wave frequency of 4 nHz, and another at 170 nHz. The
significance of the low-frequency candidate was greatly diminished when
Hellings-Downs correlations were included in the background model. The
high-frequency candidate was discounted due to the lack of a plausible host
galaxy, the unlikely astrophysical prior odds of finding such a source, and
since most of its support comes from a single pulsar with a commensurate binary
period. Finding no compelling evidence for signals from individual binary
systems, we place upper limits on the strain amplitude of gravitational waves
emitted by such systems.Comment: 23 pages, 13 figures, 2 tables. Accepted for publication in
Astrophysical Journal Letters as part of Focus on NANOGrav's 15-year Data Set
and the Gravitational Wave Background. For questions or comments, please
email [email protected]
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