Explaining Snapshots of Network Diffusions: Structural and Hardness Results

Much research has been done on studying the diffusion of ideas or technologies on social networks including the \textit{Influence Maximization} problem and many of its variations. Here, we investigate a type of inverse problem. Given a snapshot of the diffusion process, we seek to understand if the snapshot is feasible for a given dynamic, i.e., whether there is a limited number of nodes whose initial adoption can result in the snapshot in finite time. While similar questions have been considered for epidemic dynamics, here, we consider this problem for variations of the deterministic Linear Threshold Model, which is more appropriate for modeling strategic agents. Specifically, we consider both sequential and simultaneous dynamics when deactivations are allowed and when they are not. Even though we show hardness results for all variations we consider, we show that the case of sequential dynamics with deactivations allowed is significantly harder than all others. In contrast, sequential dynamics make the problem trivial on cliques even though it's complexity for simultaneous dynamics is unknown. We complement our hardness results with structural insights that can help better understand diffusions of social networks under various dynamics.Comment: 14 pages, 3 figure

Prolonged viral replication and longitudinal viral dynamic differences among respiratory syncytial virus infected infants

© 2017 2017 International Pediatric Research Foundation, Inc. BackgroundLongitudinal respiratory syncytial virus (RSV) dynamics have not been well studied despite the existence of factors favoring prolonged RSV replication including high mutation rates allowing rapid evolution and potential escape from immune control. We therefore measured viral load in previously RSV-naive infants over prolonged time spans.MethodsDuring 2014-2015, quantitative nasal aspirates were collected from 51 RSV-PCR+ infants. Multiple parallel assessments of viral loads were quantified at each collected time point using a well-validated real-time quantitative reverse transcriptase polymerase chain reaction assay. After observing viral load rebound phenomenon in some infants, the viral dynamics of 27 infants with sufficient longitudinal viral load data points were analyzed using the pre-defined criteria for viral rebound. Additional analyses were performed comparing age with viral rebound, viral clearance rates, and viral load area-under-the-curve (AUC VL).ResultsThe 51 infants (303 nasal aspirate samples; mean of 5.9 per patient) exhibited slower than expected viral clearance. Lower age trended toward slower viral clearance and greater AUC VL. Six infants had detectable viral loads ≥1 month after symptom onset. Ten of twenty-seven evaluable subjects exhibited viral rebound and this rebound was age-dependent (P=0.0259). All but one rebounder were rebound; likely representing viral mutational immune escape

Development and optimisation of spironolactone nanoparticles for enhanced dissolution rates and stability

Stable solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs) formulations to enhance the dissolution rates of poorly soluble drug spironolactone (SP) were being developed. Probe ultra-sonication method was used to prepare SLNs and NLCs. All NLCs contained stearic acid (solid lipid carrier) and oleic acid (liquid lipid content), whereas, SLNs were prepared and optimised by using the solid lipid only. The particles were characterised in terms of particle size analysis, thermal behaviour, morphology, stability and in vitro release. The zeta sizer data revealed that the increase in the concentration of oleic acid in the formulations reduced the mean particle size and the zeta potential. The increase in concentration of oleic acid from 0 to 30% (w/w) resulted in a higher entrapment efficiency. All nanoparticles were almost spherically shaped with an average particle size of about ∼170 nm. The DSC traces revealed that the presence of oleic acid in the NLC formulations resulted in a shift in the melting endotherms to a higher temperature. This could be attributed to a good long-term stability of the nanoparticles. The stability results showed that the particle size remained smaller in NLC compared to that of SLN formulations after 6 months at various temperatures. The dissolution study showed about a 5.1- to 7.2-fold increase in the release of the drug in 2 h compared to the raw drug. Comparing all nanoparticle formulations indicated that the NLC composition with a ratio of 70:30 (solid:liquid lipid) is the most suitable formulation with desired drug dissolution rates, entrapment efficiency and physical stability

Selective Serotonin Reuptake Inhibitor Use Is Associated with Right Ventricular Structure and Function: The MESA-Right Ventricle Study

PURPOSE:Serotonin and the serotonin transporter have been implicated in the development of pulmonary hypertension (PH). Selective serotonin reuptake inhibitors (SSRIs) may have a role in PH treatment, but the effects of SSRI use on right ventricular (RV) structure and function are unknown. We hypothesized that SSRI use would be associated with RV morphology in a large cohort without cardiovascular disease (N = 4114). METHODS:SSRI use was determined by medication inventory during the Multi-Ethnic Study of Atherosclerosis baseline examination. RV measures were assessed via cardiac magnetic resonance imaging. The cross-sectional relationship between SSRI use and each RV measure was assessed using multivariable linear regression; analyses for RV mass and end-diastolic volume (RVEDV) were stratified by sex. RESULTS:After adjustment for multiple covariates including depression and left ventricular measures, SSRI use was associated with larger RV stroke volume (RVSV) (2.75 mL, 95% confidence interval [CI] 0.48-5.02 mL, p = 0.02). Among men only, SSRI use was associated with greater RV mass (1.08 g, 95% CI 0.19-1.97 g, p = 0.02) and larger RVEDV (7.71 mL, 95% 3.02-12.40 mL, p = 0.001). SSRI use may have been associated with larger RVEDV among women and larger RV end-systolic volume in both sexes. CONCLUSIONS:SSRI use was associated with higher RVSV in cardiovascular disease-free individuals and, among men, greater RV mass and larger RVEDV. The effects of SSRI use in patients with (or at risk for) RV dysfunction and the role of sex in modifying this relationship warrant further study

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Hyperoxemia and excess oxygen use in early acute respiratory distress syndrome : Insights from the LUNG SAFE study

Publisher Copyright: © 2020 The Author(s). Copyright: Copyright 2020 Elsevier B.V., All rights reserved.Background: Concerns exist regarding the prevalence and impact of unnecessary oxygen use in patients with acute respiratory distress syndrome (ARDS). We examined this issue in patients with ARDS enrolled in the Large observational study to UNderstand the Global impact of Severe Acute respiratory FailurE (LUNG SAFE) study. Methods: In this secondary analysis of the LUNG SAFE study, we wished to determine the prevalence and the outcomes associated with hyperoxemia on day 1, sustained hyperoxemia, and excessive oxygen use in patients with early ARDS. Patients who fulfilled criteria of ARDS on day 1 and day 2 of acute hypoxemic respiratory failure were categorized based on the presence of hyperoxemia (PaO2 > 100 mmHg) on day 1, sustained (i.e., present on day 1 and day 2) hyperoxemia, or excessive oxygen use (FIO2 ≥ 0.60 during hyperoxemia). Results: Of 2005 patients that met the inclusion criteria, 131 (6.5%) were hypoxemic (PaO2 < 55 mmHg), 607 (30%) had hyperoxemia on day 1, and 250 (12%) had sustained hyperoxemia. Excess FIO2 use occurred in 400 (66%) out of 607 patients with hyperoxemia. Excess FIO2 use decreased from day 1 to day 2 of ARDS, with most hyperoxemic patients on day 2 receiving relatively low FIO2. Multivariate analyses found no independent relationship between day 1 hyperoxemia, sustained hyperoxemia, or excess FIO2 use and adverse clinical outcomes. Mortality was 42% in patients with excess FIO2 use, compared to 39% in a propensity-matched sample of normoxemic (PaO2 55-100 mmHg) patients (P = 0.47). Conclusions: Hyperoxemia and excess oxygen use are both prevalent in early ARDS but are most often non-sustained. No relationship was found between hyperoxemia or excessive oxygen use and patient outcome in this cohort. Trial registration: LUNG-SAFE is registered with ClinicalTrials.gov, NCT02010073publishersversionPeer reviewe