Interruption to antiplatelet therapy early after acute ischaemic stroke: a nested case-control study

Aims: Antiplatelet drugs are often discontinued early after ischaemic stroke, either because of poor compliance, complications or withdrawal of care. It is unclear whether this places patients at increased risk of recurrence. We explored the association between cardiovascular event rate and persistence with prescribed antiplatelet drugs. Methods: We used a matched case–control design using the Virtual International Stroke Trials Archive (VISTA). Cases were patients who had an acute coronary syndrome, recurrent stroke or transient ischaemic attack within 90 days post-stroke and were matched for age ± 10 years and sex with up to four controls. Antiplatelet use was categorized as persistent (used for >3 days and continued up to day 90), early cessation (used antiplatelet 3 days but stopped prior to day 90). These categories were compared in cases and controls using a conditional logistic regression model that adjusted for potential confounders. Results: A total of 970 patients were included, of whom 194 were cases and 776 were matched controls. At 90 days, 10 cases (5.2%) and 58 controls (7.5%) stopped/interrupted their antiplatelet. The risk of cardiovascular event was not different in stopped/interrupted users (adjusted odds ratio 0.70, 95% confidence interval 0.33, 1.48; P = 0.352) and early cessations (adjusted odds ratio 1.04, 95% confidence interval 0.62, 1.74; P = 0.876) when compared to persistent users. Conclusion: We found no increased risk in patients who stopped and interrupted antiplatelets early after stroke but the study was limited by a small sample size and further research is needed

Understanding Shoot and Root Development

Shoot and root development of the grass tiller is presented as a series of events on the tiller axis. Leaf, tiller bud, true stem, and root development are successive events in the life cycle of a single phytomer and the tiller is a co-ordinated series of phytomers, successive phytomers being progressively more advanced than the previous phytomer. In reviewing the individual growth processes of leaf, tiller, true stem, and root formation, fundamental determinants of light and nutrient capture are examined and examples presented to illustrate the link between component processes, plant morphogenesis, and plant performance. An example of the application of this understanding in plant improvement is given

“Choking Under Pressure” in Older Drivers

Aging can impair executive control and emotion regulation, affecting driver decision-making and behavior, especially under stress. We used an interactive driving simulator to investigate ability to make safe left-turns across oncoming traffic under pressure in 13 older (\u3e 65 years old) and 16 middle-aged (35-56 years old) drivers. Drivers made left-turns at an uncontrolled intersection with moderately heavy oncoming traffic. Gaps between oncoming vehicles varied and increased gradually from 2 s to 10 s. Drivers made two left-turns with a vehicle honking aggressively behind (pressure condition), and two left-turns without the honking vehicle (control condition). Results showed that middle-aged drivers made more cautious turning decisions under pressure (by waiting for larger and safer gaps, p \u3c .001), but older drivers did not. Further, older driver turning paths deviated under pressure compared to the control condition (p \u3c .05), but the middle-aged group did not. Moreover, across all subjects, better executive function was significantly correlated with larger increases of accepted gap size from control to honking (p \u3c .01). The findings suggest that older drivers are more sensitive to traffic challenges from environmental pressure and that neural models of older driver performance and safety must factor in age-related changes in executive control and emotion processing

Chemistry Across Multiple Phases (CAMP) version 1.0: an integrated multiphase chemistry model

A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an “abstracted aerosol representation” that allows a given chemical mechanism to be solved in atmospheric models with different aerosol representations (e.g., sectional, modal, or particle-resolved). This is accomplished by treating aerosols as a collection of condensed phases that are implemented according to the aerosol representation of the host model. The framework also allows multiple chemical processes (e.g., gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass transfer) to be solved simultaneously as a single system. The flexibility of the model is achieved by (1) using an object-oriented design that facilitates extensibility to new types of chemical processes and to new ways of representing aerosol systems, (2) runtime model configuration using JSON input files that permits making changes to any part of the chemical mechanism without recompiling the model (this widely used, human-readable format allows entire gas- and aerosol-phase chemical mechanisms to be described with as much complexity as necessary), and (3) automated comprehensive testing that ensures stability of the code as new functionality is introduced. Together, these design choices enable users to build a customized multiphase mechanism without having to handle preprocessors, solvers, or compilers. Removing these hurdles makes this type of modeling accessible to a much wider community, including modelers, experimentalists, and educators. This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the Multiscale Online AtmospheRe CHemistry (MONARCH) chemical weather prediction system for use at regional and global scales. Results from the initial deployment to box models of different complexity and MONARCH will be discussed, along with future extension to more complex gas–aerosol systems and the integration of GPU-based solvers.Matthew L. Dawson has received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. 747048. Matthew L. Dawson, Oriol Jorba, and Christian Guzman have been supported by the Ministerio de Ciencia, Innovación y Universidades (grant no. RTI2018-099894-BI00). Christian Guzman acknowledges funding from the AXA Research Fund. Nicole Riemer, Matthew West, and Jeffrey H. Curtis acknowledge funding from the National Science Foundation (grant no. AGS 19-41110). This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under cooperative agreement no. 1852977.Peer ReviewedPostprint (published version

Chemistry Across Multiple Phases (CAMP) version 1.0: an integrated multiphase chemistry model

A flexible treatment for gas- and aerosol-phase chemical processes has been developed for models of diverse scale, from box models up to global models. At the core of this novel framework is an “abstracted aerosol representation” that allows a given chemical mechanism to be solved in atmospheric models with different aerosol representations (e.g., sectional, modal, or particle-resolved). This is accomplished by treating aerosols as a collection of condensed phases that are implemented according to the aerosol representation of the host model. The framework also allows multiple chemical processes (e.g., gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass transfer) to be solved simultaneously as a single system. The flexibility of the model is achieved by (1) using an object-oriented design that facilitates extensibility to new types of chemical processes and to new ways of representing aerosol systems, (2) runtime model configuration using JSON input files that permits making changes to any part of the chemical mechanism without recompiling the model (this widely used, human-readable format allows entire gas- and aerosol-phase chemical mechanisms to be described with as much complexity as necessary), and (3) automated comprehensive testing that ensures stability of the code as new functionality is introduced. Together, these design choices enable users to build a customized multiphase mechanism without having to handle preprocessors, solvers, or compilers. Removing these hurdles makes this type of modeling accessible to a much wider community, including modelers, experimentalists, and educators. This new treatment compiles as a stand-alone library and has been deployed in the particle-resolved PartMC model and in the Multiscale Online AtmospheRe CHemistry (MONARCH) chemical weather prediction system for use at regional and global scales. Results from the initial deployment to box models of different complexity and MONARCH will be discussed, along with future extension to more complex gas–aerosol systems and the integration of GPU-based solvers.Matthew L. Dawson has received funding from the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement no. 747048. Matthew L. Dawson, Oriol Jorba, and Christian Guzman have been supported by the Ministerio de Ciencia, Innovación y Universidades (grant no. RTI2018-099894-BI00). Christian Guzman acknowledges funding from the AXA Research Fund. Nicole Riemer, Matthew West, and Jeffrey H. Curtis acknowledge funding from the National Science Foundation (grant no. AGS 19-41110). This material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under cooperative agreement no. 1852977.Peer ReviewedPostprint (published version

Predicting Driver Safety in Parkinson’s Disease: An Interim Report of an Ongoing Longitudinal Study

This article summarizes the baseline results of an ongoing longitudinal, NIH-funded study on prediction of driver safety in patients with Parkinson’s disease (PD). Patients with even mild to moderate PD who drive and live independently suffer from visual and cognitive dysfunction, which appear to be the main contributors to decreased driving performance and safety, rather than the motor dysfunction for which PD is known