Development and validation of statewide survey-based measures of livability in Connecticut.

Livability, or how a place and its systems (e.g., housing, transportation) supports the ability to lead a livable life, is a determinant of health. There is a lack of standard, validated measures to assess livability in the US. This study employed factor analytic methods to create measures of livability in Connecticut using data from the DataHaven Community Wellbeing Survey (DCWS) (n = 32,262). Results identified a 3-factor model (safety, opportunity, and infrastructure) as the best fit, explaining 69% of the variance in survey items. Newly created livability measures had high internal consistency, in addition to high convergent validity with other area-level measures.

Neighborhood Social Environment and Body Mass Index: The Mediating Role of Mental Wellbeing.

The association between neighborhood-built environment and body mass index (BMI) is well-characterized, whereas fewer studies have explored the mechanisms underlying the relationship between neighborhood social environment and obesogenic behaviors. Using data from a random sample of 16,820 residents ≥18 years from all 169 Connecticut towns and seven ZIP Codes in New York, this study examines the influence of neighborhood social environment on residents' mental wellbeing, physical activity, and BMI. Structural equation modeling was conducted to estimate direct and indirect effects of neighborhood social environment on BMI, using mental wellbeing and physical activity as intermediate variables. There were significant total [ß(SE) = 0.741 (0.170), p < 0.0001], direct [ß(SE) = 0.456 (0.1890), p = 0.016], and indirect [ß(SE) = 0.285 (0.061), p < 0.0001] effects of neighborhood social environment on BMI. Low physical activity was a partial mediator of the effect of non-favorable neighborhood social environment on BMI [ß(SE) = -0.071 (0.011), p < 0.0001]. The association between neighborhood social environment and BMI was also mediated by mental wellbeing [ß(SE) = 0.214 (0.060), p < 0.0001], and by mental wellbeing through physical activity [ß(SE) = 0.071 (0.011), p < 0.0001]. Study findings provide further support for building strong social environments to improve population health and suggest that strategies prioritizing mental wellbeing may benefit behavioral interventions aimed at reducing obesity risk and should be a focus of prevention efforts in and of itself.

Maximizing the Efficiency of Active Case Finding for SARS-CoV-2 Using Bandit Algorithms.

Even as vaccination for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) expands in the United States, cases will linger among unvaccinated individuals for at least the next year, allowing the spread of the coronavirus to continue in communities across the country. Detecting these infections, particularly asymptomatic ones, is critical to stemming further transmission of the virus in the months ahead. This will require active surveillance efforts in which these undetected cases are proactively sought out rather than waiting for individuals to present to testing sites for diagnosis. However, finding these pockets of asymptomatic cases (i.e., hotspots) is akin to searching for needles in a haystack as choosing where and when to test within communities is hampered by a lack of epidemiological information to guide decision makers' allocation of these resources. Making sequential decisions with partial information is a classic problem in decision science, the explore v. exploit dilemma. Using methods-bandit algorithms-similar to those used to search for other kinds of lost or hidden objects, from downed aircraft or underground oil deposits, we can address the explore v. exploit tradeoff facing active surveillance efforts and optimize the deployment of mobile testing resources to maximize the yield of new SARS-CoV-2 diagnoses. These bandit algorithms can be implemented easily as a guide to active case finding for SARS-CoV-2. A simple Thompson sampling algorithm and an extension of it to integrate spatial correlation in the data are now embedded in a fully functional prototype of a web app to allow policymakers to use either of these algorithms to target SARS-CoV-2 testing. In this instance, potential testing locations were identified by using mobility data from UberMedia to target high-frequency venues in Columbus, Ohio, as part of a planned feasibility study of the algorithms in the field. However, it is easily adaptable to other jurisdictions, requiring only a set of candidate test locations with point-to-point distances between all locations, whether or not mobility data are integrated into decision making in choosing places to test.

Heterogeneous parallelization and acceleration of molecular dynamics simulations in GROMACS.

The introduction of accelerator devices such as graphics processing units (GPUs) has had profound impact on molecular dynamics simulations and has enabled order-of-magnitude performance advances using commodity hardware. To fully reap these benefits, it has been necessary to reformulate some of the most fundamental algorithms, including the Verlet list, pair searching, and cutoffs. Here, we present the heterogeneous parallelization and acceleration design of molecular dynamics implemented in the GROMACS codebase over the last decade. The setup involves a general cluster-based approach to pair lists and non-bonded pair interactions that utilizes both GPU and central processing unit (CPU) single instruction, multiple data acceleration efficiently, including the ability to load-balance tasks between CPUs and GPUs. The algorithm work efficiency is tuned for each type of hardware, and to use accelerators more efficiently, we introduce dual pair lists with rolling pruning updates. Combined with new direct GPU-GPU communication and GPU integration, this enables excellent performance from single GPU simulations through strong scaling across multiple GPUs and efficient multi-node parallelization.

Sharing Data from Molecular Simulations.

Given the need for modern researchers to produce open, reproducible scientific output, the lack of standards and best practices for sharing data and workflows used to produce and analyze molecular dynamics (MD) simulations has become an important issue in the field. There are now multiple well-established packages to perform molecular dynamics simulations, often highly tuned for exploiting specific classes of hardware, each with strong communities surrounding them, but with very limited interoperability/transferability options. Thus, the choice of the software package often dictates the workflow for both simulation production and analysis. The level of detail in documenting the workflows and analysis code varies greatly in published work, hindering reproducibility of the reported results and the ability for other researchers to build on these studies. An increasing number of researchers are motivated to make their data available, but many challenges remain in order to effectively share and reuse simulation data. To discuss these and other issues related to best practices in the field in general, we organized a workshop in November 2018 ( https://bioexcel.eu/events/workshop-on-sharing-data-from-molecular-simulations/ ). Here, we present a brief overview of this workshop and topics discussed. We hope this effort will spark further conversation in the MD community to pave the way toward more open, interoperable, and reproducible outputs coming from research studies using MD simulations.

Direct-Space Corrections Enable Fast and Accurate Lorentz-Berthelot Combination Rule Lennard-Jones Lattice Summation.

Long-range lattice summation techniques such as the particle-mesh Ewald (PME) algorithm for electrostatics have been revolutionary to the precision and accuracy of molecular simulations in general. Despite the performance penalty associated with lattice summation electrostatics, few biomolecular simulations today are performed without it. There are increasingly strong arguments for moving in the same direction for Lennard-Jones (LJ) interactions, and by using geometric approximations of the combination rules in reciprocal space, we have been able to make a very high-performance implementation available in GROMACS. Here, we present a new way to correct for these approximations to achieve exact treatment of Lorentz-Berthelot combination rules within the cutoff, and only a very small approximation error remains outside the cutoff (a part that would be completely ignored without LJ-PME). This not only improves accuracy by almost an order of magnitude but also achieves absolute biomolecular simulation performance that is an order of magnitude faster than any other available lattice summation technique for LJ interactions. The implementation includes both CPU and GPU acceleration, and its combination with improved scaling LJ-PME simulations now provides performance close to the truncated potential methods in GROMACS but with much higher accuracy.

Portomesenteric venous thrombosis: a community hospital experience with 103 consecutive patients.

BACKGROUND: Portomesenteric venous thrombosis (PMVT) is uncommon but associated with ischemic bowel and mortality. OBJECTIVE: The purpose of this study was to determine the occurrence of PMVT in a community setting and evaluate current diagnosis, treatment, and outcomes. METHODS: Medical records of consecutive patients admitted to a community-based hospital diagnosed with PMVT were reviewed. Patients were divided into 2 groups: those diagnosed from 1997 to 2003 and those diagnosed from 2004 to 2009. RESULTS: One hundred three patients were included. The proportion of chronic PMVT diagnoses increased in the recent group (14% in contrast to 44%, P = .001). Treatment was more common in acute in contrast to chronic PMVTs (70% in contrast to 48%, P = .035). The median length of stay decreased over time (6 in contrast to 3 days, P = .004). Three patients underwent surgical intervention. Overall, 30-day mortality was 17% and did not change over time. CONCLUSIONS: Diagnosis and treatment have changed with increased differentiation between acute and chronic PMVT; outcomes were similar. Surgical intervention was rarely necessary. Mortality is attributed to patient comorbidity rather than PMVT.

Performance enhancements for GROMACS nonbonded interactions on BlueGene.

Several improvements to the previously optimized GROMACS BlueGene inner loops that evaluate nonbonded interactions in molecular dynamics simulations are presented. The new improvements yielded an 11% decrease in running time for both PME and other kinds of GROMACS simulations that use nonbonded table look-ups. Some other GROMACS simulations will show a small gain.

Optimization of parameters for molecular dynamics simulation using smooth particle-mesh Ewald in GROMACS 4.5.

Based on our critique of requirements for performing an efficient molecular dynamics simulation with the particle-mesh Ewald (PME) implementation in GROMACS 4.5, we present a computational tool to enable the discovery of parameters that produce a given accuracy in the PME approximation of the full electrostatics. Calculations on two parallel computers with different processor and communication structures showed that a given accuracy can be attained over a range of parameter space, and that the attributes of the hardware and simulation system control which parameter sets are optimal. This information can be used to find the fastest available PME parameter sets that achieve a given accuracy. We hope that this tool will stimulate future work to assess the impact of the quality of the PME approximation on simulation outcomes, particularly with regard to the trade-off between cost and scientific reliability in biomolecular applications.

Lamotrigine-induced aseptic meningitis: a case report.

Aseptic meningitis could be a rare side effect of lamotrigine. Aseptic meningitis is a clinical condition where symptoms, signs and laboratory findings are consistent with meningeal inflammation but routine bacterial cultures are negative. Clinical presentation of aseptic meningitis is similar to bacterial meningitis with prominent symptoms of fever, headache and neck stiffness. Drug-induced aseptic meningitis is an uncommon adverse effect of several drugs. The most common ones are nonsteroidal anti-inflammatory drugs, intravenous immunoglobulins, intrathecal agents and vaccines. Disease manifestations vary with different drugs. A few cases of lamotrigine-induced aseptic meningitis have been published earlier. This is the fifth case reported of lamotrigine-induced aseptic meningitis. However, this is the first case which is associated with a second episode on rechallenge of lamotrigine.

Ensuring Mixing Efficiency of Replica-Exchange Molecular Dynamics Simulations.

We address the question of constructing a protocol for replica-exchange molecular dynamics (REMD) simulations that make efficient use of the replica space, assess whether published applications are achieving such "mixing" efficiency, and provide a how-to guide to assist users to plan efficient REMD simulations. To address our first question, we introduce and discuss three metrics for assessing the number of replica-exchange attempts required to justify the use of a replica scheme and define a "transit number" as the lower bound for the length of an efficient simulation. Our literature survey of applications of REMD simulations of peptides in explicit solvent indicated that authors are not routinely reporting sufficient details of their simulation protocols to allow readers to make independent assessments of the impact of the method on their results, particularly whether mixing efficiency has been achieved. Necessary details include the expected or observed replica-exchange probability, together with the total number of exchange attempts, the exchange period, and estimates of the autocorrelation time of the potential energy. Our analysis of cases where the necessary information was reported suggests that in many of these simulations there are insufficient exchanges attempted or an insufficiently long period between them to provide confidence that the simulation length justifies the size of the replica scheme. We suggest guidelines for designing REMD simulation protocols to ensure mixing efficiency. Two key recommendations are that the exchange period should in general be larger than 1 ps and the number of exchange attempts should be chosen to significantly exceed the transit number for the replica scheme.