Public Performance Metrics: Driving Physician Motivation and Performance

Introduction: As providers transition from “fee-for-service” to “pay-for-performance” models, focus has shifted to improving performance. This trend extends to the emergency department (ED) where visits continue to increase across the United States. Our objective was to determine whether displaying public performance metrics of physician triage data could drive intangible motivators and improve triage performance in the ED.Methods: This is a single institution, time-series performance study on a physician-in-triage system. Individual physician baseline metrics—number of patients triaged and dispositioned per shift—were obtained and prominently displayed with identifiable labels during each quarterly physician group meeting. Physicians were informed that metrics would be collected and displayed quarterly and that there would be no bonuses, punishments, or required training; physicians were essentially free to do as they wished. It was made explicit that the goal was to increase the number triaged, and while the number dispositioned would also be displayed, it would not be a focus, thereby acting as this study’s control. At the end of one year, we analyzed metrics.Results: The group’s average number of patients triaged per shift were as follows: Q1-29.2; Q2-31.9; Q3-34.4; Q4-36.5 (Q1 vs Q4, p < 0.00001). The average numbers of patients dispositioned per shift were Q1-16.4; Q2-17.8; Q3-16.9; Q4-15.3 (Q1 vs Q4, p = 0.14). The top 25% of Q1 performers increased their average numbers triaged from Q1-36.5 to Q4-40.3 (ie, a statistically insignificant increase of 3.8 patients per shift [p = 0.07]). The bottom 25% of Q1 performers, on the other hand, increased their averages from Q1-22.4 to Q4-34.5 (ie, a statistically significant increase of 12.2 patients per shift [p = 0.0013]).Conclusion: Public performance metrics can drive intangible motivators (eg, purpose, mastery, and peer pressure), which can be an effective, low-cost strategy to improve individual performance, achieve institutional goals, and thrive in the pay-for-performance era

Biophysical Aspects of Resource Acquisition and Competition in Algal Mixotrophs

Mixotrophic organisms combine autotrophic and heterotrophic nutrition and are abundant in both freshwater and marine environments. Recent observations indicate that mixotrophs constitute a large fraction of the biomass, bacterivory, and primary production in oligotrophic environments. While mixotrophy allows greater flexibility in terms of resource acquisition, any advantage must be traded off against an associated increase in metabolic costs, which appear to make mixotrophs uncompetitive relative to obligate autotrophs and heterotrophs. Using an idealized model of cell physiology and community competition, we identify one mechanism by which mixotrophs can effectively outcompete specialists for nutrient elements. At low resource concentrations, when the uptake of nutrients is limited by diffusion toward the cell, the investment in cell membrane transporters can be minimized. In this situation, mixotrophs can acquire limiting elements in both organic and inorganic forms, outcompeting their specialist competitors that can utilize only one of these forms. This advantage can be enough to offset as much as a twofold increase in additional metabolic costs incurred by mixotrophs. This mechanism is particularly relevant for the maintenance of mixotrophic populations and productivity in the highly oligotro phic subtropical oceans.United States. National Aeronautics and Space AdministrationGordon and Betty Moore Foundatio

High Microbial Diversity Despite Extremely Low Biomass in a Deep Karst Aquifer

Despite the importance of karst aquifers as a source of drinking water, little is known about the role of microorganisms in maintaining the quality of this water. One of the limitations in exploring the microbiology of these environments is access, which is usually limited to wells and surface springs. In this study, we compared the microbiology of the Madison karst aquifer sampled via the potentiometric lakes of Wind Cave with surface sampling wells and a spring. Our data indicated that only the Streeter Well (STR), which is drilled into the same hydrogeologic domain as the Wind Cave Lakes (WCL), allowed access to water with the same low biomass (1.56–9.25 × 103 cells mL-1). Filtration of ∼300 L of water from both of these sites through a 0.2 μm filter allowed the collection of sufficient cells for DNA extraction, PCR amplification of 16S rRNA gene sequences, and identification through pyrosequencing. The results indicated that bacteria (with limited archaea and no detectable eukaryotic organisms) dominated both water samples; however, there were significant taxonomic differences in the bacterial populations of the samples. The STR sample was dominated by a single phylotype within the Gammaproteobacteria (Order Acidithiobacillales), which dramatically reduced the overall diversity and species richness of the population. In WCL, despite less organic carbon, the bacterial population was significantly more diverse, including significant contributions from the Gammaproteobacteria, Firmicutes, Chloroflexi, Actinobacteria, Planctomycetes, Fusobacter, and Omnitrophica phyla. Comparisons with similar oligotrophic environments suggest that karst aquifers have a greater species richness than comparable surface environs. These data also demonstrate that Wind Cave provides a unique opportunity to sample a deep, subterranean aquifer directly, and that the microbiology of such aquifers may be more complex than previously anticipated

Relative exposure to microplastics and prey for a pelagic forage fish

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chavarry, J. M., Law, K. L., Barton, A. D., Bowlin, N. M., Ohman, M. D., & Choy, C. A. Relative exposure to microplastics and prey for a pelagic forage fish. Environmental Research Letters, 17(6), (2022): 064038, https://doi.org/10.1088/1748-9326/ac7060.In the global ocean, more than 380 species are known to ingest microplastics (plastic particles less than 5 mm in size), including mid-trophic forage fishes central to pelagic food webs. Trophic pathways that bioaccumulate microplastics in marine food webs remain unclear. We assess the potential for the trophic transfer of microplastics through forage fishes, which are prey for diverse predators including commercial and protected species. Here, we quantify Northern Anchovy (Engraulis mordax) exposure to microplastics relative to their natural zooplankton prey, across their vertical habitat. Microplastic and zooplankton samples were collected from the California Current Ecosystem in 2006 and 2007. We estimated the abundance of microplastics beyond the sampled size range but within anchovy feeding size ranges using global microplastic size distributions. Depth-integrated microplastics (0–30 m depth) were estimated using a depth decay model, accounting for the effects of wind-driven vertical mixing on buoyant microplastics. In this coastal upwelling biome, the median relative exposure for an anchovy that consumed prey 0.287–5 mm in size was 1 microplastic particle for every 3399 zooplankton individuals. Microplastic exposure varied, peaking within offshore habitats, during the winter, and during the day. Maximum exposure to microplastic particles relative to zooplankton prey was higher for juvenile (1:23) than adult (1:33) anchovy due to growth-associated differences in anchovy feeding. Overall, microplastic particles constituted fewer than 5% of prey-sized items available to anchovy. Microplastic exposure is likely to increase for forage fishes in the global ocean alongside declines in primary productivity, and with increased water column stratification and microplastic pollution.This work originated from the Plastic Awareness Global Initiative (PAGI) international workshop, hosted by the Center for Marine Biodiversity and Conservation (CMBC) at Scripps Institution of Oceanography at the University of California San Diego in 2018, with support from Igor Korneitchouk and the Wilsdorf Mettler Future Foundation. We thank the workshop participants for early discussions and a collaborative meeting space. We thank Kelly Lance for her illustration contributions, and the SIO Communications Office for their support. We thank Miriam Doyle and Ryan Rykaczewski for their assistance in data acquisition, and we thank Penny Dockry and Stuart Sandin of CMBC for administrative and logistical support. Julia Chavarry was supported by the San Diego Fellowship. This paper is a contribution from the California Current Ecosystem Long Term Ecological Research site, supported by the National Science Foundation

The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing

Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model), generalizing our previous approach (Ising model) that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these) predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = −0.74, p = 3.6×10−6) are strongly correlated, and this was further strengthened in the regularized Ising model (r = −0.83, p = 3.7×10−12). Performance of the Potts model (r = −0.73, p = 9.7×10−9) was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion, and harnessing this knowledge for immunogen design

Counts-in-Cylinders in the Sloan Digital Sky Survey with Comparisons to N-body Simulations

Environmental statistics provide a necessary means of comparing the properties of galaxies in different environments and a vital test of models of galaxy formation within the prevailing, hierarchical cosmological model. We explore counts-in-cylinders, a common statistic defined as the number of companions of a particular galaxy found within a given projected radius and redshift interval. Galaxy distributions with the same two-point correlation functions do not necessarily have the same companion count distributions. We use this statistic to examine the environments of galaxies in the Sloan Digital Sky Survey, Data Release 4. We also make preliminary comparisons to four models for the spatial distributions of galaxies, based on N-body simulations, and data from SDSS DR4 to study the utility of the counts-in-cylinders statistic. There is a very large scatter between the number of companions a galaxy has and the mass of its parent dark matter halo and the halo occupation, limiting the utility of this statistic for certain kinds of environmental studies. We also show that prevalent, empirical models of galaxy clustering that match observed two- and three-point clustering statistics well fail to reproduce some aspects of the observed distribution of counts-in-cylinders on 1, 3 and 6-Mpc/h scales. All models that we explore underpredict the fraction of galaxies with few or no companions in 3 and 6-Mpc/h cylinders. Roughly 7% of galaxies in the real universe are significantly more isolated within a 6 Mpc/h cylinder than the galaxies in any of the models we use. Simple, phenomenological models that map galaxies to dark matter halos fail to reproduce high-order clustering statistics in low-density environments.Comment: 17 pages, 10 figures. Accepted, Ap

Report on the “Trait-based approaches to ocean life” scoping workshop, October 5-8, 2015

"Trait-based Approaches to Ocean Life” Scoping Workshop, October 5-8, 2015, Waterville Valley, NH, USAFrom the introduction: Marine ecosystems are rich and biodiverse, often populated by thousands of competing and interacting species with a vast range of behaviors, forms, and life histories. This great ecological complexity presents a formidable challenge to understanding how marine ecosystems are structured and controlled, but also how they respond to natural and anthropogenic changes. The trait-based approach to ocean life is emerging as a novel framework for understanding the complexity, structure, and dynamics of marine ecosystems, but also their broader significance. Rather than considering species individually, organisms are characterized by essential traits that capture key aspects of diversity. Trait distributions in the ocean emerge through evolution and natural selection, and are mediated by the environment, biological interactions, anthropogenic drivers, and organism behavior. Because trait variations within and across communities lead to variation in the rates of crucial ecosystem functions such as carbon export, this mechanistic approach sheds light on how variability in the environment, including climate change, impacts marine ecosystems, biogeochemical cycles, and associated feedbacks to climate and society.Funding from the National Science Foundation and National Aeronautics and Space Administration), the Simons Foundation, and the Gordon and Betty Moore Foundation

Satellite detection of dinoflagellate blooms off California by UV reflectance ratios

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kahru, M., Anderson, C., Barton, A. D., Carter, M. L., Catlett, D., Send, U., Sosik, H. M., Weiss, E. L., & Mitchell, B. G. Satellite detection of dinoflagellate blooms off California by UV reflectance ratios. Elementa: Science of the Anthropocene, 9(1), (2021): 00157, https://doi.org/10.1525/elementa.2020.00157.As harmful algae blooms are increasing in frequency and magnitude, one goal of a new generation of higher spectral resolution satellite missions is to improve the potential of satellite optical data to monitor these events. A satellite-based algorithm proposed over two decades ago was used for the first time to monitor the extent and temporal evolution of a massive bloom of the dinoflagellate Lingulodinium polyedra off Southern California during April and May 2020. The algorithm uses ultraviolet (UV) data that have only recently become available from the single ocean color sensor on the Japanese GCOM-C satellite. Dinoflagellates contain high concentrations of mycosporine-like amino acids and release colored dissolved organic matter, both of which absorb strongly in the UV part of the spectrum. Ratios 1, consistent with historical observations showing a sharp transition from dinoflagellate- to diatom-dominated waters in these areas. UV bands are thus potentially useful in the remote sensing of phytoplankton blooms but are currently available only from a single ocean color sensor. As several new satellites such as the NASA Plankton, Aerosol, Cloud, and marine Ecosystem mission will include UV bands, new algorithms using these bands are needed to enable better monitoring of blooms, especially potentially harmful algal blooms, across large spatiotemporal scales.Part of this work was funded by National Science Foundation (NSF) grants to the CCE-LTER Program, most recently OCE-1637632. Processing of Second-Generation Global Imager satellite data was funded by Japan Aerospace Exploration Agency. Data shown in Figure 1 were collected by BGM and MK with support from the NASA SIMBIOS project. DC was supported by the NASA Biodiversity and Ecological Forecasting Program (Grant NNX14AR62A), the Bureau of Ocean and Energy Management Ecosystem Studies Program (BOEM award MC15AC00006), and the NOAA through the Santa Barbara Channel Marine Biodiversity Observation Network. HMS was supported by NSF (Grant OCE-1810927) and the Simons Foundation (Grant 561126). ELW was supported by NSF GRFP (Grant DGE-1650112). Funding for Scripps and Santa Monica Piers sampling was through the Southern California Coastal Ocean Observing Harmful Algal Bloom Monitoring Program by NOAA NA16NOS0120022