An increasing number of metal bioavailability models are available for use in setting regulations and conducting risk assessments in aquatic systems. Selection of the most appropriate model is dependent on the user's needs but will always benefit from an objective, comparative assessment of the performance of available models. In 2017, an expert workshop developed procedures for assessing metal bioavailability models. The present study applies these procedures to evaluate the performance of biotic ligand models (BLMs) and multiple linear regression (MLR) models for copper. We find that the procedures recommended by the expert workshop generally provide a robust series of metrics for evaluating model performance. However, we recommend some modifications to the analysis of model residuals because the current method is insensitive to relatively large differences in residual patterns when comparing models. We also provide clarification on details of the evaluation procedure which, if not applied correctly, could mischaracterize model performance. We found that acute Cu MLR and BLM performances are quite comparable, though there are differences in performance on a species-specific basis and in the resulting water quality criteria as a function of water chemistry. In contrast, the chronic Cu MLR performed distinctly better than the BLM. Observed differences in performance are due to the smaller effects of hardness and pH on chronic Cu toxicity compared to acute Cu toxicity. These differences are captured in the chronic MLR model but not the chronic BLM, which only adjusts for differences in organism sensitivity. In general, we continue to recommend concurrent development of both modeling approaches because they provide useful comparative insights into the strengths, limitations, and predictive capabilities of each model. Environ Toxicol Chem 2021;401649-1661. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a preferred technique for analyzing complex organic mixtures. Currently, there is no consensus normalization approach, nor an objective method for selecting one, for quantitative analyses of FT-ICR-MS data. We investigate a method to evaluate and score the amount of bias various normalization approaches introduce into the data. We evaluate the ability of the Statistical Procedure for the Analysis of Normalization Strategies (SPANS) to guide the selection of appropriate normalization approaches for two different FT-ICR-MS data sets. Furthermore, we test the robustness of SPANS results to changes in SPANS parameter values and assess the impact of using various normalization approaches on downstream statistical analyses. The normalization approach identified by SPANS differed for the two data sets. Normalization methods impacted the statistical significance of peaks differently, underscoring the importance of carefully evaluating potly to the reproducibility of results than the p-value thresholds used to obtain those peaks. COVID-19 Convalescent Plasma (CCP) is a promising treatment for COVID-19. Blood collectors have rapidly scaled up collection and distribution programs. We developed a detailed simulation model of CCP donor recruitment, collection, production, and distribution processes. We ran our model using varying epidemic trajectories from 11 U.S. states and with key input parameters drawn from wide ranges of plausible values to identify key drivers of ability to scale collections capacity and meet demand for CCP. Utilization of available CCP collections capacity followed increases in COVID-19 hospital discharges with a lag. Utilization never exceeded 75% of available capacity in most simulations. Demand was met for most of the simulation period in most simulations, but a substantial portion of demand went unmet during early, sharp increases in hospitalizations. For epidemic trajectories that included multiple epidemic peaks, second wave demand could generally be met due to stockpiles established during the decline from an earlier peak. Apheresis machine capacity (number of machines) and probability that COVID-19 recovered individuals are willing to donate were the most important supply-side drivers of ability to meet demand. Recruitment capacity was important in states with early peaks. Epidemic trajectory was the most important determinant of ability to meet demand for CCP, although our simulations revealed several contributing operational drivers of CCP program success.Epidemic trajectory was the most important determinant of ability to meet demand for CCP, although our simulations revealed several contributing operational drivers of CCP program success.Conservation of North America's eastern monarch butterfly (Danaus plexippus) population would require establishment of milkweed (Asclepias spp.) and nectar plants in the agricultural landscapes of the north central United States. A variety of seed-treatment and foliar insecticides are used to manage early- and late-season pests in these landscapes. Thus, there is a need to assess risks of these insecticides to monarch butterfly life stages to inform habitat conservation practices. Chronic and acute dietary toxicity studies were undertaken with larvae and adults, and acute topical bioassays were conducted with eggs, pupae, and adults using 6 representative insecticides beta-cyfluthrin (pyrethroid), chlorantraniliprole (anthranilic diamide), chlorpyrifos (organophosphate), imidacloprid, clothianidin, and thiamethoxam (neonicotinoids). Chronic dietary median lethal concentration values for monarch larvae ranged from 1.6 × 10-3 (chlorantraniliprole) to 5.3 (chlorpyrifos) μg/g milkweed leaf, with the neonicotinoid1777. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Neutropenia is a risk factor for development of infections; however, the direct effect of neutropenia on development of bloodstream infection (BSI) is not known. D-index, which is area between the neutrophil time curve and a neutrophil count of 0.5×10 /L, incorporates the combined effect of severity and duration of neutropenia. Tenapanor We aimed to evaluate whether D-index can be used as a marker for BSI in patients with allogeneic stem cell transplantation. We conducted a retrospective cohort study of patients undergoing allogeneic stem cell transplantation between January 1, 2005, and September 30, 2015. The primary outcome measure was the development of BSI within 30days of transplantation. A total of 714 patients were included in the study of whom 101 developed BSI. Patients with BSI had a significantly higher median D-index value compared with patients who did not have BSI (4990 vs. 3570, P<.001). As a marker, the performance of the D-index was similar to that of the duration of profound neutropenia (P=.