Potential Mercurian Analogues: Aubrite and Enstatite Chondrite Impact Melt Meteorites

The MESSENGER (MErcury Surface Space ENvironment GEochemistry and Ranging Spacecraft) mission provided new data that have helped us better constrain the surficial mineralogy and composition of Mercury. Mercury has an extremely low oxygen fugacity (f O2) (Iron Wustite (IW) -7.3 to IW -2.6), and at these unique conditions, elements, which usually exhibit lithophile behavior on Earth, can exhibit chalcophile or siderophile behavior on Mercury. No samples have been returned from Mercury; therefore, we must study candidate meteorite analogs to better understand the formation conditions of minerals inferred to be present at the Mercurian surface and Mercurian magmatic processes. In this study, we present a comprehensive analysis of a representative suite of eight aubrites and four enstatite chondrite impact melts (ECIM), which both have a similar f O2 to Mercury, and contain exotic sulfides that have been inferred to be present at the Mercurian surface. These characteristics allow us to assess their relevance for understanding the mineralogy and magmatic processes of Mercury. The ECIM were previously classified as aubrites, but we show that they are actually ECIM with a potential EH (high enstatite) parent body origin due to the presence of niningerite, Si-enriched kamacite, and uniform Ni in schreibersite. We propose that, with respect to the aubrites, the ECIM represent an ideal candidate for Mercurian studies due to their mineralogy and modal mineralogy. Compared to the aubrites, the ECIM samples do not contain forsterite or diopside, show a poorer sulfide diversity, contain graphite, and have a higher volume percentage of metal phases. Although the Mercurian surface contains forsterite and diopside, graphite and a similar amount of metal and sulfides as seen in the ECIM are inferred to be present on Mercury. According to the calculated normative Mercurian mineralogy, both candidate meteorites are most analogous to the Caloris Basin and Northern Plains Lower Mg regions

A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making

West Nile virus(WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input

The effects of highly reduced magmatism revealed through aubrites

Enstatite-rich meteorites, including the aubrites, formed under conditions of very low oxygen fugacity (ƒO2: iron-wüstite buffer −2 to −6) and thus offer the ability to study reduced magmatism present on multiple bodies in our solar system. Elemental partitioning among metals, sulfides, and silicates is poorly constrained at low ƒO2; however, studies of enstatite-rich meteorites may yield empirical evidence of the effects of low ƒO2 on elemental behavior. This work presents comprehensive petrologic and oxygen isotopic studies of 14 aubrites, including four meteorites that have not been previously investigated in detail. The aubrites exhibit a variety of textures and mineralogy, and their elemental zoning patterns point to slow cooling histories for all 14 samples. Oxygen isotope analyses suggest that the aubrite parent bodies may be more heterogeneous than originally reported or may have experienced incomplete magmatic differentiation. Contrary to the other classified aubrites and based on textural and mineralogical observations, we suggest that the Northwest Africa 8396 meteorite shows an affinity for an enstatite chondrite parentage. By measuring major elemental compositions of silicates, sulfides, and metals, we calculate new metal–silicate, sulfide–silicate, and sulfide–metal partition coefficients for aubrites that are applicable to igneous systems at low ƒO2. The geochemical behavior of elements in aubrites, as determined using partition coefficients, is similar to the geochemical behavior of elements determined experimentally for magmatic systems on Mercury. Enstatite-rich meteorites, including aubrites, represent valuable natural petrologic analogues to Mercury and their study could further our understanding of reduced magmatism in our solar system.12 month embargo; first published: 14 May 2022This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making.

West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m-km, days-weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstrac

Sensitive Detection of Minimal Residual Disease in Patients Treated for Early-Stage Breast Cancer

© 2020 American Association for Cancer Research. Purpose: Existing cell-free DNA (cfDNA) methods lack the sensitivity needed for detecting minimal residual disease (MRD) following therapy. We developed a test for tracking hundreds of patient-specific mutations to detect MRD with a 1,000-fold lower error rate than conventional sequencing. Experimental Design: We compared the sensitivity of our approach to digital droplet PCR (ddPCR) in a dilution series, then retrospectively identified two cohorts of patients who had undergone prospective plasma sampling and clinical data collection: 16 patients with ER+/HER2- metastatic breast cancer (MBC) sampled within 6 months following metastatic diagnosis and 142 patients with stage 0 to III breast cancer who received curative-intent treatment with most sampled at surgery and 1 year postoperative. We performed whole-exome sequencing of tumors and designed individualized MRD tests, which we applied to serial cfDNA samples. Results: Our approach was 100-fold more sensitive than ddPCR when tracking 488 mutations, but most patients had fewer identifiable tumor mutations to track in cfDNA (median = 57; range = 2–346). Clinical sensitivity was 81% (n = 13/16) in newly diagnosed MBC, 23% (n = 7/30) at postoperative and 19% (n = 6/32) at 1 year in early-stage disease, and highest in patients with the most tumor mutations available to track. MRD detection at 1 year was strongly associated with distant recurrence [HR = 20.8; 95% confidence interval, 7.3–58.9]. Median lead time from first positive sample to recurrence was 18.9 months (range = 3.4–39.2 months). Conclusions: Tracking large numbers of individualized tumor mutations in cfDNA can improve MRD detection, but its sensitivity is driven by the number of tumor mutations available to track

Infections in Infants with SCID: Isolation, Infection Screening, and Prophylaxis in PIDTC Centers.

PurposeThe Primary Immune Deficiency Treatment Consortium (PIDTC) enrolled children with severe combined immunodeficiency (SCID) in a prospective natural history study of hematopoietic stem cell transplant (HSCT) outcomes over the last decade. Despite newborn screening (NBS) for SCID, infections occurred prior to HSCT. This study's objectives were to define the types and timing of infection prior to HSCT in patients diagnosed via NBS or by family history (FH) and to understand the breadth of strategies employed at PIDTC centers for infection prevention.MethodsWe analyzed retrospective data on infections and pre-transplant management in patients with SCID diagnosed by NBS and/or FH and treated with HSCT between 2010 and 2014. PIDTC centers were surveyed in 2018 to understand their practices and protocols for pre-HSCT management.ResultsInfections were more common in patients diagnosed via NBS (55%) versus those diagnosed via FH (19%) (p = 0.012). Outpatient versus inpatient management did not impact infections (47% vs 35%, respectively; p = 0.423). There was no consensus among PIDTC survey respondents as to the best setting (inpatient vs outpatient) for pre-HSCT management. While isolation practices varied, immunoglobulin replacement and antimicrobial prophylaxis were more uniformly implemented.ConclusionInfants with SCID diagnosed due to FH had lower rates of infection and proceeded to HSCT more quickly than did those diagnosed via NBS. Pre-HSCT management practices were highly variable between centers, although uses of prophylaxis and immunoglobulin support were more consistent. This study demonstrates a critical need for development of evidence-based guidelines for the pre-HSCT management of infants with SCID following an abnormal NBS.Trial registrationNCT01186913