Two of TESS's major science goals are to measure masses for 50 planets smaller than 4 Earth radii and to discover high-quality targets for atmospheric characterization efforts. It is important that these two goals are linked by quantifying what precision of mass constraint is required to yield robust atmospheric properties of planets. Here, we address this by conducting retrievals on simulated JWST transmission spectra under various assumptions for the degree of uncertainty in the planet's mass for a representative population of seven planets ranging from terrestrials to warm Neptunes to hot Jupiters. Only for the cloud-free, low metallicity gas giants are we able to infer exoplanet mass from transmission spectroscopy alone, to ∼10% accuracy. For low metallicity cases (< 4× Solar) we are able to accurately constrain atmospheric properties without prior knowledge of the planet's mass. For all other cases (including terrestrial-like planets), atmospheric properties can only be inferred with a mass precision of better than ±50%. At this level, though, the widths of the posterior distributions of the atmospheric properties are dominated by the uncertainties in mass. With a precision of ±20%, the widths of the posterior distributions are dominated by the spectroscopic data quality. Therefore, as a rule-of-thumb, we recommend: a ±50% mass precision for initial atmospheric characterization and a ±20% mass precision for more detailed atmospheric analyses.

The National Ambulatory Medical Care Survey collects data on office-based physician care from a nationally representative, multistage sampling scheme where the ultimate unit of analysis is a patient-doctor encounter. Patient race, a commonly analyzed demographic, has been subject to a steadily increasing item nonresponse rate. In 1999, race was missing for 17 percent of cases; by 2008, that figure had risen to 33 percent. Over this entire period, single imputation has been the compensation method employed. Recent research at the National Center for Health Statistics evaluated multiply imputing race to better represent the missing-data uncertainty. Given item nonresponse rates of 30 percent or greater, we were surprised to find many estimates’ ratios of multiple-imputation to single-imputation estimated standard errors close to 1. A likely explanation is that the design effects attributable to the complex sample design largely outweigh any increase in variance attributable to missing-data uncertainty.

This article discusses the potential effects of a shortened fielding period on an employee survey’s item and index scores and respondent demographics. Using data from the U.S. Office of Personnel Management’s 2011 Federal Employee Viewpoint Survey, we investigate whether early responding employees differ from later responding employees. Specifically, we examine differences in item and index scores related to employee engagement and global satisfaction. Our findings show that early responders tend to be less positive, even after adjusting their weights for nonresponse. Agencies vary in their prevalence of late responders, and score differences become magnified as this proportion increases. We also examine the extent to which early versus late responders differ on demographic characteristics such as grade level, supervisory status, gender, tenure with agency, and intention to leave, noting that nonminorities and females are the two demographic characteristics most associated with responding early.

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Mucins are present in mucosal membranes throughout the body and play a key role in the microbe clearance and infection prevention. Understanding the metabolic responses of pathogens to mucins will further enable the development of protective approaches against infections. We update the genome-scale metabolic network reconstruction (GENRE) of one such pathogen, Pseudomonas aeruginosa PA14, through metabolic coverage expansion, format update, extensive annotation addition, and literature-based curation to produce iPau21. We then validate iPau21 through MEMOTE, growth rate, carbon source utilization, and gene essentiality testing to demonstrate its improved quality and predictive capabilities. We then integrate the GENRE with transcriptomic data in order to generate context-specific models of P. aeruginosa metabolism. The contextualized models recapitulated known phenotypes of unaltered growth and a differential utilization of fumarate metabolism, while also revealing an increased utilization of propionate metabolism upon MUC5B exposure. This work serves to validate iPau21 and demonstrate its utility for providing biological insights.