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A large body of past work has sought to identify the underlying dimensions that capture our trait knowledge of other people. However, the importance of particular traits in determining our overall impressions of others is not well understood, and different traits may be fundamental for impressions of famous versus unfamiliar people. For instance, we may focus on competence when evaluating a famous person, but on trustworthiness when evaluating a stranger. To examine the structure of overall impressions of famous people and of unfamiliar people, we probed the contributions of 13 different trait judgments to perceived similarity judgments. We found that different sets of traits best predicted perceived similarity between famous people versus between unfamiliar people; however, the relationship between each trait and perceived similarity generalized to some extent from famous people to unfamiliar people, suggesting a degree of overlap in the structure of overall impressions. 

ABSTRACT The use of enterococci as a fecal indicator bacterial group for public health risk assessment has been brought into question by recent studies showing that “naturalized” populations of Enterococcus faecalis exist in the extraenteric environment. The extent to which these naturalized E. faecalis organisms can confound water quality monitoring is unclear. To determine if strains isolated from different habitats display different survival strategies and responses, we compared the decay patterns of three E. faecalis isolates from the natural environment (environmental strains) against three human gut isolates (enteric strains) in laboratory mesocosms that simulate an oligotrophic, aerobic freshwater environment. Our results showed similar overall decay rates between enteric and environmental isolates based on viable plate and quantitative PCR (qPCR) counts. However, the enteric isolates exhibited a spike in copy number ratios of 16S rRNA gene transcripts to 16S rRNA gene DNA copies (rRNA:rDNA ratios) between days 1 and 3 of the mesocosm incubations that was not observed in environmental isolates, which could indicate a different stress response. Nevertheless, there was no strong evidence of differential gene expression between environmental and enteric isolates related to habitat adaptation in the accompanying mesocosm metatranscriptomes. Overall, our results provide novel information on how rRNA levels may vary over different growth conditions (e.g., standard lab versus oligotrophic) for this important indicator bacteria. We also observed some evidence for habitat adaptation in E. faecalis ; however, this adaptation may not be substantial or consistent enough for integration in water quality monitoring. IMPORTANCE Enterococci are commonly used worldwide to monitor environmental fecal contamination and public health risk for waterborne diseases. However, closely related enterococci strains adapted to living in the extraenteric environment may represent a lower public health risk and confound water quality estimates. We developed an rRNA:rDNA viability assay for E. faecalis (a predominant species within this fecal group) and tested it against both enteric and environmental isolates in freshwater mesocosms to assess whether this approach can serve as a more sensitive water quality monitoring tool. We were unable to reliably distinguish the different isolate types using this assay under the conditions tested; thus, environmental strains should continue to be counted during routine water monitoring. However, this assay could be useful for distinguishing more recent (i.e., higher-risk) fecal pollution because rRNA levels significantly decreased after 1 week in all isolates. 

Abstract The unprecedented medium-resolution (R_λ∼ 1500–3500) near- and mid-infrared (1–18μm) spectrum provided by JWST for the young (140 ± 20 Myr) low-mass (12–20M_Jup) L–T transition (L7) companion VHS 1256 b gives access to a catalog of molecular absorptions. In this study, we present a comprehensive analysis of this data set utilizing a forward-modeling approach applying our Bayesian framework,ForMoSA. We explore five distinct atmospheric models to assess their performance in estimating key atmospheric parameters:T_eff, log(g), [M/H], C/O,γ,f_sed, andR. Our findings reveal that each parameter’s estimate is significantly influenced by factors such as the wavelength range considered and the model chosen for the fit. This is attributed to systematic errors in the models and their challenges in accurately replicating the complex atmospheric structure of VHS 1256 b, notably the complexity of its clouds and dust distribution. To propagate the impact of these systematic uncertainties on our atmospheric property estimates, we introduce innovative fitting methodologies based on independent fits performed on different spectral windows. We finally derived aT_effconsistent with the spectral type of the target, considering its young age, which is confirmed by our estimate of log(g). Despite the exceptional data quality, attaining robust estimates for chemical abundances [M/H] and C/O, often employed as indicators of formation history, remains challenging. Nevertheless, the pioneering case of JWST’s data for VHS 1256 b has paved the way for future acquisitions of substellar spectra that will be systematically analyzed to directly compare the properties of these objects and correct the systematics in the models.