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Human thanatomicrobiota studies have shown that microorganisms inhabit and proliferate externally and internally throughout the body and are the primary mediators of putrefaction after death. Yet little is known about the source and diversity of the thanatomicrobiome or the underlying factors leading to delayed decomposition exhibited by reproductive organs. The use of the V4 hypervariable region of bacterial 16S rRNA gene sequences for taxonomic classification (“barcoding”) and phylogenetic analyses of human postmortem microbiota has recently emerged as a possible tool in forensic microbiology. The goal of this study was to apply a 16S rRNA barcoding approach to investigate variation among different organs, as well as the extent to which microbial associations among different body organs in human cadavers can be used to predict forensically important determinations, such as cause and time of death. We assessed microbiota of organ tissues including brain, heart, liver, spleen, prostate, and uterus collected at autopsy from criminal casework of 40 Italian cadavers with times of death ranging from 24 to 432 h. Both the uterus and prostate had a significantly higher alpha diversity compared to other anatomical sites, and exhibited a significantly different microbial community composition from non-reproductive organs, which we found to be dominated by the bacterial orders MLE1-12, Saprospirales, and Burkholderiales. In contrast, reproductive organs were dominated by Clostridiales, Lactobacillales, and showed a marked decrease in relative abundance of MLE1-12. These results provide insight into the observation that the uterus and prostate are the last internal organs to decay during human decomposition. We conclude that distinct community profiles of reproductive versus non-reproductive organs may help guide the application of forensic microbiology tools to investigations of human cadavers. 

To improve the academic and professional achievement of underrepresented minorities in computing, a newfound interest in innovative mentoring practices has captivated STEM education researchers. Studies suggest that virtual mentoring conversational agents can be leveraged across multiple platforms to provide supplemental mentorship, offsetting the lack of access to in-person mentorship in disadvantaged communities. A within-subjects mixed-method experiment was carried out to assess the usability of a mentoring conversational agent. Mobile interfaces (Twitter and SMS) were compared to each other and against a web-based embodied conversational agent (ECA). Results suggest that mobile interfaces are more usable than the web-based ECA. The findings from this study help to identify areas for improvement in virtual learning alternatives and other potential applications for pervasive conversational interfaces. 

Insects are possibly the most taxonomically and ecologically diverse class of multicellular organisms on Earth. Consequently, they provide nearly unlimited opportunities to develop and test ecological and evolutionary hypotheses. Currently, however, large-scale studies of insect ecology, behavior, and trait evolution are impeded by the difficulty in obtaining and analyzing data derived from natural history observations of insects. These data are typically highly heterogeneous and widely scattered among many sources, which makes developing robust information systems to aggregate and disseminate them a significant challenge. As a step towards this goal, we report initial results of a new effort to develop a standardized vocabulary and ontology for insect natural history data. In particular, we describe a new database of representative insect natural history data derived from multiple sources (but focused on data from specimens in biological collections), an analysis of the abstract conceptual areas required for a comprehensive ontology of insect natural history data, and a database of use cases and competency questions to guide the development of data systems for insect natural history data. We also discuss data modeling and technology-related challenges that must be overcome to implement robust integration of insect natural history data. 

ABSTRACT We report on the discovery and validation of TOI 813 b (TIC 55525572 b), a transiting exoplanet identified by citizen scientists in data from NASA’s Transiting Exoplanet Survey Satellite (TESS) and the first planet discovered by the Planet Hunters TESS project. The host star is a bright (V = 10.3 mag) subgiant ($$R_\star =1.94\, R_\odot$$, $$M_\star =1.32\, M_\odot$$). It was observed almost continuously by TESS during its first year of operations, during which time four individual transit events were detected. The candidate passed all the standard light curve-based vetting checks, and ground-based follow-up spectroscopy and speckle imaging enabled us to place an upper limit of $$2\, M_{\rm Jup}$$ (99 per cent confidence) on the mass of the companion, and to statistically validate its planetary nature. Detailed modelling of the transits yields a period of $$83.8911 _{ - 0.0031 } ^ { + 0.0027 }$$ d, a planet radius of 6.71 ± 0.38 R⊕ and a semimajor axis of $$0.423 _{ - 0.037 } ^ { + 0.031 }$$ AU. The planet’s orbital period combined with the evolved nature of the host star places this object in a relatively underexplored region of parameter space. We estimate that TOI 813 b induces a reflex motion in its host star with a semi-amplitude of ∼6 m s−1, making this a promising system to measure the mass of a relatively long-period transiting planet.