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We present an atmospheric retrieval analysis of a pair of highly variable, ∼200 Myr old, early T type planetary-mass exoplanet analogs SIMP J01365662+0933473 and 2MASS J21392676+0220226 using the Brewster retrieval framework. Our analysis, which makes use of archival 1–15μm spectra, finds almost identical atmospheres for both objects. For both targets, we find that the data is best described by a patchy, high-altitude forsterite (Mg₂SiO₄) cloud above a deeper, optically thick iron (Fe) cloud. Our model constrains the cloud properties well, including the cloud locations and cloud particle sizes. We find that the patchy forsterite slab cloud inferred from our retrieval may be responsible for the spectral behavior of the observed variability. Our retrieved cloud structure is consistent with the atmospheric structure previously inferred from spectroscopic variability measurements, but clarifies this picture significantly. We find consistent C/O ratios for both objects, which supports their formation within the same molecular cloud in the Carina-Near moving group. Finally, we note some differences in the constrained abundances of H₂O and CO, which may be caused by data quality and/or astrophysical processes such as auroral activity and their differing rotation rates. The results presented in this work provide a promising preview of the detail with which we will characterize extrasolar atmospheres with JWST, which will yield higher-quality spectra across a wider wavelength range.

 

Parasitic nematodes cause a massive worldwide burden on human health along with a loss of livestock and agriculture productivity. Anthelmintics have been widely successful in treating parasitic nematodes. However, resistance is increasing, and little is known about the molecular and genetic causes of resistance for most of these drugs. The free-living roundworm Caenorhabditis elegans provides a tractable model to identify genes that underlie resistance. Unlike parasitic nematodes, C . elegans is easy to maintain in the laboratory, has a complete and well annotated genome, and has many genetic tools. Using a combination of wild isolates and a panel of recombinant inbred lines constructed from crosses of two genetically and phenotypically divergent strains, we identified three genomic regions on chromosome V that underlie natural differences in response to the macrocyclic lactone (ML) abamectin. One locus was identified previously and encodes an alpha subunit of a glutamate-gated chloride channel ( glc-1 ). Here, we validate and narrow two novel loci using near-isogenic lines. Additionally, we generate a list of prioritized candidate genes identified in C . elegans and in the parasite Haemonchus contortus by comparison of ML resistance loci. These genes could represent previously unidentified resistance genes shared across nematode species and should be evaluated in the future. Our work highlights the advantages of using C . elegans as a model to better understand ML resistance in parasitic nematodes. 

As big data becomes an important part of business analytics for gaining insights about business practices, the quality of big data is an essential factor impacting the outcomes of business analytics. Although this is quite challenging, conceptual modelling has much potential to solve it since the good quality of data comes from good quality of models. However, existing data models at a conceptual level have limitations to incorporate quality aspects into big data models. In this paper, we focus on the challenges cause by Variety of big data propose IRIS, a conceptual modelling framework for big data models which enables us to define three modelling quality notions – relevance, comprehensiveness, and relative priorities and incorporate such qualities into a big data model in a goal-oriented approach. Explored big data models based on the qualities are integrated with existing data grounded on three conventional organizational dimensions creating a virtual big data model. An empirical study has been conducted using the shipping decision process of a worldwide retail chain, to gain an initial understanding of the applicability of this approach. 

In biological systems, chemical and physical transformations of engineered silver nanomaterials (AgENMs) are mediated, in part, by proteins and other biomolecules. Metalloprotein interactions with AgENMs are also central in understanding toxicity, antimicrobial, and resistance mechanisms. Despite their readily available thiolate and amine ligands, zinc finger (ZF) peptides have thus far escaped study in reaction with AgENMs and their Ag( i ) oxidative dissolution product. We report spectroscopic studies that characterize AgENM and Ag( i ) interactions with two ZF peptides that differ in sequence, but not in metal binding ligands: the ZF consensus peptide CP-CCHC and the C-terminal zinc finger domain of HIV-1 nucleocapsid protein p7 (NCp7_C). Both ZF peptides catalyze AgENM (10 and 40 nm, citrate coated) dissolution and agglomeration, two important AgENM transformations that impact bioreactivity. AgENMs and their oxidative dissolution product, Ag( i )(aq), mediate changes to ZF peptide structure and metalation as well. Spectroscopic titrations of Ag( i ) into apo-ZF peptides show an Ag( i )–thiolate charge transfer band, indicative of Ag( i )–ZF binding. Fluorescence studies of the Zn( ii )–NCp_7 complex indicate that the Ag( i ) also effectively competes with the Zn( ii ) to drive Zn( ii ) displacement from the ZFs. Upon interaction with AgENMs, Zn( ii ) bound ZF peptides show a secondary structural change in circular dichroism spectroscopy toward an apo-like structure. The results suggest that Ag( i ) and AgENMs may alter ZF protein function within the cell.