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The bis-monosubstituted aminocarbene-P₂adduct is a generator of P₂, under the classical triple-bonded form (PP), but it also acts as a bis(phosphinidene) (P–P) synthetic equivalent. 

In situ observed data are commonly used as species occurrence response variables in species distribution models. However, the use of remotely observed data from high‐resolution multispectral remote‐sensing images as a source of presence/absence data for species distribution models remains under‐developed. Here, we describe an ensemble species distribution model of black microbial mats "Nostoc" using presence/absence points derived from the unmixing of 4‐m resolution WorldView‐2 and WorldView‐3 images in the Lake Fryxell basin region of Taylor Valley, Antarctica. Environmental and topographical characteristics such as soil moisture, snow, elevation, slope, and aspect were used as predictor variables in our models. We demonstrate that we can build and run ensemble species distribution models using both dependent and independent variables derived from remote‐sensing data to generate spatially explicit habitat suitability maps. Snow and soil moisture were found to be the most important variables accounting for about 80% of the variation in the distribution of black mats throughout the Fryxell basin. This study highlights the potential contribution of high‐resolution remote‐sensing to species distribution modeling and informs new studies incorporating remotely derived species occurrences in species distribution models, especially in remote areas where access to in situ data is often limited. 

Abstract Articular cartilage (AC) is a load-bearing tissue that covers long bones in synovial joints. The biphasic/poroelastic mechanical properties of AC help it to protect joints by distributing loads, absorbing impact forces, and reducing friction. Unfortunately, alterations in these mechanical properties adversely impact cartilage function and precede joint degeneration in the form of osteoarthritis (OA). Thus, understanding what factors regulate the poroelastic mechanical properties of cartilage is of great scientific and clinical interest. Transgenic mouse models provide a valuable platform to delineate how specific genes contribute to cartilage mechanical properties. However, the poroelastic mechanical properties of murine articular cartilage are challenging to measure due to its small size (thickness ∼ 50 microns). In the current study, our objective was to test whether the poroelastic mechanical properties of murine articular cartilage can be determined based solely on time-dependent cell death measurements under constant loading conditions. We hypothesized that in murine articular cartilage subjected to constant, sub-impact loading from an incongruent surface, cell death area and tissue strain are closely correlated. We further hypothesized that the relationship between cell death area and tissue strain can be used—in combination with inverse finite element modeling—to compute poroelastic mechanical properties. To test these hypotheses, murine cartilage-on-bone explants from different anatomical locations were subjected to constant loading conditions by an incongruent surface in a custom device. Cell death area increased over time and scaled linearly with strain, which rose in magnitude over time due to poroelastic creep. Thus, we were able to infer tissue strain from cell death area measurements. Moreover, using tissue strain values inferred from cell death area measurements, we applied an inverse finite element modeling procedure to compute poroelastic material properties and acquired data consistent with previous studies. Collectively, our findings demonstrate in the key role poroelastic creep plays in mediating cell survival in mechanically loaded cartilage and verify that cell death area can be used as a surrogate measure of tissue strain that enables determination of murine cartilage mechanical properties. 

IntroductionThroughout domestication, crop plants have gone through strong genetic bottlenecks, dramatically reducing the genetic diversity in today’s available germplasm. This has also reduced the diversity in traits necessary for breeders to develop improved varieties. Many strategies have been developed to improve both genetic and trait diversity in crops, from backcrossing with wild relatives, to chemical/radiation mutagenesis, to genetic engineering. However, even with recent advances in genetic engineering we still face the rate limiting step of identifying which genes and mutations we should target to generate diversity in specific traits. MethodsHere, we apply a comparative evolutionary approach, pairing phylogenetic and expression analyses to identify potential candidate genes for diversifying soybean (Glycine max) canopy cover development via the nuclear auxin signaling gene families, while minimizing pleiotropic effects in other tissues. In soybean, rapid canopy cover development is correlated with yield and also suppresses weeds in organic cultivation. Results and discussionWe identified genes most specifically expressed during early canopy development from the TIR1/AFB auxin receptor, Aux/IAA auxin co-receptor, and ARF auxin response factor gene families in soybean, using principal component analysis. We defined Arabidopsis thaliana and model legume species orthologs for each soybean gene in these families allowing us to speculate potential soybean phenotypes based on well-characterized mutants in these model species. In future work, we aim to connect genetic and functional diversity in these candidate genes with phenotypic diversity in planta allowing for improvements in soybean rapid canopy cover, yield, and weed suppression. Further development of this and similar algorithms for defining and quantifying tissue- and phenotype-specificity in gene expression may allow expansion of diversity in valuable phenotypes in important crops.