Larry K. Allain

Screening native botanicals for bioactivity: An interdisciplinary approach

OBJECTIVE Plant-based therapies have been used in medicine throughout recorded history. Information about the therapeutic properties of plants often can be found in local cultures as folk medicine is communicated from one generation to the next. The aim of this study was to identify native Louisiana plants from Creole folk medicine as a potential source of therapeutic compounds for the treatment of insulin resistance, type 2 diabetes, and related disorders. METHODS We used an interdisciplinary approach combining expertise in disciplines ranging from cultural anthropology and botany to biochemistry and endocrinology to screen native southwest Louisiana plants. Translation of accounts of Creole folk medicine yielded a list of plants with documented use in treating a variety of conditions, including inflammation. These plants were collected, vouchered, and catalogued before extraction of soluble components. Extracts were analyzed for bioactivity in regulating inflammatory responses in macrophages or fatty acid-induced insulin resistance in C2C12 skeletal muscle cells. RESULTS Several extracts altered gene expression of inflammatory markers in macrophages. Multiplex analysis of kinase activation in insulin-signaling pathways in skeletal muscle also identified a subset of extracts that alter insulin-stimulated protein kinase B phosphorylation in the presence of fatty-acid-induced insulin resistance. CONCLUSION An interdisciplinary approach to screening botanical sources of therapeutic agents can be successfully applied to identify native plants used in folk medicine as potential sources of therapeutic agents in treating insulin resistance in skeletal muscle or inflammatory processes associated with obesity-related insulin resistance.

The Bees (Hymenoptera: Apoidea) of Louisiana: An Updated, Annotated Checklist

Abstract An annotated checklist is provided for 243 species and subspecies of bees collected from or thought to occur in the state of Louisiana, where 163 are confirmed records, 46 are probable records, and 34 are possible records. We also list twelve records considered to be “dubious” because of the absence of supporting collection data and extralimital reported ranges. Data on parish localities, seasonality, and floral records are provided when available. Specimen data are provided from two separate surveys in the state, one focusing on the fauna of longleaf pine savannas and another focusing on Cajun prairie habitat in southwestern Louisiana. Data from a previous annotated checklist of bees from longleaf pine savannas (Bartholomew et al. 2006) are included, as well as online records from the Discover Life checklist (Ascher and Pickering 2016), and bee holdings of the Louisiana State Arthropod Museum (LSAM, Louisiana State University, Baton Rouge, LA).We highlight the role that this museum and similar small institutional insect collections play in documenting faunas on local and regional scales.

High resolution landcover for the Western Gulf Coastal Plain of Louisiana

The dataset includes Land Use/Land Cover types throughout the Chenier Eco-Region in Southwest Louisiana. Using the 2015 NAIP dataset (1m) as the basemap, E-Cognition image objects were derived from the multiresolution segmentation algorithm at 75 and 250 segments. Attempts to refine the data training methods using E-cognition, to extrapolate automating categories of this information to the entire map resulted with exceedingly low accuracy. Therefore, a raster was produced by piecing together several data resources, which provide reliable data for specific LULC categories. This process involved stitching together more reliable sources for specific categories to apply to higher resolution (75) segmentation product. Reference datasets include; 12,000 aerial points assigned to image objects derived from 75 segmentation settings (previously used to develop scripts for data training), mask created from NWI 2008 including water, wetland forested, upland forested and scrub/shrub categories, BOEM marsh classes, NLCD urban areas, and CDL data. The raster produced from this process was applied to the vector image objects derived from the 250 segmentation settings, using a majority filter (greater than 50 percent). The series of draft shapefiles were manually edited and merged, resulting in the final dataset.

Grassland quality and pollinator habitat potential in Southwest Louisiana

Potential pollinator habitat was derived by ranking land use classifications and grassland quality based on ground truthing and remotely sensed features indicative of remnant prairie. High resolution (10m) land use data served as the basemap (Hartley et al 2017) from which most categories were identified. All known prairie remnants, prairie plantings, and clusters of mima mounds were delineated. Mima mounds were detected by deriving a slope at 1m scale with greater than 5% from high resolution LiDar data (3m). Mima mounds are indicative of areas in which the topsoil has not been significantly disturbed, and therefore have a higher potential to contain native prairie vegetation. Based on an in-depth literature review of pollinator ecology, high quality grasslands and land cover categories were ranked based on their relative potential to serve as pollinator habitat. Land cover categories were ranked in descending order from highest to lowest potential pollinator habitat.