Isolation and identification of Treponema pedis and Treponema phagedenis-like organisms from bovine digital dermatitis lesions found in dairy cattle in Turkey

The isolation and identification of microorganisms associated with digital dermatitis (DD) in tur dairy cattle was investigated using punch skin biopsy samples from typical clinical lesions; they were collected from dairy farms and abattoirs in 5 different geographical locations in Turkey. Morphological characteristics and flagellation types were examined using a transmission electron microscope, and their enzyme profiles by enzyme activation kits; their catalase reaction characteristics were evaluated by the addition of 3% H2O2. Their phylogenies were identified using 16S rRNA and the results compared with known gene bank data. Bacterial cells were 5.0 to 18.2 µm long, 0.2 to 0.5 µm wide, and their minimum number of periplasmic flagellum was 4 (4:8:4) with a maximum of 8 (8:16:8). All isolates were catalase negative. Of the spirochetes isolated and identified, group I organisms showed close similarity with Treponema pedis (99% genetic homology), whereas those in group II were similar to Treponema phagedenis (98% homology). This is the first report of specific sub-groups of Treponema spp., isolated from tur dairy cattle presenting with DD lesions, being associated with this disease; these morphotypes were similar to those found globally in housed dairy cattle units and are probably significant microorganisms associated with the aetiopathogensis of this infectious disease causing acute bovine lameness. These results suggest that the distribution of DD-associated treponemes is not specific to particular geographic regions of Turkey. © 2018 American Dairy Science Associatio

Multimodal Imaging and Lighting Bias Correction for Improved μPAD-based Water Quality Monitoring via Smartphones

Smartphone image-based sensing of microfluidic paper analytical devices (mu PADs) offers low-cost and mobile evaluation of water quality. However, consistent quantification is a challenge due to variable environmental, paper, and lighting conditions, especially across large multi-target mu PADs. Compensations must be made for variations between images to achieve reproducible results without a separate lighting enclosure. We thus developed a simple method using triple-reference point normalization and a fast-Fourier transform (FFT)-based pre-processing scheme to quantify consistent reflected light intensity signals under variable lighting and channel conditions. This technique was evaluated using various light sources, lighting angles, imaging backgrounds, and imaging heights. Further testing evaluated its handle of absorbance, quenching, and relative scattering intensity measurements from assays detecting four water contaminants-Cr(VI), total chlorine, caffeine, and E. coli K12-at similar wavelengths using the green channel of RGB images. Between assays, this algorithm reduced error from mu PAD surface inconsistencies and cross-image lighting gradients. Although the algorithm could not completely remove the anomalies arising from point shadows within channels or some non-uniform background reflections, it still afforded order-of-magnitude quantification and stable assay specificity under these conditions, offering one route toward improving smartphone quantification of mu PAD assays for in-field water quality monitoring.National Science Foundation Graduate Research Fellowship [DGE-1143953]; Paul D. Coverdell Fellows Program; Water and Environmental Technology (WET) Center at the University of Arizona; Tucson WaterThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]