Canine borreliosis: a laboratory diagnostic trial

The aim of this study was to investigate samples from dogs suggestive of active canine borreliosis (group A) by culture and PCR and the detection of antibodies against Borrelia burgdorferi sensu lato in order to confirm a presumptive clinical diagnosis of canine borreliosis by laboratory results. Criteria for such a diagnosis were: history of tick exposure, lameness, neurological signs, nephropathy, lethargy, anorexia, and fever. A total of 302 samples comprising EDTA blood, urine, synovial fluid, cerebrospinal fluid, and tissue (skin, synovial membrane, kidney) from 98 dogs (26 with arthritis, 46 with neurological signs, 21 with nephropathy, 5 with non-specific symptoms) were collected and examined. Moreover, 55 healthy dogs (group B) and 236 dogs with symptoms or injuries unlikely to be associated with borreliosis (group C) were included in this study. Blood serum samples collected from all individuals (n=389) were analysed by ELISA. Twenty-one (21%) out of 98 dogs from group A, 4 (7%) out of 55 from group B and 15 (6%) out of 236 dogs from group C were positive for antibodies against B. burgdorferi sensu lato. The seroprevalences between groups A, B and C differed significantly. None of the corresponding samples investigated by PCR and culture were positive for spirochetal DNA or viable spirochetes. Borrelia afzelii was grown from one EDTA-blood sample but the corresponding blood serum sample remained antibody-negative. Consequently, the etiologic role of B. afzelii in this case is unclear. In approximately 40% of the presumptive canine borreliosis cases, other lesions have been found to be responsible for clinical signs. This study affirms that a definitive diagnosis of canine borreliosis cannot be made by clinical symptoms and serology based on a single consultation. Moreover, this study clearly revealed that the diagnostic sensitivity is enhanced by a thorough consideration and exclusion of other diseases.     

The use of photometric test kits for investigations of soil enzyme activities

The objective was to test the applicability of different photometric test kits for the determination of potential and actual nitrification and the activities of urease, invertase, and cellobiase in soil. Three water affected grassland sites, influenced by the maritime climate were investigated. The results obtained by the test kits and by standard methods were similar. Soil organic matter content was found as most important factor determining the enzyme activities on these three grassland sites with similar pH‐values. At the site with the largest soil organic matter content the highest activities for urease, invertase, and cellobiase were found. However, this was not true for the nitrification rates.     

Division of labor with a workforce of one: challenges in specifying effector and memory T cell fate

In the course of the immune response against microbes, na?ve T cells proliferate and generate varied classes of effector cells, as well as memory cells with distinct properties and functions. Owing to recent technological advances, some of the most imposing questions regarding effector and memory T cell differentiation are now becoming experimentally soluble: How many classes of antigen-specific T cells exist, and how malleable are they in their fate and in their functional state? How might a spectrum of cell fates be imparted to the clonal descendants of a single lymphocyte? Where, when, and how does pathogen-associated information refine the instruction, selection, and direction of newly activated T cells as they perform their tasks in different locations and times? Some surprising new glimpses ahead on these subjects and other yet-unanswered questions are discussed.     

Genome-wide linkage and QTL mapping in porcine F2 families generated from Pietrain, Meishan and Wild Boar crosses

Three informative pig F₂ families based on European Wild Boar (W), Meishan (M) and Pietrain (P) crosses have been used for genome‐wide linkage and quantitative trait loci (QTL) analysis. Altogether 129 microsatellites, 56 type I loci and 46 trait definitions (specific to growth, fattening, fat deposition, muscling, meat quality, stress resistance and body conformation) were included in the study. In the linkage maps of M × P, W × P and W × M families, average spacing of markers were 18.4, 19.7 and 18.8 cM, the numbers of informative meioses were 582, 534 and 625, and the total lengths of autosomes measured were 27.3, 26.0 and 26.2 Morgan units, respectively. Maternal maps were on average 1.3 times longer than paternal maps. QTLs contributing more than 3% of F₂ phenotypic variance could be identified at p < 0.05 chromosome‐wide level. Differences in the numbers and positions of QTLs were observed between families. Genome‐wide significant QTL effects were mapped for growth and fattening traits on eight chromosomes (1, 2, 4, 13, 14, 17, 18 and X), for fat deposition traits on seven chromosomes (1, 2, 3, 4, 6, 7 and X), for muscling traits on 11 chromosomes (1, 2, 3, 4, 6, 7, 8, 12, 14, 15 and X), for meat quality and stress resistance traits on seven chromosomes (2, 3, 6, 13, 16, 18 and X), and QTLs for body‐conformation traits were detected on 14 chromosomes. Closely correlated traits showed similar QTL profiles within families. Major QTL effects for meat quality and stress resistance traits were found on SSC6 in the interval RYR1‐A1BG in the W × P and M × P families, and could be attributed to segregation of the RYR1 allele T derived from Pietrain, whereas no effect in the corresponding SSC6 interval was found in family W × M, where Wild Boar and Meishan both contributed the RYR1 allele C. QTL positions were mostly similar in two of the three families for body conformation traits and for growth, fattening, fat deposition and muscling traits, especially on SSC4 (interval SW1073‐NGFB). QTLs with large effects were also mapped on SSC7 in the major histocompatibility complex (MHC) (interval CYP21A2‐S0102) and affected body length, weight of head and many other traits. The identification of DNA variants in genes causative for the QTLs requires further fine mapping of QTL intervals and a positional cloning. However, for these subsequent steps, the genome‐wide QTL mapping in F₂ families represents an essential starting point and is therefore significant for animal breeding.     

Identification of broad-leaved dock (Rumex obtusifolius L.) on grassland by means of digital image processing

Digital image processing has the potential to support the identification of plant species required for site-specific weed control in grassland swards. The present study focuses on the identification of one of the most invasive and persistent weed species on European grassland, the broad-leaved dock (Rumex obtusifolius L., R.o.), in complex mixtures of perennial ryegrass with R.o. and other herbs.A total of 108 digital photographs were obtained from a field experiment under constant recording geometry and illumination conditions. An object-oriented image classification was performed. Image segmentation was done by transforming the red, green, blue (RGB) colour images to greyscale intensity images. Based on that, local homogeneity images were calculated and a homogeneity threshold (0.97) was applied to derive binary images. Finally, morphological opening was performed. The remaining contiguous regions were considered to be objects. Features describing shape, colour and texture were calculated for each of these objects. A Maximum-likelihood classification was done to discriminate between the weed species. In addition, rank analysis was used to test how combinations of features influenced the classification result.The detection rate of R.o. varied with the training dataset used for classification. Average R.o. detection rates ranged from 71 to 95% for the 108 images, which included more than 3,600 objects. Misclassifications of R.o. occurred mainly with Plantago major (P.m.). Between 9 and 16% R.o. objects were classified incorrectly as P.m. and 17–24% P.m. objects were misclassified as R.o. The classification result was influenced by the defined object classes (R.o., P.m., T.o., soil, residue vs. R.o., residue). For instance, classification rates were 86–91% and 65–82% for R.o. exclusively and R.o. against the remaining herb species, respectively.