Identification of Bartonella species in rodents, shrews and cats in Denmark: detection of two B-henselae variants, one in cats and the other in the long-tailed field mouse

Small mammals and stray cats were trapped in two areas of North Zealand, Denmark, and their blood cultured for hemotrophic bacteria. Bacterial isolates were recovered in pure culture and subjected to 16S rDNA gene sequencing. Bartonella species were isolated from five mammalian species: B. grahamii from Microtus agrestis (field vole) and Apodemus flavicollis (yellow-necked field mouse); B. taylorii from M. agrestis, A. flavicollis and A. sylvaticus (long-tailed field mouse); B. tribocorum from A. flavicollis; R vinsonii subsp. vinsonii from M. agrestis and A. sylvaticus; and B. birtlesii from Sorex vulgaris (common shrew). In addition, two variant types of B. henselae were identified: variant I was recovered from three specimens of A. sylvaticus, and B. henselae variant 11 from I I cats; in each case this was the only B. henselae variant found. No Bartonella species was isolated from Clethrionomys glareolus (bank vole) or Micromys minutus (harvest mouse). These results suggest that B. henselae occurs in two animal reservoirs in this region, one of variant I in A. sylvaticus, which may be transmitted between mice by the tick Ixodes ricinus, and another of variant 11 in cats, which may be transmitted by the cat flea (Ctenocephalides felis). To our knowledge, this is the first report of the occurrence of B. henselae and B. tribocorum in Apodemus mice.

Parkinsonian tremor identification with multiple local field potential feature classification

This paper explores the development of multi-feature classification techniques used to identify tremor-related characteristics in the Parkinsonian patient. Local field potentials were recorded from the subthalamic nucleus and the globus pallidus internus of eight Parkinsonian patients through the implanted electrodes of a Deep brain stimulation (DBS) device prior to device internalization. A range of signal processing techniques were evaluated with respect to their tremor detection capability and used as inputs in a multi-feature neural network classifier to identify the activity of Parkinsonian tremor. The results of this study show that a trained multi-feature neural network is able, under certain conditions, to achieve excellent detection accuracy on patients unseen during training. Overall the tremor detection accuracy was mixed, although an accuracy of over 86% was achieved in four out of the eight patients.

Effectiveness of mobile apps in teaching field-based identification skills

It has been suggested that few students graduate with the skills required for many ecological careers, as field-based learning is said to be in decline in academic institutions. Here, we asked if mobile technology could improve field-based learning, using ability to identify birds as the study metric. We divided a class of ninety-one undergraduate students into two groups for field-based sessions where they were taught bird identification skills. The first group has access to a traditional identification book and the second group were provided with an identification app. We found no difference between the groups in the ability of students to identify birds after three field sessions. Furthermore, we found that students using the traditional book were significantly more likely to identify novel species. Therefore, we find no evidence that mobile technology improved students’ ability to retain what they experienced in the field; indeed, there is evidence that traditional field guides were more useful to students as they attempted to identify new species. Nevertheless, students felt positively about using their own smartphone devices for learning, highlighting that while apps did not lead to an improvement in bird identification ability, they gave greater accessibility to relevant information outside allocated teaching times.

Identification of mutations conferring insecticide-insensitive AChE in the cotton-melon aphid, Aphis gossypii Glover

We have identified two mutations in the ace1 gene of Aphis gossypii that are associated with insensitivity of acetylcholinesterase (AChE) to carbamate and organophosphate insecticides. The first of these, S431F (equivalent to F331 in Torpedo californica), is associated with insensitivity to the carbamate insecticide pirimicarb in a range of A. gossypii clones. The S431F mutation is also found in the peach-potato aphid, Myzus persicae (Sulzer), and a rapid RFLP diagnostic allows the identification of individuals of both aphid species with a resistant genotype. This diagnostic further revealed the presence of S431 in several other pirimicarb-susceptible aphid species. The serine at this position in the wild-type enzyme has only been reported for aphids and provides a molecular explanation of why pirimicarb has a specific aphicidal action. A less specific insensitivity to a wide range of carbamates and organophosphates is associated with a second mutation, A302S (A201 in T. californica).

State-space model identification of a wireless THz network

We model the large scale fading of wireless THz communications links deployed in a metropolitan area taking into account reception through direct line of sight, ground or wall reflection and diffraction. The movement of the receiver in the three dimensions is modelled by an autonomous dynamic linear system in state-space whereas the geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A subspace algorithm in conjunction with polynomial regression is used to identify a Wiener model from time-domain measurements of the field intensity.

Wiener-System subspace identification for mobile wireless mm-wave networks

We discuss the feasibility of wireless terahertz communications links deployed in a metropolitan area and model the large-scale fading of such channels. The model takes into account reception through direct line of sight, ground and wall reflection, as well as diffraction around a corner. The movement of the receiver is modeled by an autonomous dynamic linear system in state space, whereas the geometric relations involved in the attenuation and multipath propagation of the electric field are described by a static nonlinear mapping. A subspace algorithm in conjunction with polynomial regression is used to identify a single-output Wiener model from time-domain measurements of the field intensity when the receiver motion is simulated using a constant angular speed and an exponentially decaying radius. The identification procedure is validated by using the model to perform q-step ahead predictions. The sensitivity of the algorithm to small-scale fading, detector noise, and atmospheric changes are discussed. The performance of the algorithm is tested in the diffraction zone assuming a range of emitter frequencies (2, 38, 60, 100, 140, and 400 GHz). Extensions of the simulation results to situations where a more complicated trajectory describes the motion of the receiver are also implemented, providing information on the performance of the algorithm under a worst case scenario. Finally, a sensitivity analysis to model parameters for the identified Wiener system is proposed.

MIMO Wiener model identification for large scale fading of wireless mobile communications links

The large scale fading of wireless mobile communications links is modelled assuming the mobile receiver motion is described by a dynamic linear system in state-space. The geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A Wiener system subspace identification algorithm in conjunction with polynomial regression is used to identify a model from time-domain estimates of the field intensity assuming a multitude of emitters and an antenna array at the receiver end.

Identification of metabolites in human hepatic bile using 800 MHz 1H NMR spectroscopy, HPLC-NMR/MS and UPLC-MS

The first application of high field NMR spectroscopy (800 MHz for 1H observation) to human hepatic bile (as opposed to gall bladder bile) is reported. The bile sample used for detailed investigation was from a donor liver with mild fat infiltration, collected during organ retrieval prior to transplantation. In addition, to focus on the detection of bile acids in particular, a bile extract was analysed by 800 MHz 1H NMR spectroscopy, HPLC-NMR/MS and UPLC-MS. In the whole bile sample, 40 compounds have been assigned with the aid of two-dimensional 1H–1H TOCSY and 1H–13C HSQC spectra. These include phosphatidylcholine, 14 amino acids, 10 organic acids, 4 carbohydrates and polyols (glucose, glucuronate, glycerol and myo-inositol), choline, phosphocholine, betaine, trimethylamine-N-oxide and other small molecules. An initial NMR-based assessment of the concentration range of some key metabolites has been made. Some observed chemical shifts differ from expected database values, probably due to a difference in bulk diamagnetic susceptibility. The NMR spectra of the whole extract gave identification of the major bile acids (cholic, deoxycholic and chenodeoxycholic), but the glycine and taurine conjugates of a given bile acid could not be distinguished. However, this was achieved by HPLC-NMR/MS, which enabled the separation and identification of ten conjugated bile acids with relative abundances varying from approximately 0.1% (taurolithocholic acid) to 34.0% (glycocholic acid), of which, only the five most abundant acids could be detected by NMR, including the isomers glycodeoxycholic acid and glycochenodeoxycholic acid, which are difficult to distinguish by conventional LC-MS analysis. In a separate experiment, the use of UPLC-MS allowed the detection and identification of 13 bile acids. This work has shown the complementary potential of NMR spectroscopy, MS and hyphenated NMR/MS for elucidating the complex metabolic profile of human hepatic bile. This will be useful baseline information in ongoing studies of liver excretory function and organ transplantation.

Use of a LightCycler gyrA mutation assay for rapid identification of mutations conferring decreased susceptibility to ciprofloxacin in multiresistant Salmonella enterica serotype typhimurium DT104 isolates

A LightCycler-based PCR-hybridization gyrA mutation assay (GAMA) was developed to rapidly detect gyrA point mutations in multiresistant (MR) Salmonella enterica serotype Typhimurium DT104 with decreased susceptibility to ciprofloxacin (MIC, 0.25 to 1.0 mg/liter). Ninety-two isolates (49 human, 43 animal) were tested with three individual oligonucleotide probes directed against an Asp-87-to-Asn (GAC --> AAC) mutation, an Asp-87-to-Gly (GAC --> GGC) mutation, and a Ser-83-to-Phe (TCC --> TTC) mutation. Strains homologous to the probes could be distinguished from strains that had different mutations by their probe-target melting temperatures. Thirty-seven human and 30 animal isolates had an Asp-87-to-Asn substitution, 6 human and 6 animal isolates had a Ser-83-to-Phe substitution, and 5 human and 2 animal isolates had an Asp-87-to-Gly substitution. The remaining six strains all had mismatches with the three probes and therefore different gyrA mutations. The sequencing of gyrA from these six isolates showed that one human strain and two animal strains had an Asp-87-to-Tyr (GAC --> TAC) substitution and two animal strains had a Ser-83-to-Tyr (TCC --> TAC) substitution. One animal strain had no gyrA mutation, suggesting that this isolate had a different mechanism of resistance. Fifty-eight of the strains tested were indistinguishable by several different typing methods including antibiograms, pulsed-field gel gel electrophoresis, and plasmid profiling, although they could be further subdivided according to gyrA mutation. This study confirmed that MR DT104 with decreased susceptibility to ciprofloxacin from humans and food animals in England and Wales may have arisen independently against a background of clonal spread of MR DT104.

The identification of QTL controlling ergot sclerotia size in hexaploid wheat implicates a role for the Rht dwarfing alleles

The fungal pathogen Claviceps purpurea infects ovaries of a broad range of temperate grasses and cereals, including hexaploid wheat, causing a disease commonly known as ergot. Sclerotia produced in place of seed carry a cocktail of harmful alkaloid compounds that result in a range of symptoms in humans and animals, causing ergotism. Following a field assessment of C. purpurea infection in winter wheat, two varieties ‘Robigus’ and ‘Solstice’ were selected which consistently produced the largest differential effect on ergot sclerotia weights. They were crossed to produce a doubled haploid mapping population, and a marker map, consisting of 714 genetic loci and a total length of 2895 cM was produced. Four ergot reducing QTL were identified using both sclerotia weight and size as phenotypic parameters; QCp.niab.2A and QCp.niab.4B being detected in the wheat variety ‘Robigus’, and QCp.niab.6A and QCp.niab.4D in the variety ‘Solstice’. The ergot resistance QTL QCp.niab.4B and QCp.niab.4D peaks mapped to the same markers as the known reduced height (Rht) loci on chromosomes 4B and 4D, Rht-B1 and Rht-D1, respectively. In both cases, the reduction in sclerotia weight and size was associated with the semi-dwarfing alleles, Rht-B1b from ‘Robigus’ and Rht-D1b from ‘Solstice’. Two-dimensional, two-QTL scans identified significant additive interactions between QTL QCp.niab.4B and QCp.niab.4D, and between QCp.niab.2A and QCp.niab.4B when looking at sclerotia size, but not between QCp.niab.2A and QCp.niab.4D. The two plant height QTL, QPh.niab.4B and QPh.niab.4D, which mapped to the same locations as QCp.niab.4B and QCp.niab.4D, also displayed significant genetic interactions.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.