Campylobacter colonisation of slaughterhouse surfaces may be affected by ultra-thin silica coating

Campylobacteriosis is the most reported gastrointestinal zoonotic disease worldwide and is caused by the consumption of inadequately heated and contaminated food, especially poultry meat. This may result from cross-contamination events during poultry slaughtering and cutting processes. Carcass contact surfaces in slaughterhouses, such as plucking fingers of rubber or stainless-steel surfaces, are high-risk points for contamination, with intestinal contents likely containing Campylobacter bacteria that may result in the cross-contamination of subsequent carcasses. Modification of these food contact surfaces by coating can be beneficial in combating bacterial contamination, as already applied in the packaging materials of the food industry. The aim of this study was to compare the attachment, growth and detachment of Campylobacter jejuni on uncoated and nanoscale silicon dioxide coated stainless steel and plucking fingers during laboratory experiments. The coating partly resulted in significantly reduced attachment and an improved detachment of the target organism on stainless steel. In contrast, there was no significant decrease in Campylobacter adherence to the coated plucking fingers as compared to the uncoated ones. However, a significantly higher reduction of recultivable bacteria on the coated plucking fingers was observed during a five-hour period. In future studies, specific coating parameters should be investigated to further support development, and thus a better adaptation of the coating to the environmental conditions

ilastik: interactive machine learning for (bio)image analysis

We present ilastik, an easy-to-use interactive tool that brings machine-learning-based (bio)image analysis to end users without substantial computational expertise. It contains pre-defined workflows for image segmentation, object classification, counting and tracking. Users adapt the workflows to the problem at hand by interactively providing sparse training annotations for a nonlinear classifier. ilastik can process data in up to five dimensions (3D, time and number of channels). Its computational back end runs operations on-demand wherever possible, allowing for interactive prediction on data larger than RAM. Once the classifiers are trained, ilastik workflows can be applied to new data from the command line without further user interaction. We describe all ilastik workflows in detail, including three case studies and a discussion on the expected performance

Sleep deprivation increases oleoylethanolamide in human cerebrospinal fluid

This study investigated the role of two fatty acid ethanolamides, the endogenous cannabinoid anandamide and its structural analog oleoylethanolamide in sleep deprivation of human volunteers. Serum and cerebrospinal fluid (CSF) samples were obtained from 20 healthy volunteers before and after a night of sleep deprivation with an interval of about 12 months. We found increased levels of oleoylethanolamide in CSF (P = 0.011) but not in serum (P = 0.068) after 24 h of sleep deprivation. Oleoylethanolamide is an endogenous lipid messenger that is released after neural injury and activates peroxisome proliferator-activated receptor-α (PPAR-α) with nanomolar potency. Exogenous PPAR-α agonists, such as hypolipidemic fibrates and oleoylethanolamide, exert both neuroprotective and neurotrophic effects. Thus, our results suggest that oleoylethanolamide release may represent an endogenous neuroprotective signal during sleep deprivation

Distinct Neurobehavioural Effects of Cannabidiol in Transmembrane Domain Neuregulin 1 Mutant Mice

The cannabis constituent cannabidiol (CBD) possesses anxiolytic and antipsychotic properties. We have previously shown that transmembrane domain neuregulin 1 mutant (Nrg1 TM HET) mice display altered neurobehavioural responses to the main psychoactive constituent of cannabis, Δ9-tetrahydrocannabinol. Here we investigated whether Nrg1 TM HET mice respond differently to CBD and whether CBD reverses schizophrenia-related phenotypes expressed by these mice. Adult male Nrg1 TM HET and wild type-like littermates (WT) received vehicle or CBD (1, 50 or 100 mg/kg i.p.) for 21 days. During treatment and 48 h after withdrawal we measured behaviour, whole blood CBD concentrations and autoradiographic receptor binding. Nrg1 HET mice displayed locomotor hyperactivity, PPI deficits and reduced 5-HT2A receptor binding density in the substantia nigra, but these phenotypes were not reversed by CBD. However, long-term CBD (50 and 100 mg/kg) selectively enhanced social interaction in Nrg1 TM HET mice. Furthermore, acute CBD (100 mg/kg) selectively increased PPI in Nrg1 TM HET mice, although tolerance to this effect was manifest upon repeated CBD administration. Long-term CBD (50 mg/kg) also selectively increased GABAA receptor binding in the granular retrosplenial cortex in Nrg1 TM HET mice and reduced 5-HT2A binding in the substantia nigra in WT mice. Nrg1 appears necessary for CBD-induced anxiolysis since only WT mice developed decreased anxiety-related behaviour with repeated CBD treatment. Altered pharmacokinetics in mutant mice could not explain our findings since no genotype differences existed in CBD blood concentrations. Here we demonstrate that Nrg1 modulates acute and long-term neurobehavioural effects of CBD, which does not reverse the schizophrenia-relevant phenotypes

Bungowannah Pestivirus Chimeras as Novel Double Marker Vaccine Strategy against Bovine Viral Diarrhea Virus

Marker or DIVA (differentiation of infected from vaccinated animals) vaccines are beneficial tools for the eradication of animal diseases in regions with a high prevalence of the designated disease. Bovine viral diarrhea virus (BVDV)-1 (syn. Pestivirus A) is a flavivirus that infects predominantly cattle resulting in major economic losses. An increasing number of countries have implemented BVDV eradication programs that focus on the detection and removal of persistently infected cattle. No efficient marker or DIVA vaccine is yet commercially available to drive the eradication success, to prevent fetal infection and to allow serological monitoring of the BVDV status in vaccinated farms. Bungowannah virus (BuPV, species Pestivirus F), a related member of the genus Pestivirus with a restricted prevalence to a single pig farm complex in Australia, was chosen as the genetic backbone for a marker vaccine candidate. The glycoproteins E1 and E2 of BuPV were substituted by the heterologous E1 and E2, which are major immunogens, of the BVDV-1 strain CP7. In addition, the candidate vaccine was further attenuated by the introduction of a deletion within the Npro protein coding sequence, a major type I interferon inhibitor. Immunization of cattle with the chimeric vaccine virus BuPV_ΔNpro_E1E2 CP7 (modified live or inactivated) followed by a subsequent experimental challenge infection confirmed the safety of the prototype strain and provided a high level of clinical protection against BVDV-1. The serological discrimination of vaccinated cattle could be enabled by the combined detection of BVDV-1 E2- in the absence of both BVDV NS3- and BVDV Erns-specific antibodies. The study demonstrates for the first time the generation and application of an efficient BVDV-1 modified double marker vaccine candidate that is based on the genetic background of BuPV accompanied by commercially available serological marker ELISA systems

Genetic characterization and zoonotic potential of highly pathogenic Avian influenza virus A(H5N6/H5N5), Germany, 2017–2018

We genetically characterized highly pathogenic avian influenza virus A(H5N6) clade 2.3.4.4b isolates found in Germany in 2017-2018 and assessed pathogenicity of representative H5N5 and H5N6 viruses in ferrets. These viruses had low pathogenicity; however, continued characterization of related isolates is warranted because of their high potential for reassortment

Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models

Automated cell tracking methods are still error-prone. On very large data sets, uncertainty measures are thus needed to guide the expert to the most ambiguous events so these can be corrected with minimal effort. We present two easy-to-use methods to sample multiple proposal solutions from a tracking-by-assignment graphical model and experimentally evaluate the benefits of the uncertainty measures derived. Ex-pert time for proof-reading is reduced greatly compared to random selection of predicted events. Index Terms — Cell tracking, uncertainty, machine learn-ing, probabilistic graphical model