Infectious bronchitis virus infections of chickens in Belgium : an epidemiological survey

Between April 2012 and July 2015, cloacal and/or tracheal swab samples were collected from four hundred and twenty-four Belgian chicken broiler, breeder and layer flocks. All flocks were kept for production purposes and presented clinical signs suggestive of an infectious bronchitis virus (IBV) infection. The samples were analyzed by real-time polymerase chain reaction (RT-qPCR) to detect the presence of ribonucleic acid (RNA) of IBV. When positive, approximately four hundred base pairs (bp) encoding for the hypervariable region of the IBV S1 protein were sequenced. Sequencing results, cycle threshold (Ct) values and vaccination history were used as criteria to try and distinguish vaccine strains from field strains. Of all samples examined, 22.4% was negative. In 16.4% of the samples that did contain RNA from IBV, the genotype could not be determined. In most cases, this was due to the recovery of RNA quantities below the lower limit of detection of the sequencing PCR. The remaining positive submissions predominantly revealed RNA from IBV strains that belonged to the 4/91-793B (46.8%), D388-QX (25.2%), D274-D207 (5.8%) and Massachusetts (4.0%) genotypes. Estimations indicated that approximately 58%, 11%, 37% and 46% of these detections, respectively, were vaccine strains. Infections with types CK/CH/Guandong/Xindadi/0903, Ukr/27/2011, NGA/295/2006 and Q1 were observed sporadically. The results indicate that IBV infections are highly prevalent in Belgian chickens and that at least eight different IBV types were circulating during the monitored period. This underlines the necessity of providing flocks with a strong and broad protective immunity against IBV

Quality of life in patients with hereditary haemorrhagic telangiectasia (HHT)

Background: There are very few studies about general quality of life parameters, standards for the description of health status and comparison with general population data on patients with Hereditary hemorrhagic telangiectasia (HHT), a rare disease in which epistaxis is a cardinal symptom. Purpose: To assess the quality of life in a population of Spanish patients with HHT and compare it with the general population. Design and methods: Between January 1st 2005 and December 31st 2013, 187 adult patients diagnosed with HHT who were admitted to the HHT Unit of the Hospital Sierrallana, completed on their first visit, the EuroQol 5D-3L (five dimensions and three levels) quality of life descriptive test and the visual analog scale (VAS). The numerical social index value was also determined and the subjective effect of the nasal epistaxis on their quality of life was estimated classified as mild, moderate or severe. Results: Patients with HHT had greater problems than the general population in the five dimensions of the EuroQol 5D-3L, particularly considering pain/discomfort and anxiety/depression. In the VAS and the social index value, patients with HHT also scored lower than the general population, particularly older patients, males, and patients with HHT2. They also had values similar to those of populations with chronic illnesses. The subjective perception of the severity of epistaxis correlated strongly with the VAS and social index values. Conclusions: The quality of life of patients with HHT, estimated using the EuroQol 5D-3L scale, is affected across all dimensions. The scores are similar to those seen in cases of other chronic diseases. Older patients, males and the carriers of the ACVRL1 mutation generally have worse scores on these scales. The VAS and the social index value are index that correlate well with the severity of the clinical symptoms associated mainly with epistaxis

Application of a new PCR-RFLP panel suggests a restricted population structure for Eimeria tenella in UK and Irish chickens

AbstractEimeria species cause coccidiosis, most notably in chickens where the global cost exceeds US$3 billion every year. Understanding variation in Eimeria population structure and genetic diversity contributes valuable information that can be used to minimise the impact of drug resistance and develop new, cost-effective anticoccidial vaccines. Little knowledge is currently available on the epidemiology of Eimeria species and strains in different regions, or under different chicken production systems. Recently, 244 Eimeria tenella isolates collected from countries in Africa and Asia were genotyped using a Sequenom single nucleotide polymorphism (SNP) tool, revealing significant variation in haplotype diversity and population structure, with a marked North/South regional divide. To expand studies on genetic polymorphism to larger numbers of E. tenella populations in other geographic regions a cheaper and more accessible technique, such as polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), is desirable. We have converted a subset of SNP markers for use as PCR-RFLPs and re-analysed the original 244 isolates with the PCR-RFLPs to assess their utility. In addition, application of the PCR-RFLP to E. tenella samples collected from UK and Irish broiler chickens revealed a tightly restricted haplotype diversity. Just two of the PCR-RFLPs accounted for all of the polymorphism detected in the UK and Irish parasite populations, but analysis of the full dataset revealed different informative markers in different regions, supporting validity of the PCR-RFLP panel. The tools described here provide an accessible and cost-effective method that can be used to enhance understanding of E. tenella genetic diversity and population structure

Tutorial: Multivariate Classification for Vibrational Spectroscopy in Biological Samples

Vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, have been successful methods for studying the interaction of light with biological materials and facilitating novel cell biology analysis. Spectrochemical analysis is very attractive in disease screening and diagnosis, microbiological studies and forensic and environmental investigations because of its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyze biologically derived spectrochemical data to obtain accurate and reliable results. Multivariate classification comprises discriminant analysis and class-modeling techniques where multiple spectral variables are analyzed in conjunction to distinguish and assign unknown samples to pre-defined groups. The requirement for such protocols is demonstrated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical for extracting important information and visualizing it in a readily interpretable form. Hereby, we have provided a tutorial for multivariate classification analysis of vibrational spectroscopy data (FTIR, Raman and near-IR) highlighting a series of critical steps, such as preprocessing, data selection, feature extraction, classification and model validation. This is an essential aspect toward the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental