Evaluation of a competitive ELISA for antibody detection against avian influenza virus

Active serologic surveillance is necessary to control the spread of the avian influenza virus (AIV). In this study, we evaluated a commercially-available cELISA in terms of its ability to detect AIV antibodies in the sera of 3,358 animals from twelve species. cELISA detected antibodies against reference H1- through H15-subtype AIV strains without cross reactivity. Furthermore, the cELISA was able to detect antibodies produced following a challenge of the AIV H9N2 subtype in chickens, or following vaccination of the AIV H9 or H5 subtypes in chickens, ducks and geese. Next, we tested the sensitivity and specificity of the cELISA with sera from twelve different animal species, and compared these results with those obtained by the hemagglutination-inhibition (HI) test, the "gold standard" in AIV sera surveillance, a second commercially-available cELISA (IZS ELISA), or the agar gel precipitation (AGP) test. Compared with the HI test, the sensitivities and specificities of cELISA were 95% and 96% in chicken, 86% and 88% in duck, 97% and 100% in turkey, 100% and 87% in goose, and 91% and 97% in swine, respectively. The sensitivities and specificities of the cELISA in this study were higher than those of IZS ELISA for the duck, turkey, goose, and grey partridge sera samples. The results of AGP test against duck and turkey sera also showed significant correlation with the results of cELISA (R-value >0.9). In terms of flock sensitivity, the cELISA correlated better with the HI test than with commercially-available indirect ELISAs, with 100% flock sensitivity

Fourier Transform Infrared Spectroscopic Imaging and Multivariate Regression for Prediction of Proteoglycan Content of Articular Cartilage

Fourier Transform Infrared (FT-IR) spectroscopic imaging has been earlier applied for the spatial estimation of the collagen and the proteoglycan (PG) contents of articular cartilage (AC). However, earlier studies have been limited to the use of univariate analysis techniques. Current analysis methods lack the needed specificity for collagen and PGs. The aim of the present study was to evaluate the suitability of partial least squares regression (PLSR) and principal component regression (PCR) methods for the analysis of the PG content of AC. Multivariate regression models were compared with earlier used univariate methods and tested with a sample material consisting of healthy and enzymatically degraded steer AC. Chondroitinase ABC enzyme was used to increase the variation in PG content levels as compared to intact AC. Digital densitometric measurements of Safranin O –stained sections provided the reference for PG content. The results showed that multivariate regression models predict PG content of AC significantly better than earlier used absorbance spectrum (i.e. the area of carbohydrate region with or without amide I normalization) or second derivative spectrum univariate parameters. Increased molecular specificity favours the use of multivariate regression models, but they require more knowledge of chemometric analysis and extended laboratory resources for gathering reference data for establishing the models. When true molecular specificity is required, the multivariate models should be used

Identifying the unmet information and support needs of women with autoimmune rheumatic diseases during pregnancy planning, pregnancy and early parenting: mixed-methods study

Background Autoimmune rheumatic diseases (ARDs) such as inflammatory arthritis and Lupus, and many of the treatments for these diseases, can have a detrimental impact on fertility and pregnancy outcomes. Disease activity and organ damage as a result of ARDs can affect maternal and foetal outcomes. The safety and acceptability of hormonal contraceptives can also be affected. The objective of this study was to identify the information and support needs of women with ARDs during pregnancy planning, pregnancy and early parenting. Methods This mixed methods study included a cross-sectional online survey and qualitative narrative interviews. The survey was completed by 128 women, aged 18–49 in the United Kingdom with an ARD who were thinking of getting pregnant in the next five years, who were pregnant, or had young children (< 5 years old). The survey assessed quality-of-life and information needs (Arthritis Impact Measurement Scale Short Form and Educational Needs Assessment Tool), support received, what women found challenging, what was helpful, and support women would have liked. From the survey participants, a maximum variation sample of 22 women were purposively recruited for qualitative interviews. Interviews used a person-centered participatory approach facilitated by visual methods, which enabled participants to reflect on their experiences. Interviews were also carried out with seven health professionals purposively sampled from primary care, secondary care, maternity, and health visiting services. Results Survey findings indicated an unmet need for information in this population (ENAT total mean 104.85, SD 30.18). Women at the pre-conception stage reported higher needs for information on pregnancy planning, fertility, giving birth, and breastfeeding, whereas those who had children already expressed a higher need for information on pain and mobility. The need for high quality information, and more holistic, multi-disciplinary, collaborative, and integrated care consistently emerged as themes in the survey open text responses and interviews with women and health professionals. Conclusions There is an urgent need to develop and evaluate interventions to better inform, support and empower women of reproductive age who have ARDs as they navigate the complex challenges that they face during pregnancy planning, pregnancy and early parenting

Development of Epitope-Blocking ELISA for Universal Detection of Antibodies to Human H5N1 Influenza Viruses

10.1371/journal.pone.0004566PLoS ONE4

A human in vitro model system for investigating genome-wide host responses to SARS coronavirus infection

10.1186/1471-2334-4-34BMC Infectious Diseases4-BIDM