Component-resolved diagnosis of pollen allergy based on skin testing with profilin, polcalcin and lipid transfer protein pan-allergens

BACKGROUND Allergy diagnosis needs to be improved in patients suffering from pollen polysensitization due to the existence of possible confounding factors in this type of patients. OBJECTIVE To evaluate new diagnostic strategies by comparing skin responses to pan-allergens and conventional allergenic extracts with specific IgE (sIgE) to purified allergen molecules. METHODS One thousand three hundred and twenty-nine pollen-allergic patients were diagnosed by a combination of an in vitro method with a panel of 13 purified allergens, including major allergens and pan-allergens, using a high-capacity screening technology (ADVIA-Centaur®) and skin prick test (SPT) to pan-allergens and conventional extracts. RESULTS There was a high concordance (κ index) between in vitro (sIgE to major allergens) and in vivo (SPT to conventional extracts) methods in patients who were not sensitized to pan-allergens, but SPT with conventional extracts failed to diagnose patients with sensitization to pan-allergens. In patients who were simultaneously sensitized to polcalcins and profilins, there was a duplication both in the number of sensitizations to major allergens and in the years of disease evolution. There was a statistical association between sensitization to profilins and/or lipid transfer proteins and food allergy (P<0.0001). CONCLUSION The novel diagnostic strategy has proven to be a valuable tool in daily clinical practice. Introduction of routine SPT to pan-allergens is a simple and feasible way of improving diagnostic efficacy. Patients sensitized to pan-allergens should be tested by an adequate panel of allergenic molecules in order to identify the allergens that are responsible for the allergic disease

Component-Resolved in Vitro Diagnosis in Peach-Allergic Patients

BACKGROUND: The in vitro diagnosis of pollen-related food allergy presents low specifi city and reproducibility with many conventional extracts. This can be improved using natural purifi ed allergens, recombinant purifi ed allergens, or both. OBJECTIVE: We compared specifi c immunoglobulin (Ig) E determination (sIgE), the basophil activation test (BAT), the histamine release test (HRT), and the cellular allergen stimulation test (CAST) using natural and recombinant allergens in the diagnosis of peach allergy. METHODS: Thirty-two peach allergic patients were studied. Skin prick tests were performed with commercial peach and extract with Mal d 1, nPru p 3, and profi lin (nPho d 2). sIgE, BAT, CAST, and HRT were determined using rPru p 3, rMal d 3, rBet v 1, rMal d 1, and rMal d 4. RESULTS: Agreement between the techniques was good with all the allergens, except HRT with rMal d 1 and rMal d 4. With rPru p 3, sIgE, CAST, BAT, and HRT showed sensitivity values of 88%, 81%, 72%, and 69% and specifi city values of 100%, 93%, 97%, and 83%, respectively. In patients with systemic symptoms or contact urticaria, the values were 100%, 85%, 81%, and 81%. In patients with oral allergy syndrome, sensitivity to profi lins or homologues of Bet v 1 was detected in 100% of the cases by all the techniques, except by HRT with rMal d 1, which detected 66% of the cases. CONCLUSIONS: The use of single allergens in the in vitro diagnosis of peach allergy by specifi c IgE determination, BAT, and CAST offers high specifi city and sensitivity, with better results than the HRT

EXPERIENCES OF NEUTRAL RESONANT SYSTEM IMPLANTATION IN GORLIZ SUBSTATION

ABSTRAC

Constructing a 7-day Ahead Forecast Model for Grass Pollen at North London, United Kingdom

A number of media outlets now issue medium-range (~7 day) weather forecasts on a regular basis. It is therefore logical that aerobiologists should attempt to produce medium-range forecasts for allergenic pollen that cover the same time period as the weather forecasts. The objective of this study is to construct a medium-range (< 7 day) forecast model for grass pollen at north London. The forecast models were produced using regression analysis based on grass pollen and meteorological data from 1990-1999 and tested on data from 2000 and 2002. The modelling process was improved by dividing the grass pollen season into three periods; the pre-peak, peak and post peak periods of grass pollen release. The forecast consisted of five regression models. Two simple linear regression models predicting the start and end date of the peak period, and three multiple regression models forecasting daily average grass pollen counts in the pre-peak, peak and post-peak periods. Overall the forecast models achieved 62% accuracy in 2000 and 47% in 2002, reflecting the fact that the 2002 grass pollen season was of a higher magnitude than any of the other seasons included in the analysis. This study has the potential to make a notable contribution to the field of aerobiology. Winter averages of the North Atlantic Oscillation were used to predict certain characteristics of the grass pollen season, which presents an important advance in aerobiological work. The ability to predict allergenic pollen counts for a period between five and seven days will benefit allergy sufferers. Furthermore, medium-range forecasts for allergenic pollen will be of assistance to the medical profession, including allergists planning treatment and physicians scheduling clinical trials

Forecasting the onset of the grass pollen season in Melbourne (Australia)

In Melbourne, a southern hemisphere city with a cool temperate climate, the grass pollen season has been monitored using a Burkard spore trap for 12 years (11 pollen seasons, which extend from October through January). The onset of the grass pollen season (OGPS) has been defined in various ways using both arbitrary cumulative scores (Sum 75, Sum 100) and percentages (10% Pollen Fly). OGPS, based on the forecast model of pollen season devised by Lejoly-Gabriel (Acta Geogr. Lovan., 13 (1978) 1&ndash;260) has been most widely used in efforts to forecast the beginning of the pollen season. OGPS occurred in Melbourne between 20 October to 24 November (average 6 November), a difference of 35 days. Duration of the pollen season ranged from 46 to 81 days, with a mean of 55 days, one of the longest reported. The relationships between onset and various weather parameters for July have enabled us to modify a model, using linear regression analysis, to predict onset. The prediction model is based on a negative correlation between date of onset and the sum of rainfall for July (a winter month). The error of prediction (Ep) is 24% and predicted day of OGPS was precisely predicted on 2 occasions, and on others with a range of accuracy of 3 to 14 days.<br /