Background: To date, no predictive tests for the clinical response to allergen-specific immunotherapy (ASI) are available. Therefore an in vivo or in vitro test would be of great value. Objective: We sought to evaluate pretreatment parameters used in diagnosing allergic rhinitis and determining serum specific IgE (s-IgE) levels, serum total IgE (t-IgE) levels, and blood eosinophil counts and to identify whether can be used to predict clinical improvement in monosensitized patients with allergic rhinitis with or without asthma treated with immunotherapy. Methods: We analyzed 279 patients who had undergone 4 years of ASI administered either by means of the subcutaneous immunotherapy (76 patients) or sublingual immunotherapy (203 patients) routes. Serum t-IgE and s-IgE levels, blood eosinophil counts, and serum s-IgE/t-IgE ratios were calculated and tested for correlation with clinical response to ASI. Receiver operating characteristic curves were determined. Predicted probabilities and predictive areas under the curve were calculated. Results: The clinical response to ASI was effective in 145 (52.0%) of 279 total patients, 42 (55.2%) of 76 patients treated with subcutaneous immunotherapy, and 103 (50.7%) of 203 patients treated with sublingual immunotherapy. A significant correlation was found between the serum s-IgE/t-IgE ratio and the clinical response to ASI, with high ratios (>16.2) associated with an effective response. The sensitivity and specificity of the area under the curve of the ratio were higher than those of serum s-IgE and t-IgE alone. Conclusion: The calculation of the serum s-IgE/t-IgE ratio for predicting the clinical response to ASI offers an advantage over measuring t-IgE and s-IgE levels in monosensitized patients for the following allergens: grass, Parietaria judaica,

Aim of the present Consensus Statement is to provide a comprehensive and up to-date document on the pathophysiology, atherogenicity and clinical significance of low density liproproteins (LDL) subclasses. We sub-divided our statement in 2 sections. section I discusses the pathophysiology, atherogenicity and measurement issues, while section II is focused on the effects of drug and lifestyle modifications. Suggestions for future research in the field are highlighted at the end of section II. Each section includes Conclusions.

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Human rickettsial diseases comprise a variety of clinical entities caused by microorganisms belonging to the genera Rickettsia, Orientia, Ehrlichia, and Anaplasma. These microorganisms are characterized by a strictly intracellular location which has, for long, impaired their detailed study. In this paper, the critical steps taken by these microorganisms to play their pathogenic roles are discussed in detail on the basis of recent advances in our understanding of molecular Rickettsia-host interactions, preferential target cells, virulence mechanisms, three-dimensional structures of bacteria effector proteins, upstream signalling pathways and signal transduction systems, and modulation of gene expression. The roles of innate and adaptive immune responses are discussed, and potential new targets for therapies to block host-pathogen interactions and pathogen virulence mechanisms are considered.

In hyperandrogenic women, several phenotypes may be observed. This includes women with classic polycystic ovary syndrome (C-PCOS), those with ovulatory (OV) PCOS, and women with idiopathic hyperandrogenism (IHA), which occurs in women with normal ovaries. Where other causes have been excluded, we categorized 290 hyperandrogenic women who were seen consecutively for this complaint between 1993 and 2004 into these three subgroups. The aim was to compare the prevalence of obesity, insulin resistance, and dyslipidemia as well as increases in C-reactive protein and homocysteine in these different phenotypes with age-matched ovulatory controls of normal weight (n = 85) and others matched for body mass index (BMI) with women with C-PCOS (n = 42). Although BMI affected fasting serum insulin and the Quantitative Insulin-Sensitivity Check Index, these markers of insulin resistance were greatest in C-PCOS (n = 204), followed by OV-PCOS (n = 50) and then IHA (n = 33). Androgen levels were similar in OV-PCOS and IHA but were higher in C-PCOS, whereas gonadotropins were similar in all groups. Lipid abnormalities were highest in C-PCOS and OV-PCOS and were normal in IHA. C-reactive protein was elevated in C-PCOS and OV-PCOS but not IHA. Homocysteine was elevated only in C-PCOS. Overall, the prevalence of obesity (BMI > 30) was 29% in C-PCOS, 8% in OV-PCOS, and 15% in IHA and insulin resistance (Quantitative Insulin-Sensitivity Check Index < 0.33) was 68% in C-PCOS, 36% in OV-PCOS, and 26% in IHA. The prevalence of having at least one elevated cardiovascular risk marker was 45% in C-PCOS 38% in OV-PCOS and was not increased on IHA (6%). These results suggest that among hyperandrogenic women the prevalence of abnormal metabolic and cardiovascular risk parameters is greatest in C-PCOS, followed by OV-PCOS and then women with IHA. Moreover, in that in OV-PCOS and IHA, ages and weights were similar yet the prevalence of metabolic and cardiovascular risk was greater in OV-PCOS, the finding of polycystic ovaries may be a significant modifying factor.