1,721,132 research outputs found

    Comparison of AlphaLISA and RIA assays for measurement of wool cortisol concentrations

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    Radioimmunoassay (RIA) methods have always represented a technique of choice for the determination of steroids in biological samples. The Amplified Luminescent Proximity Homogenous Assay-Linked Immunosorbent Assay (AlphaLISA) is now emerging as the new-generation immunoassay technology that does not require washing/separation steps. The aim of this study was to adapt the Perkin-Elmer's AlphaLISA kit for wool cortisol and compare it with a RIA wool cortisol assay. Wool from lambs, 35 at birth (A0) and 54 at two months old (A2), was collected and each extract was evaluated for wool cortisol concentrations (HCC) both by RIA and AlphaLISA immunoassay. The two methods showed good precision, sensitivity and specificity for determining HCC. Both methods were able to detect significant differences between the high and the low HCC assessed in lambs at A0 and A2 (P < 0.01). The HCC assessed with RIA were significantly higher than those assessed with AlphaLISA (P < 0.01). Moreover, the correlation between HCC measured using the AlphaLISA and RIA methods was strong (r = 0.878). The regression analyses show a constant and not proportional error. This could be due to the diversity in the dosage steps and to the diversity of the molecules used in the two methods. Results support the validity of using AlphaLISA as an alternative method to RIA for the quantification of cortisol in sheep wool and considering the performances showed it has a great potential to be further applied as an excellent tool to evaluate HCC in samples derived from animal species

    Chronic lymphocytic leukemia: novel prognostic factors and their relevance for risk-adapted therapeutic strategies

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    Background and Objectives: Many years ago it was established that prompt treatment of early stage chronic lymphocytic leukemia (CLL), the stage at which almost two-thirds of CLL patients present, has no benefit over a management of watching and waiting, then treating progression. However, this fact was based on series treated ineffectually with chlorambucil, which were not stratified according to prognostic markers.Design and Methods: The prognosis and clinical course of CLL are heterogeneous. While some patients may have a normal life expectancy without requiring treatment, others die of drug-resistant disease as early as within two years of presentation. However, unlike the situation in non-Hodgkin’s lymphoma, there is no standard Prognostic Index that can be used to group patients with CLL according to likely outcome or to guide treatment.Results: A number of clinical and biological factors of prognostic relevance, which may add to the classical assessment provided by the staging systems, have been identified. These include clinical characteristics, such as age, gender and performance status, and laboratory parameters reflecting the tumor burden or disease activity, such as lymphocyte count, lactate dehydrogenase (LDH) increase, bone marrow infiltration pattern or lymphocyte doubling time. Recently more informative prognostic parameters have been identified: serum markers such as soluble CD23, b2-microglobulin or thymidine kinase and genetic markers of tumor cells, such as genomic aberrations, gene abnormalities (p53, ATM), the mutation status of the variable segments of the immunoglobulin heavy chain genes (IGVH) or surrogate markers for these factors, such as CD38 and ZAP-70.Interpretations and Conclusions: From the clinician’s perspective the importance of this new knowledge is how it affects treatment. It is now possible to produce molecular remissions even in advanced disease using combinations of purine analogs and monoclonal antibodies. Moreover, potentially curative therapeutic modalities such as autologous and allogeneic stem cell transplantation are becoming safer. Clinical trials of effective treatment stratified by more reliable prognostic markers are surely now warranted

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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