Autoantibodies
These self-reactive antibodies can lead to autoimmune disorders, where the immune system attacks healthy cells and tissues.
Autoantibodies are important biomarkers for the diagnosis and monitoring of many autoimmune diseases, such as rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes.
Precise detection and quantification of autoantibodies is crucial for accurate disease assessment and treament.
Reserchers can utilize PubCompare.ai's AI-driven platform to optimize their autoantibody research protocols, improve reproducibility, and streamline their findings.
Most cited protocols related to «Autoantibodies»
126 (link) Other investigators have reported their findings using new techniques associated with endoscopy to enhance the diagnosis of CD. These include confocal microscopy, high-resolution magnification endoscopy, optical band imaging127 (link) and optimal coherence tomography. These novel techniques are still limited by availability, tolerability and cost.98 (link) However, the immersion technique and dye enhancement in which the endoscopist instills water or a contrast dye (for example, indigo carmine or methylene blue) into the bowel lumen, with or without the assistance of magnification endoscopy, enhancing the visualisation of the villus128 (link) can be readily used and improves visualisation of villi, thus increasing the sensitivity for detection of villous atrophy.98 (link)
Most recents protocols related to «Autoantibodies»
Example 7
In a first screening the antigen reactivities of 129 SLE patients, 75 RA patients, and 134 healthy controls categorized in accordance with age and sex were differentially tested. For this purpose, the autoantibody reactivities of these blood samples were tested on 5857 antigens coupled to Luminex beads. In order to identify antigens with which the group of all SLE patients can be distinguished from different control croups consisting of healthy samples and patients with RA, univariate statistical tests were carried out, The result, of the statistical test is illustrated as a volcano plot for all 5857 antigens. In the volcano plot, the x-axis shows the relative change of the antigen reactivity in SLE patients compared with healthy controls (
Example 11
The autoantibody profiles of SLE patients with lupus nephritis were compared with those of SLE patients without lupus nephritis. Following univariate statistical evaluation, a threshold value of p<0.05 and a 1.5 times modified reactivity compared with the control group were applied. 85 antigens met these criteria and are detailed in Table 2.
Group 2 in Table 2 contains 30 additional and important antigens which can be used for the generation of lupus nephritis biomarker panels.
An L1-penalised logistic regression model with five-fold cross validation and twenty times repetition was computed for the selection of the best candidates. The antigens selected most frequently in this model computation with a frequency of more than 50% constituted the best candidates for the diagnosis of lupus nephritis.
Group 5 comprises further statistically significant antigens suitable for the diagnosis of lupus nephritis.
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More about "Autoantibodies"
These erroneous antibodies can lead to autoimmune disorders, where the immune system attacks healthy cells and tissues.
Autoantibodies are crucial biomarkers for the diagnosis and monitoring of numerous autoimmune diseases, such as rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes.
Precise detection and quantification of autoantibodies is vital for accurate disease assessment and treatment.
Researchers can utilize PubCompare.ai's AI-driven platform to optimize their autoantibody research protocols, improve reproducibility, and streamline their findings.
This powerful tool allows researchers to locate the best protocols from literature, pre-prints, and patents using advanced AI comparisons, enhancing their autoantibody research and increasing the impact of their findings.
In addition to PubCompare.ai, researchers may also leverage other software tools such as Prism 6, GraphPad Prism 5, SAS 9.4, GenePix Pro 6.0, and Prism 8 to further analyze and visualize their autoantibody data.
These platforms offer a range of statistical analysis, graphing, and data management capabilities, enabling researchers to gain deeper insights into their autoantibody research and communicate their findings more effectively.
Whether you're investigating the role of autoantibodies in autoimmune disorders, developing new diagnostic tests, or exploring novel therapeutic approaches, PubCompare.ai and other specialized software tools can be invaluable in streamlining your research, improving reproducibility, and maximizing the impact of your work in this critical field of study.