This comprehensive review examines the efficacy and safety of tumor necrosis factor-alpha (TNF-α) inhibitors in treating various autoimmune diseases, and focuses on their application in Iraqi patients. Elevated TNF-α levels are linked to autoimmune disorders, leading to the development of anti-TNF-α therapies such as infliximab, etanercept, adalimumab, certolizumab pegol, and golimumab, which have gained FDA approval for conditions like psoriasis, in¬flammatory bowel disease, ankylosing spondylitis, and rheumatoid arthritis. While these therapies demonstrate sig¬nificant therapeutic benefits, including improved quality of life and disease management, they also carry risks, such as increased susceptibility to infections and potential malignancies. The review highlights the variable patient re¬sponses to TNF-α inhibitors, influenced by pharmacokinetic and pharmacodynamic factors as well as genetic varia¬tions. The rise of anti-drug antibodies and inadequate drug concentrations are common challenges observed, empha¬sizing the need for therapeutic drug monitoring. Safety profiles of TNF-α inhibitors are generally favorable, but adverse effects (including infections and infusion reactions) have been reported. Genetic factors, such as polymorphisms in the TNF-α gene, may also play a role in the treatment responsiveness and adverse effects, suggesting the potential for personalized medicine approaches. While TNF-α inhibitors effectively manage autoimmune diseases in Iraqi pa¬tients, further research is warranted in order to optimize treatment strategies, assess long-term safety, and explore genetic influences on therapy outcomes. The findings underscore the importance of individualized treatment plans so as to enhance the efficacy and minimize the risks associated with these biologic therapies.
Imagination as a Path to Reality
In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
... Show MoreA new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte
... Show More. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreAbstract :In this study, amygdaline in Iraqi plant seeds was extracted and isolated from their seeds matrix using reflux procedure and subsequently identified and determined by high performance liquid chromatography (HPLC) on reversed phase column of LC-18 (150mm x 4.6mm, 5?m )with actonitrile :water ( 50 : 50 ) as mobile phase at flow rate of ( 0.5 mL/min ) and detection at wavelength of 215 nm.The experimental results indicated that the linearity of calibration is in the range of 1.0-30.0 mg L-1amygdaline with the correlation coefficient of 0.9949. The limit of detection (LOD) and limit of quantitation (LOQ) for amygdaline were of 0.88 and 2.93 mg L-1 in standard pure sample. The mean recovery percent is 97.34±0.58 at 95% confidence inte
... Show MoreAbstract Objectives: to determine efficiency and safety of three misoprostol regimens for 2nd trimester pregnancy termination in individuals with two or more cesarean section scars. Methods: a cross-sectional study included 100 pregnant ladies at 13th-26th weeks gestation with previous two cesarean sections (CSs) who were scheduled for pregnancy termination using misoprostol. Patients were conveniently assigned to 100µg/3h, 200µg/3h or 400 µg/3h regimens. Primary outcome was time to abortion, secondary outcomes were side effect and complications. Results: a significant association was found between number previous CSs and longer time to abortion (p=0.01). A highly significant association was identified between earlier gestatio
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