Background: Psoriasis is an immune-mediated inflammatory disease with unknown aetiology that may be associated with the defect in proliferation and differentiation of the keratinocytes related to inflammatory cell infiltration. According to published reports, it is universal in occurrence; its prevalence in different populations varies from 0.1% to 11.8%. Receiving Apremilast resulted in a strong reduction in interleukin 17 and interleukin 23, as well as reduced expression of other inflammatory cytokines and improvement of psoriatic lesions. Objectives: This study aimed to assess the impact of Apremilast on levels of IL-17, IL-23, and lipids in obese psoriatic patients. Methods: Thirty obese patients with psoriasis were included in this prospective interventional study to measure serum levels of lipid profile, IL-17, and IL-23, before and after receiving Apremilast treatment. A t-test was used to compare between means. Results: The mean age of the participants was 38 years. The most common age group was 30–40 years. The levels of IL-17 before the administration of Apremilast were 225.55 ± 7.70 pg/mL. After six months of treatment with Apremilast, a statistically significant reduction was seen, with the value decreasing to 183.41 ±2.33 pg/ml. IL-22 levels before the administration of Apremilast were measured to be 76.42 ± 4.03 pg/mL. After six months of treatment with Apremilast, these levels exhibited a non-significant decrease to 67.15 ± 5.40 pg/ml. Modest alterations were noted in the lipid profile. Conclusion: The use of Apremilast is effective in decreasing IL-17 levels, which have pro-inflammatory effects; this leads to improvement in psoriatic lesions. Moreover, receiving Apremilast in obese psoriatic individuals led to a reduction in TG levels and an elevation in HDL-C levels. Additionally, a rise in TC levels and LDL-C was seen.
KE Sharquie, AA Noaimi, MS Abass, American Journal of Dermatology and Venereology, 2019 - Cited by 4
With the increasing prevalence of breast cancer among female internationally, occupies about 25% of all cases of cancer, with a measured 1.57 million up to date cases in 2012. Breast cancer has turn a most warning to health of female in Iraq, where it is the major cause of death among women after cardiovascular diseases, with a mortality rate of 23% related cancer. Recently there is a crucial requirement to include community pharmacists in health elevation activities to support awareness and early diagnosis of cancer, specially breast cancer. The aim of this study is to assess knowledge, attitude and perceived barriers amongst Iraqi community pharmacists towards health promotion of breast cancer. This study is cross sectional research. A
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr
... Show MoreIncorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
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