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.
Thin films of CuPc of various thicknesses (150,300 and 450) nm have been deposited using pulsed laser deposition technique at room temperature. The study showed that the spectra of the optical absorption of the thin films of the CuPc are two bands of absorption one in the visible region at about 635 nm, referred to as Q-band, and the second in ultra-violet region where B-band is located at 330 nm. CuPc thin films were found to have direct band gap with values around (1.81 and 3.14 (eV respectively. The vibrational studies were carried out using Fourier transform infrared spectroscopy (FT-IR). Finally, From open and closed aperture Z-scan data non-linear absorption coefficient and non-linear refractive index have been calculated res
... Show MoreThe current study was designed to explore the association between the pigments production and biofilm construction in local Pseudomonas aeruginosa isolates. Out of 143 patients suffering from burns, urinary tract infections (UTI), respiratory tract infections and cystic fibrosis obtained from previous study by Mahmood (2015), twenty two isolates (15.38%) were identified from (11) hospitals in Iraq, splitted into three provinces, Baghdad, Al-Anbar and Karbala for the duration of June 2017 to April 2018. Characterization was carried out by using microscopical, morphological and biochemical methods which showed that all these isolates belong to P. aeruginosa. Screening of biofilm production isolates was carried out by usi
... Show MoreAdverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
... Show MoreVision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading to blindness. Computer-Aided Diagnosis systems play an essential role in detecting features in fundus images. Fundus images may include blood vessels, exudates, micro-aneurysm, hemorrhages, and neovascularization. In this paper, our model combines automatic detection for the diabetic retinopathy classification with localization methods depending on weakly-supervised learning. The model has four stages; in stage one, various preprocessing techniques are app