Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patien

The current study performed in order to detect and quantify epicatechin in two tea samples of Camellia sinensis (black and green tea) by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Extraction of epicatechin from black and green tea was done by using two different methods: maceration (cold extraction method) and decoction (hot extraction method). Qualitative and quantitative determinations of epicatechin in two tea samples were investigated. Epicatechin identification was made by utilizing preliminary chemical tests and TLC. This identification was also boosted by HPLC and then quantified epicatechin in all ethyl acetate fractions of two tea samples. This research revealed the existence of epica

 ABSTRACT

Two compounds were isolated from the fruit part of Rhus coriaria that grow wildly or cultivated in the north of Iraq. The compounds were separated by preparative high-Performance Liquid Chromatography and their structures were established based on detailed spectroscopic techniques like FTIR and LC-MS/MS.

Keywords: Rhus coriaria, Preparative HPLC, LC-MSMS, FTIR

A rapid high performance liquid chromatography method for the determination of sphinganine (Sa) and sphingosine (So) in urine samples by employing a silica-based monolithic column is described. The samples were first extracted using ethyl acetate and derivatized using ortho-phthaldialdehyde in the presence of 2-mercaptoethanol. C20 sphinganine was used as internal standard. Under the optimized conditions, separation was achieved using a mixture of methanol:water (93:7, v/v), column temperature at 30°C, flow rate of 1 mL min−1, and an injection volume of 10 μL. Good linearity was obtained for Sa and So over the concentration range 20–500 ng mL−1(correlation coefficients ≥0.9978). The detection limits were 0.45 ng mL−1 for Sa and

Beta-lactam medications are among the commonly used antibiotics. These drugs kill germs by disrupting cell wall formation. This drug treats bacterial infections in numerous body sections. A new, quick, high-performance liquid chromatography approach has been developed and verified by the FDA and EMA for the simultaneous estimation of drugs in their medicinal and pure forms. This study deals with the determination of beta-lactam drugs (Amoxicillin, Ampicillin, Cephalexin, Cefotaxime, Cefoxitin, Cefamandole, Cephalothin, Piperacillin, Penicillin, Oxacillin, Cloxacillin, Nafcillin, Carbenicillin, Mezlocillin, Dicloxacillin) by a Reversed-Phase High-Performance Liquid Chromatography (RP-HPLC) technique based on an UV detector using a

The global rise in temperature and the desert climatic conditions prevalent in Middle Eastern countries have exacerbated rutting distress in heavily trafficked highways. Conventional asphalt binders with a high-temperature performance grade (PG 70) have proven inadequate under such extreme conditions, necessitating the development of modified binders with enhanced high-temperature performance. While polymer modification using styrene-butadiene-styrene (SBS), an elastomeric polymer, and ethylene-vinyl acetate (EVA), a plastomeric polymer, has been widely studied, limited research provides a direct comparison of their effectiveness at both the binder and mixture levels under extremely high-temperature conditions. This study addresses this gap

Background: The final stage of endodontic therapy is complete obturation of the root canal system to provide as perfect as possible at the cementodentinal junction of the apical foramen. The purpose of this in vitro study was to evaluate the sealing ability of injection molded thermoplasticized gutta percha and lateral condensation techniques with and without the use of sealers. Materials and Methods: Forty freshly extracted adult human maxillary central incisors with complete formed apices were utilized in this study. The teeth were randomly divided into four groups for evaluation of the apical seal. Group (1) lateral condensation gutta percha technique without sealer, (2) lateral condensation gutta percha technique with sealer, (3) Inject

Since the Internet has been more widely used and more people have access to multimedia content, copyright hacking, and piracy have risen. By the use of watermarking techniques, security, asset protection, and authentication have all been made possible. In this paper, a comparison between fragile and robust watermarking techniques has been presented to benefit them in recent studies to increase the level of security of critical media. A new technique has been suggested when adding an embedded value (129) to each pixel of the cover image and representing it as a key to thwart the attacker, increase security, rise imperceptibility, and make the system faster in detecting the tamper from unauthorized users. Using the two watermarking ty

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS