Objectives Acid sphingomyelinase deficiency (ASMD) is an inherited autosomal recessive disease caused by pathogenic variants in the sphingomyelin phosphodiesterase-1 (SMPD1) gene, which encodes acid sphingomyelinase (ASM). ASMD has 3 broad phenotypes (type A, type A/B, and type B) characterized by the age of onset, symptomatology, and the rapidity of disease progression. The diagnosis of ASMD can be delayed or missed because of the wide spectrum of severity and its variable manifestations. Analysis of genotype-phenotype correlations can help to determine ASMD disease type and inform management. Here, we describe the clinical presentation of 47 patients with ASMD referred to a single center in Iraq since 2007, whose diagnosis was confirmed b

Background: Colorectal cancer, the most common gastrointestinal cancer, is a significant health issue globally. Mucin 16 plays a critical role in cancer signal transduction pathways and is a potential glycoprotein target for cancer therapy. The miRNA-200 family also regulates the expression of numerous genes that play vital roles in cancer cells. This study aimed to investigate the changes in mucin 16 and miRNA-200a in patients with colorectal cancer (CRC). Subjects and Methods: Fifty-six patients with CRC, including 26 in stage 3 and 30 in stage 4, were included in this study, along with 38 healthy volunteers as a control group. Parameters such as mucin 16, miRNA-200a, total protein, albumin, globulin, and the albumin/globulin rati

Abstract Background: Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide. Identifying novel biomarkers is critical for improving diagnosis, prognosis, and treatment strategies. This study investigates the serum levels of kisspeptin-1 (KISS1), its receptor (KISS1R), growth differentiation factor 15 (GDF15), and carcinoembryonic antigen (CEA) in Iraqi CRC patients. Objectives: Explore associations between serum levels of Kiss1, Kiss1R, GDF, and CEA and disease progression in Iraqi patients with CRC. Methods: A case-control study was conducted, including 72 CRC patients and 36 healthy controls. Patients were stratified into non-metastatic and metastatic groups. Serum biomarker levels were measured using enzyme-link

The current study investigated the stability and the extraction efficiency of emulsion liquid membrane (ELM) for Abamectin pesticide removal from aqueous solution. The stability was investigated in terms of droplet emulsion size distribution and emulsion breakage percent. The proposed ELM included a mixture of corn oil and kerosene (1:1) as a diluent, Span 80 (sorbitan monooleate) as a surfactant and hydrochloric acid (HCl) as a stripping agent without utilizing a carrier agent. Parameters such as homogenizer speed, surfactant concentration, emulsification time and internal to organic volume ratio (I/O) were evaluated. Results show that the lower droplet size of 0.9 µm and higher stable emulsion in terms of breakage percent of 1.12 % we

Multilayer reservoirs are currently modeled as a single zone system by averaging the reservoir parameters associated with each reservoir zone. However, this type of modeling is rarely accurate because a single zone system does not account for the fact that each zone's pressure decreases independently. Pressure drop for each zone has an effect on the total output and would result in inter-flow and the premature depletion of one of the zones. Understanding reservoir performance requires a precise estimation of each layer's permeability and skin factor. The Multilayer Transient Analysis is a well-testing technique designed to determine formation properties in more than one layer, and its effectiveness over the past two decades has been

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

KE Sharquie, HR Al-Hamamy, AA Noaimi, AF Tahir, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 2

Azo derivative ligand[H3L] have been synthesized by the reaction of diazonium salt of p-amino benzoic acid with orcinol in(1:1)mole ratio. The bidente ligand was reacted with the metal ions MnII,FeIIandCrIIIin(2:1)mole ratio via reflux in ethanol using Et3N as a base to give complexes of the general formula: [ M(H2L)2(H2O)x]Cly The synthesized compounds were characterized by spectroscopic methods[ I.R , UV-Vis, A.A and H1 NMR]along with melting point, chloride content and conductivity measurements. The complexes were screend for their in vitro antibacterial activity against one strain of staphylococcus as Gram(+) positive and one strain of pseudomonas as Gram(-) Negative, using the agar diffusion technique.