Salahaddin University - Erbil
Recent publications
Background Niemann-Pick disease type C (NPC) is a rare lysosomal neurovisceral storage disease caused by mutations in the NPC 1 (95%) or NPC2 (5%) genes. The products of NPC1 and NPC2 genes play considerable roles in glycolipid and cholesterol trafficking, which could consequently lead to NPC disease with variable phenotypes displaying a broad spectrum of symptoms. Materials In the present study 35 Iranian NPC unrelated patients were enrolled. These patients were first analysed by the Filipin Staining test of cholesterol deposits in cells for NPC diagnostics. Genomic DNA was extracted from the samples of peripheral blood leukocytes in EDTA following the manufacturer's protocol. All exon–intron boundaries and coding exons of the NPC1 gene were amplified by polymerase chain reaction (PCR) using appropriate sets of primers. Thereafter, the products of PCR were sequenced and analysed using the NCBI database ( ). The variants were reviewed by some databases including the Human Gene Mutation Database (HGMD) ( ) and ClinVar ( (. Moreover, all the variants were manually classified in terms of the American College of Medical Genetics and Genomics (ACMG) guideline. Results The sequence analysis revealed 20 different variations, 10 of which are new, including one nonsense mutation (c.406C > T); three small deletions, (c.3126delC, c.2920_2923delCCTG, and c.2037delG); and six likely pathogenic missense mutations, (c.542C > A, c.1970G > A, c.1993C > G, c.2821 T > C, c.2872C > G, and c.3632 T > A). Finally, the pathogenicity of these new variants was determined using the ACMG guidelines. Conclusion The present study aimed to facilitate the prenatal diagnosis of NPC patients in the future. In this regard, we identified 10 novel mutations, and verified that the majority of them occurred in six NPC1 exons (5, 8, 9, 13, 19, and 21), that should be considered with a high priority for Iranian patients' cost-effective evaluation.
We consider electronic and optical properties of group III-Nitride monolayers using first-principle calculations. The group III-Nitride monolayers have flat hexagonal structures with almost zero planar buckling, Δ. By tuning the Δ, the strong σ-σ bond through sp2 hybridization of a flat form of these monolayers can be changed to a stronger σ-π bond through sp3 hybridization. Consequently, the band gaps of the monolayers are tuned due to a dislocation of the s- and p-orbitals towards the Fermi energy. The band gaps decrease with increasing Δ for those flat monolayers, which have a band gap greater than 1.0eV, while no noticeable change or a flat dispersion of the band gap is seen for the flat monolayers, that have a band gap less than 1.0eV. The decreased band gap causes a decrease in the excitation energy, and thus the static dielectric function, refractive index, and the optical conductivity are increased. In contrast, the flat band gap dispersion of few monolayers in the group III-Nitride induces a reduction in the static dielectric function, the refractive index, and the optical conductivity. We therefore confirm that tuning of the planar buckling can be used to control the physical properties of these monolayers, both for an enhancement and a reduction of the optical properties. These results are of interest for the design of optoelectric devices in nanoscale systems.
Graphene Oxide is one of the carbon-based-materials that has wide application range such as Water purification, Flexible rechargeable battery electrode, Solar Collectors, and Energy conversion. In this research, initially, Graphene Oxide nanoparticles were dispersed in water to make a nanofluid. The nanofluid was prepared at 0.10, 0.15, 0.20, 0.25, 0.35, and 0.45% mass fractions. After that, heat transfer and viscosity (at 10 and 100 Revolutions per minute (RPM)) of the prepared samples were calculated at 25, 30, 35, 40, 45, and 50 °C temperatures. In the Flat Plate Solar Collector (FPSC) - Riser tube, from the start point to the end of tube, the temperature decreases and thus the heat transfer and viscosity change. As the calculated range does not contain all the temperatures and mass fractions, and to lower the experimental costs, thus, Fuzzy system and Artificial Neural Network models were used to predict the whole range of data. After that, the trained models were compared to detect the error and to choose the best model with the least error. Results confirmed that Fuzzy system has lower error. This means that Fuzzy system predicts the input-target dataset as definite as obtainable.
In this paper, the researchers will present geometric arithmetic mean to solve non-linear fractional programming. To do this, we shall derive the inequality using the classical optimization theorem by developing the necessary and sufficient conditions for identifying the stationary points of the general inequality constraint optimization problems. Through using the geometric arithmetic mean inequality, we shall indicate how these relationships may be used to obtain the optimal solution of non-linear fractional problems. It will be observed that when the problem has a special structure, the solution may be obtained by solving a set of linear equations. Also, the numerical results are simulated by comparing geometric arithmetic mean approach with unconstrained problems of maxima and minima approach. Several examples are presented to show the validity of the proposed approach.
Interleukin-33 (IL-33) is a member of the IL-1 family and plays an ambivalent role in autoimmune diseases. IL-33 signals via the ST2 receptor and drives cytokine production in mast cells, basophils, eosinophils, NK cells, and T lymphocyte cells. The vital role of IL-33 as an active component gives rise to aberrant local and systemic damage which has been demonstrated in numerous inflammatory disorders and immune-mediated pathological conditions including multiple sclerosis (MS), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), psoriasis, Sjogren's syndrome, inflammatory bowel disease (IBD), etc. IL-33/ST2 axis can up-regulate pro-inflammatory cytokine release in autoimmune disease, however, in some metabolic diseases like diabetes mellitus type 1 IL-33 can be considered an anti-inflammatory cytokine. The purpose of this review is to discuss selected studies on IL-33/ST2 axis in autoimmune diseases and its potential role as a pathogenic or protective cytokine.
Background: Hodgkin lymphoma (HL) has unique epidemiological features with diverse pathologies and exhibits considerable clinicopathological variations in different parts of the world. Objectives: In this study, we aimed to assess the clinicopathological features, immunohistochemistry, and outcomes of HL patients treated in Erbil, northern Iraq. Patients and Methods: This was a retrospective study conducted in Nanakaly Hospital for Blood Diseases and Oncology in Erbil, Iraq. A total of 125 patients diagnosed between January 2012 and December 2016 were assessed for their clinical characteristics, histopathology, immunophenotype, and outcome. Results: The median age was 28 years (range: 18–71 years); 55% were male and 41% had Stage II HL. The most common histological type was nodular sclerosis (51.2%) followed by mixed cellularity (43.2%). CD30 was positive in nearly all cases of classical HL. CD15 and CD20 were positive in 98.7% and 75% of patients with the nodular lymphocyte predominant subtype, respectively. Most of the patients received adriamycin, bleomycin, vinblastine, and dacarbazine chemotherapy, and the 5-year overall survival in our study is 70%. Advanced stage (IV), high lactate dehydrogenase levels, low hemoglobin, and splenomegaly are significant predictors of poor survival. Conclusions: Our patients exhibited outcomes that were lower than those reported in developed countries.
In this article, we define the new generalized Hahn sequence space h d p , where d = d k k = 1 ∞ is monotonically increasing sequence with d k ≠ 0 for all k ∈ ℕ , and 1 < p < ∞ . Then, we prove some topological properties and calculate the α − , β − , and γ − duals of h d p . Furthermore, we characterize the new matrix classes h d , λ , where λ = b v , b v p , b v ∞ , b s , c s , , and μ , h d , where μ = b v , b v 0 , b s , c s 0 , c s . In the last section, we prove the necessary and sufficient conditions of the matrix transformations from h d p into λ = ℓ ∞ , c , c 0 , ℓ 1 , h d , b v , b s , c s , and from μ = ℓ 1 , b v 0 , b s , c s 0 into h d p .
Pyrazoline and its derivatives have numerous prominent pharmacological effects. Focusing on its anti-viral property, we have designed and synthesized three novel pyrazoline derivatives (A1–A3) through one-pot three components and characterized them using different spectroscopic techniques (FT-IR, 1H NMR, 13C NMR, and UV). These compounds were evaluated against SARS-CoV-2 main protease utilizing in-silico molecular docking studies. The docking results displayed good inhibitory activity of the synthesized compounds. Among them, compound A2 was the most active against targeted protein. The drug-likeness and ADMET properties were predicted to have varied profiles but could still be developed, especially A2. DFT/TD-DFT calculations through B3LYP/6-311G++ level of theory were applied to provide comparable theoretical data along with MEP map and electronic energy gap of HOMO → LUMO.
The use of artificial intelligence (AI) and the Internet of Things (IoT), which is a developing technology in medical applications that assists physicians in making more informed decisions regarding patients’ courses of treatment, has become increasingly widespread in recent years in the field of healthcare. On the other hand, the number of PET scans that are being performed is rising, and radiologists are getting significantly overworked as a result. As a direct result of this, a novel approach that goes by the name “computer-aided diagnostics” is now being investigated as a potential method for reducing the tremendous workloads. A Smart Lung Tumor Detector and Stage Classifier (SLD-SC) is presented in this study as a hybrid technique for PET scans. This detector can identify the stage of a lung tumour. Following the development of the modified LSTM for the detection of lung tumours, the proposed SLD-SC went on to develop a Multilayer Convolutional Neural Network (M-CNN) for the classification of the various stages of lung cancer. This network was then modelled and validated utilising standard benchmark images. The suggested SLD-SC is now being evaluated on lung cancer pictures taken from patients with the disease. We observed that our recommended method gave good results when compared to other tactics that are currently being used in the literature. These findings were outstanding in terms of the performance metrics accuracy, recall, and precision that were assessed. As can be shown by the much better outcomes that were achieved with each of the test images that were used, our proposed method excels its rivals in a variety of respects. In addition to this, it achieves an average accuracy of 97 percent in the categorization of lung tumours, which is much higher than the accuracy achieved by the other approaches.
Radio over fiber system is an integral part of the 5-Generation technology which has undergone enormous changes in the last decade. This work presents a new model for the fronthaul ROF system based on the (VSCEL) as an alternative to the classical CW laser, making use of its interesting properties, that includes narrow bandwidth and high directionality generated optical beam the influences of the bias current value of the VCSEL along with channel dispersion compensation fiber, fiber Bragg grating (FBG) and optical amplifier on the proposed system performance measures like quality factor (Q), bit error rate (BER), eye diagram and optical signal-to-noise ratio (OSNR) have been studied. The simulation results showed that the proposed model can support data transmission of 5Gbps up to 200 km with a Q-factor of around 6, in the case of using dispersion compensation fiber (DCF), along with bias current of about 5 mA. The FBG compensator gave a comparable result to that of the DCF for a transmission distance of no more than 30 km. The maximum bit rate supported by the proposed system to maintain sufficient Q-factor of about 6 was found to be 10Gbps. Furthermore, it was observed that a log (BER) gain of 89, corresponding to the received power, has been achieved in comparison with those reported in a peer model in the literature. Eventually a fair comparison has been made between the proposed system and up to date peer publications which proved the superiority of the presented system model.
Drought is one of the inseparable parts of climate fluctuations that cause a lot of damage every year. Considering the effects of drought on different parts of the environment, agriculture, natural resources, wildlife, etc., its prediction can be useful for managing the crisis and reducing the damages caused by it. In the current research, monthly drought was calculated based on the standard precipitation index in several stations in the south of Iran during the years 1980–2020; Then, using the Markov chain, monthly drought was predicted for the years 2020 to 2040. According to the results, most of the stations have normal, moderate and severe drought conditions. The transition probability matrix showed that in all stations, the probability of passing from a certain state to the same state and the probability of passing from wet to dry state is high; But the probability of transition from dry to wet is low. Also, the predictive results were measured at different stations with different levels of accuracy. In addition, the results showed that the highest probability of drought in the years 2020–2040 is related to normal, moderate and severe classes, and at the level of the studied area, from class one to seven, the 13.4, 26.81, 27,74, 37.11, 4.76, 2.88, and 0.70% of the predicted months drought will happen respectively.
The first COVID-19 confirmed case was reported in Wuhan, China, and spread across the globe with an unprecedented impact on humanity. Since this pandemic requires pervasive diagnosis, developing smart, fast, and efficient detection techniques is significant. To this end, we have developed an Artificial Intelligence engine to classify the lung inflammation level (mild, progressive, severe stage) of the COVID-19 confirmed patient. In particular, the developed model consists of two phases; in the first phase, we calculate the volume and density of lesions and opacities of the CT scan images of the confirmed COVID-19 patient using Morphological approaches. The second phase classifies the pneumonia level of the confirmed COVID-19 patient. We use a modified Convolution Neural Network (CNN) and k-Nearest Neighbor; we also compared the results of both models to the other classification algorithms to precisely classify lung inflammation. The experiments show that the CNN model can provide testing accuracy up to 95.65% compared with exiting classification techniques. The proposed system in this work can be applied efficiently to CT scan and X-ray image datasets. Also, in this work, the Transfer Learning technique has been used to train the pre-trained modified CNN model on a smaller dataset than the original dataset; the modified CNN achieved 92.80% of testing accuracy for detecting pneumonia on chest X-ray images for the relatively extensive dataset.
A new aldehyde 2,2’-[propane-1,3-diylbis(oxy)] dibenzaldehyde was synthesized from refluxing 2-hydroxy acetophenone and 2-hydroxy 1,3-dichloropropanean in an alcoholic medium. The compositions and properties of the new aldehyde compound were characterized by elemental analysis, FTIR, and nuclear magnetic resonance spectroscopy studies. The extracted chitosan was made to react with a new aldehyde to form a Schiff base by a suitable method. The effects of initial concentration of metal ions, exposure time, imine weight, and pH on the adsorption of Cu(II), Cr(III), and Zn(II) metal ions were examined. An adsorption batch experiment was conducted. The adsorption process followed a second-order reaction and Langmuir model with qe 25 mg/g, 121 mg/g, and 26.31 mg/g for Cu(II), Zn(II), and Cr(III) respectively. The Gibbs free energy showed a negative value and the adsorption/desorption tests provided a high value 5 times.
Simple Summary: In traditional medicinal systems, animals play an essential role in treating health issues (zoo therapy) as different body parts are used to treat different diseases. Meanwhile, local traditional knowledge (TK) is an important aspect of cultural legacy that can depict the relationship between communities and nature. Recently ethnobiologists have focused on cross-cultural research in order to document and measure the processes that govern the evolution of traditional knowledge within a culture, as well as to use it in the future. In the present study, we documented ethnozoo-logical knowledge across eight ethnic groups in the Jammu and Kashmir Himalayas. Comparative analysis indicated that Balti and Brokapa were more closely related groups due to high overlap (N = 7) of the use of medicinal species. A total of thirteen idiosyncratic species were recorded for the Kashmiri ethnic group, followed by two idiosyncratic species (Anser indicus, Perdix hodgsoniae) for Balti and two idiosyncratic species (Capra aegagrus hircus, Cuon alpinus) for Changapa. The Pearson correlation coefficient supported the strength and direction of a link between ethnic groups and regions. Cluster analyses revealed two primary clusters of the 79 animal species recorded for eight ethnozoological uses based on fauna similarity. Furthermore, all ethnic groups primarily used the fauna for medicinal and food purposes. Chest infections were frequently treated by the maximum number of species (N = 9), followed by paralysis by seven species. The current ethnozoological study provides needed information such as cross-cultural traditional knowledge of medicine, food, and religious value; combining ethnic knowledge with a scientific approach can make a significant contribution to the long-term development of native communities. Citation: Hassan, M.; Haq, S.M.; Ahmad, R.; Majeed, M.; Sahito, H.A.; Shirani, M.; Mubeen, I.; Aziz, M.A.; Pieroni, A.; Bussmann, R.W.; et al.
Background Objective structured clinical examination (OSCE) has been used in evaluating clinical competence in health professions education around the world. Despite its implementation in Iraq for around a decade, limited studies investigated the challenges and opportunities to improve the standard and quality of this examination from student’s perspective. Methods This qualitative study was based on an online open-ended questionnaire survey that was carried out in the College of Medicine, Hawler Medical University, Iraq at the beginning of the 2018–2019 academic year. A convenience sample of 180 students in the clinical phase (4 th , 5th, and 6 th ) year of study were invited to participate. Results A total of 141 students responded to the online questionnaire. The participants were generally happy with the OSCE, and they recognized many positive aspects, including the role of the OSCE in increasing confidence, engagement and motivating learning, the role of the OSCE in achieving a higher level of learning, the content validity of the OSCE, and the quality of the OSCE. The main weak points of the OSCE identified by the students included unfairness, gender discrimination, duration of the OSCE, and the behavior of the examiners. Suggestions to improve the OSCE examination included improving the examiners’ behavior, with the focus on the training of the examiners, and avoiding discrimination among students. Conclusions Most of the students were generally satisfied with the current OSCE examination. The main concern of the students was related to the organization of the OSCE. Valuable suggestions were raised to improve the OSCE quality including examiners’ and simulated patients’ training.
The Morelli–Callaway model was used to calculate the lattice thermal conductivity (LTC) of indium arsenide in both zinc blende and wurtzite phases of bulk and nanowire (NW) forms under applied hydrostatic pressures. Calculations were performed for NWs with diameters of 50, 63, 66, 100, and 148 nm in the temperature range of (0–400) K. The melting temperature and hydrostatic pressure phase diagram of the bulk and NW forms were predicted using the Clapeyron equation. A new method was developed to examine various related parameters, such as bulk modulus and mass density. The influence of pressure on melting temperature, melting enthalpy, melting entropy, surface energy, and stress. Results indicate that the calculated values of group velocity increased with the increase in NW size. The melting temperature dropped sharply with the rise in pressure. The pressure and temperature dependencies of the LTC were obtained, and they decreased with applied hydrostatic pressure.
Penjween ophiolite is one of the ophiolitic complexes of northeastern Iraq. The serpentinites within the Penjween Ophiolite hosts many pods of hornblendite and amphibolite, and dikes of diorite among many other igneous bodies. These pods have very sharp contacts with the surrounding mantle serpentinized harzburgites. The hornblendites and amphibolites are usually intimately intergrown together as extremely hard, dark green to black colored, fine-to medium-grained pods with ∼2 x ∼2 x ∼(0.5–1) m dimensions. This study presents petrography, mineral chemistry, whole-rock major and trace element geochemistry, and electron probe microanalyses (EPMA) for the major minerals in the studied rocks. The hornblendite is composed entirely of amphiboles (>99% vol.), meanwhile the amphibolite consists of comparable amounts of amphibole and plagioclase which occasionally occurs as layered rocks with banded texture. The diorite dikes are white in color and consist dominantly of coarse-grained plagioclase and less amphiboles. The amphiboles of these rocks belong to pargasite (Mg# 0.69–0.77) ─ edenite (Mg# 0.74–0.79) endmembers where pargasite is by far the predominant mineral; meanwhile the plagioclase is albite (Ab93.4An6.4Or0.2). The amphiboles are replacement products of pyroxenes indicated from the relict pyroxene within their crystals. The amphiboles are abnormally rich in various dust-like inclusions of transparent minerals like REE-rich epidote, rutile, zircon, apatite, titanite, and ore minerals like ilmenite, and pyrrhotite, oriented along the crystallographic axes and form distinct zones in the core of amphibole crystals. The geochemical characteristics of the studied hornblendite (MgO = 13.07%, Ni = 260 ppm, Mg# = 66.57) as well as the high Sc (33 ppm) and V (254 ppm) concentrations are collectively consistent with a mantle-derived, igneous origin. The primitive-mantle normalized trace elements spidergram showed enrichment (hump) in Ba, Th, U, La, Ce, Pb, and Sr, and depletion (trough) in Nb, Ta, K, and Ti. The chondrite-normalized REE diagram showed enrichment of LREE relative to HREE, indicated from the smooth and steady decrease in the negative slope from LREE towards HREE with a negligible Eu-anomaly. Various tectonic discriminating diagrams showed that the studied hornblendite, amphibolite pods and diorite dikes are of igneous fore-arc origin, formed from calc-alkaline and/or tholeiitic magma within an active continental margin setting. The ⁴⁰Ar/³⁹Ar laser age of hornblendite is late Paleocene (Thanetian) (57.8 ± 5.1 Ma) which might represent an event during the obduction between the oceanic fore-arc Island and the Arabian Plate during the Late Cretaceous/Paleocene period.
Phytotherapy, based on medicinal plants, have excellent potential in managing several diseases. A vital part of the healthcare system is herbal medicines, consisting of therapeutic agents with high safety profile and no or least adverse effects. Herbs or medicinal plants show anticancer, antioxidant, and gene-protective activity, which is useful for pharmaceutical industries. In vitro, the extract of antioxidant compounds prevents the growth of colon and liver cancer cells, followed by a dose-dependent method. The screening of extracts is done by using in vitro models. Reactive oxygen species (ROS) and free radicals lead to diseases based on age which promotes oxidative stress. Different types of ROSs available have central roles in the normal physiology and functioning of processes. Herbal or traditional plant medicines have rich antioxidant activity. Despite the limited literature on the health effect of herbal extract or spices. There are many studies examining the encouraging health effects of single phytochemicals instigating from the medicinal plant. This review provides a detailed overview on herbal antioxidants and how application of nanotechnology can improve its biological activity in managing several major diseases, and having no reported side effects.
Objectives The genetic polymorphisms of the endothelial nitric oxide synthase (eNOS) gene are strongly associated with several cardiovascular diseases (CVDs) in various populations. The current study aimed to investigate the association of the eNOS rs1800779 (A/G) polymorphism with the progress of myocardial infarction (MI). Methods Eighty-five healthy subjects and 80 patients with MI admitted to the Erbil Cardiac Centre in the Kurdistan Region of Iraq were enrolled in the study. All participants were Kurdish from the same ethnic group. The amplification refractory mutation system polymerase chain reaction (ARMS-PCR) was used to determine the rs1800779 (A/G) polymorphism of eNOS, and the nitric oxide (NO) serum level was detected by spectrophotometer. Results The genotypic frequencies of the eNOS rs1800779 AA (wild type), AG, and GG were 58.75%, 33.75%, and 7.50%, respectively, in the MI patients, and 49.41%, 43.53%, and 7.06%, respectively, for the control group. The frequencies of the A and the G alleles were 75.6% and 24.4%, respectively, in the MI group, and 71.2% and 28.8%, respectively, in the control subjects. The results revealed a lack of association of the rs1800779 genotype distribution with the level of NO serum and increased risk of MI. Conclusion The study concluded that there is a lack of association between the genotypes and alleles of the rs1800779 eNOS and susceptibility to MI in the studied population.
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3,261 members
Asaad Hamid Ismail
  • Department of Physics
Shuokr  Qarani Aziz
  • Department of Civil Engineering
Azeez A. Barzinjy
  • Department of Physics
Hero Mohammad Ismael
  • Department of Biology
Erbil, Iraq