Iraqi Journal of Science (IJS) is a blind peer-reviewed open access journal issued by the College of Science at the University of Baghdad. It is a monthly journal that publishes original research articles in a wide range of subjects. The prestigious interdisciplinary editorial board in the journal reflects the diversity of subjects covered in the journal. The journal is being published since 1956. The journal is basically self-financed by applying fees on the researcher's work published in the journal. However, the journal is also supported by the college of science at the University of Baghdad.
College of Science - University of Baghdad
Geophysical Study to the Role of Salt in Creating BuzurganOilfield Structure, Southeast of Iraq.
This paper is an attempt to study the relation between the creation of Buzurgan oilfield structures and the role of salt in forming these structures. The study depends on the available surface geophysical data, namely; seismic reflection, gravity and magnetic data. Seismic reflection profiles show clearly how the salt of Al-Fatha Formation (evaporite) plays a clear role in creating the relatively shallow anticlinal structures of Buzurgan oilfield, in addition to the effect of the lateral stresses resulted from the collision between Arabian and Iranian plates. Gravity and magnetic data interpretations indicate that there are similar probable anticlinal structures may occur in deeper formations due to the effect of Gotnia and Hormuz salt, where these salts are piercing upward by buoyant forces resulting from the density contrast between these formations and the heavier rocks above them. Depth of the basement rocks are found to be ranged between 11.7 to 12.4 Km measured from gravity and magnetic data respectively.
Copyright (c) 2026 Iraqi Journal of Science https://creativecommons.org/licenses/by-nc/4.0
A Novel Image Decomposition Employing Gaussian Curvature based Edge preserving Filter for Brain Tumor Detection through Image Fusion
The process of combining images from multiple medical imaging sources without any distortion or loss of information is known as medical image fusion. It improves the usefulness of medical imaging for the diagnosis and treatment of medical issues by maintaining every feature in the fused image. Recent years have seen the introduction of many image fusion techniques that show the significant progress in the field of medical diagnosis. However, the fusion performance of these contemporary methods is prone to distortion, noise, and blurring. To address these drawbacks of the current methods, this work presents a novel fusion methodology for a visually pleasing appearance. Using Gaussian curvature and guided filters, a new decomposition technique with an edge-preserving smoother is firstly described. The primary objective of this approach is to preserve edge haloes while recovering the structural information. The "weighted average" technique is used to merge source images based on the weights that were computed based on significant edge details. This technique can enhance contrast and highlight significant details in the fused image. We evaluate our proposed methodology on multiple pairs of publically available medical imaging datasets. The quantitative evaluation indicates that the suggested fusion strategy for multimodal image fusion improves the average IE by 5.8, MI by 34.8%, MSSIM by 31%, and QAB/F by 40% over the current methods, making it appropriate for usage in the medical area for correct diagnosis.
Gaussian curvature, Guided filter, Medical image fusion,Weighted average, Qualitative, Quantitative evaluation
Copyright (c) 2025 Iraqi Journal of Science https://creativecommons.org/licenses/by-nc/4.0
Pharmacological Evaluation of Najas gracillima from the Bay of Bengal Coastal Regions: In Vitro and In Silico Studies
Najas gracillima is a green seaweed commonly found in North America and East Asia. This study explored its phytochemical composition and assessed its antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays, along with α-amylase inhibition and cytotoxicity evaluations via the brine shrimp lethality bioassay (BSLB) and the HeLa cancer cell line. The acetone extract of Najas gracillima (ANG) showed a total phenolic content of 14.26 ± 1.86 mg GAE/g extract and a total flavonoid content of 10.27 ± 2.24 mg QUE/g extract. ANG demonstrated strong antioxidant activity (IC₅₀ for DPPH: 14.57 ± 0.93 µg/mL; IC₅₀ for ABTS: 32.17 ± 1.35 µg/mL) and moderate α-amylase inhibition (IC₅₀: 54.97 ± 3.36 µg/mL). While it showed mild cytotoxicity in the BSLB assay (LC₅₀: 673.08 μg/mL), no cytotoxic effects were observed against HeLa cells. Molecular docking analysis revealed that the identified compounds exhibited strong binding affinities to relevant drug target proteins associated with the observed biological activities. These findings suggest that N. gracillima may serve as a valuable source of bioactive compounds with potential applications in managing oxidative stress and diabetes.
Effect of Moringa Leaves Water Extract Combined with Collagen and Vitamin C on Malondialdehyde Levels in Rats Exposed to Oxidative Stress
The increasing prevalence of free radical-related diseases has led to a greater reliance on herbal medicines, such as Moringa oleifera (ML), as antioxidants. However, limited evidence exists regarding the combined effect of herbal and conventional antioxidants on malondialdehyde (MDA) levels. This research assessed simplisia characterization, phytochemical screening, antioxidant activity of ML water extract (ML-WE), and serum MDA levels in animal models using ELISA. Forty-two Wistar rats were randomly divided into seven groups: a negative control, a positive control, and five treatment groups. All treatment groups were exposed to lead for seven days, followed by supplementation with either ML-WE (200 mg/kg BW), vitamin C (36 mg/kg BW), collagen (27 mg/kg BW), or their combinations. ML-WE showed strong antioxidant activity (IC50: 81.761 ppm). MDA levels differed significantly among groups (p < 0.001). Combining ML-WE with collagen reduced MDA levels more than ML-WE alone (14.65 ± 0.66 vs 21.32 ± 0.95 nmol/mL, p < 0.05) but was less effective than collagen monotherapy. Similarly, ML-WE combined with vitamin C showed no statistically significant improvement. These results indicate that while ML-WE has strong antioxidant properties, no synergistic effects were observed in combination therapies.
Gold Mineralisation in Metamorphic Rocks on Buru Island, Indonesia: Rock Facies, Geochemistry, Alterations, Mineralisation, and Types of Ore Deposits
Indonesia is a country rich in natural resources, one of which is gold deposits scattered across several locations, including the islands of Sumatra, Java, Sulawesi, Maluku, Nusa Tenggara and Papua. This study aims to (1) determine the type of alteration contained in the research area based on the altered mineral set resulting from the alteration process and the characteristics of gold deposits in metamorphic rocks in the study area, (2) determine the mineralisation characteristics of gold deposits by conducting geochemical analysis, (3) determine the type of metamorphic facies in host-rocks Gold deposits in the research area, (4) explain how the distribution of gold content from the results of geochemical analysis, (5) explain the genetic characteristics of gold deposits in the study area based on geochemical analysis and petrographic analysis. This study involved a field survey and random rock sampling at Mount Botak, Buru Regency, Maluku Province, Indonesia. Rock samples were analysed by petrographic analysis, XRD (X-ray Diffraction) analysis, XRF (X-ray fluorescence) analysis, ICP-OES (inductively coupled plasma-optical emission spectrometry) analysis, and AAS (atomic absorption spectrometry) analysis. The study results indicate that the host rock of gold deposits on Buru Island is a metamorphic rock formed by greenschist facies. The types of alterations are silicic, sericitization, argilic, and chloritization. The mineralisation is generally in quartz veins with a crustiform texture and a slight vein stockwork. Au levels ranged from 0.23 to 5.9 g/ton, which was not accompanied by Ag enrichment. Based on the analysis of gold deposits in the research area, it is an orogenic-type of deposit formed in a mesozonal environment, typically at a depth of 5-10 km. The implications of the research results can be applied to gold exploration purposes in Indonesia, particularly for gold deposits that have metamorphic host rocks.
Analyzing Materials and Determining their Physical Properties Using Spectral Sensing Technology from Satellite Images: Methodology and Applications
The spectral remote sensor technology was used to study the Kurdistan region of Iraq to determine the characteristics of surface minerals and by analyzing satellite images across multiple spectral ranges, distinctive spectral signatures were specified for several metals such as zinc (ZN), Lead (PB), and Parium (BA), as well as the use of thermal infrared to detect free abnormalities and the results were verified through field measurements and admonitory, where the selection accuracy was 85% according to the absolute error (MAPE) and 0.045 for RMSé and the results showed that spectral signatures for metals were distributed in nearby and remote IR ranges, helping to determine mineral sediments such as zinc and lead in carbonate rocks and infrared data and it also revealed a surface temperature between 20°C and 35°C, with thermal anomaly indicating metal concentrations and the study confirms the effectiveness of spectral remote sensing as an inexpensive and accurate tool for minerals, which enhances sustainable resource management strategies in Iraq.
Nonlinear optical characteristics of Nile blue films doped with the polymers PMMA, PVC and their blend by using z-scan technique
The nonlinear optical characteristics of the laser dye Nile blue doped with Polyvinyl chloride (Nb /PVC), poly methylmethacrylate Nb/ (PMMA) and their blend N /(blend of PMMA 50 %+PVC 50%) was studded. Free-casting technique method was used for deposited the films. The nonlinear properties of the films studded by using Z- scan technique .Z-scan experiment was performed using continuous wave (CW) diode laser at 650 nm in two parts with power of 50 mw . The first part was done using a closed-aperture placed in front of the detector to measure the nonlinear refractive index ,with the second part; the aperture in front the detector was removed (open aperture) to measure the nonlinear absorption coefficient. The open-aperture curve exhibits a normalized transmittance (valley), indicating the presence of induced absorption. The observed nonlinearity is found to be of the third order, as it fits to two photon absorption process (TPA). The closed-aperture curve exhibits a peak to valley shape, indicating a negative value of the nonlinear refractive index n2. The effective values of the nonlinear refractive index n2, the nonlinear absorption coefficient β2, real and imaginary parts of the third-order optical nonlinearity, χ(3) for Nb/PMMA+PVC films comparatively with that of Nb/PMMA and Nb/PVC has much lower optical transmittance value obtained shows that these films can be used as efficient optical limiters.
Copyright (c) 2021 Iraqi Journal of Science https://creativecommons.org/licenses/by-nc/4.0
Evaluation of the Heavy Metals Concentration Upon Occupational Workers at Several Petrol Filling Stations in Baghdad City, Iraq
Several heavy metals emitted from car petrol may accumulate in occupational workers at elevated concentrations, resulting in various impacts on these workers. The current work was designed to assess the blood content of Zn, Cu, and Pb in occupationally exposed workers. Four car filling stations situated within Baghdad city, Iraq, and 40 occupational workers were subjected to this study; in addition, a sample of 20 individuals away from these examined fuel stations was selected to act as a control sample during November 2023. From both occupational workers and control samples, 4 ml of blood from each individual was taken and placed in a gel tube for coagulation. Each blood sample was centrifuged for 40 min at 3000 rpm to separate blood serum. The serum of each sample was placed into glass tubes and kept in a refrigerator at 20º C and then used to assess blood Zn, Cu, and Pb content. Also, the ages of both control and workers samples and the working period of only occupational workers were recorded. The obtained data has shown that the mean of examined blood heavy metals content was significantly lower in the control sample than those detected in occupational workers where control sample had a mean value of Zn of 65.15 ± 11.0, Cu of 101.3 ± 14.57 and Pb of 14.625 ± 2.52 µg/dl while worker sample gave mean value of 98.03 ± 23.07, 123.26 ± 40.96 and 57.68 ±14.33 µg/dl for Zn, Cu, and Pb respectively. Also, this work has found that there were insignificant (P < 0.05) effects of age on blood heavy metals whilst a significant effect of working period (P < 0.001) on blood heavy metal content of examined workers was recorded. Also, t-test analysis has revealed significant differences (P < 0.05) between the mean values of control and occupational workers for all examined blood heavy metals content.
Enhancing the Performance of Cyberattack Detection Model on AWS Using Stacked Feature Selection and Hybrid Classification
One of the essential technologies worldwide is cloud computing. Increasing demand for its various Amazon Web Services (AWS) services make it more vulnerable to different types of attacks, such as DoS, DDoS, Infiltration, and others). The full list of attack types used in this study is presented in the classification section. Protecting cloud systems and their data mainly depends on various security technologies, including intrusion detection systems that monitor network traffic to detect suspicious activity or potential threats. This research proposes a model to contribute to solving the problem of identifying malicious activities in cloud networks. This model has three stages: the initial stage is pre-processing, encompassing data cleaning, normalization, and labelling. Stage two involved intersecting the outputs of the correlation and Information Gain methods to obtain a set of common features. Then these features were further filtered using the Chi-square method to identify the most relevant features. Lastly, a proposed classification technique was used utilizing (CNN -XGBoost) to classify traffic in the network into normal and abnormal. Experiment results on CSE-CIC-IDS2018 dataset showed that the proposed model achieved an accuracy of 99.3%, outperforming traditional filter-based feature selection.
Gene Expression of clfA , clfB, and SdrC Genes of Staphylococcus aureus Under Probiotic Stress
The significant factor that participated in virulence and pathogenesis for Gram-positive pathogen Staphylococcus aureus is biofilm development. In hospital settings, biofilm construction on medical equipment is quite concerning since it is a permanent source of infection. The infection results from S. aureus biofilm, which was considered a serious problem due to the difficulty in treating it with traditional antibiotics. In recent years, the medical community has been using probiotic bacteria to suppress biofilm development. The current work aims to investigate the impact of cell-free supernatant (CFS) of lactobacillus acidophilus on biofilm generation and gene expression of some key adhesion genes (clfA, clfB, and SdrC) in S. aureus clinical isolates. The CFS was extracted from Lactobacillus. acidophilus, and minimum inhibitory concentration was estimated. The colorimetric method was carried out to detect the impact of sub-minimum inhibitory concentrations of the CFS extracts on biofilm construction in thirty-three S. aureus isolates. Moreover, the expression level of some associated biofilm genes (clfA, clfB, and SdrC) was determined quantitatively before and after CFS treatment using real-time PCR for three isolates forming a strong biofilm. The result indicated that most isolates formed mostly strong and moderate biofilm with 42.42% and 48.48%, respectively, while 6.06% and 3.03% of isolates were weak and non-biofilm former. Regarding the clfA gene, gene expression was only detected in two isolates by which one isolate showed downregulation with a fold change value (0.0883) and another isolate showed upregulation with a fold change value (5.7134) after treatment of isolates with CFS. However, clfB and sdrC revealed a decrease in expression in two isolates, while the third isolate showed upregulation after treatment of isolates with CFS. The above result indicates that clfA, clfB, and sdrC expressed downregulation under the effect of CFS. In conclusion, the ability to produce biofilm plays a significant role in pathogenicity and antibiotic resistance in S. aureus isolates, especially when most isolates produce strong and moderate biofilm. Furthermore, the highly inhibitory effect of CFS from lactobacillus acidophilus in the reduction of biofilm activity and the drop in expression of key biofilm genes in S. aureus isolates highlights the capacity to use CFS as an alternative strategy to eliminate infection related to biofilm in this pathogen.
ADL: A New Dataset of Select Arabic-Derived Letters for Handwritten Character Recognition
Arabic text and characters recognition are among the most challenging problems in the field of optical character recognition (OCR) due to the complex nature of the letters and their variance in forms. This paper presents a new ADL dataset of the Arabic derived letters: Che (چ), Ngain (ڠ), Pe (پ), Ve (ڤ), Zhe (ژ), and the three versions of Gaf (گ, ڭ, and ݣ). This dataset consists of 55,440 images from scanned handwritten papers made by 30 participants of different ages, thus ensuring demographic and stylistic diversity. The dataset has been evaluated on three different models: a Support Vector Machine (SVM), a Convolutional Neural Network (CNN), and a Vision Transformer (ViT) to demonstrate its practical usability. Several forms for different alphabet positions are used to represent each letter: isolated, initial, medial, and final, to reflect its real-world usage, which increases the value of the dataset for machine learning applications. The dataset was enriched using data augmentation techniques based on random rotation, horizontal shift, and zooming with nearest neighbor interpolation to fill empty pixels, which allowed for representing each character in a balanced way while preserving the essential structural elements. The dataset, as the first structured resource on some derived letters of the Arabic language, aims to fill a crucial gap in datasets focused on Arabic script and to advance research on handwritten character recognition. This dataset has important implications for linguistic research, practical applications, and advances in automated text processing systems by supporting better recognition of these non-original derived letters, especially in optical character recognition (OCR) systems.
Enhancing Steganography System Using Deep Learning and Hyperparameter Optimization
Steganography plays a vital role in secure message transmission, embedding information imperceptibly within cover images. This research addresses the challenge of creating stego images visually indistinguishable from originals, while enhancing resistance to steganalysis. We propose a novel steganographic system based on Generative Adversarial Networks (GANs) with hyperparameter tuning to enhance imperceptibility and security. Multi-scale feature extraction via Inception modules within the encoder facilitates efficient embedding with minimal distortion. A new combined metric, incorporating MSE, PAD, and MAE alongside PSNR and SSIM, provides a more comprehensive performance evaluation, addressing limitations of relying solely on PSNR/SSIM. For instance, while RMSprop achieved a PSNR of 57.32 dB, its combined metric score was 16.37, reflecting its weaknesses in error metrics. Conversely, SGD, with a PSNR of 59.55 dB, achieved a combined metric score of 34.73, demonstrating its balanced performance. Multiple optimization algorithms, including Adadelta, Adam, Nosadam, SparseAdam, Adamp, L-BFGS, RAdamplus, Tadam, RMSprop, Nadam, Ftrl, AdaGrad, AdamW, Adamwt, SGD, RAdam, and Naturalgrad, were evaluated. Nadam and Adadelta achieved the highest combined metric scores (36.71 and 34.61, respectively), correlating with superior PSNR and SSIM values, thus ensuring higher image fidelity and imperceptibility. The system effectively impedes steganalysis by reducing statistical discrepancies and utilizes tanh activation functions for enhanced security. This system achieves robust steganographic performance with minimal distortion and improved security, offering significant advancements in secure image communication. The new combined metric provides a nuanced performance assessment, guiding optimal algorithm selection.
Enhanced Intelligent System Model for Managing Anxiety in In-Vitro Fertilization (IVF) Patients
In vitro fertilization (IVF) program patients have elevated anxiety levels. Therefore, they immediately contact fertility doctors through existing communication media to get treatment. However, fertility doctors cannot respond quickly due to high workloads. The intelligent health system that implements the Case-Based Reasoning (CBR) model is widely used to assist doctors in handling patient complaints. However, the system provides opportunities for modification so that the performance of the CBR model increases and further assists fertility doctors in handling IVF patient anxiety. This study modified the CBR model by integrating several previous research results (CCBR similarity formula, combination of CBR with Rule-Based Reasoning, the role of patient feedback, and the application of a minimum standard value of 80%). Measurement of the coefficient matrix to assess system performance using the Chris Case-Based Reasoning (CCBR) similarity formula produced an accuracy value of 52.58%, and the performance of the combination of the CBR model with the Rule-Based Reasoning model increased the accuracy value by 47.42%, so it can be stated that the CCBR model is a better intelligent system model for handling IVF patient anxiety.
GIS-MCDA Based Land Capability Analysis for Sustainable Food Production in the Kurdistan Region of Iraq
Food production is vital to global food security, entailing significant social, economic, and environmental implications. The Kurdistan Region of Iraq (KRI) possesses abundant natural and human resources essential for agriculture, including extensive agricultural land, water resources, and a favorable climate. However, challenges such as population growth, displacement of large numbers of residents from other provinces to the Kurdistan Region, unplanned urban expansion encroaching on agricultural areas, useless land accumulation, and agricultural land degradation pose substantial threats to sustainable food production (SFP). The study's primary objective is to assess and map the potential for SFP in the region, enabling stakeholders to formulate strategies for sustainability and ensure food security. The methodology involved classifying land capability using Geographic Information System - Multi-Criteria Decision Analysis GIS-MCDA approaches, including the fuzzy analytical hierarchy process-hybrid model (F-AHP) and fuzzy analytical network process F-ANP. The dataset encompassed variables related to land capability for food production, categorized into six main groups: topography, climate elements, water resources, land use-landcover (LULC), geology, and soil characteristics, each with about eighteen sub-factors. Results from F-AHP and F-ANP indicated consistent findings across factor weights and land capability classifications in KRI, showing no significant disparities. Only 10.72% of the region's total land 4245.7 km2 exhibited high capability, while 28.68%, 11355 km2, 34.18%, 13534 km2, and 18.1%, 7168 km2, were moderately capable, low capability, and limited capable land, respectively. An 8.32%, 3295.4 km2 of Kurdistan's land was deemed unsuitable for SFP. The study's insights are crucial for experts, planners, governments, and stakeholders, facilitating the assessment of current food production. Based on these findings, appropriate plans and strategies can be developed to uphold long-term food security in the Kurdistan region.
Sub-inhibitory Concentrations of Nitrofurantoin Modulate Enterococcus faecalis Biofilm Formation and Adherence in vitro
Biofilm formation interferes with Enterococcus faecalis infections. Modulating biofilm formation may aid in developing innovative treatment strategies for multidrug-resistant bacteria responsible for urinary tract infections (UTIs). This study aims to evaluate the effect of nitrofurantoin minimum inhibitory concentration (MIC) on E. faecalis biofilm formation and adherence. Midstream urine samples (78) were collected from patients with UTI. The biochemical tests and VITIK technology were used to identify the E. faecalis isolates. The MICs of nitrofurantoin were determined to evaluate the susceptibility of E. faecalis isolates. Biofilm levels to polystyrene and adherence to human oral mucosal epithelial cells (OMECs) in vitro were evaluated. The inhibition role of nitrofurantoin sub-MICs in biofilm formation and adherence was examined. The incidence of UTI infection with E. faecalis was 12.82%. The susceptibility of ten E. faecalis isolates to nitrofurantoin, and their biofilm formation varied. No significant relationship was observed between the susceptibility of the isolates to nitrofurantoin and their biofilm production (r: +0.37, P>0.05). Sub-MICs of nitrofurantoin (½ MIC and ¼ MIC) significantly decline bacterial biofilm formation and adherence to human OMECs (P < 0.05). Nitrofurantoin sub-MICs reduce biofilm production and E. faecalis adherence to biotic and abiotic surfaces. This can help modulate treatment strategies in the future.
Analysis of the Distribution of Globular Clusters - Specific Frequency in Different Galaxy Types
Globular clusters (GC) are important objects for tracing a galaxy's early evolution. The origin of the scaling parameters of the globular clusters as a function of galaxy mass, i.e., specific frequency, (SN), specific mass (SM), and specific number (T) of globular clusters is investigated to understand the origin of the relations between these parameters and the V-band magnitude (MV) of their host galaxies. A wide sample of data from literature, covering different galaxy masses, types, and environments, including a study of the number of globular clusters (NGC) has been used as the basis for our analysis. The sample covers the entire range of galaxy (MV = −11 to −25 mag), where this large dataset confirms that, irrespective of the type of galaxy, the specific frequencies of GCs increase around a galaxy magnitude, of MV ≃ −18 mag. Additionally, it is shown by our findings that the specific mass of GCs tends to increase significantly in galaxies with MV ≃ −21 mag, while the specific number rises considerably in lower-luminosity galaxies with MV ≃ −17 mag. Thus, highlighting the variations of GC formation efficiency, across different galaxy types.
A Comparative Analysis of Zernike and Karhunen-Loeve Polynomials for Wave-front Correction in Modal Adaptive Optics Systems
This work employed the Zernike and Karhunen-Loeve polynomials in the adaptive optics (AO) systems to correct wave-front aberrations. The present work uses MATLAB-based program for simulating wave-front distortion correction with the use of the Modal AO method. Wave-front aberrations were represented by a modified von Karman turbulence model; numerical simulations and analyses were performed. The Zernike polynomials higher values of SNR and Strehl ratios, lower values of RMSE, variance, and covariance in comparison to Karhunen-Loeve polynomials modes, proved the superiority of the Zernike polynomials in correcting wave-front distortion. The present work provides valuable insights into the quality and performance metrics of the Karhunen-Loeve and Zernike modes, with a focus on gaining a more detailed understanding of the different aberration modes for enhancing wave-front corrections in optical systems.
Efficient Uranium Removal from Contaminated Water Using Laboratory-Prepared Zeolite
Due to radioactive uranium pollution of water posing serious risks to human health and the environment, effective and sustainable cleanup techniques are required. Zeolite, a porous alumina-silicate mineral with a large surface area and ion-exchange capacity, has drawn interest as a successful uranium removal adsorbent. This study the removal of uranium from radioactively polluted water using laboratory prepared zeolite. To increase the adsorption efficiency, a number of variables were adjusted, such as pH, contact time, initial uranium content, and temperature. According to experimental studies, zeolite exhibits a great affinity for uranium ions and, in the right circumstances, can remove uranium ions with high efficiency. The results show that zeolite is an environmentally acceptable, inexpensive, and promising material for uranium decontamination in aquatic environments. By developing scalable techniques for treating radioactive wastewater, this research helps to ensure safer water supplies.
Effect of Bitter Almond Extract on Some Physiological and Histological Parameters in Male Rats
Bitter almond is a peach fruit from the Rosaceae family. Despite its diverse health benefits, some harmful and toxic properties can be produced in the body as it contains hydrocyanic acid, which gives a bitter taste. This study was conducted to investigate the harmful toxic properties of bitter almonds that can be produced in the body as they contain hydrocyanic acid; despite its many beneficial secondary metabolites. Methods: Whole bitter almond seeds collected in Iraq were extracted and dosed to rats. 20 Westar albino male rats weighing (200- 250) gm were obtained from the Biotechnology Center / AL-Nahrain University. The animals were divided into 4 groups (control group administered distill water orally only, T1 = first tested group administrated 100 mg /kg body weight, T 2 = second treated group administrated 200 mg / kg B.W. and T 3 = third treated group administrated 300 mg / kg B.W. All groups were treated by oral route every day for four weeks. Then, samples were collected for histological study of the organs of the liver and kidneys. Results: There was a significant (P≤ 0.05) rise for ALT, AST, ALP, LDH, urea, creatinine, uric acid, cholesterol, triglyceride and a significant (P ≤ 0.05) increase in LDL for both T2 and T3 in comparison with T1 plus control group. The total serum bilirubin explained no significant (P ≤ 0.05) difference between treated groups with the control. The HDL cleared a significant (P ≤ 0.05) decrease in T3 with comparison with the control group, T1 and T2. After examining tissue sections with a compound microscope, it was found that various changes occurred, such as; bleeding, cell necrosis, congestion and damage to blood vessels in both organs.
Nibrin and IL20 Potential Association With Breast Cancer: At Both Benign and Malignant Levels
Breast cancer is a major cause of malignancies–related mortalities among women worldwide. The development and progression of this disease are attributed to the contribution of key cellular modulators, including the NBN (Nibrin) gene and interleukin 20 (IL20), that are linked to genomic instability, stemness, cell cycle regulation and cancer predisposition. Due to the lack of local studies investigating NBN gene expression in the context of breast cancer, the present study aims to assess its gene expression along with the assessment of interleukin 20 (IL20) serum levels in newly diagnosed breast cancer patients in comparison to cases with benign breast lumps and healthy controls. Total RNA was extracted from the collected blood samples of all 118 participating subjects, including 73 with breast tumor (50 malignant breast tumor and 23 benign breast tumor patients) and 45 healthy controls. Relative NBN gene expression was estimated using q-PCR, while IL20 serum levels were assessed using the ELISA technique. Additionally, a number of socio-demographic/clinical features (age, BMI, breastfeeding, menopausal status and family history) were evaluated for associations between them and the measured parameters. NBN gene expression levels were significantly upregulated (p ≤ 0.05) in both malignant breast cancer group (2.33 ± 0.41) and benign breast lumps (1.25 ± 0.25) compared to that of the healthy control group. Additionally, IL-20 serum levels showed significant differences (p=0.031) between benign and malignant breast cancer patients (0.69 ± 0.014 and 0.64 ± 0.009, respectively) in comparison to healthy controls. This finding suggests the potential involvement of IL-20, as a stemness modifier in breast carcinogenic events. Overall, the present study findings support the association of NBN and IL20 overexpression to breast cancer pathogenesis, with the potential to be involved in precancerous events via its contribution to breast lumps development.
Measurements of Magnetic Susceptibility and Its Application in Pollution Detection- A Case Study in the Tigris River in Baghdad City, Iraq
The Tigris River is considered the largest river that crosses Baghdad City, the capital of Iraq. It is regarded as one of the main water suppliers to the city. River sediments can be used to detect the pollution in rivers; thirty sediment samples were collected one to two meters away from the riverside to assess the level pollution in sediments. The area is situated not so far from an industrial area, the Dura oil refinery, factories, and other facilities. A series of magnetic measurements has been performed, including magnetic susceptibility (χ), anhysteretic remanent magnetisation (ARM), saturation isothermal remanent magnetisation (SIRM) and thermomagnetic analyses (κ-T). Very high values of χ, χARM and SIRM were detected; the mean values were 2962×10-8 (m3/kg), 569×10-8 (m3/kg) and 2721×10-5 (Am2/kg), respectively. The high correlations between χ and χARM, χ and SIRM are (R2=0.78) and (R2=0.82), respectively. Thermomagnetic analyses at high and low temperatures show that the curves of high temperatures (0 to 700 ºC) decrease around 580 ºC, which is the Curie temperature of magnetite; the low-temperature curve (0 to -200ºC) shows a typical curve of magnetite, and the Verwey transition is clearly detected. These results indicate the presence of Single-Domain (SD) to Multi-Domain (MD) grains of magnetite (Fe₃O₄) in high concentrations and the absence of superparamagnetic (SP) grains in the sediments. The results indicate that the river sediments are highly polluted, which could be due to anthropogenic activities, including oil refineries, industrial activities, and atmospheric particle pollution.
Synthesis of CdFe2O4-SnO2 Nano Spinel Ferrite and Investigation of the Structural and H2S Gas Sensing Properties
In this paper, nanoferrite (CdFe2O4-SnO2) was prepared by the auto combustion method (sol-gel), with weight ratios of (x = 0.0, 0.05, 0.10, 0.15, 0.20, 0.25) for SnO2. The properties of the nanoferrite were characterized by XRD, FE-SEM, and EDX techniques. The results showed that the produced compound had a cubic spinel ferrite phase; the crystallite size was determined using the Scherrer and Williamson-Hall equation. The FE-SEM image demonstrated that the compound is porous, with nanoscale particles that have a ball-like appearance. The EDX test verified the existence of Fe, O, Cd, and Sn atoms. Gas sensing showed the compound's high sensitivity to H2S.
An Efficient Optimized Deep Model for Improving Gastrointestinal Diseases Classification
Gastrointestinal (GI) diseases are increasing day by day due to the continuous change in people's dietary habits, as these changes play a major role in several intestinal problems. Endoscopy is a medical imaging device used to detect and diagnose gastrointestinal diseases such as esophagitis and benign tumors. Manual diagnosis consumes a long time, so there is an urgent need to use computer techniques for GI disease diagnosis accurate and fast. In this study, a Bayesian optimizer-based pre-trained model architecture (BOPMA) is proposed to improve GI disease detection. The BOPMA is concerned with adapting the Bayesian optimizer in two important aspects: improving the EfficientNetV2s architecture and fine-tuning the hyperparameters of AdamW, which is the latest version currently available in the concept of backpropagation to improve the training process. In the proposed model, the Kvasir dataset of 8000 images, which includes 1,000 images for each of the eight GI disease classes, is used for training. Several transfer learning models, such as ResNet50, InceptionV3, and Xception, are adopted for comparison. To measure the quality of the model, the accuracy measure is used, whereby the accuracy of the BOPMA reached (0.9479), while the accuracy of ResNet50, InceptionV3, and Xception is (0.7995), (0.8568), and (0.9141), respectively. Additionally, the results demonstrated that the proposed model achieved better classification accuracy compared to previous studies that adopted the same dataset (Kvasir dataset). Finally, our study adopts the issuance of a prediction model that works as a doctor’s assistant to improve diagnostic accuracy within the complex domain of gastrointestinal health, opening new avenues for clinical application and contributing to better patient outcomes.
Serum Level and Single-nucleotide Polymorphism (rs1927911) of Toll-like Receptor 4 Among Type 2 Diabetes Mellitus Iraqi Patients
Toll-like receptor 4 (TLR4), a member of the TLR family, plays a key role in innate immunity. Type 2 diabetes mellitus (T2DM) is a chronic condition characterized by impaired insulin sensitivity and abnormal immune responses. This study aimed to examine the association of the TLR4 single-nucleotide polymorphism (SNP) rs1927911 with T2DM susceptibility and to evaluate the SNP's effect on TLR4 levels. The study included 60 T2DM patients and 40 healthy controls. Blood samples were collected for serum analysis and DNA extraction. TLR4 levels were significantly elevated in T2DM patients carrying the AG genotype compared to controls (0.48 ± 0.10 vs. 0.30 ± 0.02 ng/ml, p = 0.03). Conversely, the controls with AA and GG genotypes had significantly higher levels of TLR4 compared to the patients (0.50 ± 0.11 versus 0.32 ± 0.08 and 0.43 ± 0.08 versus 0.35 ± 0.03 ng/ml, respectively), T2DM risk factors include AA genotype with an elevated incidence of T2DM (OR = 4.1), GG genotype (OR = 1.04), and the A allele (OR = 1.42). However, the AG genotype was not considered a risk factor for T2DM (OR = 0.47, 95% CI: 0.21–1.06). In conclusion, the AA and GG genotypes and the A allele contribute to T2DM susceptibility, while the AG genotype influences TLR4 levels without significantly increasing disease risk.
Construction, identification, and description of molecularly imprinted polymers based on solid-phase microextraction-UV for determination of ciprofloxacin in pharmaceutical samples
Ciprofloxacin it as one of the most widely used antibiotics, making it essential to study its incorporation in pharmaceutical formulations. This study utilized a molecularly imprinted polymer (MIP) composed of styrene and ethylene glycol dimethyl acrylate to optimize the sorbent for ciprofloxacin solid-phase extraction (MISPµE). The MIP generated a maximum adsorption capacity of 6.5247 µmol/g, demonstrating high selectivity sorbent for its template molecule. Calibration curve analysis indicated a concentration value of 30 μmol/mL. The MIP-SPE method was applied to pharmaceutical samples, achieving a detection limit of 0.21 µmol/mL. Drug recovery varied between 91.28 and 96.57 % by employing this method., These outcomes proved the viability of this optimized MIP-SPµE.
Interactions of Interferons and SARS-CoV-2 Antibodies With Type 2 Diabetes
Type 2 diabetes mellitus (T2DM), clinically depicted by insulin resistance and long-standing hyperglycemia, predisposes to infections and is further exacerbated in COVID-19 patients, thereby resulting in an increased risk of severe outcomes. The main objectives of this study were to evaluate type 2 diabetes and non-diabetic patients diagnosed with COVID-19 and compare them with control samples for levels of INF-α, INF-β, and SARS-CoV-2 antibodies (IgM/IgG). The study aims to determine the impact of type 2 diabetes on the immune response against SARS-CoV-2 and to understand which immunodeficiency could explain the poor prognosis in diabetic patients. A total number of 430 nasal swabs were collected from patients in Kirkuk between January 1, 2023, and June 7, 2023. The patients' ages ranged from (18 - 83) years, and through their polymerase chain reaction (PCR) tests, there were 72 confirmed cases of SARS-CoV-2, of which (51.4%) were males and (48.6%) were females and the majority were elderly. Type 2 diabetes patients were among the confirmed cases, with 43 patients and 29 non-diabetics. Blood samples were taken from these individuals and distributed into two tubes: one containing EDTA for testing glycated haemoglobin and the other containing gel for immunological studies using an ELISA device that measures the levels of IgG, IgM, INF-α, and INF-β. Immunological analysis showed that type 1 interferons were significantly less abundant in diabetic and non-diabetic patients compared to control samples. However, the antibody response, especially in terms of IgG and IgM levels, was significantly reduced in diabetic patients compared to non-diabetic individuals. This suggests that type 2 diabetes reduces the immune response in patients infected with SARS-CoV-2. This study suggests that type 2 diabetes is associated with reducing the immune cell response to SARS-CoV-2, as supported by lower levels of antibodies and type 1 interferons among the diabetic groups.
Photo-Thermal Conversion Properties of Selective Coatings with Aluminium and Nickel Powders Additives
Efficient solar energy harvesting through selective absorber coatings is critical for advancing sustainable thermal applications, such as domestic hot water production and water purification. Enhancing photo-thermal conversion while maintaining durability and ease of fabrication remains a challenge. To address this, a composite selective coating was developed by decorating a heat-resistant paint with aluminium and nickel particles, applied via air-spraying on the base paint layer. The coatings were characterized structurally, morphologically, and compositionally using optical microscopy, field-emission electron microscopy, UV-Vis spectroscopy, energy dispersive X-ray analysis, and elemental mapping. Photo-thermal conversion performance was evaluated by measuring solar absorbance and the maximum substrate temperature under solar irradiation using a flat-plate collector setup. The study correlates the photo-thermal conversion with the coatings’ structural and compositional features. Notably, the coating decorated with nickel particles achieved a maximum solar absorbance of 96.07%, enabling substrate temperatures exceeding the boiling point of water without the need for antireflection coatings. The fabrication method and superior photo-thermal properties position this composite coating as a promising candidate for domestic hot water generation and water purification applications, outperforming conventional selective coatings regardless of collector geometry.
Cytotoxic Effect of Ethyl Acetate Fraction from the Aerial Parts of Jatropha Integerrima on the B16 Melanoma Cell
One plant with considerable therapeutic promise is Jatropha integerrima (J. integerrima ), which belongs to the Euphorbiaceae family. This study aimed to assess the cytotoxic effects on the (B16) melanoma cell line of ethyl acetate fraction obtained from the aerial parts of J. integerrima cultivated in Iraq, with six concentrations (200, 100, 50, 25, 12.5, and 6.25 µg/ml). It has drawn interest due to its possible cytotoxic effects on several cancer cell types. The bioactive chemicals responsible for the observed cytotoxic activity were analyzed qualitatively and quantitatively using High-Performance Liquid Chromatography (HPLC) on the ethyl acetate fraction. The cytotoxicity of the fraction was evaluated with the 3- [4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay. Five polyphenolic components classified as phenolic acids and flavonoids were found by phytochemical study of the J. integerrima ethyl acetate fraction. The ethyl acetate fraction with a high concentration of polyphenolic constituents showed the highest inhibition rate of 88.00% on the skin cancer (B16) cell line at a concentration of 200 µg/ml, with a significant difference as compared to the control sample during the 72-hour exposure period. Also, the values of half-maximal inhibitory concentration (IC50) of the fraction against the B16 cell lines were 27.35 µg/ml. J. integerrima plant has promising effects on cancerous lines, which calls for more in vitro and in vivo research.
Spatial Analysis of the Vegetation Condition Index of Al-Hamdania District by Remote Sensing Dataset
Drought is a natural hazard that occurs as a result of decreased rainfall and water storage. It has a significant impact on the agriculture sector. In this paper, monitoring the drought in the Al-Hamdaiya district located east of Mosul city in the Nineveh Governorate, Northern Iraq, was performed for years 2017, 2018, 2019, 2022, and 2024 by integrating remotely sensed data and geographic information systems (GIS). Spatial and temporal distribution changes of the drought phenomenon for the study area were verified by Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI) using Landsat 8 (Operational Land Imager: OLI) images during April month. The results indicated that the study area experienced relatively no drought between 2019 and 2024. However, there was a significant increase in drought conditions during 2017, 2018, and 2022. The percentage of drought-free areas fluctuated between 11.73-91.58% from 2017-2024. Among the drought categories, extreme and moderate drought accounted for the largest percentages, followed by severe and mild drought.
B-cell Lymphoma 9 (BCL9) Gene Methylation as a Biomarker for Gastrointestinal Diseases and Gastric Cancer Risk
In this study, the link between bacterial infection and BCL9 gene methylation was examined, which is crucial to cancer formation. Also, it examined patients' gene methylation levels for stomach ulcers, gastritis [acute and chronic], and duodenal ulcers and cancer risk. Using MS-RT-PCR, BCL-9 methylation was associated more strongly with clinical variables. Substantial differences in BCL-9 methylation between patients and controls (median 1.368, Interquartile Range [0.912-1.468] vs. 1.001, [0.861-1.211], p<0.05). Interestingly, males had substantially greater BCL-9 methylation levels than females (median 1.186, Interquartile Range [1.139-1.308] vs. 0.986, Interquartile Range [0.875-1.150], p<0.05). A significant difference was observed in BCL-9 methylation between acute and chronic gastritis patients (median 1.213, Interquartile Range [1.083-1.378] vs. 1.013, Interquartile Range [0.855-1.130], p<0.05), suggesting that chronic inflammation may impact BCL-9 methylation patterns. BCL-9 methylation was strongly linked with treatment status (r= 0.293, p<0.01). BCL-9 methylation was linked to gastrointestinal diseases such as chronic gastritis. This strongly suggests that BCL9 gene methylation can be detected early. This evidence can be utilized to create cancer treatment and prevention medicine.