Pure Sciences International Journal of Kerbala

Natural radioactivity levels of 226Ra, 232Th, and 40K were assessed in 10 tap water samples collected from different schools in Karbala govenorate, as well as 5 commercial bottled drinking water samples. The activity concentrations were measured using gamma spectrometry with a NaI(Tl) 3"×3" detector equipped with a specially designed shield. In tap water samples, the activity concentrations of 226Ra, 232Th, and 40K ranged from <0.063 to 0.817, <0.067 to 0.493, and <0.117 to 9.896 Bq·L⁻¹, respectively. For bottled water, 226Ra and 232Th concentrations were below the Minimum Detectable Actictivity (MDA), while 40K ranged from <0.117 to 8.180 Bq·L⁻¹. Overall, tap water samples exhibited higher concentrations than bottled water. The measured values for tap water were within the ranges reported in the literature for other countries. Health implications were estimated by calculating the annual effective dose received by school-age children due to ingestion of radionuclides. The average values of annual effective dose in tap and bottled water were 85.05 and 36.40 μSv·y-1 respectively. All calculated doses were below the global mean level of 100 μSv·y-1, as reported by World Health Organization (WHO). It is therefore concluded that both tap water and bottled water consumed in schools of Karbala Governorate are radiologically safe and pose no significant health hazard to the public.

Two types of hybrid SERS sensors, have been synthesized through integrated Au nanoparticles on horizontal oriented (HO)-Si pillars and Silicon quantum dots (SiQDs) nanostructures substrates . Aggressive Laser-induced etching process ; at high laser intensity of 450, and 550 mW/cm2 and 405 nm wavelength, was used to create the HO-Si pillars and SiQDs substrates respectively . The hybrid SERS sensors have been synthesized with simple, easy –to- work and very low cost dipping technique of HO-Si pillars and SiQDs based-substrates in HAuCl4 solution. The growth mechanism of Au nanoparticles has shown clear depending on the morphology of the based- substrate. In the case of HO-Si pillars, the creation of Au nanoparticles essentially happened at the surface of Si substrate rather than the surface boundaries of HO-Si pillars, whereas with using SiQDs substrate, the deposition of Au nanoparticles mostly occurred around the SiQDs substrate. The better performance of hybrid SERS sensor of higher development factor, with minimum LOD and outstanding reproducibility has been attained for SiQDs sensor rather than that of HO-Si pillars sensor of about (7.46 × 108) , (9*10 -14 M) and (4%), respectively.

After determining the date and location of sample collection, this study examined the external morphology of the species. Samples were collected from the Al-Hussainiya River, located north of Karbala Governorate. The genus Eudiaptomus vulgaris is widely distributed across various aquatic systems. Species identification was based on morphological characteristics of the body, including overall shape and specific diagnostic features such as the number and structure of antennae, the arrangement of spines on the basal segment of the antennule, the morphology of the fifth peduncle, and the structure of the caudal branches. This study aims to represent one of the few detailed taxonomic studies on members of the order Calanoida in Iraq, contributing to the enrichment of biodiversity records for freshwater zooplankton. Moreover, the precise description of this species provides a valuable reference for future ecological assessments and water quality monitoring, as such organisms serve as important bio indicators in aquatic ecosystems. Due to the scarcity of detailed taxonomic research on species of the order Calanoida, this study highlights the importance of clarifying their taxonomic status. This was achieved by examining their external morphology, diagnosing and describing their structures, and providing illustrative drawings of their body parts.

Smart polymers have emerged as pivotal tools in the advancement of modern nanomedicine due to their stimuli-responsive behavior, biocompatibility, and functional versatility. These materials can intelligently respond to internal and external cues such as pH, temperature, enzymes, and oxidative stress, making them ideal candidates for targeted drug delivery and diagnostic applications. This review explores the mechanisms and classifications of smart polymers, highlighting their roles in cancer therapy and chronic pulmonary diseases. Particular emphasis is placed on their integration into nanocarriers, hydrogels, and responsive implants to overcome physiological barriers and enhance therapeutic efficacy. Furthermore, current clinical trials and preclinical studies are discussed to assess their translational potential. Despite significant progress, challenges related to biocompatibility, tumor penetration, and large-scale manufacturing remain. Future directions suggest the integration of artificial intelligence, personalized medicine, and biosensor technology to accelerate smart polymer innovation. This comprehensive overview underscores the transformative potential of smart polymers in redefining personalized and precision healthcare.

In this research two electrodes were built using the clarithromycin-bromophenol blue ion pair complex in a PVC matrix and the extraction of clarithromycin from Claricide medication. The experimental section relied on using two plasticizers; tri-butyl phosphate and ortho-nitro-phenyl-octyl ether. The results indicated that slopes and linear ranges of the clarithromycin electrodes [C1 and C2] were 55.699 and 53.895 mV/decade and 10-5-10-2 and 7×10-5-10-2 M, respectively. Based on using TBP plasticizer, the best electrode [C1] had a lifetime of 16 days, a 55.699 mV/decade slope, a 0.9995 correlation coefficient, and 9x10-6M detection limit. Therefore, the main findings of this research indicated that, C1 electrode, which demonstrated excellent stability, can be employed to measure the amount of clarithromycin in drug samples. In addition, the separated and mixed methods can be conducted to study the interference measurements in the presence of certain ions, sucrose, and gelatin in order to determine the selectivity coefficient.

In Diabetes mellitus is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. The chronic hyperglycemia of diabetes is associated with long-term damage. Thrombin-Activatable Fibrinolysis Inhibitor(TAFI) is a protein that plays a major role in regulating the analysis of blood clots, It is involved in the fibrinolysis process. The study was designed to study the change concentration of TAFI, Insulin, HOMA-IR, and lipid profile in the T2DM patient in addition to studying the TAFI 1040C>T SNP (rs1926447) gene polymorphism with the development of T2DM complication. Genome study doing by restriction fragment length polymorphism PCR (RFLP-PCR). These parameters included the evaluated of glucose metabolic characteristics (FSG, insulin, HbA1C, HOMA-IR, lipid profile). The expected frequencies, calculated under the assumption of no association, were 47.61for CC, 60.03, CT, and 9.61for TT. TC genotype does not appear a statistically significant linkage to the rise risk of thrombosis, OR(3.272) is and CI (0.4173 to 1.4498), p-value <0.0002 was associated with an increased danger of the thrombosis to three times. frequency of C allele among cases is 43.5%, but it is 69% among controls. Frequency T allele was among cases is 56.5%, whereas it is 31% among controls. The findings of this investigation revealed that there was significant link between the TAFI 1040C>T polymorphism and T2DM complication in Iraqi patients. However, we recommend conducting the study in a larger sample and different sexes to confirm our findings.

Background: Chronic kidney disease (CKD) is an important health problem especially in low resource settings with limited access to sophisticated diagnostic facilities. Biochemical and inflammatory parameters, such as creatinine, urea, uric acid, and CRP, might serve as available alternatives for monitoring of the disease.
Methods: A case–control study was carried out at Al-Sadr Medical City, Kerbala, Iraq, comprising 39 hemodialysis patients and 30 gender- and age-matched healthy controls with chronic renal failure. Serum creatinine, urea, uric acid and CRP levels were determined by standard biochemical methods. The CO25 threshold was determined with receiver-operator curves (ROC) analysis, using SPSS software (version 26) and determining the sensitivity and specificity as well as area under the curve (AUC(
Results: The hemodialysis patients had a significantly higher mean level of creatinine (3.04 ± 1.60 mg.dL-1), urea (178.7 ± 96.0 mg.dL-1), uric acid (8.28 ± 3.39 mg.dL-1), and CRP (20.34 ± 2.17 mg.L-1) than the controls (p < 0.001). There was a strong positive correlation between CRP and uric acid (r = 0.542, p = 0.002) and between CRP and urea (r = 0.54, p = 0.003), while urea correlated with BMI and age (p ≤ 0.005). ROC analysis showed a very good diagnostic accuracy (AUC/0.97–1.00) for all biomarkers, of which CRP and uric acid were essentially informative predictors.
Conclusion: The results emphasize the interplay between inflammatory and metabolic biomarkers in CKD. High CRP and uric acid not only reflect renal function, but also independently predict cardiovascular outcomes. The integration of these low-cost biomarkers in routine care of dialysis patients may aid in stratifying risk among Iraqi patients. These associations need to be verified by larger, prospective studies.

This paper introduces an improvement and generalization of Hadamard inequality by using the spaces of local fractional ????????-normed spaces for 1≤????<∞, after Jacques Hadamard has presented his inequality in 1893 about bound on the determination of matrices by using the length of its column vectors. In addition, it is sometimes called Hemit Hadamard inequality with its convex function .The inequality that had been generalized to higher dimensions of function is bounded and convex domain in Euclidean space of n dimension .

Numerous dosages and formulations have been used in past studies of this ancient herbal sleep aid, valerian, utilizing a range of experimental methods. The purpose of this study is to assess how long-term valerian usage and acupuncture at ST36 affect kidney and liver function, with a focus on alterations in enzyme levels and general organ health. After the plant was ground, 4 g of the resulting powder was weighed and placed in a plastic container. The powder was then mixed with 100 milliliters of distilled water and left to steep for 15 minutes at 100°C. The mixture was then filtered through filter paper. After extracting four grams of the powdered plant material in 100 milliliters of distilled water at 100 degrees Celsius for fifteen minutes, the mixture was filtered. Rats were given the extract (40 mg/mL) orally at a dose of 400 mg/kg body weight (10 mL/kg).Before the experiment started, 32 rats (weighing 200–300 g) were kept in the lab for a week. Rats were housed in cages with free access to food and tap water. The Ethics Committee of Karbala University, Karbala, Iraq, authorized the experimental protocol and methods utilized in this study for the care and use of lab animals. The rats were randomly divided into four groups, each containing eight rats. No significant difference is noticed among study groups with control according to liver and kidney function tests (BUN, AST), except modest elevation of ALP in Valerian with acupuncture. Velerian extract did not significantly cause hepatorenal damage in rats under the study's settings. Biochemical indicators were not significantly changed by acupuncture at ST36, indicating a neutral modulatory impact.

Predicting the age of the brain using MRI is an advanced medical method that is used to diagnose brain diseases and disorders such as Alzheimer's, multiple sclerosis and other neurological diseases. Using this method, brain MRI images are analyzed using advanced algorithms and neural networks to obtain different brain characteristics such as brain volume and cortical thickness. Then, by comparing these features with the MRI imaging data of other patients, the age of the brain is estimated. In this work, used Convolutional Neural Network (CNN) and MRMR feature selection algorithm. In this method, brain MRI images are processed by a convolutional network to extract age-related features, the MRMR algorithm selects the most relevant features, and the brain age is predicted using regression layers. The main contribution of this research is in adding a feature selection layer based on the MRMR feature ranking algorithm among the layers of a deep convolutional network, which has led to the improvement of the performance of the proposed convolutional network. Based on the obtained simulation results, the prediction accuracy of the proposed method for predicting the brain age of people is 90.3%, which has improved compared to the compared works.vements.