Background: Lumbar disc degeneration (LDD) is a common musculoskeletal disorder that frequently causes low back pain (LBP). In addition to the discomfort of lower back pain, it can accompany pain in one or both legs. The lumbar spine and sacrum, consisting of five vertebrae and one bone, determine the spine's balance. Microelements are essential in bone metabolism and are associated with the prevention of osteoporosis and the alleviation of musculoskeletal pain. Objectives: To examine the correlation between lumbar spinal surgery and the concentrations of microelements, namely zinc and copper. Methods: A case-control study was conducted in Ghazi Al-Hariri Hospital in Baghdad, Iraq, during the period from October 2023 to January 2024. The study included 120 participants ranging in age from 18 to 70 years. Sixty participants underwent lumbar spine surgery and were diagnosed using X-rays or MRI scans. The other 60 were healthy controls. The zinc (Zn) and copper (Cu) levels in the blood were determined using an atomic absorption spectrometer. The body mass index (BMI) was determined using the formula: BMIg/m2 = weight/height2. Results: The patients had a lower mean zinc level (57.3 ± 14.56 Mmol/L) and a higher mean copper level (106.6 ± 39.41 Mmol/L) in comparison to healthy controls (96.4 ± 17.38 Mmol/L) and (61.0 ± 9.53 Mmol/L), respectively There was a weak relationship and a significant correlation between copper and zinc (r = -0.2). A very strong relationship and a significant correlation between copper and Cu / Zn ratio (r = 0.85) while zinc had a significant very strong correlation relationship with Cu / Zn ratio (r = -0.7) in patients. Conclusion: The present study underscores the noteworthy association between microelements (Cu, Zn) and degenerative lumbar discs, underscoring the significance of pre-operative evaluation in achieving the best possible surgical results. The study has demonstrated the utility of measuring serum zinc level and copper level, especially their link with lumbar disc degeneration (LDD) markers of patients undergoing lumbar spinal surgery.
This paper presents comprehensive analysis and investigation for 1550nm and 1310nm ring optical modulators employing an electro-optic polymer infiltrated silicon-plasmonic hybrid phase shifter. The paper falls into two parts which introduce a theoretical modeling framework and performance assessment of these advanced modulators, respectively. In this part, analytical expressions are derived to characterize the coupling effect in the hybrid phase shifter, transmission function of the modulator, and modulator performance parameters. The results can be used as a guideline to design compact and wideband optical modulators using plasmonic technology
Background: Enforcement of sustainable and green chemistry protocols has seen colossal surge in recent times, the development of an effective, eco-friendly, simple and novel methodologies towards the synthesis of valuable synthetic scaffolds and drug intermediates. Recent advances in technology have now a more efficient means of heating reactions that made microwave energy. Efforts to synthesize novel heterocyclic molecules of biological importance are in continuation. Microwave irradiation is well known to promote the synthesis of a variety of organic and inorganic compounds. The aim of current study was to conceivea mild base mediated preparation of novel Schiff base of 2-Acetylpheno with trimethoprim drug (H2TPBD) and its complexes w
... Show MoreCoupling reaction of 2-amino benzoic acid with 8-hydroxy quinoline gave bidentate azo ligand. The prepared ligand has been identified by Microelemental Analysis,1HNMR,FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (ZnII,CdII and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2]. The prepared complexes have been characterized by using flame atomic absorption, (C.H.N) Analysis, FT-IR and UV-Vis spectroscopic methods as well as conductivity measurements. The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
This work investigates the impacts of eccentric-inclined load on ring footing performance resting on treated and untreated weak sandy soil, and due to the reduction in the footing carrying capacity due to the combinations of eccentrically-inclined load, the geogrid was used as reinforcement material. Ring radius ratio and reinforcement depth ratio parameters were investigated. Test outcomes showed that the carrying capacity of the footing decreases with the increment in the eccentric-inclined load and footing radius ratio. Furthermore, footing tilt and horizontal displacement increase with increasing the eccentricity and inclination angle, respectively. At the same time, the increment in the horizontal displacement due t
... Show MoreCD40 is a type 1 transmembrane protein composed of 277 amino acids, and it belongs to the tumor necrosis factor receptor (TNFR) superfamily. It is expressed in a variety of cell types, including normal B cells, macrophages, dendritic cells, and endothelial cells, as a costimulatory molecule. This study aims to summarize the CD40 polymorphism effect and its susceptibility to immune-related disorders. The CD40 gene polymorphisms showed a significant association with different immune-related disorders and act as a risk factor for increased susceptibility to these diseases.
Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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