SOUTHERN JOURNAL OF SCIENCES

Background: A crucial aspect of electrochemical enzymatic biosensor development is the immobilization of the enzymes, as it directly influences the sensitivity of the bioelectrode. Among the different methods used to incorporate enzymes on the surface of the transducers, layer-by-layer (LbL) self-assembly based on electrostatic interaction with polyelectrolytes of opposite charge stands out due to its simplicity and reproducibility. Aims: The aim of the work was to develop an electrochemical glucose biosensor by LbL assembly of a new functionalized chitosan polycation and the enzyme glucose oxidase (GOx). Methods: Chitosan was chemically functionalized with glucose by the Maillard reaction. The resulting polycation, named G-Chit, is soluble in the medium compatible with the enzyme. The bioelectrode was obtained by alternating adsorption of G-Chit and GOx onto carbon paste electrodes. By selecting the number of bilayer of G-Chit/GOX, the enzyme concentration, and the pH, the electroanalytical performance of the biosensor was optimized. The electrochemical responses were characterized by cyclic voltammetry and chronoamperometry. Results: Under optimized experimental conditions, the biosensor exhibited a sensitivity of (0.81 ± 0.03) µA mM-1 in a glucose concentration range of (0.18 to 1.75) mM. Discussion: Results indicated that catalytic response increases both with the number of G-Chit/GOx bilayers and the enzyme concentration, obtaining the best responses for 3 bilayers and 2 mg mL-1, respectively, while the optimum working pH value was 7.0. Conclusions: The analytical response of the biosensor was tested in milk samples with negligible matrix effects, suggesting a potential application in other dairy products. Results show that G-Chit appears promising for the immobilization of enzymes.

Background: COVID-19, caused by SARS-CoV-2, has unresolved mortality risk factors and clinical course, highlighting the need for further research. Aims: The study aimed to asses D-dimer and C-Reactive Protein (CRP) as the risk factors for severity covid-19 and who are less capable of surviving. Methods: A retrospective study conduct of COVID-19 in adult inpatients aged >20 at Al-sadder and Alamal Hospital in Iraq. Demographics, clinical trials, treatments, and viral RNA samples were analyzed. The study involved 100 patients, with 67 discharged and 33 hospitalized died. The majority of the participants 45% were aged < 40, but 55% were aged >40 years. Results: A significant and 57% were male 37(55.2%) Survivor vs. 20 (60.6%) non-survivor, p=0.024), more than 43% were female (30(44.8%) Survivor vs. 13(39.4%) non-survivor, p=0.010. Patients had underlying comorbidities (66%), survivor 37(55%), and non-survivor 29(87%). The most prominent comorbidity in non-survivors more than survivors was diabetic mellitus 85%, asthma 58%, stroke 48%, renal failure 42%, heart strake 33%, and hypertension 18%. The study found significant differences in WBC, lymphocyte count, D-dimer, Ferritin, CRP, and LDH levels in non-survivors compared to survivor patients, with a positive correlation between D- dimer and these parameters. The ROC analysis curve showed CRP with a high AUC of 80.2%, 87.9% sensitivity, and 37.3% specificity, while D-dimer and LDH had AUCs of 0.74.9 and 70%, respectively. Discussion: The study found that older age, higher d-dimer, ferritin, CRP, and LDH are associated with disease severity and higher mortality risk in adult COVID-19 patients. Conclusions: These biomarkers could aid in early detection of disease progression signs and better patient management

Background: This paper presents a straightforward and intuitive method for interactive 3D reconstruction and Direct Linear Transformation (DLT) camera calibration using a single image of a structured scene with known object dimensions. The method relies on manual registration of pairs of points on both the image and the terrain, allowing for precise alignment and calibration. Aim: By utilizing this method, users can easily reconstruct 3D scenes and calibrate cameras without the need for complex algorithms or extensive computational resources. Our approach offers a user-friendly solution for 3D reconstruction and camera calibration, making it accessible to a wider audience and applicable in a range of fields such as computer vision, augmented reality, and virtual reality. Methods: This work primarily focuses on the determination of the projection matrix, which plays a crucial role in mapping 3D points onto a 2D image plane. The projection matrix encapsulates both the intrinsic parameters of the camera (such as focal length and optical center) and the extrinsic parameters (such as camera position and orientation in the world coordinate system). By accurately determining the projection matrix, we can effectively project 3D points onto the 2D image plane, enabling tasks like 3D reconstruction, camera localization, and augmented reality applications. Results: We present experimental results obtained from testing the method on an image of a known object, demonstrating its effectiveness and accuracy in producing realistic 3D reconstructions. Discussion: The method's reliance on manual registration of point pairs allows for precise alignment and calibration without the need for complex algorithms or extensive computational resources. This user-friendly approach makes 3D reconstruction and camera calibration accessible to a wider audience and applicable in various fields. Conclusions: Overall, our approach offers a practical and accessible solution for 3D reconstruction and camera calibration, expanding the potential applications in computer vision, augmented reality, and virtual reality.