Mohamed Elshaikh Elobaid Said Ahmed
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Preferred name
Mohamed Elshaikh Elobaid Said Ahmed
Official Name
Mohamed Elshaikh Elobaid , Said Ahmed
Alternative Name
Ahmed, Mohamed Elshaikh Elobaid Said
Said Ahmed, Mohamed Elshaikh Elobaid
Elobaid, Mohamed Elshaikh
Main Affiliation
Scopus Author ID
57190012447
Researcher ID
R-7502-2019

Research Output
Now showing 1 - 2 of 2
  • Publication
    AI-optimized electrochemical aptasensors for stable, reproducible detection of neurodegenerative diseases, cancer, and coronavirus
    (Elsevier, 2025)
    Amira Elsir Tayfour Ahmed
    ;
    Th.S. Dhahi
    ;
    Tahani A. Attia
    ;
    Fawzia Awad Elhassan Ali
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Tijjani Adam
    ;
    Subash Chandra Bose Gopinath
    AI-optimized electrochemical aptasensors are transforming diagnostic testing by offering high sensitivity, selectivity, and rapid response times. Leveraging data-driven AI techniques, these sensors provide a non-invasive, cost-effective alternative to traditional methods, with applications in detecting molecular biomarkers for neurodegenerative diseases, cancer, and coronavirus. The performance metrics outlined in the comparative table illustrate the significant advancements enabled by AI integration. Sensitivity increases from 60 to 75 % in ordinary aptasensors to 85–95 %, while specificity improves from 70-80 % to 90–98 %. This enhanced performance allows for ultra-low detection limits, such as 10 fM for carcinoembryonic antigen (CEA) and 20 fM for mucin-1 (MUC1) using Electrochemical Impedance Spectroscopy (EIS), and 1 pM for prostate-specific antigen (PSA) with Differential Pulse Voltammetry (DPV). Similarly, Square Wave Voltammetry (SWV) and potentiometric sensors have detected alpha-fetoprotein (AFP) at 5 fM and epithelial cell adhesion molecule (EpCAM) at 100 fM, respectively. AI integration also enhances reproducibility, reduces false positives and negatives (from 15-20 % to 5–10 %), and significantly decreases response times (from 10-15 s to 2–3 s). These advancements improve data processing speeds (from 10 to 20 min per sample to 2–5 min) and calibration accuracy (<2 % margin of error compared to 5–10 %), while expanding application scope to multi-target biomarker detection. This review highlights how these advancements position AI-optimized electrochemical aptasensors as powerful tools for personalized treatment, point-of-care testing, and continuous health monitoring. Despite a higher cost ($500-$1,500/unit), their enhanced portability and diagnostic performance promise to revolutionize healthcare, environmental monitoring, and food safety, ultimately improving public health outcomes.
  • Publication
    Application of Nanobiosensor engineering in the diagnosis of neurodegenerative disorders
    (Elsevier, 2024)
    Thikra S. Dhahi
    ;
    Alaa Kamal Yousif Dafhalla
    ;
    A. Wesam Al-Mufti
    ;
    Mohamed Elshaikh Elobaid Said Ahmed
    ;
    Tijjani Adam
    ;
    Subash Chandra Bose Gopinath
    Neurodegenerative diseases like Alzheimer's disease and Parkinson's disease are hard to diagnose and treat early. They are characterised by progressive loss of neuronal function and structure leading to crippling cognitive, motor and psychiatric impairments. In recent years, nanobiosensor engineering has emerged as a promising way to address the limitations of traditional diagnostic methods for neurodegenerative diseases. Nanobiosensors which combine nanotechnology and biosensing principles can detect disease specific biomarkers with high sensitivity and specificity to enable early and accurate diagnosis. One of the key advantages of nanobiosensors in diagnosing neurodegenerative diseases is their ability to detect and quantify specific proteins or molecules that are biomarkers for these conditions. For example, accumulation of amyloid beta peptides and hyperphosphorylation of tau protein are hallmarks of Alzheimer's disease. Nanobiosensors can be designed to selectively bind to these biomarkers providing rapid and non-invasive method for early disease detection. This enables more targeted and personalized treatment approaches. Furthermore, nanomaterials have shown potential in biosensing applications due to their unique physical, optical, and electrical properties. Their small size, large surface-to-volume ratio, and tunable properties enable them to interact with biological molecules in remarkable ways. One notable property is their ability to be functionalized with molecular beacons, reporter molecules, pacification layers, and targeting biomolecules, creating highly sensitive and specific biofunctional nanoprobes. This review aims to explore the promising role of nanobiosensor engineering in the early diagnosis and management of neurodegenerative disorders.