Tijjani Adam
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Preferred name
Tijjani Adam
Official Name
Tijjani, Adam
Alternative Name
Adam, T.
Adama, Tijjani
Adam, Tijjani
Adam, Tijjan
Tijjani, A.
Main Affiliation
Scopus Author ID
55074964600
Researcher ID
AAH-5534-2019

Research Output
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Selective detection of alpha synuclein amyloid fibrils by faradaic and non-faradaic electrochemical impedance spectroscopic approaches

2025-02 , Hussaini Adam , Subash Chandra Bose Gopinath , Hemavathi Krishnan , Tijjani Adam , Makram A. Fakhri , Evan T. Salim , A. Shamsher , Sreeramanan Subramaniam , Yeng Chen

This study utilized faradaic and non-faradaic electrochemical impedance spectroscopy to detect alpha synuclein amyloid fibrils on gold interdigitated tetraelectrodes (AuIDTE), providing valuable insights into electrochemical reactions for clinical use. AuIDE was purchased, modified with zinc oxide for increased hydrophobicity. Functionalization was conducted with hexacyanidoferrate and carbonyldiimidazole. Faradaic electrochemical impedance spectroscopy has been extensively explored in clinical diagnostics and biomedical research, providing information on the performance and stability of electrochemical biosensors. This understanding can help develop more sensitive, selective, and reliable biosensing platforms for the detection of clinically relevant analytes like biomarkers, proteins, and nucleic acids. Non-faradaic electrochemical impedance spectroscopy measures the interfacial capacitance at the electrode–electrolyte interface, eliminating the need for redox-active species and simplifying experimental setups. It has practical implications in clinical settings, like real-time detection and monitoring of biomolecules and biomarkers by tracking changes in interfacial capacitance. The limit of detection (LOD) for normal alpha synuclein in faradaic mode is 2.39-fM, The LOD for aggregated alpha synuclein detection is 1.82-fM. The LOD for non-faradaic detection of normal alpha synuclein is 2.22-fM, and the LOD for nonfaradaic detection of aggregated alpha synuclein is 2.40-fM. The proposed EIS-based AuIDTEs sensor detects alpha synuclein amyloid fibrils and it is highly sensitive.

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Cyclic and differential pulse voltammetric measurements on fibrils formation of alpha synuclein in Parkinson's disease by a gold interdigitated tetraelectrodes

2024-01-01 , Adam Hussaini , Subash Chandra Bose Gopinath , Krishnan Hemavathi , Tijjani Adam , Mohammed M. , Perumal V. , Fakhri M.A. , Salim E.T. , Raman P. , Subramaniam, Sreeramanan , Chen Y. , Sasidharan S.

Parkinson's disease is a neurodegenerative disorder characterized by the aggregation and deposition of alpha-synuclein protein, which are pathological hallmarks. To understand the fibril formation of alpha-synuclein in Parkinson's disease, this study uses cyclic and differential pulse voltammetric measurements. These measurements analyze the electrochemical properties and behavior of alpha-synuclein during its fibril formation process. By applying a potential sweep or pulse to the alpha-synuclein sample, it is possible to gain insights into its redox activity and structural changes during fibril formation. This could lead to the development of therapeutic strategies to prevent or disrupt this pathological event in Parkinson's disease. To detect Parkinson's disease, a 15 nm sized gold conjugated antibody was used as the probe and seeded on gold interdigitated tetraelectrodes (AuIDTE). Alpha synuclein variations (fibriled and non-fibriled) were detected using phosphate-buffer saline and glycine buffer based on cyclic voltammetry and differential pulse voltammetry techniques. Discriminated by Tau protein measurement that was employed as a control. The linear regression for detecting alpha synuclein aggregation using differential pulse voltammetry was R2 = 0.9987 [y = 9E-06x - 4E-07], with a limit of detection of 10 aM, on a linear range of 1 aM-1 pM. Cyclic voltammetry determined the limit of detection of aggregated alpha synuclein to be 100 aM, with a linear relationship of R2 = 0.9939 [y = 7E-06x - 2E-06]. The sensor has excellent analytical performance in terms of detection limit, sensitivity, selectivity, repeatability, and stability.

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