Subash Chandra Bose Gopinath
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Preferred name
Subash Chandra Bose Gopinath
Official Name
Subash Chandra Bose, Gopinath
Alternative Name
Gopinath, S.
Gopinath, S. C.B
Subash Gopinath, C. B.
Subash, Gopinath
Subash C. B. Gopinath
Main Affiliation
Scopus Author ID
7006558013
Researcher ID
D-2953-2015

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Longitudinal Zeolite-Iron Oxide Nanocomposite Deposited Capacitance Biosensor for Interleukin-3 in Sepsis Detection

2021-01-01 , Chen C. , Subash Chandra Bose Gopinath , Anbu P.

Sepsis is an extreme condition involving a physical response to severe microbial infection and causes fatal and life-threatening issues. Sepsis generates during the chemicals release with the immune system into the bloodstream for fighting against an infection, which causes the inflammation and leads to the medical emergency. A complexed longitudinal zeolite and iron oxide nanocomposite was extracted from coal mine fly ash and utilized to improve the surface characteristics of the capacitance biosensor to identify sepsis attacks. Anti-interleukin-3 (anti-IL-3) antibody was attached to the zeolite- and iron oxide-complexed capacitance electrode surface through an amine linker to interact with the sepsis biomarker IL-3. The morphological and chemical components of the nanocomplex were investigated by FESEM, FETEM, and EDX analyses. At approximately 30 nm, the longitudinal zeolite and iron oxide nanocomposite aided in attaining the limit of IL-3 detection of 3 pg/mL on the linear curve, with a regression coefficient (R2) of 0.9673 [y = 1.638x − 1.1847]. A lower detection limit was achieved in the dose-dependent range (3–100 pg/mL) due to the higher amount of antibody immobilization on the sensing surface due to the nanomaterials and the improved surface current. Furthermore, control experiments with relevant biomolecules did not show capacitance changes, and spiked IL-3 in human serum increased capacitance, indicating the specific and selective detection of IL-3. This study identifies and quantifies IL-3 via potentially useful methods and helps in diagnosing sepsis attack.

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Publication

An update on pathogenesis and clinical scenario for Parkinson’s disease: diagnosis and treatment

2023 , Adam Hussaini , Subash Chandra Bose Gopinath , Nor Azizah Parmin , Tijjani Adam , Mohd Khairuddin Md Arshad , Husein Irzaman , Uda Hashim

In severe cases, Parkinson’s disease causes uncontrolled movements known as motor symptoms such as dystonia, rigidity, bradykinesia, and tremors. Parkinson’s disease also causes non-motor symptoms such as insomnia, constipation, depression and hysteria. Disruption of dopaminergic and non-dopaminergic neural networks in the substantia nigra pars compacta is a major cause of motor symptoms in Parkinson’s disease. Furthermore, due to the difficulty of clinical diagnosis of Parkinson’s disease, it is often misdiagnosed, highlighting the need for better methods of detection. Treatment of Parkinson’s disease is also complicated due to the difficulties of medications passing across the blood–brain barrier. Moreover, the conventional methods fail to solve the aforementioned issues. As a result, new methods are needed to detect and treat Parkinson's disease. Improved diagnosis and treatment of Parkinson's disease can help avoid some of its devastating symptoms. This review explores how nanotechnology platforms, such as nanobiosensors and nanomedicine, have improved Parkinson’s disease detection and treatment. Nanobiosensors integrate science and engineering principles to detect Parkinson’s disease. The main advantages are their low cost, portability, and quick and precise analysis. Moreover, nanotechnology can transport medications in the form of nanoparticles across the blood–brain barrier. However, because nanobiosensors are a novel technology, their use in biological systems is limited. Nanobiosensors have the potential to disrupt cell metabolism and homeostasis, changing cellular molecular profiles and making it difficult to distinguish sensor-induced artifacts from fundamental biological phenomena. In the treatment of Parkinson’s disease, nanoparticles, on the other hand, produce neurotoxicity, which is a challenge in the treatment of Parkinson’s disease. Techniques must be developed to distinguish sensor-induced artifacts from fundamental biological phenomena and to reduce the neurotoxicity caused by nanoparticles.

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A Review on Graphene Analytical Sensors for Biomarker-based Detection of Cancer

2024-01-01 , Subash Chandra Bose Gopinath , Ramanathan S. , More M. , Patil K. , Patil S.J. , Patil N. , Mahajan M. , Madhavi V.

The engineering of nanoscale materials has broadened the scope of nanotech-nology in a restricted functional system. Today, significant priority is given to immediate health diagnosis and monitoring tools for point-of-care testing and patient care. Graphene, as a one-atom carbon compound, has the potential to detect cancer biomarkers and its derivatives. The atom-wide graphene layer specialises in physicochemical characteristics, such as improved electrical and thermal conductivity, optical transparency, and increased chemical and mechanical strength, thus making it the best material for cancer biomarker detection. The outstanding mechanical, electrical, electrochemical, and optical properties of two-dimensional graphene can fulfil the scientific goal of any biosensor development, which is to develop a more compact and portable point-of-care device for quick and early cancer diagnosis. The bio-functionalisation of recognised biomarkers can be improved by oxygenated graphene layers and their composites. The significance of graphene that gleans its missing data for its high expertise to be evaluated, including the variety in surface modification and analytical reports. This review provides critical insights into graphene to inspire research that would address the current and remaining hurdles in cancer diagnosis.

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Integration of microfluidic channel on electrochemical-based nanobiosensors for monoplex and multiplex analyses: An overview

2023 , Adam Hussaini , Subash Chandra Bose Gopinath , Mohd Khairuddin Md Arshad , Tijjani Adam , Uda Hashim , Zaliman Sauli , Fakhri Makram A. , Subramaniam Sreeramanan , Chen Yeng , Sasidharan Sreenivasan , Wu Yuan Seng

Background: Microfluidic devices have evolved into low-cost, simple, and powerful analytical tool platforms. Herein, an electrochemically-based microfluidic nanobiosensor array for monoplex and multiplex detection of physiologically relevant analytes is reviewed. Unlike other analyte detection methods, microfluidics-based embedded electrochemical nanobiosensors are portable, custom electrochemical readers for signal reading. Methods: Microfluidic devices and electrochemical sensors can be integrated into monoplex or multiplex systems. The integrated system is simple to use and sensitive, and so has great potential as a powerful tool for profiling immune-mediated treatment responses in real time. It may also be developed further as a point-of-care diagnostic device for conducting near-patient tests using biological samples. Therefore, using mutiplex analysis, a biosensor array may detect multiple analytes in a sample solution and provide different outputs for each analyte. A microfluidic electrochemical nanobiosensor, for example, can detect urine glucose, lactate, and uric acid. The microfluidic array of integrated nanobiosensors and electrochemical sensors enables fast and cost-effective selection of high-quality and statistically significant diagnostic data at the point of care. The multiplex analytical test is an important molecular tool for academic research as well as clinical diagnosis. Although key approaches for analysing numerous analytes have been developed, none of them are suitable for point-of-care diagnostics, especially in situations with limited resources. Significant findings: In this study, monoplex and multiplex microfluidic assays for rapid measurement of single and multiple analytes at the point of care are presented. Since this test can analyse both single and multiple analytes, it is exceptionally specific, easy to use, and inexpensive. The ability of integrated electrochemical-based microfluidic devices with single channel and multiple channels systems to perform monoplex and multiplex analysis simultaneously and independently is the novelty of this review.

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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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