Advancing Genetic Disorder Detection: Integrating Nanomaterial-Enhanced Biosensors with Genetic Markers
Genetic disorders pose significant challenges in health care because of the more nuanced and costly methods that prolong patient treatment and recovery times. In addition, to ensure a more accurate diagnosis, the process for the detection of this disease can be quite complex and requires excessive testing and counseling, such as hereditary testing. Given these challenges, a new option has arisen in recent decades: nanomaterial-enhanced biosensors. These diagnostic methods are cutting edge and stand out from traditional methods in many areas, some of which include sensitivity, selectivity, and stability. Among other nanomaterials, gold nanoparticles (AUNPs), carbon nanotubes (CNTs), graphene (GR), and quantum dots (QDs) stand out in terms of their performance metrics and are the most promising for the field. Thus, they are examined in depth in this paper. AUNPs enable visible color changes for genetic disorder detection through DNA hybridization, CNTs have high sensitivity and conductivity for detecting genetic mutations, GR provides exceptional electrical conductivity and biocompatibility for various biosensing utilizations, and QDs allow for precise and accurate diagnostics owing to their light-emitting properties. Nanomaterial biosensor technology has greatly improved in the field of genetics, including innovations in wireless technology and advancements in faster and more specific disease detection. These findings have helped significantly improve the diagnosis of health conditions. Even with all of these benefits, there are still issues with sensitivity, stability, biocompatibility, nonspecific binding, a low dynamic range, and high costs. Other major obstacles are ethical concerns, such as data privacy. Nanomaterial-based biosensors undoubtedly can change the game in regard to diagnosing and treating genetic conditions, but additional research must be done to improve the cost, applicability, and reliability.
Authors
- D. B. Niranjan
- Tanushri Talla
- Hiteshree Dirisala
- Sanjay Gadadas
- Nitya Mandowara
- Snigdha Sujith
Institutions
- Forsyth County Schools (US)
- Morristown High School (US)
- Windsor University School of Medicine (KN)
- American Dairy Science Association (US)
- Brunswick (United States) (US)
- Manufacturing Advocacy & Growth Network (United States) (US)
Publication Details
- Journal
- Journal of Knowledge Learning and Science Technology ISSN 2959-6386 (online)
- Published
- 2024-09-03
- DOI
- https://doi.org/10.60087/jklst.v3.n4.p57
- Citations
- 1
- Primary Topic
- Advanced biosensing and bioanalysis techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.23