ReviewBiosensors2023
Advancements in Nanofiber-Based Electrochemical Biosensors for Diagnostic Applications.
Review in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 34 citations in OpenAlex.
- Nanoarchitectonics of aptamer-based electrochemical sensor using electrospun carbon nanofibers and Au nanoparticles for cd (II) analysis.Scientific reports · 2026Article
- Progress on encapsulation and entrapment of enzymes in electrospun nanofibers.Bioprocess and biosystems engineering · 2026Review
- Nanobiosensors for Single-Molecule Diagnostics: Toward Integration with Super-Resolution Imaging.Biosensors · 2025Review
- Graphene-based LSPR sensors enable polarization-independent detection of CEA antigens.Scientific reports · 2025Article
- Multifunctional Conductive Nanofibers for Self-Powered Glucose Biosensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- State of the art and future research directions of materials science applied to electrochemical biosensor developments.Analytical and bioanalytical chemistry · 2024Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biosensors are analytical tools that can be used as simple, real-time, and effective devices in clinical diagnosis, food analysis, and environmental monitoring. Nanoscale functional materials possess unique properties such as a large surface-to-volume ratio, making them useful for biomedical diagnostic purposes. Nanoengineering has resulted in the increased use of nanoscale functional materials in biosensors. Various types of nanostructures i.e., 0D, 1D, 2D, and 3D, have been intensively employed to enhance biosensor selectivity, limit of detection, sensitivity, and speed of response time to display results. In particular, carbon nanotubes and nanofibers have been extensively employed in electrochemical biosensors, which have become an interdisciplinary frontier between material science and viral disease detection. This review provides an overview of the current research activities in nanofiber-based electrochemical biosensors for diagnostic purposes. The clinical applications of these nanobiosensors are also highlighted, along with a discussion of the future directions for these materials in diagnostics. The aim of this review is to stimulate a broader interest in developing nanofiber-based electrochemical biosensors and improving their applications in disease diagnosis. In this review, we summarize some of the most recent advances achieved in point of care (PoC) electrochemical biosensor applications, focusing on new materials and modifiers enabling biorecognition that have led to improved sensitivity, specificity, stability, and response time.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.