ReviewSensors (Basel, Switzerland)2014
Hybrid integrated label-free chemical and biological sensors.
Review in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Nano-Theranostics for the Sensing, Imaging and Therapy of Prostate Cancers.Frontiers in chemistry · 2022Review
- Handheld plasmonic biosensor for virus detection in field-settings.Sensors and actuators. B, Chemical · 2021Article
- Nanobased Platforms for Diagnosis and Treatment of COVID-19: From Benchtop to Bedside.ACS biomaterials science & engineering · 2021Review
- Review
- Engineering photonics solutions for COVID-19.APL photonics · 2020Review
- VLSI Structures for DNA Sequencing-A Survey.Bioengineering (Basel, Switzerland) · 2020Review
- Plasmon-Coupled Whispering Gallery Modes on Nanodisk Arrays for Signal Enhancements.Scientific reports · 2017Article
- Applications of Optical Microcavity Resonators in Analytical Chemistry.Annual review of analytical chemistry (Palo Alto, Calif.) · 2016Article
- Lead-Free Piezoelectric Diaphragm Biosensors Based on Micro-Machining Technology and Chemical Solution Deposition.Sensors (Basel, Switzerland) · 2016Article
- Label-Free Biosensing with High Selectivity in Complex Media using Microtoroidal Optical Resonators.Scientific reports · 2015Article
- Real-time detection of lipid bilayer assembly and detergent-initiated solubilization using optical cavities.Applied physics letters · 2015Article
- Temperature sensor based on a hybrid ITO-silica resonant cavity.Optics express · 2015Article
- Electrochemical processes and mechanistic aspects of field-effect sensors for biomolecules.Journal of materials chemistry. C · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Label-free sensors based on electrical, mechanical and optical transduction methods have potential applications in numerous areas of society, ranging from healthcare to environmental monitoring. Initial research in the field focused on the development and optimization of various sensor platforms fabricated from a single material system, such as fiber-based optical sensors and silicon nanowire-based electrical sensors. However, more recent research efforts have explored designing sensors fabricated from multiple materials. For example, synthetic materials and/or biomaterials can also be added to the sensor to improve its response toward analytes of interest. By leveraging the properties of the different material systems, these hybrid sensing devices can have significantly improved performance over their single-material counterparts (better sensitivity, specificity, signal to noise, and/or detection limits). This review will briefly discuss some of the methods for creating these multi-material sensor platforms and the advances enabled by this design approach.
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.