Evidence map›Paper›PMID 38131766›Full record

ArticleBiosensors2023

Gradient Guided-Mode Resonance Biosensor with Smartphone Readout.

Ting-Zhou Lin, Cheng-Hao Chen, Yuan-Pei Lei, Cheng-Sheng Huang

Abstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ting-Zhou LinDepartment of Mechanical Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.
Cheng-Hao ChenDepartment of Mechanical Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.
Yuan-Pei LeiDepartment of Mechanical Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.
Cheng-Sheng HuangDepartment of Mechanical Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.

Funding

National Health Research Institutes NHRI-EX111-10921EI
6 · The paper itself

Abstract

Integrating biosensors with smartphones is becoming an increasingly popular method for detecting various biomolecules and could replace expensive laboratory-based instruments. In this work, we demonstrate a novel smartphone-based biosensor system with a gradient grating period guided-mode resonance (GGP-GMR) sensor. The sensor comprises numerous gratings which each correspond to and block the light of a specific resonant wavelength. This results in a dark band, which is observed using a CCD underneath the GGP-GMR sensor. By monitoring the shift in the dark band, the concentration of a molecule in a sample can be determined. The sensor is illuminated by a light-emitting diode, and the light transmitted through the GGP-GMR sensor is directly captured by a smartphone, which then displays the results. Experiments were performed to validate the proposed smartphone biosensor and a limit of detection (LOD) of 1.50 × 10

Indexed as

Biosensing TechniquesSmartphoneLimit of Detectionalbumincreatinineguided-mode resonanceoptical biosensorsmartphone biosensor

Identifiers

PMID38131766
PMCPMC10741440

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.