Evidence map›Paper›PMID 34900090›Full record

ArticleIEEE photonics journal2022

FPGA Integrated Optofluidic Biosensor for Real-Time Single Biomarker Analysis.

Mohammad Julker Neyen Sampad, Md Nafiz Amin, Aaron R Hawkins, Holger Schmidt

Open access · goldAbstract read
In one paragraph

Article in IEEE photonics journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 34% of its field
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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Microacoustic Metagratings at Ultra-High Frequencies Fabricated by Two-Photon Lithography.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    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 at 2 institutions in 1 country.

Mohammad Julker Neyen SampadSchool of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064 USA.ORCID 0000-0003-0725-9747
Md Nafiz AminSchool of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064 USA.ORCID 0000-0001-5636-2471
Aaron R HawkinsECEn Department, Brigham Young University, Provo, UT 84602 USA.ORCID 0000-0002-3882-0771
Holger SchmidtSchool of Engineering, University of California Santa Cruz, Santa Cruz, CA 95064 USA.ORCID 0000-0003-2340-8108
University of California, Santa Cruz · USBrigham Young University · US

Funding

Multiplexed, Non-Amplified, Nucleic Acid-Based Identification of Multidrug Resistant Pathogens Using an Integrated Optofluidic PlatformR01AI116989 · NIAID · BRIGHAM YOUNG UNIVERSITY · PI HAWKINS, AARON R., PITT, WILLIAM G · 2015 to 2019
$5.4M
Nanopore-based multi-target analysis of Zika virus infectionR01EB028608 · NIBIB · UNIVERSITY OF CALIFORNIA SANTA CRUZ · PI SCHMIDT, HOLGER · 2019 to 2022
$2.7M
NIAID NIH HHS R01 AI116989NIBIB NIH HHS R01 EB028608
6 · The paper itself

Abstract

Integrated optofluidic biosensors can fill the need for sensitive, amplification-free, multiplex single molecule detection which is relevant for containing the spread of infectious diseases such as COVID-19. Here, we demonstrate a rapid sample-to-answer scheme that uses a field programmable gate array (FPGA) to enable live monitoring of single particle fluorescence analysis on an optofluidic chip. Fluorescent nanobeads flowing through a micro channel are detected with 99% accuracy and particle concentrations in clinically relevant ranges from 3.4×10

Indexed as

anti-resonant reflecting optical waveguide (ARROW)biophotonicsfield programmable gate array (FPGA)Optofluidicsreal-timesingle molecule detection

Identifiers

PMID34900090
PMCPMC8658630
OpenAlexW3212148945

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.