Evidence map›Paper›PMID 37754113›Full record

ArticleBiosensors2023

Protein Identification and Quantification Using Porous Silicon Arrays, Optical Measurements, and Machine Learning.

Simon J Ward, Tengfei Cao, Xiang Zhou, Catie Chang, Sharon M Weiss

Abstract read
PubMed Full text at PMC Publisher
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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

5 authors.

Simon J WardDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Tengfei CaoInterdisciplinary Material Science Program, Vanderbilt University, Nashville, TN 37235, USA.
Xiang ZhouDepartment of Chemistry, Vanderbilt University, Nashville, TN 37235, USA.ORCID 0000-0002-9527-6338
Catie ChangDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA.
Sharon M WeissDepartment of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA.ORCID 0000-0003-2252-3104

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We report a versatile platform based on an array of porous silicon (PSi) thin films that can identify analytes based on their physical and chemical properties without the use of specific capture agents. The ability of this system to reproducibly classify, quantify, and discriminate three proteins separately is demonstrated by probing the reflectance of PSi array elements with a unique combination of pore size and buffer pH, and by analyzing the optical signals using machine learning. Protein identification and discrimination are reported over a concentration range of two orders of magnitude. This work represents a significant first step towards a low-cost, simple, versatile, and robust sensor platform that is able to detect biomolecules without the added expense and limitations of using capture agents.

Indexed as

Biosensing TechniquesMachine LearningProteinsSiliconPorosityProteinsSiliconbiosensingdimensionality reductionelectronic noseslinear discriminant analysismachine learningpoint-of-careporous siliconprincipal component analysissensor arraysupport vector machines

Identifiers

PMID37754113
PMCPMC10526835

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.