Evidence map›Paper›PMID 34395990›Full record

ArticleACS omega2021

Tuning SLOCK toward Chronic Disease Diagnostics and Management: Label-free Sweat Interleukin-31 Detection.

Sayali Upasham, Shalini Prasad

Open access · goldAbstract read
In one paragraph

Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Sayali UpashamDepartment of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States.
Shalini PrasadDepartment of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States.ORCID https://orcid.org/0000-0002-2404-3801
The University of Texas at Dallas · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SLOCK (sensor for circadian clock) is an electrochemical sweat-based biosensing platform designed for the diagnosis and management of circadian abnormalities. Previously, the SLOCK platform was designed to detect adrenal steroids, cortisol, and DHEA for tracking the circadian rhythm. This work aims at tuning this SLOCK platform toward the detection of the cytokine, interleukin-31, for building a noninvasive, chronic disease diagnostics and management platform. This research provides a detailed characterization of the sensing surface and immunochemistry. The results show that SLOCK has good sensitivity to IL-31 concentrations in synthetic and human sweat. The limit of detection is 50 and 100 pg/mL for synthetic and human sweat, respectively. The dynamic range of the system is 50-1000 pg/mL, which encompasses the physiological ranges of 150-620 pg/mL. This is the first demonstration of sweat-based, label-free, electrochemical detection of IL-31. In addition to this, the data show good correlation (

Identifiers

PMID34395990
PMCPMC8359127
OpenAlexW3189345098

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.