Evidence map›Paper›PMID 37159949›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2023

A Computationally Assisted Approach for Designing Wearable Biosensors toward Non-Invasive Personalized Molecular Analysis.

Daniel Mukasa, Minqiang Wang, Jihong Min, Yiran Yang, Samuel A Solomon, Hong Han, Cui Ye, Wei Gao

Open access · greenAbstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
7.0field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 64 citations in OpenAlex.

  1. Pooled it
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  9. Advances in 2D materials for wearable biomonitoring.Materials science & engineering. R, Reports : a review journal · 2025
    Article
  10. Article
  11. Flexible Optoelectronic Hybrid Microfiber Long-period Grating Multimodal Sensor.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
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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

8 authors at 1 institution in 1 country.

Daniel MukasaAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA.
Minqiang WangAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA.
Jihong MinAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA.
Yiran YangAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA.
Samuel A SolomonAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA.
Hong HanAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA.
Cui YeAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA.
Wei GaoAndrew and Peggy Cherng Department of Medical Engineering, Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA, 91125, USA.ORCID https://orcid.org/0000-0002-8503-4562
California Institute of Technology · US

Funding

Laser-Engraved Wearable Sweat Sensors to Detect and Monitor Cardiometabolic DiseaseR01HL155815 · NHLBI · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI GAO, WEI · 2021 to 2025
$2.0M
Cutaneous uric acid and metabolite monitoring to improve individual response to pharmaceutical and dietary treatment in patients with goutR21DK132666 · NIDDK · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI FITZGERALD, JOHN D, GAO, WEI · 2022 to 2023
$461k
NHLBI NIH HHS R01 HL155815NIDDK NIH HHS R21 DK132666NIH HHS R01HL155815NIH HHS R21DK13266
6 · The paper itself

Abstract

Wearable sweat sensors have the potential to revolutionize precision medicine as they can non-invasively collect molecular information closely associated with an individual's health status. However, the majority of clinically relevant biomarkers cannot be continuously detected in situ using existing wearable approaches. Molecularly imprinted polymers (MIPs) are a promising candidate to address this challenge but haven't yet gained widespread use due to their complex design and optimization process yielding variable selectivity. Here, QuantumDock is introduced, an automated computational framework for universal MIP development toward wearable applications. QuantumDock utilizes density functional theory to probe molecular interactions between monomers and the target/interferent molecules to optimize selectivity, a fundamentally limiting factor for MIP development toward wearable sensing. A molecular docking approach is employed to explore a wide range of known and unknown monomers, and to identify the optimal monomer/cross-linker choice for subsequent MIP fabrication. Using an essential amino acid phenylalanine as the exemplar, experimental validation of QuantumDock is performed successfully using solution-synthesized MIP nanoparticles coupled with ultraviolet-visible spectroscopy. Moreover, a QuantumDock-optimized graphene-based wearable device is designed that can perform autonomous sweat induction, sampling, and sensing. For the first time, wearable non-invasive phenylalanine monitoring is demonstrated in human subjects toward personalized healthcare applications.

Indexed as

Biosensing TechniquesGraphiteWearable Electronic DevicesHumansMolecular Docking SimulationSweatGraphitedensity functional theorygraphenemolecularly imprinted polymerssweatwearable sensors

Identifiers

PMID37159949
PMCPMC10529901
OpenAlexW4376108714

What OpenQuestion holds

Textmetadata
LicenceTDM
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.