Evidence map›Paper›PMID 33718694›Full record

ReviewACS omega2021

Next-Generation Continuous Metabolite Sensing toward Emerging Sensor Needs.

Ashlesha Bhide, Antra Ganguly, Tejasvi Parupudi, Mohanraj Ramasamy, Sriram Muthukumar, Shalini Prasad

Open access · goldAbstract readReview
In one paragraph

Review in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

18 citing papers in PubMed, 40 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. Investigation of pH-dependentInternational journal of obesity (2005) · 2025
    Article
  7. Review
  8. Article
  9. Beyond Flexible: Unveiling the Next Era of Flexible Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2024
    Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Review
  17. Article
  18. Digital Phenotyping in Livestock Farming.Animals : an open access journal from MDPI · 2021
    Review
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

6 authors at 2 institutions in 1 country.

Ashlesha BhideDepartment of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States.
Antra GangulyDepartment of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States.
Tejasvi ParupudiDepartment of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States.
Mohanraj RamasamyDepartment of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States.
Sriram MuthukumarEnLiSense LLC, 1813 Audubon Pond Way, Allen, Texas 75013, United States.
Shalini PrasadDepartment of Bioengineering, University of Texas at Dallas, Richardson, Texas 75080, United States.
The University of Texas at Dallas · USNational Audubon Society · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article discusses the emergent biosensor technology focused on continuous biosensing of metabolites by non-invasive sampling of body fluids emphasized on physiological monitoring in mobility-constrained populations, resource-challenged settings, and harsh environments. The boom of innovative ideas and endless opportunities in healthcare technologies has transformed traditional medicine into a sustainable link between medical practitioners and patients to provide solutions for faster disease diagnosis. The future of healthcare is focused on empowering users to manage their own health. The confluence of big data and predictive analysis and the internet of things (IoT) technology have shown the potential of converting the abundant health profile data amassed from medical diagnosis of patients into useable information, whilst allowing caregivers to provide suitable treatment plans. The implementation of the IoT technology has opened up advanced approaches in real-time, continuous, remote monitoring of patients. Wearable, point-of-care biosensors are the future roadmap to providing direct, real-time information of health status to the user and medical professionals in this digitized era.

Identifiers

PMID33718694
PMCPMC7948241
OpenAlexW3131566806

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.