Evidence map›Paper›PMID 37698743›Full record

ArticleMikrochimica acta2023

Ingestible pH sensing device for gastrointestinal health monitoring based on thread-based electrochemical sensors.

Cihan Asci, Atul Sharma, Ruben Del-Rio-Ruiz, Sameer Sonkusale

Abstract read
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In one paragraph

Article in Mikrochimica acta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

4 authors.

Cihan AsciDepartment of Electrical and Computer Engineering, Tufts University, 161 College Ave, Medford, 02155, MA, USA.
Atul SharmaDepartment of Electrical and Computer Engineering, Tufts University, 161 College Ave, Medford, 02155, MA, USA.
Ruben Del-Rio-RuizDepartment of Electrical and Computer Engineering, Tufts University, 161 College Ave, Medford, 02155, MA, USA.
Sameer SonkusaleDepartment of Electrical and Computer Engineering, Tufts University, 161 College Ave, Medford, 02155, MA, USA. sameer@ece.tufts.edu.ORCID http://orcid.org/0000-0003-3579-910X

Funding

National Institute of Health R21AI144521National Institute of Health R21DK132314
6 · The paper itself

Abstract

There exists a strong correlation between the pH levels of the gastrointestinal (GI) tract and GI diseases such as inflammatory bowel disease (IBS), ulcerative colitis, and pancreatis. Existing methods for diagnosing many GI diseases predominantly rely on invasive, expensive, and time-consuming techniques such as colonoscopy and endoscopy. In this study, an autonomous ingestible smart biosensing system in a pill format with integrated pH sensors is reported. The smart sensing pills will measure the pH profile as they transit through the GI tract. The data is then downloaded from the pills after they are collected from the feces. The sensor is based on electrodeposited PANI on carbon-coated conductive threads providing high pH sensitivity. Engineering innovations allowed integration of thread-based sensors on 3D-printed pill surfaces with front-end readout electronics, memory, and microcontroller assembled on mm-size circular printed circuit boards. The entire smart sensing pill possesses an overall length of 22.1 mm and an outer diameter of 9 mm. The modular biosensing system allows integration of thread-based biosensors to monitor other biomarkers in GI tract that mitigates the complex sensor fabrication process as well as overall pill assembly.

Indexed as

CarbonGastrointestinal TractElectric ConductivityFecesHydrogen-Ion ConcentrationCarbonGastrointestinal monitoringIngestible devicespH sensorSmart pillSmart suturesSmart threads

Identifiers

PMID37698743

What OpenQuestion holds

Textmetadata
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.