Evidence map›Paper›PMID 42645049›Full record

ReviewBiosensors2026

Carbon Nanotube-Based Biosensors for Non-Invasive Biofluid Analysis.

Samriddha Dutta, Ashok Mulchandani

Abstract readReview
In one paragraph

Review in Biosensors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Samriddha DuttaDepartment of Chemical & Environmental Engineering, University of California, Riverside, Riverside, CA 92521, USA.
Ashok MulchandaniDepartment of Chemical & Environmental Engineering, University of California, Riverside, Riverside, CA 92521, USA.ORCID 0000-0002-2831-4154

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon nanotube (CNT)-based biosensors have emerged as promising platforms for non-invasive biofluid analysis because of their high electrical conductivity, large surface area, tunable optical properties, and versatile surface chemistry, enabling miniaturized, flexible sensing devices. Sweat, saliva, tears, and urine are increasingly recognized as attractive alternatives to blood for point-of-care diagnostics because they enable repeated, non-invasive sampling while containing clinically relevant metabolites, electrolytes, proteins, hormones, nucleic acids, pathogens, and other biomarkers. However, the low abundance of many analytes, matrix complexity, biofouling, and biofluid-specific variability present significant analytical challenges. This review critically examines the different CNT-based sensor architectures, and their recent advances in non-invasive analysis of sweat, saliva, tears, and urine. It integrates sensor architecture, biofluid-specific analytical challenges, sample-validation level, and translational readiness within a single comparative framework. Representative applications are discussed for metabolic monitoring, renal health assessment, infectious disease testing, and other clinically relevant uses. Beyond clinical diagnostics, emerging non-clinical applications, including drug-of-abuse detection, forensic body-fluid identification, and occupational or environmental exposure assessment, are also highlighted. Finally, we discuss key barriers limiting real-world translation of CNT biosensors, including material reproducibility issues, biofouling, physiological interpretation of biofluid biomarkers, scalable manufacturing, and long-term operational stability, and outline future strategies to advance these platforms toward robust, reliable, and widely deployable biosensing technologies.

Indexed as

Biosensing TechniquesBody FluidsNanotubes, CarbonBiomarkersHumansSweatBiomarkersNanotubes, Carbonbiomarkerbiosensorcarbon nanotubenon-invasive biofluid

Identifiers

PMID42645049
PMCPMC13510900

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.