Quick Navigation

Topics

Spin Qubits Silicon Quantum Computing Quantum Machine Learning Quantum Chemistry

Routine monitoring of microRNAs in salivary exosomes using a cellulose nanofiber sheet.

PubMed
Authors: Ajiri T, Zhang M, Mizukami N, Iida M, Kawaguchi S, Sekihara Y, Chattrairat K, Zhu Z, Baba Y, Koga H, Yasui T

Year

2026

Paper ID

4574

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

184

Citations

3

Abstract

Liquid biopsy is a promising approach for non-invasive disease monitoring, offering the potential for frequent sampling and early risk assessment. Among various biofluids, saliva is particularly well-suited for daily sampling due to its ease of collection and minimal invasiveness. Here, we present a cellulose nanofiber sheet as a novel platform for the rapid, low-volume recovery and stable storage of miRNAs associated with small extracellular vesicles in saliva. The sheet captures vesicles via its nanoscale porous networks and preserves their contents at room temperature, enabling efficient extraction of vesicle-associated miRNAs. Compared to ultracentrifugation, the method demonstrated superior miRNA recovery and required only 10 μL of saliva and less than 1 min of processing. Analysis of salivary miRNA profiles from healthy individuals and cancer patients revealed distinct expression patterns, enabling identification of candidate cancer-related miRNAs. Furthermore, daily saliva sampling during 20 days demonstrated the feasibility of longitudinal miRNA profiling and highlighted the effects of factors such as food intake. These findings underscore the potential of cellulose nanofiber sheets as a practical tool for salivary miRNA monitoring, with applications in personalized health management, early risk detection, and decentralized testing environments.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.
  • Liquid biopsy is a promising approach for non-invasive disease monitoring, offering the potential for frequent sampling and early risk assessment.

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

Local Citation Graph (Related-Paper Links)

Current Paper #4574 #78837 TLS loss in superconducting res... #78828 Verifiable Sampling for Delegat... #78813 Large-Scale Benchmarking of Qua... #78797 Local polarization control of o...

External citation index: OpenAlex citation signal • updated 2026-10-25 14:13:24

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.