Evidence map›Paper›PMID 37569541›Full record

ReviewInternational journal of molecular sciences2023

Practices, Potential, and Perspectives for Detecting Predisease Using Raman Spectroscopy.

Yusuke Oshima, Takayuki Haruki, Keiichi Koizumi, Shota Yonezawa, Akinori Taketani, Makoto Kadowaki, Shigeru Saito

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

7 authors.

Yusuke OshimaFaculty of Engineering, University of Toyama, Toyama 930-8555, Japan.ORCID 0000-0002-2304-8600
Takayuki HarukiResearch Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, Japan.ORCID 0000-0003-2718-0972
Keiichi KoizumiResearch Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, Japan.ORCID 0000-0002-0349-4144
Shota YonezawaResearch Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, Japan.
Akinori TaketaniResearch Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, Japan.ORCID 0000-0003-4637-8167
Makoto KadowakiResearch Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, Japan.ORCID 0000-0002-5945-9380
Shigeru SaitoResearch Center for Pre-Disease Science, University of Toyama, Toyama 930-8555, Japan.ORCID 0000-0002-8940-3708

Funding

Japan Science and Technology Agency JPMJMS2021
6 · The paper itself

Abstract

Raman spectroscopy shows great potential for practical clinical applications. By analyzing the structure and composition of molecules through real-time, non-destructive measurements of the scattered light from living cells and tissues, it offers valuable insights. The Raman spectral data directly link to the molecular composition of the cells and tissues and provides a "molecular fingerprint" for various disease states. This review focuses on the practical and clinical applications of Raman spectroscopy, especially in the early detection of human diseases. Identifying predisease, which marks the transition from a healthy to a disease state, is crucial for effective interventions to prevent disease onset. Raman spectroscopy can reveal biological processes occurring during the transition states and may eventually detect the molecular dynamics in predisease conditions.

Indexed as

Early DiagnosisSpectrum Analysis, RamanCellsHumansclinical applicationDNBdynamical network biomarkermolecular fingerprintprediseaseRaman spectroscopystate transition

Identifiers

PMID37569541
PMCPMC10418989

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.