Evidence map›Paper›PMID 31565498›Full record

ArticleBiomedical optics express2019

Hyperspectral Raman microscopy can accurately differentiate single cells of different human thyroid nodules.

Marcos A S de Oliveira, Michael Campbell, Alaa M Afify, Eric C Huang, James W Chan

Open access · goldAbstract read
In one paragraph

Article in Biomedical optics express, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 6% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. The Potential of Metabolomics in the Diagnosis of Thyroid Cancer.International journal of molecular sciences · 2020
    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

5 authors at 3 institutions in 1 country.

Marcos A S de OliveiraDepartment of Pathology & Laboratory Medicine, Univ. of California Davis, Sacramento, CA 95817, USA.
Michael CampbellDepartment of Surgery, Univ. of California Davis, Sacramento, CA 95817, USA.
Alaa M AfifyDepartment of Pathology & Laboratory Medicine, Univ. of California Davis, Sacramento, CA 95817, USA.
Eric C HuangDepartment of Pathology, Univ. of Washington, Seattle, WA 98104, USA.
James W ChanDepartment of Pathology & Laboratory Medicine, Univ. of California Davis, Sacramento, CA 95817, USA.ORCID https://orcid.org/0000-0002-6643-7139
University of California, Davis · USCenter for Health and Gender Equity · USUniversity of Washington · US

Funding

Staff InvestigatorsP30CA093373 · NCI · UNIVERSITY OF CALIFORNIA DAVIS · PI Laura Marcu · 2002 to 2026
$84.9M
NCI NIH HHS P30 CA093373
6 · The paper itself

Abstract

We report on the use of line-scan hyperspectral Raman microscopy in combination with multivariate statistical analyses for identifying and classifying single cells isolated from clinical samples of human thyroid nodules based on their intrinsic Raman spectral signatures. A total of 248 hyperspectral Raman images of single cells from benign thyroid (n = 127) and classic variant of papillary carcinoma (n = 121) nodules were collected. Spectral differences attributed to phenylalanine, tryptophan, proteins, lipids, and nucleic acids were identified for benign and papillary carcinoma cells. Using principal component analysis and linear discriminant analysis, cells were identified with 97% diagnostic accuracy. In addition, preliminary data of cells from follicular adenoma (n = 20), follicular carcinoma (n = 25), and follicular variant of papillary carcinoma (n = 18) nodules suggest the feasibility of further discrimination of subtypes. Our findings indicate that hyperspectral Raman microscopy can potentially be developed into an objective approach for analyzing single cells from fine needle aspiration (FNA) biopsies to enable the minimally invasive diagnosis of "indeterminate" thyroid nodules and other challenging cases.

Identifiers

PMID31565498
PMCPMC6757446
OpenAlexW2964775221

What OpenQuestion holds

Textmetadata
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Registered trials

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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.