Evidence map›Paper›PMID 32577625›Full record

ArticleCell reports. Medicine2020

Label-free, High-Resolution Optical Metabolic Imaging of Human Cervical Precancers Reveals Potential for Intraepithelial Neoplasia Diagnosis.

Dimitra Pouli, Hong-Thao Thieu, Elizabeth M Genega, Laura Baecher-Lind, Michael House, Brian Bond, Danielle M Roncari, Megan L Evans, Francisca Rius-Diaz, Karl Munger and 1 more

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Cell reports. Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

20 citing papers in PubMed, 34 citations in OpenAlex.

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  14. Label-Free Optical Metabolic Imaging in Cells and Tissues.Annual review of biomedical engineering · 2023
    Review
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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

11 authors at 2 institutions in 2 countries.

Dimitra PouliDepartment of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA.
Hong-Thao ThieuDepartment of Obstetrics and Gynecology, Tufts University School of Medicine, Tufts Medical Center, 800 Washington Street, Boston, MA 02111, USA.
Elizabeth M GenegaDepartment of Pathology and Laboratory Medicine, Tufts University School of Medicine, Tufts Medical Center, 800 Washington Street, Boston, MA 02111, USA.
Laura Baecher-LindDepartment of Obstetrics and Gynecology, Tufts University School of Medicine, Tufts Medical Center, 800 Washington Street, Boston, MA 02111, USA.
Michael HouseDepartment of Obstetrics and Gynecology, Tufts University School of Medicine, Tufts Medical Center, 800 Washington Street, Boston, MA 02111, USA.
Brian BondDepartment of Obstetrics and Gynecology, Tufts University School of Medicine, Tufts Medical Center, 800 Washington Street, Boston, MA 02111, USA.
Danielle M RoncariDepartment of Obstetrics and Gynecology, Tufts University School of Medicine, Tufts Medical Center, 800 Washington Street, Boston, MA 02111, USA.
Megan L EvansDepartment of Obstetrics and Gynecology, Tufts University School of Medicine, Tufts Medical Center, 800 Washington Street, Boston, MA 02111, USA.
Francisca Rius-DiazDepartment of Preventive Medicine and Public Health, Faculty of Medicine, University of Málaga, 32 Louis Pasteur Boulevard, 29071 Málaga, Spain.
Karl MungerDepartment of Developmental, Molecular, and Chemical Biology, Tufts University School of Medicine, 136 Harrison Avenue, Boston, MA 02111, USA.
Irene GeorgakoudiDepartment of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA.
Tufts University · USUniversidad de Málaga · ES

Funding

Acquisition of Leica confocal/multiphoton microscopeS10OD021624 · OD · TUFTS UNIVERSITY MEDFORD · PI GEORGAKOUDI, IRENE · 2016 to 2016
$600k
Label-free, high resolution, functional, two-photon imaging for non-invasive early cancer detectionR03CA235053 · NCI · TUFTS UNIVERSITY MEDFORD · PI GEORGAKOUDI, IRENE · 2019 to 2020
$150k
NCI NIH HHS R03 CA235053NIH HHS S10 OD021624
6 · The paper itself

Abstract

While metabolic changes are considered a cancer hallmark, their assessment has not been incorporated in the detection of early or precancers, when treatment is most effective. Here, we demonstrate that metabolic changes are detected in freshly excised human cervical precancerous tissues using label-free, non-destructive imaging of the entire epithelium. The images rely on two-photon excited fluorescence from two metabolic co-enzymes, NAD(P)H and FAD, and have micron-level resolution, enabling sensitive assessments of the redox ratio and mitochondrial fragmentation, which yield metrics of metabolic function and heterogeneity. Simultaneous characterization of morphological features, such as the depth-dependent variation of the nuclear:cytoplasmic ratio, is demonstrated. Multi-parametric analysis combining several metabolic metrics with morphological ones enhances significantly the diagnostic accuracy of identifying high-grade squamous intraepithelial lesions. Our results motivate the translation of such functional metabolic imaging to

Indexed as

Cervix UteriEpitheliumFemaleFlavin-Adenine DinucleotideHumansMetabolic Networks and PathwaysMitochondrial DynamicsNADNADPOptical ImagingPrecancerous ConditionsReproducibility of ResultsSensitivity and SpecificityStaining and LabelingUterine Cervical DysplasiaUterine Cervical NeoplasmsFlavin-Adenine DinucleotideNADNADP

Identifiers

PMID32577625
PMCPMC7311071
OpenAlexW3026801251

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.