Evidence map›Paper›PMID 32908180›Full record

ArticleScientific reports2020

Chronic neural activity recorded within breast tumors.

Grant A McCallum, Jay Shiralkar, Diana Suciu, Gil Covarrubias, Jennifer S Yu, Efstathios Karathanasis, Dominique M Durand

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

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  13. The tumor-nerve circuit in breast cancer.Cancer metastasis reviews · 2023
    Review
  14. Article
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  16. Review
  17. A review of the neurological complications of breast cancer.Journal of family medicine and primary care · 2022
    Review
  18. Article
  19. Article
  20. 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.

Grant A McCallumDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA. gam19@case.edu.
Jay ShiralkarDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Diana SuciuDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Gil CovarrubiasDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Jennifer S YuCase Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA.
Efstathios KarathanasisDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
Dominique M DurandDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA. dxd6@case.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nerve fibers are known to reside within malignant tumors and the greater the neuronal density the worse prognosis for the patient. Recent discoveries using tumor bearing animal models have eluded to the autonomic nervous system having a direct effect on tumor growth and metastasis. We report the first direct and chronic in vivo measurements of neural activity within tumors. Using a triple-negative mammary cancer mouse model and chronic neural interface techniques, we have recorded neural activity directly within the tumor mass while the tumor grows and metastasizes. The results indicate that there is a strong connection between the autonomic nervous system and the tumor and could help uncover the mechanisms of tumor growth and metastasis.

Indexed as

AnimalsCell Line, TumorFemaleMammary Glands, AnimalMammary Neoplasms, ExperimentalMiceMice, Inbred BALB CNeoplasm MetastasisTriple Negative Breast Neoplasms

Identifiers

PMID32908180
PMCPMC7481786

What OpenQuestion holds

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LicenceCC BY
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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.