Identification of metastatic cell nucleus in human prostate cancer by electron microscopy.

Open access · goldAbstract read

In one paragraph

Article in Future science OA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

0.1field-weighted citation impact, top 48% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

Using deep learning to detect patients at risk for prostate cancer despite benign biopsies.iScience · 2022
Article

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

1 author at 1 institution in 1 country.

Akhouri A SinhaResearch Service, Minneapolis Veterans Affairs Healthcare System, Minneapolis, MN 55417, USA.ORCID https://orcid.org/doi/10.1101/7787853

University of Minnesota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimMetastatic prostate cancer is responsible for a large proportion of deaths worldwide. The aim of this study was to identify metastatic cells and determine if stromal invasion by cancer cells differs from those during metastasis. METHODS &

resultsTissue biopsy/prostatectomy samples, visualized by transmission electron microscopy, identified that metastatic cells are a lineage of stem cells, which have dedifferentiated into cancerous columnar/cuboidal cells. These cells demonstrate nuclear plasticity; the loss of nuclear membranes and boundary between nucleus and cytoplasm; and the presence of electron dense molecules, which can readily pass through basement membranes and enter the capillary, ready for dissemination to metastatic sites.

conclusionThis is the first study to demonstrate differences between invasive and metastatic cell types.

Indexed as

cancer requires mutationchromatin harbors mutated DNA/geneselectron dense DNA moleculesinvasive and metastatic cell typesloss of nuclear membranes releases DNA/genesmutation imparts proliferation advantagenuclear plasticity is indicative of the metastatic cell

Identifiers

PMID33235806

DOI10.2144/fsoa-2019-0141

PMCPMC7668137

OpenAlexW3038274999

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.