Evidence map›Paper›PMID 38163006›Full record

ArticleBladder (San Francisco, Calif.)2023

Single-cell analyses

Jinqiao Li, Jianyu Liu, Honglei Wang, Jinpeng Ma, Yueze Wang, Wanhai Xu

Open access · hybridAbstract read
In one paragraph

Article in Bladder (San Francisco, Calif.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact, top 30% 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

8 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. New Strategies for Macrophage Re-Education in Cancer: An Update.International journal of molecular sciences · 2024
    Review
  8. 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

6 authors at 1 institution in 1 country.

Jinqiao LiUrology Surgery Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150081, PR China.
Jianyu LiuBreast Surgery Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150081, PR China.
Honglei WangUrology Surgery Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150081, PR China.
Jinpeng MaUrology Surgery Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150081, PR China.
Yueze WangUrology Surgery Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150081, PR China.
Wanhai XuUrology Surgery Department, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150081, PR China.
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bladder cancer is among the most lethal urinary system cancers across the globe. Macrophage 1 and Macrophage 2 play an essential role in the pathogenesis of tumors. Nevertheless, prior studies failed to investigate the implication of the two cells, working in combination, in the development, growth, progression and metastasis of bladder cancer. Methods: We computed the M1/M2 ratio of the samples retrieved from The Cancer Genome Atlas (TCGA) by using the Cibersortx algorithm and calculated the ratio in 32 patients in our series by employing flow cytometry. SurvivalRandomForest was utilized to reduce the dimension of the list of the M1/M2-related genes, with an aim to obtain the most survival-predictive gene ( Results: The results showed that higher M1/M2 ratio was found to be associated with a more favorable prognosis of bladder cancer. Conclusion: Our study identified

Indexed as

bladder cancerEMP1EMTFN1-SDC1macrophage

Identifiers

PMID38163006
PMCPMC10754694
OpenAlexW4389868344

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.