Evidence map›Paper›PMID 39682291›Full record

ReviewCancers2024

Tumor Biomechanics-Inspired Future Medicine.

Yuqing Dong, Mengnan Lu, Yuting Yin, Cong Wang, Ningman Dai

Abstract readReview
In one paragraph

Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. 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

5 authors.

Yuqing DongThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
Mengnan LuThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
Yuting YinThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
Cong WangThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.
Ningman DaiThe Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China.

Funding

China Postdoctoral Science Foundation 2021M692570
6 · The paper itself

Abstract

Malignant tumors pose a significant global health challenge, severely threatening human health. Statistics from the World Health Organization indicate that, in 2022, there were nearly 20 million new cancer cases and 9.7 million cancer-related deaths. Therefore, it is urgently necessary to study the pathogenesis of cancer and explore effective diagnostic and treatment strategies. In recent years, research has highlighted the importance of mechanical cues in tumors, which have become a new hallmark of cancer and a key factor in regulating tumor behavior. This suggests that studying the mechanical properties of tumors may open potential new avenues for understanding the pathogenesis, diagnosis, and therapeutic intervention of cancer. This review summarizes the mechanical characteristics of tumors and the development of tumor diagnostics and treatments targeting specific mechanical factors. Finally, we propose new ideas and insights for the application of mechanomedicine in cancer diagnosis and treatment in the future.

Indexed as

tumor biomechanicstumor mechanobiologytumor mechanomedicine

Identifiers

PMID39682291
PMCPMC11640100

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.