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Front Endocrinol (Lausanne) May 2023 PMID 37152941

Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework.

Songyun Zhao, Lanyu Wang, Wei Ding, Bicheng Ye, Chao Cheng, Jianfeng Shao, Jinhui Liu, Hongyi Zhou

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Mentions

3
Peak: 1 in Apr 2023
across 2 sources since Apr 2023

Extended reach

5,302
potential audience

Total likes

0

Video views

39

Mentions per month

Apr 2023 – Jul 2023

Where it's discussed

  • X / Twitter2 posts
  • YouTube1 videos

AI synopsis

What people are saying

The discussions highlight the significance of the research by emphasizing its focus on prognosis and immune infiltration in bladder cancer, with posts mentioning the use of machine learning to stratify patients. Words like 'potential' and 'important' show a cautious recognition of its value, while the tone remains generally neutral and informative, reflecting a community interested but not deeply engaged yet.

AgreementModerate agreement

Most discussions acknowledge the importance of the new research, especially the development of the DRPS for bladder cancer prognosis.

InterestModerate interest

Participants show moderate interest, noting the relevance of the study to bladder cancer and its potential for advancing personalized treatments.

EngagementNeutral engagement

The posts reflect superficial engagement, with some references to the study's background or methodology but lacking deep analysis.

ImpactModerate impact

The discussions suggest this research could influence future studies or clinical approaches, indicating a modest perceived impact.

Abstract in brief

  • This study explores how genes related to disulfidptosis, a form of cell death caused by disulfide stress, influence bladder cancer prognosis and immune responses.
  • Using machine learning algorithms, researchers built a prognostic signature called DRPS to predict patient survival, immunotherapy response, and tumor microenvironment characteristics.
  • Findings suggest that DRPS and related gene clusters can effectively stratify patients into different risk groups, aiding personalized treatment planning for bladder cancer.
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Top posts

Most liked on X and Bluesky
Frontiers - Endocrinology
@FrontEndocrinol · X

New Research: Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework: Background Bladder cancer… https://t.co/MLdUsOEWSH #Endocrinology #Endo

Apr 19, 2023 · 5,050 followers View post →
Oncology & Machine Learning
@MlOncology · X

Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework https://t.co/Fj764H1DXi

May 8, 2023 · 213 followers View post →

All mentions

Oncology & Machine Learning
@MlOncology · X

Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework https://t.co/Fj764H1DXi

May 8, 2023 · 213 followers View post →
Frontiers - Endocrinology
@FrontEndocrinol · X

New Research: Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework: Background Bladder cancer… https://t.co/MLdUsOEWSH #Endocrinology #Endo

Apr 19, 2023 · 5,050 followers View post →