Evidence map›Paper›PMID 39344350›Full record

ArticleJournal of microbiology and biotechnology2024

Impact of Mitophagy-Related Genes on the Diagnosis and Development of Esophageal Squamous Cell Carcinoma via Single-Cell RNA-seq Analysis and Machine Learning Algorithms.

Xuzhi Mo, Feng Ji, Jianguang Chen, Chengcheng Yi, Fang Wang

Abstract read
In one paragraph

Article in Journal of microbiology and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Xuzhi MoDepartment of Thoracic Surgery, Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying 257088, P.R. China.
Feng JiDepartment of Thoracic Surgery, Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying 257088, P.R. China.
Jianguang ChenDepartment of Thoracic Surgery, Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying 257088, P.R. China.
Chengcheng YiDepartment of Thoracic Surgery, Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying 257088, P.R. China.
Fang WangDepartment of Oncology, Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying 257088, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a treatment for esophageal squamous cell carcinoma (ESCC), which is common and fatal, mitophagy is a conserved cellular mechanism that selectively removes damaged mitochondria and is crucial for cellular homeostasis. While tumor development and resistance to anticancer therapies are related to ESCC, their role in ESCC remains unclear. Here, we investigated the relationship between mitophagy-related genes (MRGs) and ESCC to provide novel insights into the role of mitophagy in ESCC prognosis and diagnosis prediction. First, we identified MRGs from the GeneCards database and examined them at both the single-cell and transcriptome levels. Key genes were selected and a prognostic model was constructed using least absolute shrinkage and selection operator analysis. External validation was performed using the GSE53624 dataset and Kaplan-Meier survival analysis was performed to identify

Indexed as

Esophageal NeoplasmsEsophageal Squamous Cell CarcinomaMachine LearningMitophagyRNA-SeqSingle-Cell AnalysisAlgorithmsApoptosis Regulatory ProteinsBiomarkers, TumorCell Line, TumorCell MovementCell ProliferationGene Expression Regulation, NeoplasticHumansMitochondriaMitochondrial ProteinsApoptosis Regulatory ProteinsBiomarkers, TumorDIABLO protein, humanMitochondrial ProteinsESCCmachine learningmitophagy-related genesprediction modelsingle-cell RNA-seq

Identifiers

PMID39344350
PMCPMC11637838

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.