Evidence map›Paper›PMID 37957848›Full record

ArticleCurrent gene therapy2024

Prediction of SARS-CoV-2 Infection Phosphorylation Sites and Associations of these Modifications with Lung Cancer Development.

Wei Li, Gen Li, Yuzhi Sun, Liyuan Zhang, Xinran Cui, Yuran Jia, Tianyi Zhao

Abstract read
PubMed Publisher
In one paragraph

Article in Current gene therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.9field-weighted citation impact, top 5% 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

13 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. 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

7 authors at 2 institutions in 1 country.

Wei LiInstitute of Bioinformatics, Harbin Institute of Technology, Harbin, China.
Gen LiDepartment of Radiation Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
Yuzhi SunInstitute for Bioinformatics, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
Liyuan ZhangInstitute for Bioinformatics, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
Xinran CuiInstitute for Bioinformatics, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
Yuran JiaInstitute for Bioinformatics, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China.
Tianyi ZhaoSchool of Medicine and Health, Harbin Institute of Technology, Harbin, China.
Harbin Institute of Technology · CNHarbin Medical University · CN

Funding

Natural Science Foundation of China 62102116
6 · The paper itself

Abstract

introductionSince the emergence of SARS-CoV-2 viruses, multiple mutant strains have been identified. Infection with SARS-CoV-2 virus leads to alterations in host cell phosphorylation signal, which systematically modulates the immune response.

methodsIdentification and analysis of SARS-CoV-2 virus infection phosphorylation sites enable insight into the mechanisms of viral infection and effects on host cells, providing important fundamental data for the study and development of potent drugs for the treatment of immune inflammatory diseases. In this paper, we have analyzed the SARS-CoV-2 virus-infected phosphorylation region and developed a transformer-based deep learning-assisted identification method for the specific identification of phosphorylation sites in SARS-CoV-2 virus-infected host cells.

resultsFurthermore, through association analysis with lung cancer, we found that SARS-CoV-2 infection may affect the regulatory role of the immune system, leading to an abnormal increase or decrease in the immune inflammatory response, which may be associated with the development and progression of cancer.

conclusionWe anticipate that this study will provide an important reference for SARS-CoV-2 virus evolution as well as immune-related studies and provide a reliable complementary screening tool for anti-SARS-CoV-2 virus drug and vaccine design.

Indexed as

COVID-19Lung NeoplasmsSARS-CoV-2HumansPhosphorylationDeep learningimmune inflammatory diseases.lung cancerphosphorylationSARS-CoV-2transformer

Identifiers

PMID37957848
OpenAlexW4388568063

What OpenQuestion holds

Textmetadata
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.