Evidence map›Paper›PMID 28820289›Full record

ReviewAutophagy2017

Recent advances in quantitative and chemical proteomics for autophagy studies.

Yin-Kwan Wong, Jianbin Zhang, Zi-Chun Hua, Qingsong Lin, Han-Ming Shen, Jigang Wang

Abstract readReview
In one paragraph

Review in Autophagy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

  1. Guideline
  2. Activity-based protein profiling: A graphical review.Current research in pharmacology and drug discovery · 2023
    Review
  3. Studying Autophagy Using a TMT-Based Quantitative Proteomics Approach.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
  4. Article
  5. Tetra-arylborate lipophilic anions as targeting groups.Chemical communications (Cambridge, England) · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Guidelines for evaluating myocardial cell death.American journal of physiology. Heart and circulatory physiology · 2019
    Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Understanding and exploiting the roles of autophagy in plants through multi-omics approaches.Plant science : an international journal of experimental plant biology · 2018
    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.

Yin-Kwan Wonga Department of Physiology, Yong Loo Lin School of Medicine , National University of Singapore , Singapore.
Jianbin Zhangb Department of Oncology, Clinical Research Institute , Zhejiang Provincial People's Hospital , Hangzhou , China.
Zi-Chun Huac Changzhou High-Tech Research Institute of Nanjing University and the State Key Laboratory of Pharmaceutical Biotechnology, College of Life Sciences , Nanjing University , Nanjing , China.
Qingsong Lind Department of Biological Sciences , National University of Singapore , Singapore.
Han-Ming Shena Department of Physiology, Yong Loo Lin School of Medicine , National University of Singapore , Singapore.
Jigang Wanga Department of Physiology, Yong Loo Lin School of Medicine , National University of Singapore , Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macroautophagy/autophagy is an evolutionarily well-conserved cellular degradative process with important biological functions that is closely implicated in health and disease. In recent years, quantitative mass spectrometry-based proteomics and chemical proteomics have emerged as important tools for the study of autophagy, through large-scale unbiased analysis of the proteome or through highly specific and accurate analysis of individual proteins of interest. At present, a variety of approaches have been successfully applied, including (i) expression and interaction proteomics for the study of protein post-translational modifications, (ii) investigating spatio-temporal dynamics of protein synthesis and degradation, and (iii) direct determination of protein activity and profiling molecular targets in the autophagic process. In this review, we attempted to provide an overview of principles and techniques relevant to the application of quantitative and chemical proteomics methods to autophagy, and outline the current landscape as well as future outlook of these methods in autophagy research.

Indexed as

AutophagyAnimalsHumansIsotope LabelingModels, BiologicalProtein Processing, Post-TranslationalProteomicsProteostasisactivity-based protein profilingautophagyBONCATchemical proteomicsiTRAQpost-translational modificationprotein degradationprotein synthesisproteomicsSILAC

Identifiers

PMID28820289
PMCPMC5612287

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.