Evidence map›Paper›PMID 35252203›Full record

ReviewFrontiers in cell and developmental biology2022

The Applications of Metabolic Glycoengineering.

Liwei Ying, Junxi Xu, Dawei Han, Qingguo Zhang, Zhenghua Hong

Abstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Biomarkers and targeted therapy for cancer stem cells.Trends in pharmacological sciences · 2024
    Review
  6. Cell Surface Engineering Tools for Programming Living Assemblies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
    Review
  7. Reducing Sialylation Enhances Electrotaxis of Corneal Epithelial Cells.International journal of molecular sciences · 2023
    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.

Liwei YingOrthopedic Department, Taizhou Hospital Affiliated to Wenzhou Medical University, Linhai, China.
Junxi XuDepartment of Medical Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Dawei HanOrthopedic Department, Taizhou Hospital Affiliated to Wenzhou Medical University, Linhai, China.
Qingguo ZhangOrthopedic Department, Taizhou Hospital Affiliated to Wenzhou Medical University, Linhai, China.
Zhenghua HongOrthopedic Department, Taizhou Hospital Affiliated to Wenzhou Medical University, Linhai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mammalian cell membranes are decorated by the glycocalyx, which offer versatile means of generating biochemical signals. By manipulating the set of glycans displayed on cell surface, it is vital for gaining insight into the cellular behavior modulation and medical and biotechnological adhibition. Although genetic engineering is proven to be an effective approach for cell surface modification, the technique is only suitable for natural and genetically encoded molecules. To circumvent these limitations, non-genetic approaches are developed for modifying cell surfaces with unnatural but functional groups. Here, we review latest development of metabolic glycoengineering (MGE), which enriches the chemical functions of the cell surface and is becoming an intriguing new tool for regenerative medicine and tissue engineering. Particular emphasis of this review is placed on discussing current applications and perspectives of MGE.

Indexed as

cell-based therapycell membrane modificationimagingManNAc analogsmetabolic glycoengineering.

Identifiers

PMID35252203
PMCPMC8892211

What OpenQuestion holds

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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.