Evidence map›Paper›PMID 40626724›Full record

ArticleJournal of the American Chemical Society2025

DNA Aptamer-Guided Glycomimetics for Developmental Stage-Specific Glycocalyx Engineering to Control Stem Cell Differentiation.

Sean C Purcell, Matthew R Naticchia, Julianna L Follmar, Nathaniel Marroquin, Hans Jefferson C Ng, Kamil Godula

Abstract read
In one paragraph

Article in Journal of the American Chemical Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Chemical Biology 2025: Highlights From the Ch/Bi145 Course at Caltech.Chembiochem : a European journal of chemical biology · 2026
    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.

Sean C Purcell
Matthew R Naticchia
Julianna L Follmar
Nathaniel Marroquin
Hans Jefferson C Ng

Funding

In vivo glycan engineering at the cell-matrix interface to control stem cell fateDP2HD087954 · NICHD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GODULA, KAMIL · 2015 to 2015
$2.3M
Cell membrane-targeting proteoglycan chimeras as selective growth factor signaling actuatorsR01GM145913 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Kamil Godula · 2023 to 2026
$2.1M
NICHD NIH HHS DP2 HD087954NIGMS NIH HHS R01 GM145913
6 · The paper itself

Abstract

Heparan sulfate glycosaminoglycans in the stem cell glycocalyx are crucial in controlling growth factor activity during development. Augmenting the surface of stem cells with synthetic heparan sulfate mimetics with defined compositions and growth factor binding profiles has emerged as a promising strategy to fine-tune cellular signaling responses and differentiation. However, current glycocalyx engineering methods lack specificity for stem cells or require prior genetic manipulation, limiting their applicability in a therapeutic context. Here, we report a heparan sulfate mimetic containing a DNA aptamer with affinity for the membrane-associated pluripotency marker, alkaline phosphatase, that can be selectively targeted to the surface of embryonic stem cells. The glycomimetic-enhanced fibroblast growth factor 2 recruitment to the stem cell surface activated signaling through the mitogen-activated protein kinase pathway and promoted neural differentiation. While the present work targets pluripotent cells specifically, it can be more broadly applicable to progenitor cells at other developmental stages to better control their differentiation and enhance their therapeutic potential.

Indexed as

Aptamers, NucleotideCell DifferentiationGlycocalyxHeparan SulfateAnimalsHumansMiceAptamers, NucleotideHeparan Sulfate

Identifiers

PMID40626724
PMCPMC12981361

What OpenQuestion holds

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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.