Evidence map›Paper›PMID 42154217›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

The Polymers of Life: Exploring Cellular Function Through Polymer Concepts.

Mark Chen, Ashutosh Chilkoti

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Mark ChenDepartment of Radiation Oncology, Duke University, Durham, NC, USA.
Ashutosh ChilkotiDepartment of Biomedical Engineering, Duke University, Durham, NC, USA.

Funding

Duke Radiation Oncology and Radiology Stimulating Access to Research in ResidencyR38CA245204 · NCI · DUKE UNIVERSITY · PI FLOYD, SCOTT R · 2020 to 2023
$1.4M
Air Force Office of Scientific Research FA9550-20-1-0241ASTRO Residents/Fellows Seed GrantDuke University Pratt School of Engineering BeyondtheHorizonNCI NIH HHS R38 CA245204
6 · The paper itself

Abstract

Biological organization has traditionally been viewed through the lens of distinct organelles and lock-and-key molecular interactions. The recent explosion of interest in phase separation has reshaped this view, revealing that cells also organize through membraneless organelles, also called biomolecular condensates, for spatial, temporal, and functional organization of its constituents. A key outcome of this shift has been the integration of polymer physics into cell biology, opening new avenues for understanding macromolecular behavior in living systems. This review traces the evolution of the field from foundational polymer physics, connects polymer properties to biological processes, and proposes a framework for interrogating cellular function through the lens of polymer science. While polymers are ubiquitous in daily life, their relevance to natural macromolecules and biological organization in cells is less apparent outside the discipline. Notably, current explorations at the biology-polymer interface echo much of the early pioneering work in polymer science. Accordingly, this review serves both as a primer on polymer concepts central to cellular processes and as a synthesis of recent advances and emerging tools for studying condensates in living cells.

Indexed as

Biomolecular CondensatesCell Physiological PhenomenaPolymersAnimalsHumansPhase SeparationPolymersbiomolecular condensatesgene regulationphase separationpolymer physicssynthetic biology

Identifiers

PMID42154217
PMCPMC13271645

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.