Evidence map›Paper›PMID 40212624›Full record

ArticleSmall science2024

Entropy-Mediated Nanoparticle Cellular Uptake.

Haixiao Wan, Duo Xu, Lijuan Gao, Li-Tang Yan

Abstract read
In one paragraph

Article in Small science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. High-Entropy Materials for Prospective Biomedical Applications: Challenges and Opportunities.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    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

4 authors.

Haixiao WanState Key Laboratory of Chemical Engineering Department of Chemical Engineering Tsinghua University Beijing 100084 P. R. China.
Duo XuState Key Laboratory of Chemical Engineering Department of Chemical Engineering Tsinghua University Beijing 100084 P. R. China.
Lijuan GaoState Key Laboratory of Chemical Engineering Department of Chemical Engineering Tsinghua University Beijing 100084 P. R. China.
Li-Tang YanState Key Laboratory of Chemical Engineering Department of Chemical Engineering Tsinghua University Beijing 100084 P. R. China.ORCID 0000-0002-6090-3039

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Entropy, as one of the key parameters defining thermodynamic systems, is extensively explored in various scientific fields covering physics, chemistry, biology, etc. Particularly, understanding the entropic effects in cellular uptake is critical to understanding how physicochemical interactions govern the structure, response, and function of biological systems. Herein, the major types of entropy in biological systems, the underlying physical principles of their entropic forces, as well as the entropic effects emerging at the interfaces between nanoparticles and cell membrane in diverse biological processes, are introduced. The emphasis is on the physical principles arisen from entropy in the cellular uptake process. Finally, the remaining challenges and future directions for understanding and thereby manipulating entropy-meditated nanoparticle cellular uptake are discussed. It is hoped that this review can explain some complicated and/or unique phenomena observed during cellular uptake, elucidate the physical mechanisms underlying their structures and dynamical processes, and advance entropy-controlled strategy in the design and development of novel functional systems and materials toward advantageous biomedical applications.

Indexed as

biophysicscellular uptakeentropyentropy-controlled strategynanoparticle

Identifiers

PMID40212624
PMCPMC11935243

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.