Evidence map›Paper›PMID 33677957›Full record

ArticleACS nano2021

Ultrafast Directional Janus Pt-Mesoporous Silica Nanomotors for Smart Drug Delivery.

Paula Díez, Elena Lucena-Sánchez, Andrea Escudero, Antoni Llopis-Lorente, Reynaldo Villalonga, Ramón Martínez-Máñez

Open access · hybridAbstract read
In one paragraph

Article in ACS nano, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed
19.3field-weighted citation impact, top 1% of its field
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

42 citing papers in PubMed, 162 citations in OpenAlex.

  1. Article
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  6. Artificial chemotaxis in micro/nanomotors.Nature communications · 2026
    Review
  7. Article
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  9. Recent Advances in Collective Behaviors of Micro/Nanomotor Swarms.Advanced materials (Deerfield Beach, Fla.) · 2026
    Review
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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 at 2 institutions in 1 country.

Paula DíezInstituto Interuniversitario de Investigacio'n de Reconocimiento Molecular y Desarrollo Tecnolo'gico (IDM), Universitat Politècnica de València, Universitat de València, Spain, Camino de Vera s/n, 46022 València, Spain.
Elena Lucena-SánchezInstituto Interuniversitario de Investigacio'n de Reconocimiento Molecular y Desarrollo Tecnolo'gico (IDM), Universitat Politècnica de València, Universitat de València, Spain, Camino de Vera s/n, 46022 València, Spain.
Andrea EscuderoInstituto Interuniversitario de Investigacio'n de Reconocimiento Molecular y Desarrollo Tecnolo'gico (IDM), Universitat Politècnica de València, Universitat de València, Spain, Camino de Vera s/n, 46022 València, Spain.
Antoni Llopis-LorenteInstituto Interuniversitario de Investigacio'n de Reconocimiento Molecular y Desarrollo Tecnolo'gico (IDM), Universitat Politècnica de València, Universitat de València, Spain, Camino de Vera s/n, 46022 València, Spain.
Reynaldo VillalongaNanosensors & Nanomachines Group, Department of Analytical Chemistry, Faculty of Chemistry, Complutense University of Madrid, 28040 Madrid, Spain.
Ramón Martínez-MáñezInstituto Interuniversitario de Investigacio'n de Reconocimiento Molecular y Desarrollo Tecnolo'gico (IDM), Universitat Politècnica de València, Universitat de València, Spain, Camino de Vera s/n, 46022 València, Spain.ORCID 0000-0001-5873-9674
Universitat de València · ESUniversidad Complutense de Madrid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Development of bioinspired nanomachines with an efficient propulsion and cargo-towing has attracted much attention in the last years due to their potential biosensing, diagnostics, and therapeutics applications. In this context, self-propelled synthetic nanomotors are promising carriers for intelligent and controlled release of therapeutic payloads. However, the implementation of this technology in real biomedical applications is still facing several challenges. Herein, we report the design, synthesis, and characterization of innovative multifunctional gated platinum-mesoporous silica nanomotors constituted of a propelling element (platinum nanodendrite face), a drug-loaded nanocontainer (mesoporous silica nanoparticle face), and a disulfide-containing oligo(ethylene glycol) chain (S-S-PEG) as a gating system. These Janus-type nanomotors present an ultrafast self-propelled motion due to the catalytic decomposition of low concentrations of hydrogen peroxide. Likewise, nanomotors exhibit a directional movement, which drives the engines toward biological targets, THP-1 cancer cells, as demonstrated using a microchip device that mimics penetration from capillary to postcapillary vessels. This fast and directional displacement facilitates the rapid cellular internalization and the on-demand specific release of a cytotoxic drug into the cytosol, due to the reduction of the disulfide bonds of the capping ensemble by intracellular glutathione levels. In the microchip device and in the absence of fuel, nanomotors are neither able to move directionally nor reach cancer cells and deliver their cargo, revealing that the fuel is required to get into inaccessible areas and to enhance nanoparticle internalization and drug release. Our proposed nanosystem shows many of the suitable characteristics for ideal biomedical destined nanomotors, such as rapid autonomous motion, versatility, and stimuli-responsive controlled drug release.

Indexed as

NanoparticlesPharmaceutical PreparationsCatalysisPlatinumSilicon DioxidePharmaceutical PreparationsPlatinumSilicon Dioxidedirectional motiondrug deliveryJanus nanomotorson-command controlled releaseultrafast self-propulsion

Identifiers

PMID33677957
PMCPMC8719758
OpenAlexW3134200710

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.