Evidence map›Paper›PMID 36181993›Full record

ReviewAdvanced drug delivery reviews2022

Soft nano and microstructures for the photomodulation of cellular signaling and behavior.

Nicolas Muzzio, Manuel Eduardo Martinez-Cartagena, Gabriela Romero

Abstract readReview
In one paragraph

Review in Advanced drug delivery reviews, 2022. 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. Review
  3. Review
  4. 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

3 authors.

Nicolas MuzzioDepartment of Biomedical Engineering and Chemical Engineering, The University of Texas at San Antonio, San Antonio, TX 78249, USA. Electronic address: nicolas.muzzio@utsa.edu.
Manuel Eduardo Martinez-CartagenaAdvanced Materials Department, Research Center in Applied Chemistry (CIQA), Saltillo, Coahuila, Mexico.
Gabriela RomeroDepartment of Biomedical Engineering and Chemical Engineering, The University of Texas at San Antonio, San Antonio, TX 78249, USA. Electronic address: gabrielaromero.uribe@utsa.edu.

Funding

Non-invasive Excitation and Inhibition of Neural Activity via On-Demand Magnetothermal Drug ReleaseSC1GM130542 · NIGMS · UNIVERSITY OF TEXAS SAN ANTONIO · PI ROMERO URIBE, GABRIELA · 2019 to 2022
$1.0M
NIGMS NIH HHS SC1 GM130542
6 · The paper itself

Abstract

Photoresponsive soft materials are everywhere in the nature, from human's retina tissues to plants, and have been the inspiration for engineers in the development of modern biomedical materials. Light as an external stimulus is particularly attractive because it is relatively cheap, noninvasive to superficial biological tissues, can be delivered contactless and offers high spatiotemporal control. In the biomedical field, soft materials that respond to long wavelength or that incorporate a photon upconversion mechanism are desired to overcome the limited UV-visible light penetration into biological tissues. Upon light exposure, photosensitive soft materials respond through mechanisms of isomerization, crosslinking or cleavage, hyperthermia, photoreactions, electrical current generation, among others. In this review, we discuss the most recent applications of photosensitive soft materials in the modulation of cellular behavior, for tissue engineering and regenerative medicine, in drug delivery and for phototherapies.

Indexed as

Drug Delivery SystemsLightHumansPhototherapyRegenerative MedicineCell BehaviorDrug DeliveryPhotocleavagePhotodynamicPhotoisomerizationPhototherapiesPhotothermalPhotovoltaic/OptoelectronicRegenerative MedicineSmart Soft Materials

Identifiers

PMID36181993
PMCPMC11610523

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.