Evidence map›Paper›PMID 36077300›Full record

ArticleInternational journal of molecular sciences2022

Erythro-Magneto-HA-Virosome: A Bio-Inspired Drug Delivery System for Active Targeting of Drugs in the Lungs.

Alessio Vizzoca, Gioia Lucarini, Elisabetta Tognoni, Selene Tognarelli, Leonardo Ricotti, Lisa Gherardini, Gualtiero Pelosi, Mario Pellegrino, Arianna Menciassi, Settimio Grimaldi and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. 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

11 authors at 5 institutions in 1 country.

Alessio VizzocaInstitute of Organic Synthesis and Photoreactivity (ISOF), National Research Council of Italy, Via Gobetti 101, 40129 Bologna, Italy.ORCID 0000-0002-4947-6830
Gioia LucariniThe BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56127 Pisa, Italy.
Elisabetta TognoniNational Institute of Optics (INO), National Research Council of Italy, Via G Moruzzi 1, 56124 Pisa, Italy.
Selene TognarelliThe BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56127 Pisa, Italy.ORCID 0000-0003-1135-8625
Leonardo RicottiThe BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56127 Pisa, Italy.
Lisa GherardiniInstitute of Clinical Physiology (IFC), National Research Council of Italy, Via G Moruzzi 1, 56124 Pisa, Italy.ORCID 0000-0002-7003-4295
Gualtiero PelosiInstitute of Clinical Physiology (IFC), National Research Council of Italy, Via G Moruzzi 1, 56124 Pisa, Italy.
Mario PellegrinoNational Institute of Optics (INO), National Research Council of Italy, Via G Moruzzi 1, 56124 Pisa, Italy.
Arianna MenciassiThe BioRobotics Institute, Scuola Superiore Sant'Anna, Piazza Martiri della Libertà 33, 56127 Pisa, Italy.
Settimio GrimaldiInstitute of Translational Pharmacology (IFT), National Research Council of Italy, Via Fosso del Cavaliere 100, 00133 Rome, Italy.
Caterina CintiInstitute of Organic Synthesis and Photoreactivity (ISOF), National Research Council of Italy, Via Gobetti 101, 40129 Bologna, Italy.ORCID 0000-0001-8049-0369
Scuola Superiore Sant'Anna · ITInstitute of Organic Synthesis and Photoreactivity · ITIstituto di Fisiologia Clinica · ITNational Research Council · ITIstituto di Farmacologia Traslazionale · IT

Funding

Fase1-Sardegna Ricerche srl 54/0071296
6 · The paper itself

Abstract

Over the past few decades, finding more efficient and selective administration routes has gained significant attention due to its crucial role in the bioavailability, absorption rate and pharmacokinetics of therapeutic substances. The pulmonary delivery of drugs has become an attractive target of scientific and biomedical interest in the health care research area, as the lung, thanks to its high permeability and large absorptive surface area and good blood supply, is capable of absorbing pharmaceuticals either for local deposition or for systemic delivery. Nevertheless, the pulmonary drug delivery is relatively complex, and strategies to mitigate the effects of mechanical, chemical and immunological barriers are required. Herein, engineered erythrocytes, the Erythro-Magneto-Hemagglutinin (HA)-virosomes (EMHVs), are used as a novel strategy for efficiently delivering drugs to the lungs. EMHV bio-based carriers exploit the physical properties of magnetic nanoparticles to achieve effective targeting after their intravenous injection thanks to an external magnetic field. In addition, the presence of hemagglutinin fusion proteins on EMHVs' membrane allows the DDS to anchor and fuse with the target tissue and locally release the therapeutic compound. Our results on the biomechanical and biophysical properties of EMHVs, such as the membrane robustness and deformability and the high magnetic susceptibility, as well as their in vivo biodistribution, highlight that this bio-inspired DDS is a promising platform for the controlled and lung-targeting delivery of drugs, and represents a valuable alternative to inhalation therapy to fulfill unmet clinical needs.

Indexed as

NanoparticlesVirosomesDrug CarriersDrug Delivery SystemsHemagglutininsLungPharmaceutical PreparationsTissue DistributionDrug CarriersHemagglutininsPharmaceutical PreparationsVirosomesactive targetingcell-based drug delivery systemsengineered erythrocytesmagnetic platformpulmonary drug delivery

Identifiers

PMID36077300
PMCPMC9455992
OpenAlexW4294307818

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.