Evidence map›Paper›PMID 38375317›Full record

ArticleMaterials today. Bio2024

Slow and steady wins the race: Fractionated near-infrared treatment empowered by graphene-enhanced 3D scaffolds for precision oncology.

Giordano Perini, Valentina Palmieri, Andrea Papait, Alberto Augello, Daniela Fioretti, Sandra Iurescia, Monica Rinaldi, Elsa Vertua, Antonietta Silini, Riccardo Torelli and 6 more

Abstract read
In one paragraph

Article in Materials today. Bio, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

16 authors.

Giordano PeriniDipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy.
Valentina PalmieriFondazione Policlinico Universitario A. Gemelli IRCSS, 00168, Rome, Italy.
Andrea PapaitFondazione Policlinico Universitario A. Gemelli IRCSS, 00168, Rome, Italy.
Alberto AugelloFondazione Policlinico Universitario A. Gemelli IRCSS, 00168, Rome, Italy.
Daniela FiorettiIstituto di Farmacologia Traslazionale (IFT), Dipartimento di Scienze Biomediche, CNR, 00133, Rome, Italy.
Sandra IuresciaIstituto di Farmacologia Traslazionale (IFT), Dipartimento di Scienze Biomediche, CNR, 00133, Rome, Italy.
Monica RinaldiIstituto di Farmacologia Traslazionale (IFT), Dipartimento di Scienze Biomediche, CNR, 00133, Rome, Italy.
Elsa VertuaCentro di Ricerca Eugenia Menni, Fondazione Poliambulanza Istituto Ospedaliero, 25124, Brescia, Italy.
Antonietta SiliniCentro di Ricerca Eugenia Menni, Fondazione Poliambulanza Istituto Ospedaliero, 25124, Brescia, Italy.
Riccardo TorelliDipartimento di Scienze di Laboratorio e Infettivologiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy.
Angela CarlinoDipartimento di Medicina e Chirurgia, Università Internazionale San Camillo per la Salute e le Scienze Mediche (Unicamillus), 00131, Rome, Italy.
Teresa MusarraUnità di Patologia Testa e Collo, Polmone e Endocrinologia, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, 00168, Rome, Italy.
Maurizio SanguinettiDipartimento di Scienze di Laboratorio e Infettivologiche, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy.
Ornella ParoliniFondazione Policlinico Universitario A. Gemelli IRCSS, 00168, Rome, Italy.
Marco De SpiritoDipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy.
Massimiliano PapiDipartimento di Neuroscienze, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Surgically addressing tumors poses a challenge, requiring a tailored, multidisciplinary approach for each patient based on the unique aspects of their case. Innovative therapeutic regimens combined to reliable reconstructive methods can contribute to an extended patient's life expectancy. This study presents a detailed comparative investigation of near-infrared therapy protocols, examining the impact of non-fractionated and fractionated irradiation regimens on cancer treatment. The therapy is based on the implantation of graphene oxide/poly(lactic-co-glycolic acid) three-dimensional printed scaffolds, exploring their versatile applications in oncology by the examination of pro-inflammatory cytokine secretion, immune response, and in vitro and in vivo tumor therapy. The investigation into cell death patterns (apoptosis vs necrosis) underlines the pivotal role of protocol selection underscores the critical influence of treatment duration on cell fate, establishing a crucial parameter in therapeutic decision-making. In vivo experiments corroborated the profound impact of protocol selection on tumor response. The fractionated regimen emerged as the standout performer, achieving a substantial reduction in tumor size over time, surpassing the efficacy of the non-fractionated approach. Additionally, the fractionated regimen exhibited efficacy also in targeting tumors in proximity but not in direct contact to the scaffolds. Our results address a critical gap in current research, highlighting the absence of a standardized protocol for optimizing the outcome of photodynamic therapy. The findings underscore the importance of personalized treatment strategies in achieving optimal therapeutic efficacy for precision cancer therapy.

Indexed as

3D printed scaffoldsCancer therapyGraphene oxideNear-infrared radiationPhotodynamic therapy

Identifiers

PMID38375317
PMCPMC10875229

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.