Evidence map›Paper›PMID 40940745›Full record

ArticleCells2025

Doxorubicin-Loaded Nanoparticle Treatment Enhances Diffuse Large B-Cell Lymphoma Cell Death.

Ihab Abd-Elrahman, Noha Khairi, Taher Nassar, Riki Perlman, Dina Ben Yehuda

Abstract read
In one paragraph

Article in Cells, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Ihab Abd-ElrahmanDepartment of Hematology, Hadassah Medical Center, Jerusalem 9112001, Israel.ORCID 0000-0003-2012-2024
Noha KhairiDepartment of Hematology, Hadassah Medical Center, Jerusalem 9112001, Israel.
Taher NassarFaculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9112001, Israel.
Riki PerlmanDepartment of Hematology, Hadassah Medical Center, Jerusalem 9112001, Israel.
Dina Ben YehudaDepartment of Hematology, Hadassah Medical Center, Jerusalem 9112001, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug resistance remains a major obstacle in cancer treatment despite advances in therapeutic regimens. To address this, we explored the potential of Doxorubicin (Dox) delivery in poly (lactide-co-glycolic acid) (PLGA) nanoparticles to enhance Diffuse large B-cell lymphoma (DLBCL) cell death. This research investigates the potential of Doxorubicin and advanced delivery methods. We used PLGA nanoparticles with Oleyl cysteineamide (OCA); its amphiphilic nature enables interfacial anchoring and thiol surface functionalization of PLGA NPs. Compared to PLGA-NPs, PLGA-OCA-NPs enhance immunity and induce tumor cell death. They also show significant apoptotic cell death and induced immune responses in DLBCL mouse models. Dox-conjugated PLGA-OCA-NPs (DOX-OCA) exhibit significant in vitro and in vivo anticancer activity compared to free DOX, showing remarkable antitumor effects with reduced systemic toxicity in mouse models. Our findings underscore the promising potential of PLGA-OCA-NPs in DLBCL treatment, offering a hopeful future in cancer therapy. This innovative delivery system offers enhanced immune responses and effectively addresses toxicity concerns, marking a significant step forward in cancer therapy.

Indexed as

DoxorubicinLymphoma, Large B-Cell, DiffuseNanoparticlesAnimalsApoptosisCell DeathCell Line, TumorDrug CarriersFemaleHumansMicePolylactic Acid-Polyglycolic Acid CopolymerDoxorubicinDrug CarriersPolylactic Acid-Polyglycolic Acid Copolymercancer therapyDLBCLdoxorubicindrug deliveryoleyl cysteineamidePLGA nanoparticles

Identifiers

PMID40940745
PMCPMC12428780

What OpenQuestion holds

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Registered trials

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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.