Evidence map›Paper›PMID 39339158›Full record

ReviewPharmaceutics2024

A Review of the Efficacy of Nanomaterial-Based Natural Photosensitizers to Overcome Multidrug Resistance in Cancer.

Jagadeesh Rajaram, Lokesh Kumar Mende, Yaswanth Kuthati

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

3 authors.

Jagadeesh RajaramDepartment of Biochemistry and Molecular Medicine, National Dong Hwa University, Hualien 974, Taiwan.ORCID 0000-0003-0824-2293
Lokesh Kumar MendeDepartment of Anesthesiology, Cathy General Hospital, Taipei 106, Taiwan.
Yaswanth KuthatiDepartment of Anesthesiology, Cathy General Hospital, Taipei 106, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Natural photosensitizers (PS) are compounds derived from nature, with photodynamic properties. Natural PSs have a similar action to that of commercial PSs, where cancer cell death occurs by necrosis, apoptosis, and autophagy through ROS generation. Natural PSs have garnered great interest over the last few decades because of their high biocompatibility and good photoactivity. Specific wavelengths could cause phytochemicals to produce harmful ROS for photodynamic therapy (PDT). However, natural PSs have some shortcomings, such as reduced solubility and lower uptake, making them less appropriate for PDT. Nanotechnology offers an opportunity to develop suitable carriers for various natural PSs for PDT applications. Various nanoparticles have been developed to improve the outcome with enhanced solubility, optical adsorption, and tumor targeting. Multidrug resistance (MDR) is a phenomenon in which tumor cells develop resistance to a wide range of structurally and functionally unrelated drugs. Over the last decade, several researchers have extensively studied the effect of natural PS-based photodynamic treatment (PDT) on MDR cells. Though the outcomes of clinical trials for natural PSs were inconclusive, significant advancement is still required before PSs can be used as a PDT agent for treating MDR tumors. This review addresses the increasing literature on MDR tumor progression and the efficacy of PDT, emphasizing the importance of developing new nano-based natural PSs in the fight against MDR that have the required features for an MDR tumor photosensitizing regimen.

Indexed as

multidrug resistancenanotechnologynatural PSsphotodynamic therapy

Identifiers

PMID39339158
PMCPMC11434998

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.