Evidence map›Paper›PMID 41255463›Full record

ReviewInternational journal of nanomedicine2025

Subcellular Organelle-Targeted Drug Delivery of Photodynamic Therapy and Gas-Photodynamic Combination Therapy.

Xuhui Zhang, Jing Wang, Sijia Wang, Lei Fu, Xiaofan Du, Qiangzhou Rong, Cuiping Yao, Jing Xin

Abstract readReview
In one paragraph

Review in International journal of nanomedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

8 authors.

Xuhui Zhang *Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Photonics and Sensing, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, People's Republic of China.
Jing WangKey Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Photonics and Sensing, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, People's Republic of China.
Sijia WangKey Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Photonics and Sensing, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, People's Republic of China.
Lei FuKey Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Photonics and Sensing, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, People's Republic of China.
Xiaofan DuKey Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Photonics and Sensing, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, People's Republic of China.
Qiangzhou RongKey Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Photonics and Sensing, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, People's Republic of China.
Cuiping YaoKey Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Photonics and Sensing, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, People's Republic of China.ORCID 0000-0002-7110-0696
Jing Xin *Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Biomedical Photonics and Sensing, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Photodynamic therapy (PDT), as a clinically viable non-invasive modality for tumor treatment, is characterized by precise spatiotemporal control with minimal systemic toxicity. The therapeutic efficacy of PDT is critically contingent upon subcellular photosensitizer localization, attributable to the restricted diffusion radius of reactive oxygen species (ROS, 20-40 nm). Consequently, the development of organelle-targeted drug delivery systems constitutes an essential strategy for PDT optimization. Nevertheless, the clinical translation of PDT remains constrained by inherent physicochemical and pathophysiological barriers, even following targeting refinement. These constraints-predominantly limited tissue penetration depth (<1 cm) and hypoxia-mediated therapeutic resistance-have driven the development of combinatorial therapeutic approaches. Among emerging strategies, gas-enhanced PDT has gained prominence due to its bifunctional capacity to modulate tumor pathophysiology and potentiate photosensitizer activity. The application of biocompatible gaseous agents enhances therapeutic outcomes through enhanced tumoral drug accumulation, amplified ROS generation, tumor microenvironment modulation, and reversal of multidrug resistance mechanisms. This review systematically evaluates organelle-targeted PDT delivery mechanisms, advanced strategies for gas-PDT synergistic therapy, and spatiotemporally controlled gas prodrug platforms. Collectively, these approaches establish subcellular precision medicine as a transformative paradigm for tumor therapy.

Indexed as

Drug Delivery SystemsGasesNeoplasmsOrganellesPhotochemotherapyPhotosensitizing AgentsAnimalsHumansProdrugsReactive Oxygen SpeciesTumor MicroenvironmentGasesPhotosensitizing AgentsProdrugsReactive Oxygen Speciesgas therapyphotodynamic therapysubcellular organelle-targeted

Identifiers

PMID41255463
PMCPMC12620582

What OpenQuestion holds

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LicenceCC BY-NC
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.