Evidence map›Paper›PMID 41386764›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

A Closed-Loop Hybrid Discovery System of Type I Photosensitizers for Hypoxic Tumor Therapy.

Xia Ling, Yixin Zhu, Min Li, Zongliang Xie, Lei Cao, Wentao Song, Dandan Wang, Duo Mao, Xiaonan Wang, Bin Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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. Article
  2. A Closed-Loop Hybrid Discovery System of Type I Photosensitizers for Hypoxic Tumor Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    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

10 authors.

Xia LingJoint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou, 350207, China.
Yixin ZhuDepartment of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, 117585, Singapore.
Min LiInstitute of Precision Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou, 510080, China.
Zongliang XieDepartment of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, 117585, Singapore.
Lei CaoJoint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou, 350207, China.
Wentao SongJoint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou, 350207, China.
Dandan WangJoint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou, 350207, China.
Duo MaoInstitute of Precision Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou, 510080, China.
Xiaonan WangDepartment of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
Bin LiuJoint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou, 350207, China.ORCID https://orcid.org/0000-0002-0956-2777

Funding

College of Design and Engineering, National University of Singapore A-0009163-01-00National Key R&D Program of China 2022ZD0117501Tan Chin Tuan Centennial Professorship E-467-00-0012-02Tsinghua Initiative Scientific Research Program
6 · The paper itself

Abstract

Type I photosensitizers (PSs), which operate effectively under low-oxygen conditions, offer a promising approach to overcome hypoxia-associated challenges in solid tumor therapy. However, their design remains challenging due to the limited number of reported molecules with diverse structures, as well as insufficient understanding of the underlying mechanisms. Herein, a closed-loop hybrid discovery system is developed that combines molecular excited-state calculations with machine learning (ML) to rationally design and predict high-performance Type I PSs for hypoxic tumor therapy. Through a support vector machine (SVM) classification model, 664 potential Type I PSs are identified from a molecular space based on donor-acceptor (D-A) and donor-acceptor-donor (D-A-D) structures. Among these, two candidates, M1 and M2, are synthesized and experimentally verified as Type I PSs, exhibiting aggregate-induced enhancement of Type I reactive oxygen species (ROS) generation. Both in vitro and in vivo studies demonstrated their ability to induce intracellular Type I ROS generation and effectively suppress tumor growth. The work highlights the potential of ML in the design and prediction of Type I PSs for hypoxic tumor therapy.

Indexed as

NeoplasmsPhotosensitizing AgentsTumor HypoxiaAnimalsCell Line, TumorHumansMiceReactive Oxygen SpeciesPhotosensitizing AgentsReactive Oxygen Speciesclosed‐loop hybrid discovery systemhypoxic tumor therapymachine learningType І photosensitizer

Identifiers

PMID41386764
PMCPMC12903996

What OpenQuestion holds

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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 OpenQuestion graph.