Evidence map›Paper›PMID 33381047›Full record

ArticleFrontiers in pharmacology2020

pH-Sensitive and Long-Circulation Nanoparticles for Near-Infrared Fluorescence Imaging-Monitored and Chemo-Photothermal Synergistic Treatment Against Gastric Cancer.

Yun Zhou, Xuanzi Sun, Liansuo Zhou, Xiaozhi Zhang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 27% of its field
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

8 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Article
  3. Enhanced Persistent Luminescence from CrNanomaterials (Basel, Switzerland) · 2025
    Article
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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

4 authors at 2 institutions in 1 country.

Yun ZhouDepartment of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an Jiaotong University, Xi'an, China.
Xuanzi SunDepartment of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an Jiaotong University, Xi'an, China.
Liansuo ZhouCollege of Clinical Medicine, Xi'an Medical University, Xi'an, China.
Xiaozhi ZhangDepartment of Radiation Oncology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an Jiaotong University, Xi'an, China.
First Affiliated Hospital of Xi'an Jiaotong University · CNXi'an Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastrectomy is the primary therapeutic option for gastric cancer. Postoperative treatment also plays a crucial role. The strategy to improve the postoperative prognosis of gastric cancer requires a combined system that includes a more efficient synergistic treatment and real-time monitoring after surgery. In this study, photothermal-chemotherapy combined nanoparticles (PCC NPs) were prepared via π-π stacking to perform chemo-photothermal synergistic therapy and continuous imaging of gastric cancer. PCC NPs had a spherical morphology and good monodispersity under aqueous conditions. The hydrodynamic diameter of PCC NPs was 59.4 ± 3.6 nm. PCC NPs possessed strong encapsulation ability, and the maximum drug loading rate was approximately 37%. The NPs exhibited extraordinary stability and pH-response release profiles. The NPs were rapidly heated under irradiation. The maximum temperature was close to 58°C. PCC NPs showed good biocompatibility both

Indexed as

chemotherapycontinuous imaginggastric cancerphotothermal therapysynergistic treatment

Identifiers

PMID33381047
PMCPMC7768901
OpenAlexW3107692888

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.