Evidence map›Paper›PMID 36777573›Full record

ArticleACS omega2023

Tween-20-Modified BiVO

Bo Peng, Yifan Hao, Chao Si, Bo Wang, Chengfeng Luo, Menghao Chen, Cheng Luo, Baijuan Gong, Zhimin Li

Abstract read
In one paragraph

Article in ACS omega, 2023. 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

9 authors.

Bo PengDepartment of Oral Radiology, School of Stomatology, China Medical University, Shenyang 110002, P. R. China.
Yifan HaoDepartment of Oral Radiology, Hospital of Stomatology, Jilin University, Changchun 130021, P. R. China.
Chao SiDepartment of Oral Radiology, Hospital of Stomatology, Jilin University, Changchun 130021, P. R. China.
Bo WangDepartment of Oral Radiology, School of Stomatology, China Medical University, Shenyang 110002, P. R. China.
Chengfeng LuoDepartment of Oral Radiology, School of Stomatology, China Medical University, Shenyang 110002, P. R. China.
Menghao ChenDepartment of Oral Radiology, School of Stomatology, China Medical University, Shenyang 110002, P. R. China.
Cheng LuoDepartment of Orthodontics, School of Stomatology, China Medical University, Shenyang 110002, P. R. China.
Baijuan GongDepartment of Orthodontics, School of Stomatology, China Medical University, Shenyang 110002, P. R. China.
Zhimin LiDepartment of Oral Radiology, School of Stomatology, China Medical University, Shenyang 110002, P. R. China.ORCID https://orcid.org/0000-0003-0892-4999

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oral cancer is the most common malignant tumor in the oral and maxillofacial region, which seriously threatens the health of patients. At present, radiotherapy is one of the commonly used methods for oral cancer treatment. However, the resistance of cancerous tissues to ionizing radiation, as well as the side effects of X-rays on healthy tissues, still limit the application of radiotherapy. Therefore, how to effectively solve the above problems is still a challenge at present. Generally speaking, elements with high atomic numbers, such as bismuth, tungsten, and iodine, have a high X-ray attenuation capacity. Using nanomaterials containing these elements as radiosensitizers can greatly improve the radiotherapy effect. At the same time, the modification of nanomaterials based on the above elements with the biocompatible polymer can effectively reduce the side effects of radiosensitizers, providing a new method for the realization of efficient and safe radiotherapy for oral cancer. In this work, we prepared Tween-20-modified BiVO

Identifiers

PMID36777573
PMCPMC9910094

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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.