Evidence map›Paper›PMID 35023300›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2022

Intelligent SERS Navigation System Guiding Brain Tumor Surgery by Intraoperatively Delineating the Metabolic Acidosis.

Ziyi Jin, Qi Yue, Wenjia Duan, An Sui, Botao Zhao, Yinhui Deng, Yuting Zhai, Yuwen Zhang, Tao Sun, Guang-Ping Zhang and 5 more

Open access · goldAbstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

24 citing papers in PubMed, 77 citations in OpenAlex.

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  15. Advancements in Neurosurgical Intraoperative Histology.Tomography (Ann Arbor, Mich.) · 2024
    Review
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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

15 authors at 3 institutions in 3 countries.

Ziyi JinKey Laboratory of Smart Drug Delivery Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai, 201203, China.ORCID 0000-0002-3115-7225
Qi YueDepartment of neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Wenjia DuanKey Laboratory of Smart Drug Delivery Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai, 201203, China.
An SuiSchool of Information Science and Technology, Fudan University, Shanghai, 200438, China.
Botao ZhaoInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Yinhui DengSchool of Information Science and Technology, Fudan University, Shanghai, 200438, China.
Yuting ZhaiInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Yuwen ZhangInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Tao SunKey Laboratory of Smart Drug Delivery Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai, 201203, China.
Guang-Ping ZhangSchool of Physics and Electronics, Shandong Normal University, Jinan, 250358, China.
Limei HanKey Laboratory of Smart Drug Delivery Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai, 201203, China.
Ying MaoDepartment of neurosurgery, Huashan Hospital, Fudan University, Shanghai, 200040, China.
Jinhua YuSchool of Information Science and Technology, Fudan University, Shanghai, 200438, China.
Xiao-Yong ZhangInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.ORCID 0000-0001-8965-1077
Cong LiKey Laboratory of Smart Drug Delivery Ministry of Education, State Key Laboratory of Medical Neurobiology, School of Pharmacy, Fudan University, Shanghai, 201203, China.ORCID 0000-0001-7731-8031
Fudan University · CNShanghai Medical College of Fudan University · CNShandong Normal University · CN

Funding

Double First Class University Plan IDH1232075Ministry of Science and Technology of China 2018YFE0118800National Key Research & Development Project,National Natural Science Foundation of China 81771895National Natural Science Foundation of China 81873893National Natural Science Foundation of China 91959127National Natural Science Foundation of China 92159304National Science Fund for Distinguished Young Scholars 82025019Program of Shanghai Science and Technology Committee 18441900600Program of Shanghai Science and Technology Committee 19431900400Program of Shanghai Science and Technology Committee 20ZR1407800Science and Technology Commission of Shanghai Municipality 2018SHZDZX01Shanghai Center for Brain Science and Brain-Inspired Technology
6 · The paper itself

Abstract

Surgeons face challenges in intraoperatively defining margin of brain tumors due to its infiltrative nature. Extracellular acidosis caused by metabolic reprogramming of cancer cells is a reliable marker for tumor infiltrative regions. Although the acidic margin-guided surgery shows promise in improving surgical prognosis, its clinical transition is delayed by having the exogenous probes approved by the drug supervision authority. Here, an intelligent surface-enhanced Raman scattering (SERS) navigation system delineating glioma acidic margins without administration of exogenous probes is reported. With assistance of this system, the metabolites at the tumor cutting edges can be nondestructively transferred within a water droplet to a SERS chip with pH sensitivity. Homemade deep learning model automatically processes the Raman spectra collected from the SERS chip and delineates the pH map of tumor resection bed with increased speed. Acidity correlated cancer cell density and proliferation level are demonstrated in tumor cutting edges of animal models and excised tissues from glioma patients. The overall survival of animal models post the SERS system guided surgery is significantly increased in comparison to the conventional strategy used in clinical practice. This SERS system holds the promise in accelerating clinical transition of acidic margin-guided surgery for solid tumors with infiltrative nature.

Indexed as

AcidosisBrain NeoplasmsGliomaAnimalsHumansMargins of ExcisionSpectrum Analysis, Ramanartificial intelligencebrain tumormetabolic acidosissurface enhanced Raman spectroscopysurgery navigation system

Identifiers

PMID35023300
PMCPMC8895125
OpenAlexW4205438376

What OpenQuestion holds

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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 OpenQuestion graph.