Evidence map›Paper›PMID 38002287›Full record

ArticleBiomolecules2023

Machine Learning Technology for EEG-Forecast of the Blood-Brain Barrier Leakage and the Activation of the Brain's Drainage System during Isoflurane Anesthesia.

Oxana Semyachkina-Glushkovskaya, Konstantin Sergeev, Nadezhda Semenova, Andrey Slepnev, Anatoly Karavaev, Alexey Hramkov, Mikhail Prokhorov, Ekaterina Borovkova, Inna Blokhina, Ivan Fedosov and 15 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomolecules, 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
0.6field-weighted citation impact, top 32% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

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

25 authors at 1 institution in 2 countries.

Oxana Semyachkina-GlushkovskayaDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.ORCID 0000-0001-6753-7513
Konstantin SergeevInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Nadezhda SemenovaInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Andrey SlepnevInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Anatoly KaravaevInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Alexey HramkovInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Mikhail ProkhorovInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.ORCID 0000-0003-4069-9410
Ekaterina BorovkovaInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.ORCID 0000-0002-9621-039X
Inna BlokhinaDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.ORCID 0000-0003-1517-0857
Ivan FedosovInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Alexander ShirokovDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.ORCID 0000-0003-4321-735X
Alexander DubrovskyInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Andrey TerskovDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Maria ManzhaevaDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Valeria KrupnovaDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Alexander DmitrenkoDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Daria ZlatogorskayaDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Viktoria AdushkinaDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Arina EvsukovaDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Matvey TuzhilkinDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.ORCID 0009-0007-7450-7022
Inna ElizarovaDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Egor IlyukovInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Dmitry MyagkovInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Dmitry TuktarovInstitute of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Jürgen KurthsDepartment of Biology, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov, Russia.
Saratov State University · RU

Funding

Russian Ministry of Science and High Education 075-15-2022-1094Russian Science Foundation 23-75-30001; 21-75-10088
6 · The paper itself

Abstract

Anesthesia enables the painless performance of complex surgical procedures. However, the effects of anesthesia on the brain may not be limited only by its duration. Also, anesthetic agents may cause long-lasting changes in the brain. There is growing evidence that anesthesia can disrupt the integrity of the blood-brain barrier (BBB), leading to neuroinflammation and neurotoxicity. However, there are no widely used methods for real-time BBB monitoring during surgery. The development of technologies for an express diagnosis of the opening of the BBB (OBBB) is a challenge for reducing post-surgical/anesthesia consequences. In this study on male rats, we demonstrate a successful application of machine learning technology, such as artificial neural networks (ANNs), to recognize the OBBB induced by isoflurane, which is widely used in surgery. The ANNs were trained on our previously presented data obtained on the sound-induced OBBB with an 85% testing accuracy. Using an optical and nonlinear analysis of the OBBB, we found that 1% isoflurane does not induce any changes in the BBB, while 4% isoflurane caused significant BBB leakage in all tested rats. Both 1% and 4% isoflurane stimulate the brain's drainage system (BDS) in a dose-related manner. We show that ANNs can recognize the OBBB induced by 4% isoflurane in 57% of rats and BDS activation induced by 1% isoflurane in 81% of rats. These results open new perspectives for the development of clinically significant bedside technologies for EEG-monitoring of OBBB and BDS.

Indexed as

AnesthesiaAnesthetics, InhalationIsofluraneAnimalsBlood-Brain BarrierBrainElectroencephalographyMaleRatsAnesthetics, InhalationIsofluraneanesthesiablood–brain barrierbrain’s drainage systemmachine learning technologyspectral power analysis

Identifiers

PMID38002287
PMCPMC10669477
OpenAlexW4388226961

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.