Evidence map›Paper›PMID 39691450›Full record

ArticleCyborg and bionic systems (Washington, D.C.)2023

Emulation of Brain Metabolic Activities Based on a Dynamically Controllable Optical Phantom.

Yuxiang Lin, Cheng Chen, Zhouchen Ma, Nabil Sabor, Yanyan Wei, Tianhong Zhang, Mohamad Sawan, Guoxing Wang, Jian Zhao

Abstract read
In one paragraph

Article in Cyborg and bionic systems (Washington, D.C.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Article
  9. Article
  10. 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

9 authors.

Yuxiang LinDepartment of Micro-Nano Electronics, Shanghai Jiao Tong University, Shanghai, China.
Cheng ChenDepartment of Micro-Nano Electronics, Shanghai Jiao Tong University, Shanghai, China.ORCID https://orcid.org/0000-0001-9239-9490
Zhouchen MaDepartment of Micro-Nano Electronics, Shanghai Jiao Tong University, Shanghai, China.
Nabil SaborElectrical Engineering Department, Faculty of Engineering, Assiut University, Assiut, Egypt.
Yanyan WeiShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tianhong ZhangShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Mohamad SawanCenBRAIN Neurotech, School of Engineering, Westlake University, Hangzhou, China.
Guoxing WangDepartment of Micro-Nano Electronics, Shanghai Jiao Tong University, Shanghai, China.
Jian ZhaoDepartment of Micro-Nano Electronics, Shanghai Jiao Tong University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a dynamic optical phantom for the simulation of metabolic activities in the brain, and a linear equivalent model is built for control voltage versus substance concentration. A solid-solid dynamic optical phantom is realized by using liquid crystal film as a voltage-controlled light intensity regulator on the surface of basic phantom, which uses epoxy resin as matrix material and nanometer carbon powder and titanium dioxide powder as absorption and scattering dopants, respectively. The dynamic phantom could mimic near-infrared spectrum (NIRS) signals with sampling rate up to 10 Hz, and the maximum simulation errors for oxy-hemoglobin and deoxy-hemoglobin concentrations varying in the range of 1 μmol/l are 7.0% and 17.9%, respectively. Compared with similar solid biomimetic phantoms, the adjustable mimic substance concentration range is extended by an order of magnitude, which meets the simulation requirements of most brain NIRS signals.

Identifiers

PMID39691450
PMCPMC11651414

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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.