Evidence map›Paper›PMID 39852068›Full record

ArticleBiosensors2025

Glucose Sensor Design Based on Monte Carlo Simulation.

Gang Xue, Ruiping Zhang, Yihao Chen, Wei Xu, Changxing Zhang

Abstract read
In one paragraph

Article in Biosensors, 2025. 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

5 authors.

Gang XueFaculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China.
Ruiping ZhangLaboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China.ORCID 0009-0009-9441-3271
Yihao ChenLaboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China.
Wei XuFaculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China.
Changxing ZhangFaculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China.ORCID 0000-0001-8751-0342

Funding

National Natural Science Foundation of China 12162017 and 12272022
6 · The paper itself

Abstract

Continuous glucose monitoring based on the minimally invasive implantation of glucose sensor is characterized by high accuracy and good stability. At present, glucose concentration monitoring based on fluorescent glucose capsule sensor is a new development trend. In this paper, we design a fluorescent glucose capsule sensor with a design optimization study. The motion trajectory of incident light in the fluorescent gel layer is simulated based on the Monte Carlo method, and the cloud maps of light intensity with the light intensity distribution at the light-receiving layer are plotted. Altering the density of fluorescent molecules, varying the thickness of tissue layers, and adjusting the angle of incidence deflection, the study investigates the influence of these parameter changes on the optimal position of reflected light at the bottom. Finally, the simulation results were utilized to design and fabricate a fluorescent glucose capsule sensor. Rabbit subcutaneous tissue glucose level tests and real-time glucose solution concentration monitoring experiments were performed. This work contributes to the real-time monitoring of glucose levels and opens up new avenues for research on fabricating glucose sensors.

Indexed as

Biosensing TechniquesGlucoseAnimalsBlood GlucoseEquipment DesignMonte Carlo MethodRabbitsBlood GlucoseGlucosebiosensorglucose sensorMonte Carlo simulationreal-time monitoring

Identifiers

PMID39852068
PMCPMC11763743

What OpenQuestion holds

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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.