Evidence map›Paper›PMID 40853620›Full record

ArticleJournal of fluorescence2025

Reliable and Reproducible Protocol for Evaluating Detection Sensitivity in Bioimaging Systems Using Near-Infrared Fluorescent Dyes.

Qinglai Yan, Zhaotai Gu, Nana Li, Qinyuan Zhang, Siyue Wu, Haozhi Yang, Junyu Ren

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Article in Journal of fluorescence, 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
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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

7 authors.

Qinglai YanZhejiang Institute of Medical Device Supervision and Testing, Hangzhou, 310018, Zhejiang, China. jimyan820504@163.com.
Zhaotai GuGuangdong OptoMedic Technologies, Inc, Foshan, 528200, Guangdong, China.
Nana LiGuangdong OptoMedic Technologies, Inc, Foshan, 528200, Guangdong, China.
Qinyuan ZhangZhejiang Institute of Medical Device Supervision and Testing, Hangzhou, 310018, Zhejiang, China.
Siyue WuGuangdong OptoMedic Technologies, Inc, Foshan, 528200, Guangdong, China.
Haozhi YangGuangdong OptoMedic Technologies, Inc, Foshan, 528200, Guangdong, China.
Junyu RenGuangdong OptoMedic Technologies, Inc, Foshan, 528200, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The traditional method of establishing the relationship between fluorescence brightness and dye concentration through concentration gradient, and evaluating the sensitivity of imaging detection is too repetitive and cumbersome, and is obviously affected by handwork. Therefore, the reliability and reproducibility of the data are low. This work provides a standard concentration and imaging luminance relationship curve for equipment manufacturers through concentration preparation and detection quantification by authoritative institutions based on indocyanine green dye. It only needs to detect the excitation light power and simulated fluorescence radiation of the equipment in the imaging system, and find the relationship curve to obtain the relationship between "radiation and concentration" and "signal-to-background ratio-concentration", which can be used as a quantitative basis for the camera system. All operations can achieve traceability operation, which greatly reduces the human experimental error, and provides reliable evidence for the detection sensitivity evaluation of bioimaging system based on fluorescent dyes.

Indexed as

Fluorescent DyesIndocyanine GreenInfrared RaysOptical ImagingHumansReproducibility of ResultsFluorescent DyesIndocyanine GreenIndocyanine greenNear-infrared fluorescence imagingQuantitative standardizationRadiometric calibrationSimulation of near-infrared fluorescence

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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.