Evidence map›Paper›PMID 42423900›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Integrating Maker Technology with Research: DIY Continuous Flow Colorimetric Detector with Integrated Data Acquisition and Processing.

Adam Ee Xian Loh, Kheng Soo Tay

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. 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

2 authors.

Adam Ee Xian LohDepartment of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia.
Kheng Soo TayDepartment of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia. khengsoo@um.edu.my.ORCID https://orcid.org/0000-0003-1402-6175

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Continuous flow analysis (CFA) offers a robust platform for real-time chemical monitoring and analysis, but the high cost and complexity of commercial systems limit their usage. This chapter describes a practical, low-cost, and reproducible approach for developing a continuous flow colorimetric detection system using open-source electronics, 3D-printed components, and custom data processing software. The setup incorporates a peristaltic pump, an Arduino-controlled solenoid valve, and an AS7341 visible light sensor aligned with a flow-through cuvette. A key innovation of this system is the integration of a Python-based algorithm to process real-time absorbance data and automatically identify and exclude interference-induced signal artifacts. This method enables low-cost detection of colorimetric changes in flowing samples and is particularly suited for biological and chemical analyses involving colorimetric detection, as well as educational settings. The system's modular design allows for easy customization, and its reproducibility makes it useful for dissemination across teaching laboratories or low-resource research environments.

Indexed as

ColorimetryAlgorithmsEquipment DesignSoftwareArduinoAS7341 sensorBubble correctionColorimetric detectionDIY analytical instrumentsFlow injection analysisOpen-source hardwarePeristaltic pumpSolenoid valve

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.