Evidence map›Paper›PMID 41654589›Full record

ArticleScientific reports2026

Design and implementation of an open-access arsenic biosensor.

Javier Gasulla, Adrian I Teijeiro, Ezequiel J Alba Posse, Alejandro D Nadra

Abstract read
In one paragraph

Article in Scientific reports, 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

4 authors.

Javier GasullaFacultad de Ciencias Exactas y Naturales, Departamento de Fisiología, Biología Molecular y Celular, Instituto de Biociencias, Biotecnología y Biología Traslacional, Universidad de Buenos Aires, Buenos Aires, Argentina.
Adrian I TeijeiroFacultad de Arquitectura, Diseño y Urbanismo, Universidad de Buenos Aires, Cátedra Louzau, Buenos Aires, Argentina.
Ezequiel J Alba PosseFacultad de Ciencias Exactas y Naturales, Departamento de Fisiología, Biología Molecular y Celular, Instituto de Biociencias, Biotecnología y Biología Traslacional, Universidad de Buenos Aires, Buenos Aires, Argentina.
Alejandro D NadraFacultad de Ciencias Exactas y Naturales, Departamento de Fisiología, Biología Molecular y Celular, Instituto de Biociencias, Biotecnología y Biología Traslacional, Universidad de Buenos Aires, Buenos Aires, Argentina. anadra@fbmc.fcen.uba.ar.

Funding

Agencia Nacional de Promoción Científica y Tecnológica PICT-2015-3834Universidad de Buenos Aires PDE 24, 2024
6 · The paper itself

Abstract

Arsenic contamination in groundwater is a critical global issue, affecting over 140 million people worldwide and posing severe public health risks, particularly in low-resource and rural communities. Argentina alone has approximately 4 million people exposed to arsenic. The measurement of arsenic in private wells is often limited by high costs, specialized personnel requirements, and geographical distances to analytical laboratories. In this paper, we describe the design and implementation of a portable, open-access arsenic biosensor that combines synthetic biology and industrial design. The biosensor employs genetically modified Escherichia coli and a colorimetric readout to detect arsenic concentrations as low as 5 µg/L. Validation studies on 61 samples yielded a sensitivity of 98.1% and specificity of 99.0%. By using paper-based, dehydrated bacterial modules and a 3D-printed housing, this device is cost-effective, easy to use, and amenable to replication in low-resource settings. In addition, the open-access approach ensures that critical knowledge such as plasmid sequences, device schematics, and protocols can be freely shared and locally adapted. Beyond the technical advantages, this biosensor can potentially influence global policies and Argentinian programs on water quality monitoring, empowering communities to take charge of arsenic surveillance and safeguard public health.

Indexed as

ArsenicBiosensing TechniquesEnvironmental MonitoringWater Pollutants, ChemicalArgentinaColorimetryEscherichia coliGroundwaterArsenicWater Pollutants, ChemicalArsenicBiosensorColorimetric detectionE. coli whole-cell biosensorGroundwater monitoringOpen source hardwareWhole cellµPAD

Identifiers

PMID41654589
PMCPMC12946344

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.