Evidence map›Paper›PMID 41562349›Full record

ReviewACS infectious diseases2026

Biosensor-Based Platforms for the Detection and Screening of

Augusto César Parreiras de Jesus, Ana Laura Grossi de Oliveira, Flavia Di Scala, Cristiane Alves da Silva Menezes, Lilian Lacerda Bueno, Bart van Grinsven, Rocio Arreguin-Campos, Ricardo Toshio Fujiwara, Thomas J Cleij

Abstract readReview
In one paragraph

Review in ACS infectious diseases, 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

9 authors.

Augusto César Parreiras de JesusSensor Engineering Department, Faculty of Science and Engineering, Maastricht University, Duboisdomein 30, 6200MD Maastricht, The Netherlands.ORCID 0000-0002-2445-220X
Ana Laura Grossi de OliveiraPost-Graduate Program in Infectious Diseases and Tropical Medicine, School of Medicine, Federal University of Minas Gerais, Av. Prof. Alfredo Balena 190, 30130-100 Belo Horizonte, Brazil.
Flavia Di ScalaSensor Engineering Department, Faculty of Science and Engineering, Maastricht University, Duboisdomein 30, 6200MD Maastricht, The Netherlands.
Cristiane Alves da Silva MenezesDepartment of Clinical and Toxicological Analysis, Faculty of Pharmacy, Federal University of Minas Gerais, Av. Pres. Antônio Carlos 6627, 31270-901 Belo Horizonte, Brazil.
Lilian Lacerda BuenoPost-Graduate Program in Infectious Diseases and Tropical Medicine, School of Medicine, Federal University of Minas Gerais, Av. Prof. Alfredo Balena 190, 30130-100 Belo Horizonte, Brazil.ORCID 0000-0003-3510-4590
Bart van GrinsvenSensor Engineering Department, Faculty of Science and Engineering, Maastricht University, Duboisdomein 30, 6200MD Maastricht, The Netherlands.ORCID 0000-0002-6939-0866
Rocio Arreguin-CamposSensor Engineering Department, Faculty of Science and Engineering, Maastricht University, Duboisdomein 30, 6200MD Maastricht, The Netherlands.ORCID 0000-0002-6727-4749
Ricardo Toshio FujiwaraPost-Graduate Program in Infectious Diseases and Tropical Medicine, School of Medicine, Federal University of Minas Gerais, Av. Prof. Alfredo Balena 190, 30130-100 Belo Horizonte, Brazil.ORCID 0000-0002-4713-575X
Thomas J CleijSensor Engineering Department, Faculty of Science and Engineering, Maastricht University, Duboisdomein 30, 6200MD Maastricht, The Netherlands.ORCID 0000-0003-0172-9330

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Leprosy remains an important neglected tropical disease with about 200,000 new cases detected annually worldwide. Although the disease is highly responsive to treatment, a timely and accurate diagnosis continues to be a critical barrier to disease control. Traditional diagnostic methods, including PCR, bacilloscopy, histopathology, and serology, are hindered by limited sensitivity, procedural complexity, and restricted accessibility in resource-constrained settings. This review summarizes studies from the past decade on biosensor-based strategies for leprosy diagnosis. Biosensor platforms for leprosy include electrochemical, piezoelectric, and optical systems, with recent innovations encompassing immunosensors, biomimetic, and DNA-based approaches, some achieving diagnostic accuracies above 90%. These platforms employ different bioreceptors such as conjugated peptides, DNA probes, and molecularly imprinted polymers. Certain platforms can also differentiate paucibacillary from multibacillary cases, addressing a critical limitation of the current methods. These capabilities highlight the potential of biosensors as powerful tools for point-of-care testing. However, clinical translation is constrained by challenges such as affordability, robustness under field conditions, and the lack of large-scale validation studies. Additional operational barriers, including regulatory approval, supply chain logistics, and user training, must also be addressed. Future progress will depend on multidisciplinary strategies, integrating novel biomarker discovery as recognition elements and exploring detection systems previously used for other mycobacterial and infectious diseases. Large multicenter trials and user-centered design approaches are essential for clinical implementation. By overcoming these challenges, biosensors have the potential to redefine leprosy diagnostics, enabling earlier detection and improved surveillance, and accelerating progress toward global elimination goals.

Indexed as

Biosensing TechniquesLeprosyMycobacterium lepraeHumansRapid Diagnostic Testsbiosensorsdiagnostic techniques and procedureselectrochemical techniquesleprosyMycobacterium lepraeneglected tropical diseasespoint-of-care systems

Identifiers

PMID41562349
PMCPMC12910598

What Socratic holds

Textmetadata
LicenceCC BY
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.