Evidence map›Paper›PMID 41542956›Full record

ReviewMycoses2026

Infrared Spectroscopy as a Promising Tool for Diagnosing and Typing Human Pathogenic Fungi.

Anthony G J Medeiros, Ayrton L F Nascimento, Luana Rossato, Daniel Assis Santos, Nalu Teixeira de Aguiar Peres, Reginaldo Goncalves de Lima Neto, Jacques F Meis, Kássio M G Lima, Rafael Wesley Bastos

Abstract readReview
In one paragraph

Review in Mycoses, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. UnmaskingPathogens (Basel, Switzerland) · 2026
    Article
  4. Differentiation ofFrontiers in microbiology · 2026
    Article
  5. Review
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.

Anthony G J MedeirosCentro de Biociências, Universidade Federal Do Rio Grande Do Norte, Natal, Brazil.ORCID https://orcid.org/0009-0000-0495-1477
Ayrton L F NascimentoLaboratório de Química Biológica e Quimiometria, Instituto de Química, Universidade Federal Do Rio Grande Do Norte, Natal, Brazil.ORCID https://orcid.org/0000-0001-6922-3825
Luana RossatoLaboratório de Pesquisa Em Ciências da Saúde, Universidade Federal da Grande Dourados, Dourados, Brazil.ORCID https://orcid.org/0000-0002-6115-3313
Daniel Assis SantosLaboratório de Micologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.ORCID https://orcid.org/0000-0002-1108-5666
Nalu Teixeira de Aguiar PeresLaboratório de Micologia, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
Reginaldo Goncalves de Lima NetoMedicina Tropical Do Centro de Ciências Médicas da, Universidade Federal de Pernambuco, Recife, Brazil.ORCID https://orcid.org/0000-0002-8846-877X
Jacques F MeisInstitute of Translational Research, Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), excellence Center for Medical Mycology (ECMM), University of Cologne, Cologne, Germany.ORCID https://orcid.org/0000-0003-3253-6080
Kássio M G LimaLaboratório de Química Biológica e Quimiometria, Instituto de Química, Universidade Federal Do Rio Grande Do Norte, Natal, Brazil.ORCID https://orcid.org/0000-0002-3827-3800
Rafael Wesley BastosCentro de Biociências, Universidade Federal Do Rio Grande Do Norte, Natal, Brazil.ORCID https://orcid.org/0000-0001-6781-9617

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 303762/2020-9Conselho Nacional de Desenvolvimento Científico e Tecnológico 309210/2025-9Conselho Nacional de Desenvolvimento Científico e Tecnológico 405934/2022Conselho Nacional de Desenvolvimento Científico e Tecnológico 444501/2023-1Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 001Fundação Norte-Rio-Grandense de Pesquisa e Cultura 06/2023Ministry of Health
6 · The paper itself

Abstract

Fungal infections are increasingly recognised as a global health challenge, responsible for millions of cases annually and substantial mortality, especially in immunocompromised individuals. Yet, the diagnosis of these infections remains notoriously difficult, often delayed by slow culture-based methods or hindered by the high cost and infrastructure demands of molecular diagnostics. In recent years, infrared (IR) spectroscopy has emerged as a promising alternative, offering rapid, cost-effective and reagent-free identification of human pathogenic fungi. This review provides an in-depth examination of how IR-based techniques, specifically, mid-infrared (MIR) and near-infrared (NIR) spectroscopy, are being applied in medical mycology. We explore the underlying chemical principles and highlight how recent advances in multivariate analysis and machine learning have enhanced their diagnostic accuracy. Studies have demonstrated the capacity of IR spectroscopy to accurately identify and type major fungal pathogens, while also providing insights into antifungal resistance profiles and outbreak tracking. While challenges remain, particularly regarding protocol standardisation and expansion of spectral databases, IR spectroscopy stands out as a valuable diagnostic strategy, especially in resource-limited settings. By reducing diagnostic time and cost, and expanding accessibility, IR-based methods have the potential to transform the clinical management of fungal infections, contributing to faster decision-making and improved patient outcomes.

Indexed as

FungiMycosesHumansMycological Typing TechniquesSpectrophotometry, InfraredSpectroscopy, Near-InfraredBiotyperfungal identificationinfrared radiationmedical mycology

Identifiers

PMID41542956
PMCPMC12809877

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.