Evidence map›Paper›PMID 41744749›Full record

ReviewBiosensors2026

Fungal Frontiers in (Bio)sensing.

Gerardo Grasso

Abstract readReview
In one paragraph

Review in Biosensors, 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

1 author.

Gerardo GrassoIstituto per lo Studio dei Materiali Nanostrutturati, Sede Roma-Sapienza, Consiglio Nazionale delle Ricerche, P.le Aldo Moro 5, 00185 Rome, Italy.ORCID 0000-0002-4886-7362

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Filamentous fungi are increasingly recognized as versatile biological platforms for the development of advanced (bio)sensing technologies, owing to their extensive secretory capacity, material-forming ability, and intrinsic bioelectrical activity. This review critically surveys recent progress in fungal-based sensing within a multiscale framework spanning molecular, material, computational, and ecological domains, with particular emphasis on developments reported over the past five years. Key advances involving secretome-derived biomolecules, mycogenic nanomaterials, mycelium-based living materials, and fungal electrophysiology are discussed alongside emerging approaches for environmental monitoring that integrate sensor networks, imaging platforms, and data-driven analytics. Collectively, these works demonstrate that fungal systems can enhance biosensor sensitivity, selectivity, and sustainability, while enabling unconventional paradigms of signal transduction, material-integrated sensing, and biologically mediated computation. At larger spatial and temporal scales, mycelial growth dynamics and electrical activity provide measurable responses to mechanical, chemical, and environmental perturbations, supporting early applications in wearable devices, structural materials, and ecosystem monitoring. Despite significant progress, challenges remain in reproducibility, long-term stability, mechanistic understanding, and scalable device integration. Overall, the evidence reviewed highlights filamentous fungi as biologically adaptive and ecologically embedded systems with substantial potential to support next-generation (bio)sensing technologies, while underscoring the need for integrative approaches that combine biological insight with materials science, electronics, and artificial intelligence.

Indexed as

artificial intelligencebio-inspired computingfungal electrophysiologyfungal secretomeliving sensorsmycelium-based materialsmycosynthesiswood wide net

Identifiers

PMID41744749
PMCPMC12938827

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.