Seasonal variations in mold identification in medical microbiology laboratories using MSI-2 application, France (2020-2024)
Clicks: 1
ID: 315982
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
0.0
/100
1 views
0 readers
AI Quality Assessment
Not analyzed
Readership in this journal
Ranked #156 of 159 articles by views in medical mycology
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 159 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Molds are ubiquitous environmental microorganisms with major implications for human health, ranging from allergic reactions to invasive infections. Although the environmental seasonality of several fungal spores has long been recognized, its reflection in clinical isolates remains poorly explored. A total of 218,682 fungal spectra generated by 97 medical microbiology laboratories across France between 2020 and 2024 were analyzed, based on identifications performed using the MSI-2 MALDI-TOF MS web platform. Seasonal patterns were assessed through additive decomposition, autocorrelation, and formal statistical testing. Distinct seasonal variation patterns were identified across taxa. Significant seasonality was detected for multiple taxa, including Alternaria, Cladosporium, Aspergillus sections Nigri and Flavi, Talaromyces, several taxa of Basidiomycota, and Rhizopus arrhizus. Positive or negative correlations between fungal identification counts and national mean temperature values were observed depending on the taxon. This study highlights the importance of considering seasonality in understanding the epidemiology of fungal diseases and demonstrates the value of multicenter MALDI-TOF MS data as a tool for epidemiological surveillance.
| Reference Key |
openalex_W7163667295
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Arnaud Jabet, Anne‐Cécile Normand, Laurence Delhaes, Pierre‐Yves Boëlle, Pamela Chauvin, Maria-Alexandra Stoica, Laurence Lachaud, Frédéric Dalle, Lilia Hasseine, Juliette Guitard, Yaye Senghor, Christine Bonnal, Marie Lavollay, Caroline Mahinc, Christine Schuttler, Anne-Pauline Bellanger, Noémie Coron, Françoise Botterel, Cécile Garnaud, Éric Dannaoui, Lucie Limousin, A Huguenin, Edith Mazars, Aymeric Coutard, Jean-Pierre Gangneux, G. Laurent, Damien Dupont, Solene Le Gal, Sébastien Larréché, C. Darles, Boualem Sendid, Sophie Brun, Fabienne Artur, Taïeb Chouaki, Patrice Le Pape, Nicolas Bruffaerts, Pierre Becker, Arnaud Fekkar, Renaud Piarroux, Mold Seasonality MSI-2 Study Group:, Guillaume Aubin, José Duarte Bras Cachinho, Julie Bonhomme, Milène Sasso, Marie Siatkowski, Elena Guillotel, Maxime Moniot, Florence Micas, Safia Nadji, Claire Cottrel, Valérie Letscher-Bru, Mathieu Maillard, Maïté Micaëlo, Océane Marchand, Olivier Augereau, B. Lesimple, Laura Courtellement, Amélie Lesueur, Alexi Lienard, Marie-Sarah Fangous, Céline Tournus, Fabienne Mermet-Jeanvoine, Ali Benabdeljelil, Meggie Guerin, Ann Packeu |
| Journal | medical mycology |
| Year | 2026 |
| DOI |
10.1093/mmy/myag059
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.