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Record W4405965810 · doi:10.3390/jof11010023

Trachemys scripta Eggs as Part of a Potential In Vivo Model for Studying Sea Turtle Egg Fusariosis

2025· article· en· W4405965810 on OpenAlexfundno aff
María Martínez-Ríos, Laura Martín-Torrijos, Javier Diéguez‐Uribeondo

Bibliographic record

VenueJournal of Fungi · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsnot available
FundersConsejo Superior de Investigaciones CientíficasMinisterio de Ciencia e InnovaciónCanadian Institute of Steel Construction
KeywordsBiologyFusariosisZoologyPathogenHatchingFungal pathogenTurtle (robot)IridovirusFusariumEcologyMicrobiologyFisheryFish <Actinopterygii>Botany

Abstract

fetched live from OpenAlex

The fungal pathogens Fusarium keratoplasticum and Fusarium falciforme are responsible for the emerging infectious disease named sea turtle egg fusariosis (STEF). This disease affects all sea turtle species throughout the world, causing low hatching success and mass mortalities. In this study, we investigated the potential use of widely available and easy-to-handle eggs of the invasive alien red-eared slider turtle, Trachemys scripta, as part of an in vivo host model to improve our knowledge of the biological properties of the pathogens responsible of the STEF. Specifically, we performed in vivo experiments, in which T. scripta eggs were challenged with conidia of F. keratoplasticum isolated from diseased sea turtle eggs. We found that the pathogen could colonize and develop similar signs to those observed in nature and fulfill Koch’s postulates. The pathogen showed high virulence properties (e.g., high disease incidence, severity, and low hatching success) and its ability to modify the pH in both the egg surface and culture media, confirming previously described fungal pathogen models. These results support the use of T. scripta as an experimental in vivo host model for studying the biological characteristics of STEF, thus providing valuable insights into the mechanisms underlying the emergence of this fungal disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.266
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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