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Record W3210674623 · doi:10.3390/ani11113058

Evidence of Hearing Loss and Unrelated Toxoplasmosis in a Free-Ranging Harbour Porpoise (Phocoena phocoena)

2021· article· en· W3210674623 on OpenAlexaff
Maria Morell, Lonneke L. IJsseldijk, Alinda J. Berends, Andrea Gröne, Ursula Siebert, Stephen Raverty, Robert E. Shadwick, Marja Kik

Bibliographic record

VenueAnimals · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicToxoplasma gondii Research Studies
Canadian institutionsMinistry of AgricultureMinistry of HealthUniversity of British Columbia
Fundersnot available
KeywordsPhocoenaPorpoiseToxoplasmosisBiologyPathologyHistopathologyAnatomyCochleaAudiogramHearing lossMedicineAudiologyHarbour

Abstract

fetched live from OpenAlex

Evidence of hearing impairment was identified in a harbour porpoise (Phocoena phocoena) on the basis of scanning electron microscopy. In addition, based on histopathology and immunohistochemistry, there were signs of unrelated cerebral toxoplasmosis. The six-year old individual live stranded on the Dutch coast at Domburg in 2016 and died a few hours later. The most significant gross lesion was multifocal necrosis and haemorrhage of the cerebrum. Histopathology of the brain revealed extensive necrosis and haemorrhage in the cerebrum with multifocal accumulations of degenerated neutrophils, lymphocytes and macrophages, and perivascular lymphocytic cuffing. The diagnosis of cerebral toxoplasmosis was confirmed by positive staining of protozoa with anti-Toxoplasma gondii antibodies. Tachyzoites were not observed histologically in any of the examined tissues. Ultrastructural evaluation of the inner ear revealed evidence of scattered loss of outer hair cells in a 290 µm long segment of the apical turn of the cochlea, and in a focal region of ~ 1.5 mm from the apex of the cochlea, which was compatible with noise-induced hearing loss. This is the first case of concurrent presumptive noise-induced hearing loss and toxoplasmosis in a free-ranging harbour porpoise from the North Sea.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.001
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 head0.041
GPT teacher head0.292
Teacher spread0.251 · 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 designBench or experimental
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

Citations5
Published2021
Admission routes1
Has abstractyes

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