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Record W3091198580 · doi:10.3390/microorganisms8101507

Treponema spp. Isolated from Bovine Digital Dermatitis Display Different Pathogenicity in a Murine Abscess Model

2020· article· en· W3091198580 on OpenAlexafffund
Rakel Arrazuria, Cameron G. Knight, Priyoshi Lahiri, Eduardo R. Cobo, Herman W. Barkema, Jeroen De Buck

Bibliographic record

VenueMicroorganisms · 2020
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsUniversity of Calgary
FundersAlberta Agriculture and Forestry
KeywordsTreponemaAbscessLesionInoculationBiologyLamenessMicrobiologyPathogenicityImmunologyMedicinePathologySurgerySyphilis

Abstract

fetched live from OpenAlex

Digital dermatitis (DD) causes lameness in cattle with substantial negative impact on sustainability and animal welfare. Although several species of Treponema bacteria have been isolated from various DD stages, their individual or synergistic roles in the initiation or development of lesions remain largely unknown. The objective of this study was to compare effects of the three most common Treponema species isolated from DD lesions in cattle (T. phagedenis, T. medium and T. pedis), both as individual and as mixed inoculations, in a murine abscess model. A total of 109 or 5 × 108Treponema spp. were inoculated subcutaneously, and produced abscess was studied after 7 days post infection. There were no synergistic effects when two or three species were inoculated together; however, T. medium produced the largest abscesses, whereas those produced by T. phagedenis were the smallest and least severe. Treponema species were cultured from skin lesions at 7 days post infection and, additionally, from the kidneys of some mice (2/5), confirming systemic infection may occur. Taken together, these findings suggest that T. medium and T. pedis may have more important roles in DD lesion initiation and development than T. phagedenis.

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 score0.303
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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

Citations13
Published2020
Admission routes2
Has abstractyes

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