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Record W3089459709

INVESTIGATION OF THE SUBCLINICAL TOXICOLOGICAL EFFECTS OF ERGOT ALKALOID MYCOTOXIN (Claviceps purpurea) EXPOSURE IN BEEF COWS AND BULLS

2020· dissertation· en· W3089459709 on OpenAlexaboutno aff
Vanessa Cowan

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2020
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and fungal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsClaviceps purpureaMycotoxinSubclinical infectionBiologyAlkaloidToxicologyAnimal scienceFood scienceBotany
DOInot available

Abstract

fetched live from OpenAlex

In my dissertation, I examine the effects of ergot alkaloid mycotoxins on vascular and reproductive systems in beef cows and bulls. Ergot alkaloids are toxic secondary metabolites produced by the pathogenic plant fungus Claviceps purpurea. Ergot alkaloids are commonly occurring adulterating toxins in livestock feed and constitute a great concern for the health of animals that consume such feeds. Consumption of these toxins can cause a broad suite of pathophysiological effects. Relevant and up-to-date scientific information on ergotism in livestock is largely unavailable to address this growing issue. The purpose of this research was to better characterize and understand the effects of ergot alkaloids in Canadian beef cattle and to ascertain concentrations at which these effects may occur.\nIn my first two chapters, beef cows were fed increasing concentrations of ergot alkaloids over a short-term (Chapter 2) and long-term (Chapter 3) basis. As ergot alkaloids have a well-known vasoactive effect, hemodynamics of different arteries were evaluated with ultrasonography (B-mode and Doppler). In both studies, concentration-dependent, subclinical physiological changes in hemodynamics were observed in the caudal artery. These results are significant as a common end-stage manifestation of ergot alkaloid mycotoxicosis is the ischemic necrosis of the tail of exposed cattle. Further, these results indicate that subclinical changes occur at concentrations below current Canadian permissible values. Therefore, vascular changes appear to be the more sensitive indicator of ergot exposure than plasma prolactin changes in cows. Plasma or serum prolactin concentration is an accepted biomarker of ergot alkaloid exposure in livestock. \n To address the lack of pharmacokinetic information available on ergot alkaloids in cattle, I conducted two oral pharmacokinetics studies and attempted to develop an analytical method to detect ergot alkaloids in bovine plasma (Chapter 4). Although the method was promising for spiked plasma, ergot alkaloids were not detected in plasma samples collected from ergot-exposed cows. Likely, low oral bioavailability explained the lack of detection of ergot alkaloids in plasma from ergot-exposed cattle. An important practical conclusion of this work is that blood samples from suspected poisoning cases will not be clinically useful. \n In my last research chapter (Chapter 5), adult beef bulls were fed diets containing ergot alkaloids for one spermatogenic cycle (i.e., 61 days) to assess the potential negative effects of ergot exposure on sperm production or function. Results of this study indicated that ergot exposure had, at most, a subtle effect on bull sperm endpoints. However, plasma prolactin was affected by treatment. Spermatogenesis is not a sensitive endpoint for ergot exposure in adult bulls. Overall, this work answered questions related to ergot alkaloid exposure that are practically important. This work will enable policy makers to make scientifically-based decisions on guidelines for ergot alkaloids in cattle feed; will bolster the working knowledge of clinicians diagnosing and treating ergot-exposed cattle in the field; and will provide the much sought after information for producers working with ergot-contaminated grain or ergot exposed animals.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.174
Teacher spread0.163 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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