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Record W2753512692

PROTEOMIC ANALYSIS OF BOVINE MILK PROTEINS TO IDENTIFY PUTATIVE BIOMARKERS OF Staphylococcus aureus SUBCLINICAL MASTITIS

2017· dissertation· en· W2753512692 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Atrium (University of Guelph) · 2017
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolism and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsStaphylococcus aureusMastitisSubclinical infectionMicrobiologyBiologyBacteriaVirologyGenetics
DOInot available

Abstract

fetched live from OpenAlex

Bovine mastitis remains a primary focus of dairy cattle disease research due to its negative economic impact on the dairy industry. In Canada, total losses are estimated more than four hundred million dollars per year, or about 15 % of the industry’s total net revenue. Clinical mastitis is associated with visible local and systemic signs of inflammation of the udder. In contrast, subclinical mastitis (SCM) lacks clinical signs and often leads to persistent and chronic infections that represent a serious problem to the dairy industry. Staphylococcus aureus is the most common contagious pathogen associated with bovine SCM. Current diagnosis of S. aureus SCM is based on bacteriological culture of milk samples and somatic cell counts both of have limitations. The main objective of this study was to identify, characterize and quantify the differential expression of whey proteins in milk samples collected from healthy control cows and cows that are infected with S. aureus SCM utilizing different proteomic approaches. The first study characterized variations in the composition of the whey proteome in healthy and S. aureus mastitic milk samples using an optimized fractionation strategy to enrich for low- abundance proteins. Fractionation of the whey proteins using low speed ultracentrifugation resulted in partial depletion of casein and minimized protein losses. In addition, two-dimensional difference gel electrophoresis enhanced the separation and resolution of low abundant whey proteins. In the second study, 2D-DIGE coupled with liquid chromatography and tandem mass spectrometry (LC-MS/MS) showed the differentially expressed proteomic signatures of S. aureus-positive whey fractions compared to samples from healthy controls. Twenty-eight upregulated proteins in mastitic milk were identified, 11 of which had related host defense functions. In the third study, quantitative proteomic analyses using direct LC-MS/MS and label-free quantification resulted in identification of 90 proteins in both control and mastitic milk samples of which 25 proteins were differentially regulated including pathogen-recognition and acute phase proteins. The comprehensive proteomic and bioinformatics analyses resulted in four candidate biomarkers including cathelicidin-4, haptoglobin, cathepsin B and lactotransferrin for mastitis diagnosis that also provide insight to understanding the role of milk proteins in host-pathogen interaction during S. aureus intramammary infection.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.704

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 science0.0010.000
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 head0.014
GPT teacher head0.287
Teacher spread0.272 · 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