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Record W2077771769 · doi:10.1186/s12953-015-0068-3

Towards further defining the proteome of mouse saliva

2015· article· en· W2077771769 on OpenAlex
Anne Blanchard, Peyman Ezzati, Dmitry Shamshurin, Andreea Nistor, Etienne Leygue, John A. Wilkins, Yvonne Myal

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProteome Science · 2015
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSalivaProteomeProteomicsEnsemblBiologySalivary ProteinsComputational biologyFunction (biology)GeneBioinformaticsGenomeGeneticsGenomicsBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Knowledge of the mouse salivary proteome is not well documented and as a result, very limited. Currently, several salivary proteins remain unidentified and for some others, their function yet to be determined. The goal of the present study is to utilize mass spectrometry analysis to widen our knowledge of mouse salivary proteins, and through extensive database searches, provide further insight into the array of proteins that can be found in saliva. A comprehensive mouse salivary proteome will also facilitate the development of mouse models to study specific biomarkers of many human diseases. RESULTS: Individual saliva samples were collected from male and female mice, and later pooled according to sex. Two pools of saliva from female mice (2 samples/pool) and 2 pools of saliva from male mice were used for analysis utilizing high performance liquid chromatograph mass spectrometry (nano-RPLC-MS/MS). The resulting datasets identified 345 proteins: 174 proteins were represented in saliva obtained from both sexes, as well as 82 others that were more female specific and 89 that were more male specific. Of these sex linked proteins, twelve were identified as exclusively sex-limited; 10 unique to males and 2 unique to females. Functional analysis of the 345 proteins identified 128 proteins with catalytic activity characteristics; indicative of proteins involved in digestion, and 35 proteins associated with stress response, host defense, and wound healing functions. Submission of the list of 345 proteins to the BioMart data mining tool in the Ensembl database further allowed us to identify a total of 283 orthologous human genes, of which, 131 proteins were recently reported to be present in the human salivary proteome. CONCLUSIONS: The present study is the most comprehensive list to date of the proteins that constitute the mouse salivary proteome. The data presented can serve as a useful resource for identifying potentially useful biomarkers of human health and 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.

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 score0.072
Threshold uncertainty score0.221

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.037
GPT teacher head0.295
Teacher spread0.258 · 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