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Record W3177122029 · doi:10.1097/md.0000000000026369

PHoral: Effects of carnosine supplementation on quantity/quality of oral salivae in healthy volunteer and in subjects affected by common oral pathologies

2021· article· en· W3177122029 on OpenAlexaboutno aff
Michele M. Ciulla, Dino Re, Ettore Gilardoni, Alfonsina D’Amato, Alessandra Altomare, Giovanna Baron, Stefano Carugo, Giancarlo Aldini

Bibliographic record

VenueMedicine · 2021
Typearticle
Languageen
FieldMedicine
TopicBiochemical effects in animals
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOral MicrobiomeSalivaCarnosinePopulationMicrobiomeOral cavityPhysiologyDiseaseInternal medicineDentistryBioinformaticsEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Diseases of the oral cavity (OC) with an infectious trigger such as caries and periodontal disease are extremely common in the general population and can also have effects at the cardiovascular level. The oral salivary flow, with its buffering capacity, is able to regulate the pH of the OC and, therefore, significantly contribute to the ecological balance of the microenvironment in which the oral microbiome (OM) develops. On the other side, when the quality/quantity of salivary flow is altered it is supposed the disruption of this balance with the potential increase in oral pathogens and triggered diseases. Among the endogenous substances able to exert a significant effect on the salivary flow and its characteristics, carnosine (Car), a dipeptide originally isolated in skeletal muscle, represents, thanks to the known buffering properties, a promising principle. METHODS: We aimed this protocol to evaluate the quantitative/qualitative characteristics of the salivary flow in healthy volunteer subjects (n = 20) and in subjects suffering from common OC pathologies (n = 40), before and after 7 days of supplementation with SaliflussTM (Metis Healthcare srl, Milan, Italy), a Class I medical device on the market as 400 mg mucoadhesive oral tablets that has Car as the main ingredient. DISCUSSION: Combining the characteristics of saliva with the OM and comparing them with OC pathologies, we expect to clarify their reciprocal relationship and, using quantitative proteomics techniques, to help clarify the mechanism of action of Car.

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)0.002
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 score0.290
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.385
Teacher spread0.351 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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