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Record W7064157642

Analysis of nutritional status and oral veillonella in caries-free and caries-affected preschool children in Manitoba

2022· dissertation· en· W7064157642 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2022
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsnot available
Fundersnot available
KeywordsVeillonellaStreptococcus salivariusAnaerobic bacteriaStreptococcus sobrinusStreptococcusMicrobiome
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Early childhood caries (ECC) is a widespread, multifactorial disease. Dental decay is a result of low-pH demineralization caused by acidogenic bacteria living in oral biofilms. Nutrition is a key determinant of ECC, as these bacteria require fermentable carbohydrates to grow. Veillonella are important bacteria that facilitate the activity of acidogenic bacteria by removing excess lactate products. A majority of oral microbiome studies focus on the importance of well-known cariogenic bacteria, such as Streptococcus mutans, while few studies have characterized Veillonella in ECC. The purpose of this study was to gain a greater understanding of the relationship between nutrition, oral Veillonella, and ECC. Methods: A case-control study design was used. The nutritional profiles of 158 children (75 caries-free, 83 with ECC) from Manitoba were determined via NutriSTEP (Nutrition Screening Tool for Every Preschooler and Toddler). Veillonella species were assessed using relative abundance data from 16S rRNA sequencing of dental plaque samples. A multivariable logistic regression model was used to estimate the association of ECC with NutriSTEP scores and relative abundance of Veillonella. Results: Caries-affected children tended to be older, established residents, Indigenous, live in rural or remote areas, and have less-educated parents (p ≤ 0.05). Children with ECC had higher total NutriSTEP scores (23.7 ± 6.8) than children without ECC (21.1 ± 6.6; p ≤ 0.05). Relative abundance data revealed significantly higher levels of Veillonella dispar, Streptococcus mutans, and Streptococcus salivarius in caries-affected children (p ≤ 0.05). Children with a high abundance of Veillonella parvula (OR = 2.33; 95% CI: 1.10, 4.91) and greater nutritional risk/NutriSTEP scores (OR = 1.08; 95% CI: 1.02, 1.14) were more likely to experience ECC than children with insignificant levels of the bacteria and lower nutritional risk/NutriSTEP scores. Conclusions: Our findings reflect the importance of Veillonella dispar and Veillonella parvula for ECC, and support a tentative association between oral Veillonella, nutrition, and dental caries. Children with abundant oral Veillonella and greater nutritional risk may be more susceptible to ECC. Future research including metagenomic and mechanistic studies are needed to characterize the causative role of Veillonella in ECC.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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.

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
Published2022
Admission routes1
Has abstractyes

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