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Record W4364381166 · doi:10.1016/j.jtumed.2023.03.014

Applications of Metformin in Dentistry—A review

2023· review· en· W4364381166 on OpenAlexaff
Muhammad Khawaja Hammad Uddin, Muhammad Shahrukh Khan Sadiq, Ashfaq Ahmed, Mariam Khan, Tooba Maniar, Syeda Mamoona Mateen, Bilquees Saba, Syed Muhammad Kashif, Shumaila Usman, Shariq Najeeb, Zohaib Khurshid, Muhammad Sohail Zafar

Bibliographic record

VenueJournal of Taibah University Medical Sciences · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsWestern University
Fundersnot available
KeywordsMetforminMedicineDentistryPeriodontitisOsseointegrationDiabetes mellitusClinical trialOsteoblastImplantInternal medicineSurgeryEndocrinology

Abstract

fetched live from OpenAlex

Metformin is a versatile drug with numerous medical uses. It is known primarily as an anti-hyperglycemic drug that has become the main oral blood-glucose-lowering medication for managing type 2 diabetes mellitus globally. Its use has been reported in a variety of oral conditions and dentistry in general. Recent clinical trials have indicated the effectiveness of adjunct topical application of metformin in improving the periodontal parameters of patients with diabetes and periodontitis. Additionally, studies have suggested that metformin stimulates odontogenic differentiation and mineral synthesis of stem cells in the tooth pulp. Metformin also stimulates osteoblast proliferation, decreases osteoclast activity and exerts regenerative effects on periodontal bone, thus making it a viable candidate for periodontal regeneration. Metformin monotherapy significantly enhances osseointegration of endosseous implants and has been reported to have anti-cancer effects on oral squamous cell carcinoma by impeding tumor progression. Animal studies have indicated that metformin improves orthodontic tooth movement and resists orthodontic appliance corrosion. This narrative review aims to provide a current summary of research highlighting the prospective uses of metformin in dentistry.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.065
GPT teacher head0.378
Teacher spread0.313 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2023
Admission routes1
Has abstractyes

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