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Record W4391716629 · doi:10.1186/s12903-024-03980-w

Precise control of digital dental unit to reduce aerosol and splatter production: new challenges for future epidemics

2024· article· en· W4391716629 on OpenAlexfundno aff
Yuedi Yu, Xueling Wu, Yang Sun

Bibliographic record

VenueBMC Oral Health · 2024
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchCollege of Dental Medicine, Columbia UniversityNational Natural Science Foundation of China
KeywordsAerosolSplashViral loadMedicineEnvironmental scienceDentistryVirologyMechanical engineeringMeteorologyEngineeringPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: During dental procedures, critical parameters, such as cooling condition, speed of the rotary dental turbine (handpiece), and distance and angle from pollution sources, were evaluated for transmission risk of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), simulated by spiking in a plasmid encoding a modified viral spike protein, HexaPro (S6P), in droplets and aerosols. METHODS: To simulate routine operation in dental clinics, dental procedures were conducted on a dental manikin within a digital dental unit, incorporating different dental handpiece speeds and cooling conditions. The tooth model was immersed in Coomassie brilliant blue dye and was pre-coated with 100 μL water spiked-in with S6P-encoding plasmid. Furthermore, the manikin was surrounded by filter papers and Petri dishes positioned at different distances and angles. Subsequently, the filter papers and Petri dishes were collected to evaluate the aerosol splash points and the viral load of S6P-encoding plasmid in aerosols and splatters generated during the dental procedure. RESULTS: Aerosol splashing generated a localized pollution area extended up to 60 cm, with heightened contamination risks concentrated within a 30 cm radius. Significant differences in aerosol splash points and viral load by different turbine handpiece speeds under any cooling condition (P < 0.05) were detected. The highest level of aerosol splash points and viral load were observed when the handpiece speed was set at 40,000 rpm. Conversely, the lowest level of aerosol splash point and viral load were found at a handpiece speed of 10,000 rpm. Moreover, the aerosol splash points with higher viral load were more prominent in the positions of the operator and assistant compared to other positions. Additionally, the position of the operator exhibited the highest viral load among all positions. CONCLUSIONS: To minimize the spread of aerosol and virus in clinics, dentists are supposed to adopt the minimal viable speed of a dental handpiece with limited cooling water during dental procedures. In addition, comprehensive personal protective equipment is necessary for both dental providers and dental assistants.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.135
GPT teacher head0.425
Teacher spread0.290 · 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
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

Citations5
Published2024
Admission routes1
Has abstractyes

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