MétaCan
Menu
Back to cohort
Record W2916020868 · doi:10.1371/journal.pone.0212995

Manual polishing of 3D printed metals produced by laser powder bed fusion reduces biofilm formation

2019· article· en· W2916020868 on OpenAlexafffund
Marissa McGaffey, Alex zur Linden, Nathanael Bachynski, Michelle L. Oblak, Fiona James, J. Scott Weese

Bibliographic record

VenuePLoS ONE · 2019
Typearticle
Languageen
FieldDentistry
TopicDental materials and restorations
Canadian institutionsUniversity of Guelph
FundersOVC Pet TrustOntario Veterinary College, University of Guelph
KeywordsBiofilmMaterials scienceSurface roughnessScanning electron microscopeAlloyPolishingTitaniumChromiumCobaltMetallurgyAgar plateComposite materialBacteriaBiology

Abstract

fetched live from OpenAlex

Certain 3D printed metals and surface finishes may be better suited for canine patient specific orthopedic implants on the basis of minimizing potential bacterial biofilm growth. Thirty disks each of titanium alloy, stainless steel, and cobalt chromium alloy were 3D printed via laser powder bed fusion. Fifteen disks of each metal were subsequently polished. After incubation with a robust biofilm-forming methicillin-resistant Staphylococcus pseudintermedius isolate, disks were rinsed and sonicated to collect biofilm bacteria. Serial dilutions were plated on blood agar, and colony forming units were counted log (ln) transformed for analysis of variance. Interference microscopy quantified surface roughness for comparison to biofilm growth. Scanning electron microscopy on both pre- and post-sonicated disks confirmed biofilm presence and subsequent removal, and visualized surface features on cleaned disks. Significantly more bacteria grew on rough versus polished metal preparations (p < 0.0001). Titanium alloy had more bacterial biofilm growth compared to cobalt chromium alloy (p = 0.0001) and stainless steel (p < 0.0001). There were no significant growth differences between cobalt chromium alloy and stainless steel (p = 0.4737). Relationships between biofilm growth and surface roughness varied: positive with the rough preparations and negative with the smooth. Polished preparations had increased variance in surface roughness compared to rough preparations, and within disk variance predominated over between disk variance for all preparations with the exception of rough cobalt chromium alloy and rough stainless steel. Using scanning electron microscopy, bacterial biofilms tended to form in crevices. Overall, manual polishing of 3D printed surfaces significantly reduced biofilm growth, with preparation-specific relationships between surface roughness and biofilm growth. These results suggest that metallic implants produced by laser powder bed fusion should be polished. Further research will elucidate the optimal surface roughness per preparation to reduce potential biofilm formation and implant associated infection.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.827

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.028
GPT teacher head0.256
Teacher spread0.228 · 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

Citations30
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuePLoS ONESame topicDental materials and restorationsFrench-language works237,207