Bibliographic record
Abstract
Sir: Dr. Myckatyn et al.’s comments regarding our article reflect the challenges of reporting biofilm analyses in scanning electron microscopy studies. The current definition of biofilm includes two main elements: (1) bacterial cells irreversibly attached to a living or inert surface/interface and (2) an extracellular polymeric substance matrix, comprising noncellular and abiotic components, produced by these cells.1 Biofilms cannot be simply regarded as an aggregate of bacteria; in our article, we described the biofilms using features and terms found across the medical and industrial literature. In our study, we observed thick biofilms presenting as acellular layers; importantly, the outer borders of our samples do in fact reveal bacteria in variable amounts, progressively embedded inside the maturing biofilm (Fig. 1). Biofilm characterization was performed by obtaining multiple high-magnification images before concluding that the thick acellular slime was the result of bacterial production.Fig. 1: Maturing biofilm. (Left) The thicker part of the biofilm is located on the left side of the image and is in complete continuity with the right side, where bacteria are still visible, along with a leukocyte and a red blood cell (original magnification, × 3000, with a working distance of 11.68 mm). (Right) Matured and thick porous biofilm showing variable cell size of bacteria (original magnification, × 3000, with a working distance of 9.93 mm).Bacteria with a sessile phenotype secrete the extracellular polymeric substances, which are composed of variable amounts of polysaccharide proteins, nucleic acids, lipids, and other biopolymers. Biofilm may also contain red blood cells and leukocytes. Its overall thickness may be up to 50 to 100 μm because of the layering of multiple stacks of bacteria, which themselves measure only 0.2 to 2 μm.2,3 Moreover, the sessile bacteria phenotype is induced by the most turbulent flow conditions.1 Biofilm that develops during exposure to high shear stress demonstrates a modified composition that is characteristically thicker and stronger.4 In catheter and implant infections, Staphylococcus aureus produces a slimy biofilm, whereas in vitro the extracellular polymeric substance production is inconsistent.5 Therefore, the direct comparison of human periprosthetic samples and bacteria grown in a petri dish as presented by Dr. Myckatyn is not acceptable, as physiologic and nurturing conditions are completely different. We believe that the shear stress induced by early inflation of the expander contributes to alteration in bacteria phenotype and their extracellular polymeric substance expression, thereby potentially rendering them thicker. Biofilms observed in human conditions cannot be considered equivalent to in vitro biofilms. Importantly, the precise science and implications of biofilm are still under investigation; moving forward, it is essential to synthesize the relevant findings found across multiple platforms in various scientific domains to further advance our knowledge in this field. Only then will a clear consensus on definitions and ultrastructural descriptions be possible. DISCLOSURE Dr. Danino is a consultant and speaker for Allergan, Inc. The other authors have no commercial associations or financial interests to declare with respect to any of the information or products presented in this communication. Operational study costs were partially supported by an Allergan, Inc., industry research grant. Jean-Philippe Giot, M.D., Ph.D. Laurence S. Paek, M.D. M. Alain Danino, M.D., Ph.D. Division of Plastic and Reconstructive Surgery University of Montreal Hospital Center Université de Montréal Montreal, Quebec, Canada
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.014 | 0.022 |
| Insufficient payload (model declined to judge) | 0.020 | 0.017 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".