Rapid in situ imaging and whole genome sequencing of biofilm in neonatal feeding tubes: A clinical proof of concept
Bibliographic record
Abstract
The bacterial flora of nasogastric feeding tubes and faecal samples were analysed for a low-birth weight (725 g) neonate EGA 25 weeks in intensive care. Samples were collected at age 6 and 8 weeks of life. Optical coherence tomography (OCT) was used to visualise bacterial biofilms inside the nasogastric feeding tubes. The biofilm was heterogeneously distributed along the tube lumen wall, and had a depth of up to 500 µm. The bacterial biofilm and faecal samples included Enterococcus faecalis and Enterobacter hormaechei. Representative strains, recovered from both feeding tubes and faecal samples, were whole genome sequenced using Illumina, Mi-Seq, which revealed indistinguishable strains, each with less than 28 SNP differences, of E. faecalis and E. hormaechei. The E. faecalis strains were from two sequence types (ST191 and ST211) and encoded for a number of traits related to biofilm formation (BopD), adherence (Epb pili), virulence (cps loci, gelatinase, SprE) and antibiotic resistances (IsaA, tetM). The E. hormaechei were all ST106, and encoded for blaACT-15 β-lactamase and fosfomycin resistance (fosA). This proof of concept study demonstrates that bacterial flora within the neonatal feeding tubes may influence the bacterial colonisation of the intestinal tract and can be visualised non-destructively using OCT.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".