Next-Generation Sequencing for Typing and Detection of ESBL and MBL E. coli causing UTI
Bibliographic record
Abstract
Next-generation sequencing (NGS) has the potential to provide typing results and detect resistance genes in a single assay, thus guiding timely treatment decisions and allowing rapid tracking of transmission of resistant clones. We can be evaluated the performance of a new NGS assay during an outbreak of sequence type 131 (ST131) Escherichia coli infections in a teaching hospital. The assay will be performed on 100 extended-spectrum- beta-lactamase (ESBL) E. coli isolates collected from UTI during last 5 years. Typing results will be compared to those of amplified fragment length polymorphism (AFLP), whereby we will be visually assessed the agreement of the Bio-Detection phylogenetic tree with clusters defined by AFLP. A microarray will be considered the gold standard for detection of resistance genes. AFLP will be identified a large cluster of different indistinguishable isolates on adjacent departments, indicating clonal spread. The BioDetection phylogenetic tree will be showed that all isolates of this outbreak cluster will be strongly related, while the further arrangement of the tree also largely agreed with other clusters defined by AFLP. With these experiments we will detect the ESBL and MBL strains and the patient can be prescribed the antibiotics accordingly.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".