Antimicrobial Susceptibility and Genomic Profiles of Multidrug-Resistant Staphylococcus aureus from Nasopharynx of Asymptomatic Children in Dhaka, Bangladesh
Bibliographic record
Abstract
Children carrying Staphylococcus aureus in their nasopharynx are at a higher risk of contracting systemic infection. Due to lack of sufficient information regarding such carriage, this study was conducted to explore the prevalence, antibiotic susceptibility, and genomic profiles of S. aureus isolated from nasopharyngeal samples of 163 randomly selected asymptomatic Bangladeshi children aged from 5–<15 years. Antibiotic susceptibility pattern and genomic analysis of the samples were conducted using standard microbiological methods and genomic tools. The carriage was confirmed in 44 (27%) children who were mostly well nourished without respiratory symptoms in the last 3 months. Higher carriage was observed among the younger age group (5–<10 years) who completed vaccines for pneumonia (p = 0.002) and influenza (p = 0.004). Among the isolates, 84.1% were multidrug-resistant and 47.5% (n = 40) were methicillin-resistant S. aureus (MRSA). All the isolates (100%) were resistant to cefixime with higher resistance to ampicillin (95.5%) and penicillin (90.9%). Among the three investigated isolates, two were ST80 (ID-1 and ID-52) and one was a novel strain (ID-19) with the presence of aph-Stph, blaI, blaZ, dha1, fosB, lmrS, mepA, norA, and tet38 genes. The current research demonstrates a high incidence of multidrug-resistant S. aureus and reports the first instance of ST80 in asymptomatic children in Bangladesh.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 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".