Tracking Age-Linked Antibiotic Resistance Patterns through Building-Level Wastewater Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Antimicrobial resistance (AMR) is a global health challenge, and monitoring different demographic populations can improve our understanding of its spread and prevalence in urban settlements. This study applies building-level wastewater-based epidemiology (WBE) to analyze the resistome and mobilome of age-segregated populations from an elementary school (School), a university residence (UnivRes), and an elderly care facility (ElderlyRes) all located in Girona (Catalonia, Spain). Metagenomic analyses were subsequently conducted to investigate differences in bacterial communities, antibiotic resistance genes (ARGs), and mobile genetic elements (MGEs). The results revealed age-linked variations in the relative abundance and diversity of ARGs. The wastewater collected at the School exhibited the highest abundance of ARGs, while the ElderlyRes showed the highest diversity. Furthermore, sequences affiliated with bacterial pathogens were more prevalent in samples from both the School and the ElderlyRes, emphasizing potential public health implications. Among the 12 bacterial genera most strongly correlated with ARGs (Pearson R > 0.7), 11 were identified as members of the gut microbiota, underscoring their predominant role as reservoirs of resistance compared to bacteria of environmental origin. By integrating localized wastewater sampling with metagenomics, our study uncovers demographic-specific resistome patterns, delivering actionable evidence to strengthen AMR surveillance and intervention strategies in urban populations.
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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) | 0.002 | 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 it