Detection of enteric‐ and non‐enteric adenoviruses in gastroenteritis patients, Bangladesh, 2012‐2015
Bibliographic record
Abstract
Human adenoviruses (HAdVs) are common cause of nonbacterial acute gastroenteritis worldwide. Limited data exist on HAdVs molecular epidemiology associated with acute gastroenteritis in Bangladesh. We describe the genetic diversity and epidemiology of HAdVs among hospitalized diarrhea patients, including HAdV genotypes, clinical symptoms, and co-infecting enteric pathogens. Stool samples were collected from ongoing diarrhea surveillance during 2012-2015. HAdV was detected using PCR and genotyped by sequencing and phylogenetic analysis. Detailed socio-demographic and clinical information regarding each individual was recorded such as duration of diarrhea, dehydration status, vomiting, abdominal pain, fever, and severity. Of 871 fecal specimens, HAdV DNA was detected in 93 (10.7%). Among them 56% were co-infected with other known enteric viral and bacterial pathogens and 31.6% had severe gastroenteritis. The majority (55%) of HAdV positives were children <5 years of age. Two main clinical symptoms in HAdV infected patients were diarrhea and vomiting. HAdVs were detected throughout the year with low prevalence in winter (November-January). Five HAdV species (A, B, C, D, and F) including 17 different genotypes were identified during the study period, with enteric HAdV species F (HAdV-40/41) being the most dominant. However, non-enteric HAdV were also detected in substantial proportion of specimens (15% species C, 15% species D, 10.8% species A, and 4.3% species B). Our study demonstrates high genetic diversity of HAdVs including enteric and non-enteric HAdVs among diarrhea patients and provides a foundation for further clarification of the role of non-enteric HAdVs in diarrheal diseases.
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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 | 0.000 | 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 | 0.000 |
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".