First human case report of sepsis due to infection with Streptococcus suis serotype 31 in Thailand
Bibliographic record
Abstract
BACKGROUND: Streptococcus suis is a zoonotic pathogen that causes invasive infections in humans and pigs. It has been reported that S. suis infection in humans is mostly caused by serotype 2. However, human cases caused by other serotypes have rarely been reported. This is the first report of a human case of infection with S. suis serotype 31 in Thailand. CASE PRESENTATION: A 55-year-old male alcohol misuser with liver cirrhosis was admitted with sepsis to a hospital in the Central Region of Thailand. He had consumed a homemade, raw pork product prior to the onset of illness. He was alive after treatment with ceftriaxone and no complication occurred. An isolate from blood culture at the hospital was suspected as viridans group Streptococcus. It was confirmed at a reference laboratory as S. suis serotype 31 by biochemical tests, 16S rDNA sequencing, and multiplex polymerase chain reaction for serotyping, but it was untypable by the co-agglutination test with antisera against recognized S. suis serotypes, suggesting loss of capsular material. The absence of a capsule was confirmed by transmission electron microscopy. The isolate was confirmed to be sequence type 221, with 13 putative virulence genes that are usually found in serotype 2 strains. CONCLUSION: We should be aware of the emergence of S. suis infections caused by uncommon serotypes in patients with predisposing conditions. Laboratory capacity to identify S. suis in the hospital is needed in developing countries, which can contribute to enhanced surveillance, epidemiological control, and prevention strategies in the prevalent area.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".