The 30th anniversary of Campylobacter, Helicobacter, and Related Organisms workshops—what have we learned in three decades?
Bibliographic record
Abstract
As we commemorate the 30th anniversary of the Campylobacter, Helicobacter and Related Organisms (CHRO) workshops with this special Frontiers edition, we look back upon three decades of research and provide some highlights from the 16th International CHRO meeting. As Martin Skirrow noted, Elizabeth King was the first to isolate campylobacters in the 1950’s, although Escherich himself provided drawings of these fecal organisms back in the 1880’s. Helicobacter is a more recent organism, first described to be the causative agent of stomach ulcers at a CHRO meeting by Barry Marshall and Robin Warren – who then later received the Nobel Prize for their findings that bacteria could cause diseases previously believed to be caused by human factors. Studies of the intersection of host microbial ecology and pathogen infection have been pioneered by scientists such as Brett Finlay, who described his current work on this topic. And as general antibiotics are routinely administered, we see a rise in bacterial antibiotic resistance. Julian Davies emphasized that there is a growing need for the development of new bioactive compounds on the horizon as we advance our knowledge on these pathogens. The first genome of C. jejuni was published in 2000; now one decade later we have 30 Campyobacter taxa sequenced, and this number continues to rise quickly. However, we continue to obtain “unexpected results” as a pioneer in CHRO research, Martin Blaser explained – i.e., although H. pylori is now classified as a level I carcinogen, there may be benefits to carrying this organism as part of your normal flora. Other findings indicate that Campylobacters and Helicobacters do not follow classic paradigms of other well-characterized gastrointestinal pathogens. And we are learning that there is a whole world of interesting related organisms beyond C. jejuni and H. pylori. This review summarizes some of the history of CHRO research and the exciting directions ahead.
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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 | 0.006 | 0.014 |
| 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 | 0.003 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.072 | 0.037 |
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".