Stress Responses, Adaptation, and Virulence of Bacterial Pathogens During Host Gastrointestinal Colonization
Bibliographic record
Abstract
Invading pathogens are exposed to a multitude of harmful conditions imposed by the host gastrointestinal tract and immune system. Bacterial defenses against these physical and chemical stresses are pivotal for successful host colonization and pathogenesis. Enteric pathogens, which are encountered due to the ingestion of or contact with contaminated foods or materials, are highly successful at surviving harsh conditions to colonize and cause the onset of host illness and disease. Pathogens such as Campylobacter, Helicobacter, Salmonella, Listeria, and virulent strains of Escherichia have evolved elaborate defense mechanisms to adapt to the diverse range of stresses present along the gastrointestinal tract. Furthermore, these pathogens contain a multitude of defenses to help survive and escape from immune cells such as neutrophils and macrophages. This chapter focuses on characterized bacterial defenses against pH, osmotic, oxidative, and nitrosative stresses with emphasis on both the direct and indirect mechanisms that contribute to the survival of each respective stress response.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 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".