Bibliographic record
Abstract
Salmonella species are masters at subverting various host processes for their own use. The interactions that occur between Salmonella species and host cells are complex. They have been studied more extensively with nonphagocytic cells such as epithelial cells than with macrophages, although some of the processes are common between these two cell types. For the review in this chapter, the author has concentrated on the events that occur in the host cell rather than to focus on the bacterial genes that mediate these events. Study of the cell biology of these interactions has revealed several interesting processes and provided new tools for the study of eukaryotic cell function. It has recently been shown that Salmonella species trigger extensive membrane ruffling and macropinocytosis in macrophages and enter into a spacious phagosome. Bacterial invasins appear to significantly enhance uptake into phagocytic cells such as macrophages, since noninvasive Salmonella typhimurium mutants have decreased levels of invasion into cultured macrophages. One recurring theme about all of these exploitations of host cell function is that the bacteria achieve the desired effect by “nonconventional” mechanisms, as viewed by cell biologists. The advancement of this field is heavily dependent on other fields, especially cell biology. In addition, further characterization of the bacterial products that are involved in the various stages of infection will enhance the cell biology studies.
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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".