Acute intraperitoneal infection with a hypervirulent Acinetobacter baumannii isolate in mice
Bibliographic record
Abstract
Acinetobacter baumannii infection has become a major cause of healthcare-associated infection and a critical pathogen in the WHO antimicrobial resistance research and development priority list. Catheter-related septicemia is one of the major clinical manifestations of A. baumannii infection associated with high morbidity and mortality. In this study, we used a clinical A. baumannii strain (LAC-4) that is hypervirulent to immunocompetent C57BL/6 and BALB/c mice and established a mouse model of intraperitoneal (i.p.) A. baumannii infection. Our study showed that i.p. LAC-4 infection of C57BL/6 and BALB/c mice induces a lethal or sublethal infection with high bacterial burdens in peritoneal cavity, blood and tissues and the infected mice either succumbed to the infection within 24 hours or completely recovered from the infection. The infection induces acute peritoneal recruitment of neutrophils and other innate immune cells, and the local and systemic production of proinflammatory cytokines and chemokines (IL-1β, IL-5, IL-6, TNF-α, RANTES, MIP-1β, MCP-1, KC and IL-10). Mechanistic studies suggest an important role of macrophages in the host innate defense in this model in that in vitro stimulation of peritoneal macrophages with killed LAC-4 induced a similar pattern of cytokine/chemokine responses to those in the infected mice, and depletion of peritoneal macrophages rendered the mice significantly more susceptible to the infection. Thus, this mouse infection model will provide an alternative and useful tool for future pathogenesis studies of A. baumannii-associated septicemia and identification and characterization of important virulence factors, as well as serve as a surrogate model for rapid evaluation of novel therapeutics and vaccines for this emerging infectious agent.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".