Roles of natural resistance‐associated macrophage protein‐1 in modulating bacterial distribution and immune responses during <i>Salmonella enterica</i> serovar Typhimurium infection in murine pregnancy
Bibliographic record
Abstract
PROBLEM: mice during pregnancy can lead to profound bacterial growth in the feto-placental unit and adverse pregnancy outcomes, including fetal loss, maternal illness and death. The kinetics and mechanisms by which S.Tm gains entry within individual feto-placental unit, and disseminates through tissues leading to placental resorption and fetal demise remain unclear. METHOD OF STUDY: Mice were systemically infected with S.Tm. Bacterial burden within spleen and individual placentas, and placental/fetal resorptions were quantified. Flow cytometric analysis of immune cell types in the spleen and individual placentas was performed. Cytokine expression in maternal serum was determined through cytometric bead array. RESULTS: mice. At 24 h post-infection, the mean infection rate of individual placentas per mouse was ∼50%, increasing to >75% by 72 h post-infection, suggesting that initial infection in few sites progresses to rapid spread of infection through the uterine milieu. This correlated with a steady increase in placental/fetal resorption rates. Placental infection was associated with local increased neutrophil percentages, whereas numbers and percentages in the spleen remained unchanged, suggesting dichotomous modulation of inflammation between the systemic compartment and the feto-maternal interface. Reduced survival rates of pregnant mice during infection correlated with decreased serum IFN-γ but increased IL-10 levels relative to non-pregnant controls. CONCLUSION: Pregnancy compromises host resistance conferred by Nramp1 against S.Tm through compartment-specific regulation of maternal and placental cellular responses, and modulation of systemic cytokine expression.
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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 | 0.000 |
| 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 | 0.000 | 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".