Inflammatory responses to <i>Listeria monocytogenes</i> infection in the placenta
Bibliographic record
Abstract
Abstract The immunological defense of the developing fetus is crucial for a successful pregnancy. The placenta plays key roles in protecting the fetus against rejection by the maternal immune system, while it ensures its defense against most pathogens. The mechanisms that orchestrate the placental immune functions are still poorly understood. The bacterial pathogen Listeria monocytogenes (Lm) breaches the maternal/fetal barrier, infects the placental chorionic villi, and reaches the fetus resulting in poor pregnancy outcomes. We studied the interplay between Lm and key players of the placental antimicrobial defense: trophoblasts (TCs), which are epithelial cells covering placental chorionic villi at the maternal/fetal interface, and placental macrophages (Hofbauer cells, or HBCs), which are the only leukocytes residing in chorionic villi. Both cell types form a critical immune barrier protecting the fetus from infection. We isolated human primary TCs and HBCs from healthy term placentas to study the Lm intracellular lifecycle as well as the cellular responses to infection (RNAseq and cytokine arrays). We found that both cell types were permissive to Lm infection and mounted a pro-inflammatory response to the pathogen including HBCs repolarization towards a pro-inflammatory phenotype favoring the innate immune responses. However, consistent with their placental homeostatic functions, TCs and repolarized HBCs maintained the expression of tolerogenic factors known to prevent maternal anti-fetal adaptive immunity. We will discuss our published studies (PMID 34399615 and 34367171) and recent data that teased apart the role of the Lm virulence factors in the inflammatory responses of placental cells. Supported by NIH (R01AI157205, R21AI105588, R03AI149371)
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".