Immunocompetent Human 3D Organ-Specific Hormone-Responding Vaginal Mucosa Model of HIV-1 Infection
Bibliographic record
Abstract
The lack of appropriate experimental models often limits our ability to investigate the establishment of infections in specific tissues. To reproduce the structural and spatial organization of vaginal mucosae to study human immunodeficiency virus type-1 (HIV-1) infection, we used the self-assembly technique to bioengineer tridimensional vaginal mucosae using human cells extracted from HIV-1-negative healthy pre- and postmenopausal donors. We produced a stroma, free of exogenous material, that can be adapted to generate near-to-native vaginal tissue with the best complexity obtained with seeded epithelial cells on the organ-specific stroma. The autologous engineered tissues had mechanical properties close to native mucosa and shared similar glycogen production, which declined in reconstructed tissues of the postmenopausal donor. The in vitro -engineered tissues were also rendered immune competent by adding human monocyte-derived macrophages (MDMs) on the epithelium or in the stroma layers. The model was infected with HIV-1, and viral replication and transcytosis were observed when immunocompetent reconstructed vaginal mucosa tissue has incorporated MDMs into the stroma and infected with free HIV-1 green fluorescent protein (GFP) viral particles. These data illustrate a natural permissiveness of immunocompetent untransformed human vaginal mucosae to HIV-1 infection. This model offers a physiological tool to explore viral load, HIV-1 transmission in an environment that may contribute to the virus propagation, and new antiviral treatments in vitro . Impact statement This study introduces an innovative immunocompetent three-dimensional human organ-specific vaginal mucosa free of exogenous material for in vitro modeling of human immunodeficiency virus type-1 (HIV-1) infection. The proposed model is histologically close to native tissue, especially by presenting glycogen accumulation in the epithelium's superficial cells, responsive to estrogen, and able to sustain a monocyte-derived macrophage population infected or not by HIV-1 during ∼2 months.
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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 | 0.001 |
| 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".