Placenta analysis of Hofbauer cell profile according to the class of antiretroviral therapy used during pregnancy in people living with HIV
Bibliographic record
Abstract
The use of antiretroviral therapy drastically reduces vertical transmission of Human Immunodeficiency Virus. However, recent studies demonstrate associations between ART use during pregnancy and placental inflammation, particularly within protease inhibitor (PI)-based regimens. We sought to characterize placental macrophages, namely Hofbauer cells, according to the class of ART used during pregnancy. Using immunofluorescence and immunohistochemistry, placentas from 79 pregnant people living with HIV (PPLWH) and 29 HIV-uninfected people were analyzed to quantify the numbers and frequencies of leukocytes (CD45+) and Hofbauer cells (CD68+ and/or CD163+). PPLWH were stratified into three groups based on class of ART: non-nucleoside reverse transcriptase inhibitor (NNRTI)-based, integrase strand-transfer inhibitor (INSTI)-based, and PI-based regimens. Placentas of PPLWH contained significantly more leukocytes and Hofbauer cells than controls. Multivariable analyses revealed that this increase in immune cells was associated with a predominantly CD163+ profile in all ART subgroups compared to the HIV-negative group. This was characterized by an increase in total CD163+ cells in the PI and INSTI subgroups, and a higher frequency of CD163+ cells and CD163+/CD68+ ratio in the NNRTI and PI subgroups. Placentas of PPLWH treated with any ART regimen during their entire pregnancy displayed a selection for CD163+ cells compared to the HIV-negative group, regardless of class of ART, suggesting that class of ART does not intrinsically affect selection of CD163+ and CD68+ Hofbauer cells. Further investigations into the role of Hofbauer cells in ART-associated placental inflammation are warranted to identify the mechanisms behind their potential involvement in maternal-fetal tolerance maintenance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".