Periluminal Distribution of HIV-Binding Target Cells and Gp340 in the Oral, Cervical and Sigmoid/Rectal Mucosae: A Mapping Study
Bibliographic record
Abstract
Studies have shown that the transmission of HIV is most likely to occur via rectal or vaginal routes, and rarely through oral exposure. However, the mechanisms of virus entry at mucosal surfaces remain incompletely understood. Prophylactic strategies against HIV infection may be attainable once gaps in current knowledge are filled. To address these gaps, we evaluated essentially normal epithelial surfaces and mapped the periluminal distribution of CD4+ HIV target cells, including T cells and antigen-presenting cells, and an HIV-binding molecule gp340 that can be expressed by epithelial cells in secreted and cell-associated forms. Immunohistochemistry for CD4, CD16, CD3, CD1a and gp340 in human oral, rectal/sigmoid and cervical mucosal samples from HIV-negative subjects demonstrated that periluminal HIV target cells were more prevalent at rectal/sigmoid and endocervical surfaces lined by simple columnar epithelium, than at oral and ectocervical surfaces covered by multilayered stratified squamous epithelium (p<0.001). gp340 expression patterns at these sites were also distinct and strong in oral minor salivary gland acini and ducts, including ductal saliva, in individual rectum/sigmoid and endocervix periluminar columnar cells, and in ectocervix squamous cells. Only weak expression was noted in the oral non-ductal squamous epithelium. We conclude that periluminal HIV target cells, together with periluminal epithelial cell-associated gp340 appear to be most accessible for HIV transmission at rectal/sigmoid and endocervical surfaces. Our data help define vulnerable structural features of mucosal sites exposed to HIV.
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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".