Spatial characterization of immunosenescence within HIV infected lymph nodes 2718
Bibliographic record
Abstract
Abstract Description Persistent HIV replication is hypothesized to induce chronic inflammation in antiretroviral therapy (ART)-suppressed people living with HIV (PLWH). Molecular and spatial characterization of this chronic inflammation within human lymph nodes from PLWH provide valuable information on the immunological microenvironment that limits viral eradication. This study investigated the underlying mechanisms of this inflammation within lymph nodes from PLWH using 10X Visium spatial transcriptomics and proteomics, analyzing ART-suppressed, viremic, and HIV- control samples. Following infection, a strong Type-I interferon response was observed in antigen presenting cells within lymph nodes from viremic individuals, potentially through the cGAS-STING pathway. This interferon signature, particularly within the myeloid and B cell populations, was alleviated following viral suppression with antiretroviral drugs; however, a proinflammatory signature remained in aviremic individuals. In HIV+ lymph nodes, pro-inflammatory T cells remained within T cell zones, while two distinct pro-inflammatory myeloid cell populations were identified within the afferent and efferent lymphatics. The CD4+ T cell signature from viremic lymph nodes indicated a decrease in ARP2/3 complex genes, a reported senescence regulator. Ongoing research is investigating the role of ARP2/3 in HIV-associated inflammation, aiming to understand its contribution to persistent immune activation both before and after ART initiation. Funding Sources Funded in part by NIH grants UM1AI126617, UM1AI164559, U01DA058527, R01CA260691, and R01DA052027. Topic Categories Viral Immunology (VIR)
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".