Impact of TNFα, LTα, FcγRII and complement receptor on HIV-1 trapping in lymphoid tissue from HIV-infected patients
Bibliographic record
Abstract
OBJECTIVES: To investigate HIV trapping mechanisms in patients with acute infection and in asymptomatic individuals prior to and during antiretroviral therapy. To determine the role of complement receptor (CR), Fc gamma receptor II (Fc gammaRII), tumour necrosis factor alpha (TNFalpha), and lymphotoxin alpha (LTalpha) expression in HIV trapping efficiency. METHODS: Lymphoid tissues from three acutely HIV-infected patients and six asymptomatic, chronically HIV-infected patients collected prior to and during antiretroviral therapy were compared with lymphoid tissues from six HIV-seronegative subjects. HIV, TNFalpha and LTalpha RNA expression was detected and quantified by fluorescence in situ hybridization. CR, Fc gammaRII and HIV p24 antigen were detected and quantified by fluorescence immunohistochemistry. RESULTS: The amount of trapped HIV did not differ significantly between patients with acute HIV infection and asymptomatic individuals, and was independent of the presence of CR or Fc gammaRII expression. However, in patients with acute infection, the amount of trapped virus was correlated inversely with the number of HIV-infected cells (P = 0.0092) and with the size of the light zone (P = 0.037). In these patients, the number of TNFalpha-expressing cells was correlated inversely with the amount of trapped virus (P = 0.014) and positively correlated with the size of the light zone in germinal centers (P = 0.041). No correlations were observed between TNFalpha or LTalpha expression and Fc gammaRII or CR expression. CONCLUSION: This report provides the first evidence that in humans TNFalpha is involved in the development of lymphoid follicles, HIV trapping, and, consequently, in early host immune responses. A model is proposed for early events in patients during acute HIV infection.
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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 | 0.001 |
| 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 | 0.000 |
| 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".