HTLV Type 1 Tax Transduction in Microglial Cells and Astrocytes by Lentiviral Vectors
Bibliographic record
Abstract
Infection with human T cell leukemia virus type 1 (HTLV-1) can result in the development of HAM/TSP, a nonfatal, chronic inflammatory disease involving neuronal degeneration and demyelination of the central nervous system. Elevated levels of the proinflammatory cytokines tumor necrosis factor alpha (TNF-alpha), interleukin-6 (IL-6), and IL-1 observed in the cerebrospinal fluid of HAM-TSP patients suggest that cytokine dysregulation within the CNS is involved in neuropathogenesis. HTLV-1 infection and enhanced expression of TNF-alpha by microglial cells, astrocytes, and macrophages has been hypothesized to lead to the destruction of myelin and oligodendrocytes in the CNS. Although the association of HTLV-2 infection and development of neurological disease is more tenuous, HTLV-2 has also been found to be associated with peripheral neuropathies. To investigate the roles of HTLV Tax(1) and Tax(2) in the induction of cytokine disregulation in these cell types, we are currently developing gene delivery vectors based on human immunodeficiency virus type-1 (HIV-1) capable of stably coexpressing the HTLV-1 or -2 tax and eGFP reporter genes in primary human cells. Transduction frequencies of up to 50%, as assessed by eGFP expression, can be achieved in human monocyte-derived macrophages and in explanted cultures of human microglia. Preliminary data suggest that Tax(1) expression is sufficient to up-regulate the proinflammatory cytokine profile in explanted human microglial cells. Future experiments will compare and evaluate the effect of tax(1) and tax(2) gene expression on the cellular proinflammatory cytokine expression profile, as well as demonstrate the effects of transducing human fetal astrocytes and PBMC-derived macrophages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| 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 teacher head, 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".