Impact of HIV Infection and HAART Therapy on CD4 T Helper Cell Subset Expression and Function
Bibliographic record
Abstract
Regulation of T helper (Th) cell differentiation and proliferation depends on which cytokines are present in the microenvironment of a nave Th cell. Induction of specific transcription factors results in programming of the nave Th0 cell into one of several subsets. Currently there are four well characterized Th cell subsets, namely Th1, Th2, Th17, and the T regulatory (Treg) cells (Figure In this chapter we will be focusing on the Th1, Th17, and Treg cell populations. However, at this point it is also worth mentioning the relatively newly described Th9 and follicular (Tfh) cell subsets. Here we briefly discuss the differentiation pathways taken by a Th0 cell that ultimately results in the formation of these different subsets. Since the early 1980's, the Th1/Th2 paradigm has been well-studied. Th1 cells are known for expression of the signature cytokine IFN-and resulting anti-viral activities. The necessary driving cytokine for these cells is IL-12 in conjunction with the Th1-specific transcription factor T-bet IL-27, related to IL-12, has been recently shown to play a role in the induction of Th1 cells, while also actively repressing development of other subsets. On the other hand, Th2 cells are largely recognized to support humoral immunity and are induced by the presence of IL-4 and resulting activation of the STAT6 transcription factor Equally important is the activation of the GATA binding protein 3 (GATA-3), the main regular of Th2 development The newly defined Th17 cells have been implicated in a number of inflammatory disorders and are recognized as key Th cells that trigger massive proinflammatory responses. They are characterized by production of IL-17 and differentiation of these cells requires both tumor growth factor (TGF)- and IL-6 which act together to promote development of the Th17 subset Additionally important to the generation of these cells is IL-23, which functions to aid in the development and proliferation of Th17 cells. The key transcription factors required belong to the retinoic acid-related orphan receptors (ROR)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".