Where in the Cell Are You? Probing HIV-1 Host Interactions through Advanced Imaging Techniques
Bibliographic record
Abstract
Viruses must continuously evolve to hijack the host cell machinery in order to successfully replicate and orchestrate key interactions that support their persistence. The type-1 human immunodeficiency virus (HIV-1) is a prime example of viral persistence within the host, having plagued the human population for decades. In recent years, advances in cellular imaging and molecular biology have aided the elucidation of key steps mediating the HIV-1 lifecycle and viral pathogenesis. Super-resolution imaging techniques such as stimulated emission depletion (STED) and photoactivation and localization microscopy (PALM) have been instrumental in studying viral assembly and release through both cell-cell transmission and cell-free viral transmission. Moreover, powerful methods such as Forster resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC) have shed light on the protein-protein interactions HIV-1 engages within the host to hijack the cellular machinery. Specific advancements in live cell imaging in combination with the use of multicolor viral particles have become indispensable to unravelling the dynamic nature of these virus-host interactions. In the current review, we outline novel imaging methods that have been used to study the HIV-1 lifecycle and highlight advancements in the cell culture models developed to enhance our understanding of the HIV-1 lifecycle.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.005 |
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".