AMMI Canada – CACMID Annual Conference
Bibliographic record
Abstract
Objective: Similar to cancer cells, HIV-infected cells differ from HIVuninfected cells in that they have altered interferon signaling pathways, the apparent reason for the selectivity of certain oncolytic viruses (OVs).The objective of this study was to determine whether the OV recombinant Maraba virus (MG1) would have a greater propensity to target and kill HIV-infected cells compared to non-infected cells.MethOds: U1, ACH-2, OM-10 and J1.1 cells, harbouring 1-2 copies of integrated proviral DNA per cell, were infected with varying multiplicities of infection (MOI) of green fluorescent protein (GFP)-encoded MG1.Controls included HIV-uninfected U937, A301, HL60 and Jurkat parent lines.CD4+CD25-HLADR-cells from 20 HIV-infected individuals on antiretroviral therapy were infected with MG1 and flow cytometry and MTT assay were performed to quantify MG1 infection and cell viability, respectively.PCR for total HIV DNA in cells, in addition to RT-PCR for total HIV RNA and ELISA for p24 antigen on cell-free supernatants, were performed after a 2-week stimulation period.Results: MG1 infected and killed a greater proportion of U1 than U937 cells at most MOIs tested but this was not observed in the other cell lines.With the initial experimental approach, MG1 did not appear to infect CD4 + CD25 -HLADR -cells and viability appeared preserved.Similarly, we were unable to detect any effect of MG1 on quantities of total HIV DNA in cells, or total HIV RNA or p24 antigen levels in supernatants.cOnclusiOn: MG1 infects and kills latently HIV-infected U1 cells to a greater degree than the HIV-uninfected parent U937 cells and may be a promising model to facilitate further studies of MG1 as a potential therapy for the eradication of latently HIV-infected cells.Further optimization of the experimental approach for primary cell experiments is required in order to determine the effect of MG1 on cells which constitute the HIV reservoir.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.470 | 0.138 |
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".