Inhibition and comprehensive analysis of hiv-1 vpu, examination of retroviral trafficking, and characterization of sars-cov-2 genetic material in wastewater
Bibliographic record
Abstract
Both HIV-1 and SARS-CoV-2 have been responsible for millions of infectionrelated deaths. Despite advances in treatment for both viruses, neither has a cure, and those living with the disease can unknowingly spread the virus. Because of this, research efforts to further the understanding, and control of both HIV-1 and SARS-CoV-2 are of upmost importance. A potential target for additional treatments for HIV -1 is Vpu, an accessory protein. Vpu counteracts host proteins that are detrimental to the virus, such as CD4 and Tetherin, enhancing viral dissemination and evasion of the host immune system. We have generated a library of Vpu clones in which each codon was individually randomized, resulting in a possible 1,620 amino acid mutants. With this library, we are able to look Vpu : target interactions in a comprehensive manner increasing our understanding of important residues in the functional protein. In a similar manner, we used a known target of Vpu, GaLV Env, to create a high throughput screening method for Vpu inhibitors and successfully identified two inhibitors with Vpu specificity that rescued CD4 and Tetherin downmodulation while also rescuing ADCC killing of infectious cells. In another retroviral study, examining pseudotype compatibility between various retroviruses and glycoproteins, we identified a mis-trafficking event within assembly of MLV gag protein inside HeLa but not HEK293FT cells. This suggests that the viral particles are mis-trafficked, and are either surrounded by or directly adjacent to lysosomal particles. In 2020, SARS-CoV-2 became a global pandemic, and many research efforts transitioned to finding treatments, vaccines, cures, and methods of understanding and tracking viral spread. It was soon noted that SARS-CoV-2 genetic material was detectable in wastewater. Here, we characterize genetic material collected from wastewater samples and find that wastewater likely contains fully intact enveloped particles. Taken together, these 4 studies contribute to a better understanding of HIV-1 and SARS-CoV-2 and provide tools that can be used long-term to further the understanding of these viruses.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".