<i>Short Communication:</i> Rapid Preparation of Preventive and Therapeutic Whole-Killed Retroviral Vaccines Using the Microbicide Taurine Chloramine
Bibliographic record
Abstract
A current urgent priority is to develop microbicides and vaccines to combat retroviruses like human immunodeficiency virus (HIV). We show that the cysteine-selective natural compound, taurine chloramine (T-NCl), can be effective in this task. A number of proteins in all retroviruses contain highly conserved cysteine-rich regions that are essential for infection and replication. Our data show that by targeting these essential cysteine residues, T-NCl (2 or 5 mM) acts as a highly effective and safe microbicide that fully blocks the infectivity of high HIV-1 titers (10(6) TCID(50) units/ml) but is not injurious to eukaryotic cells. We also demonstrate that T-NCl can be used to prepare a highly effective whole-killed vaccine against murine AIDS (MAIDS) that shows both preventive and therapeutic efficacy. The vaccine consists of a T-NCl-inactivated retrovirus suspension in host cell lysate. The novelty of our approach lies in the ease and speed of vaccine preparation and its avoidance of harsh inactivation or purification steps that can alter native viral conformation. Our approach is therefore likely to overcome a number of intractable obstacles to the preparation of an effective whole-killed HIV vaccine, such as surviving infective viral particles, rapid viral mutation rates, numerous viral strains, and harsh purification steps. Our approach may also permit the rapid preparation of autologous, or custom-made, vaccines for individual patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.034 | 0.023 |
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".