Immunogenicity of CIGB‐230, a therapeutic DNA vaccine preparation, in HCV‐chronically infected individuals in a Phase I clinical trial
Bibliographic record
Abstract
SUMMARY: Hepatitis C virus (HCV) is a worldwide health problem. No vaccine is available against this pathogen and therapeutic treatments currently in use are of limited efficacy. In the present study, the immunogenicity of the therapeutic vaccine candidate CIGB-230, based on the mixture of pIDKE2, a plasmid expressing HCV structural antigens, with a recombinant HCV core protein, Co.120, was evaluated. CIGB-230 was administered by intramuscular injection on weeks 0, 4, 8, 12, 16 and 20 to 15 HCV-chronically infected individuals, non-responders to previous treatment with interferon (IFN) plus ribavirin. Interestingly, following the final immunization, neutralizing antibody responses against heterologous viral pseudoparticles were modified in eight individuals, including six de novo responders. In addition, 73% of vaccinees exhibited specific T cell proliferative response and T cell IFN-gamma secretory response 24 weeks after primary immunization with CIGB-230. Furthermore, 33.3% of individuals developed de novo cellular immune response against HCV core and the number of patients (46.7% at the end of treatment) with cellular immune response against more than one HCV structural antigen increased during vaccination (P = 0.046). In addition, despite persistent detection of HCV RNA, more than 40% percent of vaccinated individuals improved or stabilized liver histology, particularly reducing fibrosis, which correlated with cellular immune response against more than one HCV antigen (P = 0.0053). In conclusion, CIGB-230 is a promising candidate for effective therapeutic interventions based on its ability for enhancing the immune response in HCV chronically infected individuals.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".