[Molecular mechanisms of the hepatitis C virus, potential therapeutic targets].
Bibliographic record
Abstract
Hepatitis C Virus (HCV) is an emerging virus of great medical significance, because infection with this virus, which is essentially transmitted by blood, is a leading cause of chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma worldwide. HCV is an enveloped plus-strand RNA virus that belongs to the Flaviviridae family. The first cloning of the HCV genome, about 13 years ago, initiated research efforts leading to the elucidation of genomic organization and definition of the functions of the most viral proteins. While current therapeutic options for hepatitis C are limited, recent progress in the understanding of HCV molecular virology (genomic sequence, viral replication mechanisms, translational control mechanisms and tridimensional structure of viral proteins) led to the identification of potential new viral targets for antiviral strategies. Based upon these current knowledge, molecular and immunotherapeutic strategies to inhibit HCV replication or viral gene expression are being explored. This review focuses on the viral structure organization, protein functions and novel antiviral therapy approaches along with their biological and clinical significance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.008 |
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".