The Molecular Tool‐Kit of Viral Hemorrhagic Fevers
Bibliographic record
Abstract
Ebola and Marburg viruses cause hemorrhagic fever with up to 90% lethality, and their genomes encode just seven genes. The few gene products encoded, their “tool‐kit”, are leveraged into a greater array of functions, by remodeling or rearranging of the 3D protein structures. The surface glycoprotein adopts a massive, heavily glycosylated form on the viral surface, but is remodeled into a minimal receptor‐binding core once inside the endosome. As a result, binding of many potential antibodies is lost as their epitopes are stripped form the virus. Crystal structures of potently neutralizing antibodies, however, reveal how one remains bound and reaches into the cryptic receptor‐binding site. Others likely neutralize by locking the GP structure in place. Additional protein transformation takes place at the other end of the virus life cycle, assembly and budding of nascent virions. Through multiple crystal structures, biochemistry and cellular microscopy, we illustrated that the matrix protein VP40 rearranges into different structures, each with a distinct function required for the ebolavirus life cycle. A butterfly‐shaped VP40 dimer trafficks to the cellular membrane. A distinct, linear hexamer structure is critical for assembly and release of the virion. A third structure of VP40, an RNA‐binding ring, regulates viral transcription inside infected cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".