Intra-host Ebola viral adaption during human infection
Bibliographic record
Abstract
The onsite next generation sequencing (NGS) of Ebola virus (EBOV) genomes during the 2013-2016 Ebola epidemic in Western Africa provides an opportunity to trace the origin, transmission, and evolution of this virus. Herein, we have diagnosed a cohort of EBOV patients in Sierra Leone in 2015, during the late phase of the outbreak. The surviving EBOV patients had a recovery process characterized by decreasing viremia, fever, and biochemical parameters. EBOV genomes sequenced through the longitudinal blood samples of these patients showed dynamic intra-host substitutions of the virus during acute infection, including the previously described short stretches of 13 serial T>C mutations. Remarkably, within individual patients, samples collected during the early phase of infection possessed Ts at these nucleotide sites, whereas they were replaced by Cs in samples collected in the later phase, suggesting that these short stretches of T>C mutations could emerge independently. In addition, up to a total of 35 nucleotide sites spanning the EBOV genome were mutated coincidently. Our study showed the dynamic intra-host adaptation of EBOV during patient recovery and gave more insight into the complex EBOV-host interactions.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".