Adipose Tissues from Human and Bat-Derived Cell Lines Support Ebola Virus Infection
Bibliographic record
Abstract
Ebola virus is a zoonotic pathogen with a geographic range covering diverse ecosystems that are home to many potential reservoir species. Although researchers have detected Ebola virus RNA and serological evidence of previous infection in different rodents and bats, the infectious virus has not been isolated. The field is missing critical knowledge about where the virus is maintained between outbreaks, either because the virus is rarely encountered, overlooked during sampling, and/or requires specific unknown conditions that regulate viral expression. This study assessed adipose tissue as a previously overlooked tissue capable of supporting Ebola virus infection. Adipose tissue is a dynamic endocrine organ helping to regulate and coordinate homeostasis, energy metabolism, and neuroendocrine and immune functions. Through in vitro infection of human and bat (Eptesicus fuscus) brown adipose tissue cultures using wild-type Ebola virus, this study showed high levels of viral replication for 28 days with no qualitative indicators of cytopathic effects. In addition, alterations in adipocyte metabolism following long-term infection were qualitatively observed through an increase in lipid droplet number while decreasing in size, a harbinger of lipolysis or adipocyte browning. The finding that bat and human adipocytes are susceptible to Ebola virus infection has important implications for potential tissue tropisms that have not yet been investigated. Additionally, the findings suggest how the metabolism of this tissue may play a role in pathogenesis, viral transmission, and/or zoonotic spillover events.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".