Adipose Tissue in <scp>SARS</scp> ‐ <scp>CoV</scp> ‐2 Viral Tropism, Viral Replication, and the Concept of a Viral Reservoir: An Update
Bibliographic record
Abstract
Since the onset of the COVID-19 pandemic, obesity has been consistently associated with worse clinical outcomes. In 2020, we hypothesized that adipose tissue (AT) might serve as a viral reservoir and amplifier of immune responses in SARS-CoV-2 infection. Five years on, accumulating evidence supports this hypothesis. Recent autopsy and in vitro studies support that SARS-CoV-2 disseminates to and may replicate within human adipocytes. While several studies have detected SARS-CoV-2 RNA and proteins in AT, the recovery of infectious virus from this tissue has not yet been demonstrated. This remains a critical gap in our understanding of SARS-CoV-2 viral tropism and replication within adipocytes. Viral entry is mediated via angiotensin-converting enzyme-2 and neuropilin-1 receptors. Infected AT exhibits immune cell infiltration and cytokine activation, implicating it in systemic inflammation. Persistent viral RNA in AT correlates with prolonged metabolic dysfunction. These findings highlight the dual role of AT as a potential viral reservoir and immunometabolic organ. Understanding these mechanisms is critical to mitigating the long-term impact of COVID-19 and guiding responses to future pandemics involving metabolically active tissues.
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 | 0.002 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".