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.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".