SARS-CoV-2 may hijack GPCR signaling pathways to dysregulate lung ion and fluid transport
Bibliographic record
Abstract
The tropism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a virus responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic, toward the host cells is determined, at least in part, by the expression and distribution of its cell surface receptor, angiotensin-converting enzyme 2 (ACE2). The virus further exploits the host cellular machinery to gain access into the cells; its spike protein is cleaved by a host cell surface transmembrane serine protease 2 (TMPRSS2) shortly after binding ACE2, followed by its proteolytic activation at a furin cleavage site. The virus primarily targets the epithelium of the respiratory tract, which is covered by a tightly regulated airway surface liquid (ASL) layer that serves as a primary defense mechanism against respiratory pathogens. The volume and viscosity of this fluid layer is regulated and maintained by a coordinated function of different transport pathways in the respiratory epithelium. We argue that SARS-CoV-2 may potentially alter evolutionary conserved second-messenger signaling cascades via activation of G protein-coupled receptors (GPCRs) or by directly modulating G protein signaling. Such signaling may in turn adversely modulate transepithelial transport processes, especially those involving cystic fibrosis transmembrane conductance regulator (CFTR) and epithelial Na + channel (ENaC), thereby shifting the delicate balance between anion secretion and sodium absorption, which controls homeostasis of this fluid layer. As a result, activation of the secretory pathways including CFTR-mediated Cl − transport may overwhelm the absorptive pathways, such as ENaC-dependent Na + uptake, and initiate a pathophysiological cascade leading to lung edema, one of the most serious and potentially deadly clinical manifestations of COVID-19.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".