SARS-CoV2 infectivity is potentially modulated by host redox status
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The current coronavirus disease (COVID-19) outbreak caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV2) has emerged as a threat to global social and economic systems. Disparity in the infection of SARS-CoV2 among host population and species is an established fact without any clear explanation. To initiate infection, viral S-protein binds to the Angiotensin-Converting Enzyme 2 (ACE2) receptor of the host cell. Our analysis of retrieved amino acid sequences deposited in data bases shows that S-proteins and ACE2 are rich in cysteine (Cys) residues, many of which are conserved in various SARS-related coronaviruses and participate in intra-molecular disulfide bonds. High-resolution protein structures of S-proteins and ACE2 receptors highlighted the probability that two of these disulfide bonds are potentially redox-active, facilitating the primal interaction between the receptor and the spike protein. Presence of redox-active disulfides in the interacting parts of S-protein, ACE2, and a ferredoxin-like fold domain in ACE2, strongly indicate the role of redox in COVID-19 pathogenesis and severity. Resistant animals lack a redox-active disulfide (Cys133-Cys141) in ACE2 sequences, further strengthening the redox hypothesis for infectivity. ACE2 is a known regulator of oxidative stress. Augmentation of cellular oxidation with aging and illness is the most likely explanation of increased vulnerability of the elderly and persons with underlying health conditions to COVID-19.
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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 it