Neuroinvasion by Human Respiratory Coronaviruses
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
Human coronaviruses (HCoV) cause common colds but can also infect neural cell cultures. To provide definitive experimental evidence for the neurotropism and neuroinvasion of HCoV and its possible association with multiple sclerosis (MS), we have performed an extensive search and characterization of HCoV RNA in a large panel of human brain autopsy samples. Very stringent reverse transcription-PCR with two primer pairs for both viral strains (229E and OC43), combined with Southern hybridization, was performed on samples from 90 coded donors with various neurological diseases (39 with MS and 26 with other neurological diseases) or normal controls (25 patients). We report that 44% (40 of 90) of donors were positive for 229E and that 23% (21 of 90) were positive for OC43. A statistically significant higher prevalence of OC43 in MS patients (35.9%; 14 of 39) than in controls (13.7%; 7 of 51) was observed. Sequencing of nucleocapsid protein (N) gene amplicons revealed point mutations in OC43, some consistently found in three MS patient brains and one normal control but never observed in laboratory viruses. In situ hybridization confirmed the presence of viral RNA in brain parenchyma, outside blood vessels. The presence of HCoV in human brains is consistent with neuroinvasion by these respiratory pathogens. Further studies are needed to distinguish between opportunistic and disease-associated viral presence in human brains.
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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