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Record W2039747951 · doi:10.1086/382597

Severe Acute Respiratory Syndrome–Related Coronavirus Is Inhibited by Interferon‐α

2004· article· en· W2039747951 on OpenAlexaff
Ute Ströher, Antonino Di, Yan Li, James E. Strong, Fred Y. Aoki, Frank Plummer, Heinz Feldmann

Bibliographic record

VenueThe Journal of Infectious Diseases · 2004
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of ManitobaHealth CanadaManitoba Health
Fundersnot available
KeywordsMedicineInterferonRespiratory systemCoronavirus disease 2019 (COVID-19)CoronavirusVirologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakSevere acute respiratory syndromeImmunologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Current treatment schemes for severe acute respiratory syndrome (SARS) include broad-spectrum antibiotics, glucocorticoids, and ribavirin. We evaluated the susceptibility of the SARS-related coronavirus (SARS CoV) to ribavirin and interferon (IFN)- alpha in vitro by use of cytopathic effect, plaque assay, and immunoblot analysis. Ribavirin did not inhibit viral growth at concentrations attainable in human serum. In contrast, IFN- alpha showed an in vitro inhibitory effect starting at concentrations of 1000 IU/mL. In conclusion, ribavirin alone is unlikely to be beneficial in the prophylaxis or treatment of SARS CoV infections. Clinical trials with IFN- alpha might be justified to determine a beneficial effect on the outcome of SARS.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.022
GPT teacher head0.325
Teacher spread0.303 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations209
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Infectious DiseasesSame topicSARS-CoV-2 and COVID-19 ResearchFrench-language works237,207