MétaCan
Menu
Back to cohort
Record W2041449821 · doi:10.1089/vim.2007.0038

Protection from Infection with Severe Acute Respiratory Syndrome Coronavirus in a Chinese Hamster Model by Equine Neutralizing F(ab′) <sub>2</sub>

2007· article· en· W2041449821 on OpenAlexaff
Deyan Luo, Bing Ni, Guangyu Zhao, Zhengcai Jia, Lili Zhou, Marek Pacal, Liangyan Zhang, Zhang Songle, Li Xing, Zhihua Lin, Li Wang, Jintao Li, Yunfei Liang, Xinfu Shi, Tingting Zhao, Liyun Zou, Yuzhang Wu, Xiliang Wang

Bibliographic record

VenueViral Immunology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsVirologyCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Respiratory system2019-20 coronavirus outbreakCoronavirusHamsterMedicineImmunologyBiologyInternal medicineOutbreakDisease

Abstract

fetched live from OpenAlex

To warrant potential clinical testing, the equine anti-severe acute respiratory syndrome coronavirus (SARS-CoV) F(ab')(2) requires evaluation in as many animal models as possible. In this study, we established a new animal model, the Chinese hamster, susceptible to SARS-CoV infection. SARS-CoV could propagate effectively and sustain high levels for 1 wk in animal lungs. All animals were protected from SARS-CoV infection in preventive settings. Further, when used therapeutically this antibody led to an approximately 4-log(10) decrease in viral burden in infected animal lungs. The pathological changes in lungs correlated closely with the dose of antibody administered. The excellent preventive and therapeutic roles of equine anti-SARS-CoV F(ab')(2) in several animal models, including the novel Chinese hamster model described in this study, have provided exciting data concerning its potential clinical study.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.732

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.248
Teacher spread0.223 · 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 teacher head, 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

Citations21
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueViral ImmunologySame topicAnimal Virus Infections StudiesFrench-language works237,207