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Record W2100594252 · doi:10.1128/mbio.00595-12

Predicting the Next Eye Pathogen: Analysis of a Novel Adenovirus

2013· article· en· W2100594252 on OpenAlexaff
Christopher M. Robinson, Xiaohong Zhou, Jaya Rajaiya, M. Yousuf, Gurdeep Singh, Joshua J. DeSerres, Michael P. Walsh, Sallene Wong, Donald Seto, David W. Dyer, James Chodosh, Morris S. Jones

Bibliographic record

VenuemBio · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsProvincial Laboratory of Public Health
FundersNational Eye InstituteNational Institutes of HealthMassachusetts Lions Eye Research FundResearch to Prevent BlindnessFalk Foundation
KeywordsBiologyVirologyTropismIn silicoTissue tropismVirusHuman pathogenPathogenComputational biologyPathogenicityGeneticsGeneMicrobiology

Abstract

fetched live from OpenAlex

UNLABELLED: For DNA viruses, genetic recombination, addition, and deletion represent important evolutionary mechanisms. Since these genetic alterations can lead to new, possibly severe pathogens, we applied a systems biology approach to study the pathogenicity of a novel human adenovirus with a naturally occurring deletion of the canonical penton base Arg-Gly-Asp (RGD) loop, thought to be critical to cellular entry by adenoviruses. Bioinformatic analysis revealed a new highly recombinant species D human adenovirus (HAdV-D60). A synthesis of in silico and laboratory approaches revealed a potential ocular tropism for the new virus. In vivo, inflammation induced by the virus was dramatically greater than that by adenovirus type 37, a major eye pathogen, possibly due to a novel alternate ligand, Tyr-Gly-Asp (YGD), on the penton base protein. The combination of bioinformatics and laboratory simulation may have important applications in the prediction of tissue tropism for newly discovered and emerging viruses. IMPORTANCE: The ongoing dance between a virus and its host distinctly shapes how the virus evolves. While human adenoviruses typically cause mild infections, recent reports have described newly characterized adenoviruses that cause severe, sometimes fatal human infections. Here, we report a systems biology approach to show how evolution has affected the disease potential of a recently identified novel human adenovirus. A comprehensive understanding of viral evolution and pathogenicity is essential to our capacity to foretell the potential impact on human disease for new and emerging viruses.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.290

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.300
Teacher spread0.270 · 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

Citations51
Published2013
Admission routes1
Has abstractyes

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