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Record W3081295866 · doi:10.3390/microorganisms8091284

Recent Advances in Novel Antiviral Therapies against Human Adenovirus

2020· review· en· W3081295866 on OpenAlexafffund
Bratati Saha, Robin J. Parks

Bibliographic record

VenueMicroorganisms · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchGovernment of Ontario
KeywordsDiseaseMedicineAntiviral therapyHuman pathogenVirusVirologyImmunologyBioinformaticsIntensive care medicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

Human adenovirus (HAdV) is a very common pathogen that typically causes minor disease in most patients. However, the virus can cause significant morbidity and mortality in certain populations, including young children, the elderly, and those with compromised immune systems. Currently, there are no approved therapeutics to treat HAdV infections, and the standard treatment relies on drugs approved to combat other viral infections. Such treatments often show inconsistent efficacy, and therefore, more effective antiviral therapies are necessary. In this review, we discuss recent developments in the search for new chemical and biological anti-HAdV therapeutics, including drugs that are currently undergoing preclinical/clinical testing, and small molecule screens for the identification of novel compounds that abrogate HAdV replication and disease.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.037
GPT teacher head0.347
Teacher spread0.310 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations34
Published2020
Admission routes2
Has abstractyes

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