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Record W3133088650 · doi:10.1177/2515690x20978394

Review of Whole Plant Extracts With Activity Against Herpes Simplex Viruses In Vitro and In Vivo

2021· review· en· W3133088650 on OpenAlexaff
Anna Garber, Lianna Barnard, Chris Pickrell

Bibliographic record

VenueJournal of Evidence-Based Integrative Medicine · 2021
Typereview
Languageen
FieldImmunology and Microbiology
TopicToxin Mechanisms and Immunotoxins
Canadian institutionsCanadian College of Naturopathic Medicine
Fundersnot available
KeywordsHerpes simplex virusHSL and HSVIn vivoOutbreakVirologyBiologyIn vitroVirusMedicinePharmacologyImmunologyBiotechnology

Abstract

fetched live from OpenAlex

Herpes simplex viruses, HSV-1 and HSV-2, are highly contagious and cause lifelong, latent infections with recurrent outbreaks of oral and/or genital lesions. No cure exists for HSV-1 or HSV-2 infections, but antiviral medications are commonly used to prevent and treat outbreaks. Resistance to antivirals has begun to emerge, placing an importance on finding new and effective therapies for prophylaxis and treatment of HSV outbreaks. Botanicals may be effective HSV therapies as the constituents they contain act through a variety of mechanisms, potentially making the development of antiviral resistance more challenging. A wide variety of plants from different regions in the world have been studied for antiviral activity against HSV-1 and/or HSV-2 and showed efficacy of varying degrees. The purpose of this review is to summarize research conducted on whole plant extracts against HSV-1 and/or HSV-2 in vitro and in vivo. The majority of the research reviewed was conducted in vitro using animal cell lines, and some studies used an animal model design. Also summarized are a limited number of human trials conducted using botanical therapies on HSV lesions.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.130
GPT teacher head0.372
Teacher spread0.242 · 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 designSystematic review
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

Citations50
Published2021
Admission routes1
Has abstractyes

Explore more

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