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Record W4385442640 · doi:10.1080/14786419.2023.2239995

Antiviral activity and active components of the leaves from <i>Sabia parviflora</i> Wall. ex Roxb

2023· article· en· W4385442640 on OpenAlexaff
Yongqiang Zhou, Sumei Li, Bo‐Wen Pan, Junwei Xiao, Tingting Tang, Shouxia Xie, Xin Yang, G Wu, Jian Yang, Ying Zhou, Yuxin Pang, Ying Wei

Bibliographic record

VenueNatural Product Research · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTraditional medicineIC50ProteaseHIV-1 proteaseHuman immunodeficiency virus (HIV)ChemistryBiologyVirologyEnzymeIn vitroMedicineBiochemistry

Abstract

fetched live from OpenAlex

Sabia parviflora (SP, “xiao hua qing feng teng” in Chinese) was recorded as an important ethnic medicine to be used for treating viral hepatitis. The antiviral activity of four SP extracts and potent antiviral compounds evaluated with cathepsin L protease (Cat L PR) and HIV-1 protease (HIV-1 PR). UPLC-HRMS was used for identifying the bioactive components. In addition, the possible inhibitory mechanism of the identified compounds on viral protease was further discussed by molecular docking. As a result, four extracts of SP exhibited inhibitory activity of HIV-1 PR and Cat L PR with IC50 range from 0.015 to 0.80 mg/mL. Meanwhile, six compounds inhibited HIV-1 PR with IC50 range from 0.032 to 0.80 mg/mL. Moreover, procyanidin B2 had good affinity for HIV-1 PR and CatL PR protein, respectively. These findings suggest S. parviflora leaves can be used for treating HIV and procyanidin B2 may play a role in antiviral protease.

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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.345
Teacher spread0.288 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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