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Record W4402334287 · doi:10.1016/j.jafr.2024.101396

Mechanistic Elucidation of green seaweed compounds in orthodontic relapse management via RANKL/TNF-α-mediated ROS/Keap1/Nrf2 signaling: In silico and Ex Vivo studies

2024· article· en· W4402334287 on OpenAlexaff
Ananto Ali Alhasyimi, Alexander Patera Nugraha, Aulia Ayub, Trianna Wahyu Utami, Timothy Sahala Gerardo, Nuril Farid Abshori, Mohammad Adib Khumaidi, Trina Ekawati Tallei, Nurpudji Astuti Taslim, Bonglee Kim, Raymond R. Tjandrawinata, Apollinaire Tsopmo, Fahrul Nurkolis

Bibliographic record

VenueJournal of Agriculture and Food Research · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeaweed-derived Bioactive Compounds
Canadian institutionsCarleton University
Fundersnot available
KeywordsIn silicoEx vivoRANKLTumor necrosis factor alphaIn vivoKEAP1ChemistryCell biologyCancer researchMedicineBiologyImmunologyBiochemistryReceptorGeneGeneticsTranscription factor

Abstract

fetched live from OpenAlex

Orthodontic relapse, the return to a pre-treatment position after orthodontic correction, is driven by the RANKL/TNF-α-mediated ROS/Keap1/Nrf2 signaling axis. This mechanism triggers aseptic inflammation and oxidative stress, influencing bone resorption and formation. Antioxidants can mitigate oxidative stress, potentially improving post-orthodontic outcomes. This study explores the efficacy of antioxidant compounds derived from green seaweed/algae in managing orthodontic relapse. Green seaweed/algae extracts were prepared via sonication, and bioactive compounds were identified using ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) analysis. Compounds underwent bioactivity prediction, toxicity assessment, and drug-likeness evaluation, revealing significant therapeutic potential. Network pharmacology and molecular docking identified key proteins associated with orthodontic relapse, including IL-1β, STAT3, ESR1, MAPK1, JAK2, and HMOX1. Molecular docking simulations indicated favorable binding energies for green seaweed compounds, particularly the alkaloids adenosine (ΔG −6.9 to −7.3 kcal/mol) and lycopodine (ΔG −6.3 to −8.5 kcal/mol), against targeted proteins, matching or outperforming standard drugs such as s-ibuprofen (ΔG −6.7 kcal/mol). In vitro assays confirmed the antioxidant activity of these compounds, with EC 50 dose of 52.2–54.2 μg/mL for ABTS radical scavenging capacities. Protein expression analysis in tibial-femoral bone marrow cells further demonstrated the potential of green seaweed/algae compounds to suppress osteoclastogenesis by modulating the RANKL/TNF-α-mediated ROS/Keap1/Nrf2 pathway. This research highlights the promise of green seaweed-derived antioxidants in reducing oxidative stress and managing orthodontic relapse, providing a foundation for future therapeutic developments. • Green seaweed potential in reducing oxidative stress and preventing orthodontic relapse. • Green seaweed suppresses osteoclastogenesis by modulating the RANKL/TNF-α-mediated ROS/Keap1/Nrf2 pathway. • Pharmacologists and clinicians must collaborate to bring promising food functional findings from the bench to the bedside.

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: Simulation or modeling · Consensus signal: none
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)0.0000.001
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)0.0010.000

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 head0.075
GPT teacher head0.322
Teacher spread0.247 · 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 designSimulation or modeling
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
Published2024
Admission routes1
Has abstractyes

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