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Record W4413219358 · doi:10.1021/acsomega.5c03992

Hepatoprotective Potential of Green Synthesized Nanoparticles from <i>Citrus reticulata</i> Peel Extract against HFS Diet-Induced NASH in Mice, Integrated with Chemical Profiling and Molecular Modeling

2025· article· en· W4413219358 on OpenAlexaff
Sameh S. Elhady, Alaa S. Wahba, Ahmed K. Ibrahim, Gharieb S. El‐Sayyad, Ahmed M. El‐Khawaga, Nehal S. Wahba, Mohamed S. Nafie, Safwat A. Ahmed, Amany K. Ibrahim, Jihan M. Badr, Samar S. A. Murshid, Alaa Bagalagel, Eman S. Habib, Reda F. A. Abdelhameed

Bibliographic record

VenueACS Omega · 2025
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsCentre for Drug Research and Development
FundersKing Abdulaziz University
KeywordsChemistryNanoparticleTraditional medicineBiochemistryNanotechnologyMaterials scienceMedicine

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Citrus reticulata is known for its wide variety of secondary metabolites, including essential oil, alkaloids, flavonoids, and phenolic acids, which are considered the reason for its diverse potential medical uses. Herein, Citrus reticulata extract was prepared using different formulas of metal oxide nanoparticles as ZnO NPs and MgO NPs with 22.5 ± 1.3 and 18.3 ± 1.5 nm average particle sizes, respectively. The protective effects of Citrus reticulata extract and its two nano formulas against NASH induced by a high-fat, high-sucrose (HFS) diet in mice were evaluated. The NASH mice showed hepatic steatosis, inflammation, reduced liver function, increased body, liver, and fat weights, elevated hepatic index, and disrupted serum lipid profiles. Additionally, the mice displayed heightened hepatic oxidative stress and increased expression of inflammatory and profibrotic markers, along with altered lipid metabolism, indicated by elevated levels of SIRT-1, FGF-21, and SREBP-1c. Notably, treatment with Citrus reticulata extract and its metallic nanoparticle formulations alleviated these abnormalities, with the most significant improvement observed in the MgO NP formulation. Finally, Citrus reticulata extract was subjected to a deep phytochemical screening through Liquid chromatography combined with mass spectrometry (LC–MS/MS) analysis, revealing the presence of a high diversity of polyphenolics that may contribute to the suggested therapeutic effects of the Citrus reticulata crude extract. A molecular docking study highlighted the binding affinities of all identified flavonoid compounds, especially Quercetin, toward IL-1β, TNF-α, and TGF-β target proteins. This shows good translation for the cumulative anti-inflammatory effect depicted by the Citrus reticulata crude extract. Thermodynamic stability of Quercetin toward each bound proinflammatory protein was confirmed through 150 ns all-atom molecular dynamics simulations. Overall, current findings suggest that Citrus reticulata exerts a protective effect against NASH, which could be enhanced by nano formulas.

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 score0.019
Threshold uncertainty score0.676

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 head0.009
GPT teacher head0.232
Teacher spread0.224 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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