A comprehensive multi-evidence framework for network pharmacology-based prediction of dietary flavonoid effects.

Koyo Fujisaki, Osei Horikoshi, Yukitoshi Nagahara, Kengo Morohashi

Abstract read

In one paragraph

Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Natural Products as a Pipeline for Next-Generation Neurodegenerative Drugs: From Single-Target Failure to Multi-Target Opportunity in Alzheimer's and Parkinson's Disease.Molecules (Basel, Switzerland) · 2026
Review

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Koyo FujisakiFaculty of Science and Technology, Department of Applied Chemistry and Bioscience, Chitose Institute of Science and Technology, Chitose, Hokkaido, Japan.

Osei HorikoshiDivision of Life Science, School of Science and Engineering, Tokyo Denki University, Hiki-gun, Saitama, Japan.

Yukitoshi NagaharaDivision of Life Science, School of Science and Engineering, Tokyo Denki University, Hiki-gun, Saitama, Japan.

Kengo MorohashiFaculty of Science and Technology, Department of Applied Chemistry and Bioscience, Chitose Institute of Science and Technology, Chitose, Hokkaido, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dietary flavonoids associate with various aspects of disease prevention, yet systematic frameworks integrating computational prediction with experimental and epidemiological evidence remain limited. We develop a multi-tiered network pharmacology framework that quantitatively predicts flavonoid-related therapeutic properties and supports these predictions with integrated computational, experimental, and epidemiological evidence. We constructed a master network of 17,869 human proteins, 14 dietary flavonoids, and 1,496 FDA-approved drugs (278,768 interactions). Flavonoids averaged 45.3 target proteins compared to 16.8 for FDA-approved drugs (2.7-fold higher;

Indexed as

dietary bioactivesflavonoidsfood composition databasemulti-evidence assessmentnetwork pharmacologypolypharmacologyprecision nutrition

Identifiers

PMID42058711

DOI10.3389/fnut.2026.1792521

PMCPMC13120915

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.