Evidence map›Paper›PMID 42943705›Full record

ReviewMolecules (Basel, Switzerland)2026

Medicine-Food Homology Bioactives for Polyendocrine Metabolic Ovarian Syndrome: Multi-Target Mechanisms and Functional Food Translation.

Xiaoman Lv, Wenjuan Long, Zhongyang Hu, Mingqin Shi, Xinyao Li, Yujun Feng, Jiarong Du, Zhicheng Yang, Fang Peng, Liwei Xing and 1 more

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Xiaoman LvCollege of Pharmaceutical Science, Dali University, Dali 671003, China.
Wenjuan LongKey Laboratory of Traditional Chinese Medicine for Prevention and Treatment of Neuropsychiatric Diseases, Yunnan University of Chinese Medicine, Kunming 650500, China.
Zhongyang HuKey Laboratory of Traditional Chinese Medicine for Prevention and Treatment of Neuropsychiatric Diseases, Yunnan University of Chinese Medicine, Kunming 650500, China.
Mingqin ShiThe First Clinical Medical College, Yunnan University of Chinese Medicine, Kunming 650500, China.ORCID 0009-0001-9700-1549
Xinyao LiThe First Clinical Medical College, Yunnan University of Chinese Medicine, Kunming 650500, China.
Yujun FengKey Laboratory of Traditional Chinese Medicine for Prevention and Treatment of Neuropsychiatric Diseases, Yunnan University of Chinese Medicine, Kunming 650500, China.
Jiarong DuKey Laboratory of Traditional Chinese Medicine for Prevention and Treatment of Neuropsychiatric Diseases, Yunnan University of Chinese Medicine, Kunming 650500, China.
Zhicheng YangYunnan Academy of Agricultural Engineering, Kunming 650215, China.
Fang PengCollege of Pharmaceutical Science, Dali University, Dali 671003, China.
Liwei XingThe First Clinical Medical College, Yunnan University of Chinese Medicine, Kunming 650500, China.
Dongdong QinKey Laboratory of Traditional Chinese Medicine for Prevention and Treatment of Neuropsychiatric Diseases, Yunnan University of Chinese Medicine, Kunming 650500, China.ORCID 0000-0002-2005-8408

Funding

National Natural Science Foundation of China 82460974
6 · The paper itself

Abstract

Polyendocrine Metabolic Ovarian Syndrome (PMOS) is characterized by insulin resistance, hyperandrogenism, chronic inflammation, and oxidative stress, with a global prevalence of 10-13% and limited current drug treatments. Medicine-Food Homology (MFH) materials are rich in bioactive compounds such as polyphenols, flavonoids, and polysaccharides, offering potential multi-target nutritional interventions for PMOS, although safety data remain limited mainly to single compounds. A systematic search of the literature was conducted across PubMed/MEDLINE, Web of Science CNKI, and Wanfang Data, spanning from database inception to August 2026, utilizing predefined search terms and inclusion/exclusion criteria. This review summarizes research on MFH-derived bioactive compounds in PMOS, covering active component identification, network pharmacology-based target prediction, key signaling pathways (PI3K/AKT, AMPK, NF-κB, Nrf2/HO-1), and formulation strategies including green extraction, nano-encapsulation, and controlled release. It further discusses functional food development from five perspectives: meal replacement powders, functional teas, fermented beverages, dietary supplements, and compound formulations. Key bottlenecks hindering commercialization are analyzed, including insufficient high-quality clinical evidence, unclear dose-response relationships, and limited long-term stability data. Future directions are proposed, such as organoids, organ-on-a-chip, AI-driven formulation optimization, and international multicenter trials. In summary, MFH bioactive compounds show potential as multi-target interventions for PMOS; however, most mechanistic evidence comes from non-PMOS metabolic models, and direct PMOS-specific evidence is limited. Their translation from empirical use to evidence-based intervention requires PMOS-specific preclinical validation, randomized controlled trials, safety assessments, bioavailability evaluation, and standardized product validation, alongside collaborative efforts across research paradigms, technology development, and industrial translation.

Indexed as

Functional FoodMetabolic SyndromePhytochemicalsAnimalsFemaleHumansSignal TransductionPhytochemicalsbioavailabilitygut microbiotananoencapsulationnetwork pharmacologyPI3K/AKT signalingpolycystic ovary syndromepolyendocrine metabolic ovarian syndromepolyphenols

Identifiers

PMID42943705
PMCPMC13707406

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.