Evidence map›Paper›PMID 42729060›Full record

ArticleTranslational andrology and urology2026

Mouse models of obesity and male fertility: a systematic review and network meta-analysis.

Ying-Jun Deng, Feng Zhao, Sheng-Jing Liu, Qi Liu, Si-Han Sun, Bin Yan, Jun Guo

Abstract read
In one paragraph

Article in Translational andrology and urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ying-Jun Deng *Department of Gynaecology and Obstetrics, Hubei Provincial Hospital of Traditional Chinese Medicine, Affiliated Hospital of Hubei University of Chinese Medicine, Wuhan, China.
Feng Zhao *Department of Andrology, First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.
Sheng-Jing LiuDepartment of Andrology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Qi LiuDepartment of Gynaecology and Obstetrics, Hubei Provincial Hospital of Traditional Chinese Medicine, Affiliated Hospital of Hubei University of Chinese Medicine, Wuhan, China.
Si-Han SunNational Clinical Research Center for Chinese Medicine, Tianjin, China.
Bin YanDepartment of Andrology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, China.
Jun GuoDepartment of Andrology, Xiyuan Hospital of China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As the problem of obesity‑induced reduction in male fertility is attracting growing concern, we conducted this network meta-analysis to assess the effects of different high-fat diet (HFD) interventions on male fertility in obese mouse models, aiming to identify the most suitable modeling approach for obesity-related male infertility research. Methods: Sixty-three studies were included. Interventions were categorized based on fat proportion and duration into four HFD groups and compared to a normal diet (ND) group. Network meta-analysis assessed outcomes including body weight, relative testes mass and sperm parameters. Results: The network meta-analysis demonstrated that HFD interventions exerted distinct effects on obesity and reproductive indicators in male mice. HFD4, characterized by high dietary fat content and prolonged feeding duration, induced the most significant weight gain and fertility potential loss. Conclusions: Elevated dietary fat content and prolonged HFD intervention are two indispensable synergistic factors for establishing stable mouse models of obesity with reproductive impairment. HFD-induced obesity primarily triggers oligozoospermia and asthenospermia, with negligible impacts on sperm morphology. Given the inherent heterogeneity and incomplete methodological reporting of preclinical animal studies, the present bias assessment and result interpretation remain preliminary. Standardized unified HFD formulations and rigorous, well-designed animal experiments are required in future studies to further validate relevant findings and optimize obese reproductive injury modeling protocols.

Indexed as

male fertilityMice modelnetwork meta-analysisobesity

Identifiers

PMID42729060
PMCPMC13561733

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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.