Evidence map›Paper›PMID 42370369›Full record

ArticleFrontiers in nutrition2026

Integrative AI driven microbiome analysis for optimizing sports nutrition and enhancing athletic performance through personalized dietary interventions.

Yankun Zhang, Hongjing Wang, Ting Deng

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. 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

3 authors.

Yankun ZhangSchool of Physical Education, Suihua University, Suihua, China.
Hongjing WangSchool of Special Education, Suihua University, Suihua, China.
Ting DengSchool of Electrical Engineering, Nanjing Normal University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The relationship between microbiome composition, athletic performance, and personalized nutrition offers significant potential for optimizing sports nutrition and enhancing athletic outcomes through tailored dietary strategies. Methods: This study presents a novel framework, Integrative Microbiome Athletic Performance Optimization Network (IMAPON), designed to address this challenge by integrating microbiome data, athletic performance metrics, and demographic and physiological information to generate precise dietary recommendations. IMAPON consists of three core modules: the Microbiome Feature Extraction Module (MFEM), the Athletic Performance Prediction Module (APPM), and the Personalized Dietary Recommendation Module (PDRM). Two innovative strategies, the Adaptive Feature Integration Strategy (AFIS) and the Performance Driven Optimization Strategy (PDOS), are incorporated to improve system efficacy. AFIS facilitates dynamic integration of features from heterogeneous data sources, while PDOS aligns dietary interventions with specific athletic performance objectives. The framework employs advanced computational techniques, including feature extraction, representation learning, and optimization, formalized through mathematical models to capture latent interactions between microbiome composition, physiological factors, and performance metrics. Results and discussion: Experimental results demonstrate the effectiveness of IMAPON in generating actionable dietary recommendations, highlighting its potential to transform sports nutrition by enabling precise, data driven interventions tailored to individual athletes. This approach represents a significant advancement in leveraging artificial intelligence for personalized nutrition and athletic performance enhancement.

Indexed as

athletic performancedietary recommendationsIMAPONmicrobiome compositionpersonalized nutrition

Identifiers

PMID42370369
PMCPMC13303024

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.