Evidence map›Paper›PMID 41140583›Full record

ArticleFood chemistry: X2025

High-value utilization of brewers' spent grain in extruded corn-based foods: physicochemical, functional, and metabolomic insights.

Yan Huang, Zhengjie Xie, Guohua Zhao, Yu Zhang, Jiajia Song, Xiaoqi Xu, Damao Wang

Abstract read
In one paragraph

Article in Food chemistry: X, 2025. 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

7 authors.

Yan HuangYibin academy of Southwest University, Yibin 644000, China.
Zhengjie XieYibin academy of Southwest University, Yibin 644000, China.
Guohua ZhaoYibin academy of Southwest University, Yibin 644000, China.
Yu ZhangYibin academy of Southwest University, Yibin 644000, China.
Jiajia SongCollege of Food Science, Southwest University, Chongqing 400715, China.
Xiaoqi XuCollege of Food and Light Industry, Nanjing Tech University, Nanjing 211800, China.
Damao WangYibin academy of Southwest University, Yibin 644000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high-value utilization of brewers' spent grain (BSG), a protein- and polyphenol-rich by-product of the brewing industry, holds great promise for developing functional foods. In this study, BSG was incorporated into extruded corn-based products at varying levels (0-35 wt%), and its effects on physicochemical properties, antioxidant capacity, α-amylase inhibition, and metabolic profile were systematically investigated. The inclusion of BSG significantly improved water- and oil-holding capacities, total dietary fiber, and total phenolic content (TPC), with 30 wt% identified as an optimal formulation balancing functionality and sensory acceptability. Following in vitro digestion, the BSG-enriched extrudates exhibited significantly enhanced antioxidant activity (FRAP and DPPH assays) and α-amylase inhibitory potential, supporting their hypoglycemic potential. UHPLC-MS-based untargeted metabolomics further revealed key bioactive compounds, including 9-cis-retinoic acid and tryptophylproline, contributing to the enrichment of immune- and glucose-regulating pathways (e.g., intestinal IgA, PI3K-Akt, FoxO signaling). These results highlight the potential of BSG-fortified extrudates as value-added, fiber-enriched functional foods and provide mechanistic insights for their future nutritional development and clinical evaluation.

Indexed as

antioxidant activityBrewers' spent grainfunctional food innovationmetabolomicsα-amylase inhibition

Identifiers

PMID41140583
PMCPMC12547939

What OpenQuestion holds

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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.