Evidence map›Paper›PMID 42712992›Full record

ReviewFood chemistry: X2026

Multi-scale hierarchical regulation of starch chain length distribution and its consequential impact on starch digestibility: From molecular structure to granular degradation.

Zixuan Liu, Tianshuang Xia, Chunfan Guo, Jingxuan Ma, Mingyue Chen, Zhaoxia Wu

Abstract readReview
In one paragraph

Review in Food chemistry: X, 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

6 authors.

Zixuan LiuCollege of Food Science, Shenyang Agricultural University, Dongling Road, Shenhe District, Shenyang 110866, China.
Tianshuang XiaPanjin Center for Disease Control and Prevention, Food Hygiene Section, Panjin 124010, China.
Chunfan GuoCollege of Food Science, Shenyang Agricultural University, Dongling Road, Shenhe District, Shenyang 110866, China.
Jingxuan MaCollege of Food Science, Shenyang Agricultural University, Dongling Road, Shenhe District, Shenyang 110866, China.
Mingyue ChenCollege of Food Science, Shenyang Agricultural University, Dongling Road, Shenhe District, Shenyang 110866, China.
Zhaoxia WuCollege of Food Science, Shenyang Agricultural University, Dongling Road, Shenhe District, Shenyang 110866, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Starch chain length distribution (CLD) hierarchically modulates starch digestibility from enzyme recognition to granular degradation. This review summarizes CLD characteristics of amylose (short, medium, long chains) and amylopectin (A, B1, B2, B3 chains). The hierarchical regulatory rules are elucidated at molecular (chain flexibility, hydrogen bonding), aggregated (double helix, crystalline-amorphous regions), and granular (morphology, pores) scales. It further clarifies how distinct CLD profiles dynamically modulate the proportions of rapidly digestible starch (RDS), slowly digestible starch (SDS), and resistant starch (RS) by modulating enzyme accessibility and hydrolysis kinetics through hierarchical structures. Precise CLD regulation technologies (molecular modification, physical processing, biological regulation) and their digestibility modulation effects are summarized. Finally, key controversies (cross-scale transfer mechanisms of CLD regulation from molecular conformation to granular degradation,

Indexed as

Aggregated state structureGranular degradationMolecular conformationResistant starchSlowly digestible starchStarch chain length distribution

Identifiers

PMID42712992
PMCPMC13551939

What OpenQuestion holds

Textmetadata
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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.