Skip to content
#protein folding Open access

Ultrasound-Assisted Enzymatic Deamidation Treatment for Developing Soft Surimi Gel for Dysphagia: Gel Properties, In Vitro Digestibility, and Protein Mechanisms

Aug 2026 · Foods · 0 citations · 44 references
Dysphagia Assessment and Management

TL;DR

A fundamental theoretical framework for the development of specialized foods that possess safe swallowing and nutritional attributes is offered and the polarity of the tryptophan residue microenvironment alters and impeding the further folding of unfolded protein structures during heat-induced gelation is examined.

Abstract

An urgent necessity exists to create foods that cater to the requirements of patients with dysphagia. The softened surimi gel appropriate for dysphagia patients was produced through ultrasonic-assisted Protein-glutaminase (PG) deamidation treatment. In comparison to the control group, the hardness and gel strength of softened surimi gel with a 0.2% PG addition diminished from 607.40 g and 530.79 g mm to 244.60 g and 78.61 g mm, respectively, satisfying the IDDSI Level 5 classification criteria (p < 0.05). The incorporation of PG transformed free water in the fish paste gel into less mobile water, markedly improving the gel’s water holding capacity. The ultrasound-assisted enzymatic deamidation treatment made the surimi gel produce more small molecular peptides and free amino acids during digestion. This treatment diminished hydrophobic interactions in myofibrillar protein gel, augmented hydrogen bonding, elevated the α-helix structure to 46.27%, and decreased the β-sheet structure to 19.18%, with significant differences compared to the control group (p < 0.05). The polarity of the tryptophan residue microenvironment alters and impeding the further folding of unfolded protein structures during heat-induced gelation. This study offers a fundamental theoretical framework for the development of specialized foods that possess safe swallowing and nutritional attributes.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.