Evidence map›Paper›PMID 36553806›Full record

ReviewFoods (Basel, Switzerland)2022

Bacterial Cellulose Nanofibril-Based Pickering Emulsions: Recent Trends and Applications in the Food Industry.

Xingzhong Zhang, Dan Wang, Shilin Liu, Jie Tang

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

4 authors.

Xingzhong ZhangCollege of Food and Bioengineering, Xihua University, Chengdu 610039, China.
Dan WangCollege of Food and Bioengineering, Xihua University, Chengdu 610039, China.
Shilin LiuCollege of Food Science & Technology, Huazhong Agricultural University, Wuhan 430070, China.
Jie TangCollege of Food and Bioengineering, Xihua University, Chengdu 610039, China.

Funding

Xihua University Talent Introduction Project Z222040
6 · The paper itself

Abstract

The Pickering emulsion stabilized by food-grade colloidal particles has developed rapidly in recent decades and attracts extensive attention for potential applications in the food industry. Bacterial cellulose nanofibrils (BCNFs), as green and sustainable colloidal nanoparticles derived from bacterial cellulose, have various advantages for Pickering emulsion stabilization and applications due to their unique properties, such as good amphiphilicity, a nanoscale fibrous network, a high aspect ratio, low toxicity, excellent biocompatibility, and sustainability. This review provides a comprehensive overview of the recent advances in the Pickering emulsion stabilized by BCNF particles, including the classification, preparation method, and physicochemical properties of diverse BCNF-based particles as Pickering stabilizers, as well as surface modifications with other substances to improve their emulsifying performance and functionality. Additionally, this paper highlights the stabilization mechanisms and provides potential food applications of BCNF-based Pickering emulsions, such as nutrient encapsulation and delivery, edible coatings and films, fat substitutes, etc. Furthermore, the safety issues and future challenges for the development and food-related applications of BCNFs-based Pickering emulsions are also outlined. This work will provide new insights and more ideas on the development and application of nanofibril-based Pickering emulsions for researchers.

Indexed as

bacterial cellulose nanofibrilsnutrient encapsulation and deliveryPickering emulsionstabilization mechanism

Identifiers

PMID36553806
PMCPMC9778365

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.