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1.
Food Chem ; 449: 139305, 2024 Aug 15.
Article in English | MEDLINE | ID: mdl-38615636

ABSTRACT

The main objective of this study is to investigate the impact and mechanism of soy lecithin incorporation into the gelatin-cinnamaldehyde emulsion, focusing on how it influences emulsion stability during the electrospinning process. In this work, a cinnamaldehyde/gelatin/soy lecithin (CGS) fiber membrane with excellent antibacterial properties was successfully created. The addition of soy lecithin improves the stability of the emulsion and improves the loading performance and fiber morphology of the CGS fiber membrane. Fourier Transform infrared spectroscopy (FTIR) and urea addition confirmed that soy lecithin may strengthen the interface structure of gelatin in the oil and water phases through hydrogen bonds, thus enhancing the stability of the emulsion in electrospinning. The application tests also revealed that the CGS fiber membrane effectively preserved the sensory quality of beef. This study indicates that the vector construction method can extend the utilization of cinnamaldehyde in food industry.


Subject(s)
Acrolein , Acrolein/analogs & derivatives , Emulsions , Gelatin , Glycine max , Lecithins , Nanofibers , Acrolein/chemistry , Acrolein/pharmacology , Gelatin/chemistry , Emulsions/chemistry , Lecithins/chemistry , Nanofibers/chemistry , Glycine max/chemistry , Animals , Cattle , Anti-Bacterial Agents/chemistry , Anti-Bacterial Agents/pharmacology
2.
Small ; : e2310191, 2024 Mar 03.
Article in English | MEDLINE | ID: mdl-38431965

ABSTRACT

Wearable heaters with multifunctional performances are urgently required for the future personal health management. However, it is still challengeable to fabricate multifunctional wearable heaters simultaneously with flexibility, air-permeability, Joule heating performance, electromagnetic shielding property, and anti-bacterial ability. Herein, silver nanoparticles (AgNPs)@MXene heterostructure-decorated graphite felts are fabricated by introducing MXene nanosheets onto the graphite felts via a simple dip-coating method and followed by a facile in situ growth approach to grow AgNPs on MXene layers. The obtained AgNPs@MXene heterostructure decorated graphite felts not only maintain the intrinsic flexibility, air-permeability and comfort characteristics of the matrixes, but also present excellent Joule heating performance including wide temperature range (30-128 °C), safe operating conditions (0.9-2.7 V), and rapid thermal response (reaching 128 °C within 100 s at 2.7 V). Besides, the multifunctional graphite felts exhibit excellent electromagnetic shielding effectiveness (53 dB) and outstanding anti-bacterial performances (>95% anti-bacterial rate toward Bacillus subtilis, Escherichia coli and Staphy-lococcus aureus). This work sheds light on a novel avenue to fabricate multifunctional wearable heaters for personal healthcare and personal thermal management.

3.
BMC Bioinformatics ; 23(1): 297, 2022 Jul 25.
Article in English | MEDLINE | ID: mdl-35879669

ABSTRACT

Since the completion of the Human Genome Project at the turn of the century, there has been an unprecedented proliferation of sequencing data. One of the consequences is that it becomes extremely difficult to store, backup, and migrate enormous amount of genomic datasets, not to mention they continue to expand as the cost of sequencing decreases. Herein, a much more efficient and scalable program to perform genome compression is required urgently. In this manuscript, we propose a new Apache Spark based Genome Compression method called SparkGC that can run efficiently and cost-effectively on a scalable computational cluster to compress large collections of genomes. SparkGC uses Spark's in-memory computation capabilities to reduce compression time by keeping data active in memory between the first-order and second-order compression. The evaluation shows that the compression ratio of SparkGC is better than the best state-of-the-art methods, at least better by 30%. The compression speed is also at least 3.8 times that of the best state-of-the-art methods on only one worker node and scales quite well with the number of nodes. SparkGC is of significant benefit to genomic data storage and transmission. The source code of SparkGC is publicly available at https://github.com/haichangyao/SparkGC .


Subject(s)
Algorithms , Data Compression , Data Compression/methods , Genome , High-Throughput Nucleotide Sequencing/methods , Humans , Sequence Analysis, DNA/methods , Software
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