The effects of air classification and lactic acid bacteria fermentation on the reduction of anti-nutritional factors (vicine and convicine, trypsin inhibitor activity, condensed tannins and phytic acid) and in vitro protein and starch digestibility of faba bean flour were studied. Free amino acid (FAA) profile analysis was also carried out. Air classification allowed the separation of the flour into protein and starch rich fractions, showing different chemical compositions and microstructures. Lactobacillus plantarum growth and acidification in faba bean flour and its fractions were assessed. The anti-nutritional compounds were separated mostly to the fine protein-rich fraction. Fermentation caused the decrease of vicine and convicine contents by more than 91% and significantly reduced trypsin inhibitor activity and condensed tannins (by more than 40% in the protein-rich fraction). No significant (P>0.05) variation was observed for total phenols and phytic acid content. Fermentation increased the amount of FAA, especially of the essential amino acids and γ-aminobutyric acid, enhanced the in vitro protein digestibility and significantly lowered the hydrolysis index. This work showed that the combination of air classification and fermentation improved nutritional functionality of faba bean flour which could be utilized in various food applications.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.ijfoodmicro.2014.10.012 | DOI Listing |
BMC Cancer
January 2025
Department of Thoracic Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Background: The refinement of risk stratification in lung adenocarcinoma (LUAD) plays a pivotal role in advancing precision medicine; however, the current staging classification falls short of comprehensiveness, particularly in the case of stage IA patients. We aimed to molecularly stratify LUAD patients especially for stage IA.
Methods: We analysed tumour heterogeneity and identified highly proliferating cancer cells (HPCs) in LUAD by performing single-cell RNA sequencing (scRNA-seq) analysis, immunohistochemical (IHC) staining using a tissue microarray, flow cytometry and biological experiments.
Micromachines (Basel)
December 2024
School of Mechanical Engineering, Sichuan University, Chengdu 610065, China.
This study addresses the challenge of multi-dimensional and small gas sensor data classification using a gelatin-carbon black (CB-GE) composite film sensor, achieving 91.7% accuracy in differentiating gas types (ethanol, acetone, and air). Key techniques include Principal Component Analysis (PCA) for dimensionality reduction, the Synthetic Minority Over-sampling Technique (SMOTE) for data augmentation, and the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) algorithms for classification.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Medical and Health Sciences Tarnobrzeg, State Higher Vocational School Memorial of Prof. Stanislaw Tarnowski in Tarnobrzeg, 39-400 Tarnobrzeg, Poland.
The World Health Organization (WHO) estimates that 180,000 patients die from burns every year, which is considered a serious public health issue. Patients with burns require immediate pre-hospital care and transport to specialized treatment facilities. The aim of this study was to outline the profile of the burn patient from the perspective of the Polish Medical Air Rescue (PMAR), as well as to analyze the medical procedures being implemented.
View Article and Find Full Text PDFSci Rep
January 2025
Computer Vision Center, Universitat Autònoma de Barcelona, Barcelona, 08193, Spain.
In this study, we explore an enhancement to the U-Net architecture by integrating SK-ResNeXt as the encoder for Land Cover Classification (LCC) tasks using Multispectral Imaging (MSI). SK-ResNeXt introduces cardinality and adaptive kernel sizes, allowing U-Net to better capture multi-scale features and adjust more effectively to variations in spatial resolution, thereby enhancing the model's ability to segment complex land cover types. We evaluate this approach using the Five-Billion-Pixels dataset, composed of 150 large-scale RGB-NIR images and over 5 billion labeled pixels across 24 categories.
View Article and Find Full Text PDFAppl Microbiol Biotechnol
January 2025
Department of Ultrasound Medicine, The Second Affiliated Hospital of Air Force Medical University, No.569 Xinsi Road, Xi'an, 710038, Shaanxi, China.
Bacteria-based tumor therapy, which releases therapeutic payloads or remodels the tumor's immune-suppressive microenvironment and directly kills tumor cells or initiates an anti-tumor immune response, is recently recognized as a promising strategy. Bacteria could be endowed with the capacities of tumor targeting, tumor cell killing, and anti-tumor immune activating by established gene engineering. Furthermore, the integration of synthetic biology and nanomedicine into these engineered bacteria could further enhance their efficacy and controllability.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!