Display omitted
•Glycation induced unfolding and dissociation of the myofibrillar protein (MP).•100–200 W ultrasound treatment accelerated the later stage of glycation reaction.•100 W ultrasound ...developed a well-controlled glycation between MP and dextran (DX).•Introduction of DX could improve the solubility and emulsifying properties of MP.•Conjugates prepared by 100 W ultrasound exhibited optimal emulsifying behaviors.
In this study, we investigated the effect of the ultrasound-assisted Maillard reaction on the structural and emulsifying properties of myofibrillar protein (MP) and dextran (DX) conjugates with different molecular weights (40, 70 and 150 kDa). Compared with classical heating, mild and moderate ultrasound-assisted methods (100–200 W) could accelerate the later stage of the Maillard reaction, which increased the degree of graft (DG) and the content of advanced Maillard reaction products (MPRs). Structural analysis revealed conjugates obtained by Maillard reaction induced the loss of ordered secondary structures (α-helix, β-sheets) and red-shift of maximum emission wavelength of intrinsic fluorescence spectrum. The conjugate containing 40 kDa DX exhibited higher extent of Maillard reaction compared to those containing 70 kDa and 150 kDa DX under various treating methods. Moreover, the ultrasound-assisted Maillard reaction could effectively improve the emulsifying behaviors. 100 W ultrasound-induced conjugates grafted by 70 kDa DX produced the smallest emulsion size with optimum storage stability. Confocal laser scanning microscopy and analytical centrifugal analyzer further confirmed MP grafted by 70 kDa DX with the assistance of 100 W ultrasound field could produce the smallest and most homogeneous MP-base emulsion with no flocculation. Our study demonstrated that mild ultrasound treatment resulted in well-controlled Maillard reaction, and the related glycoconjugate grafted with 70 kDa DX showed the greatest improvements in emulsifying ability and stability. These findings provided a theoretical foundation for the development of emulsion-based foods with excellent characteristics.
Monascus vinegar is one of the most famous and popular Chinese vinegars. The present study identified 60 volatile compounds, 23 amino acids, and seven organic acids during the traditional brewing of ...Monascus vinegar. Acetic acid, alanine, alcohols, esters, lactic acid, and valine were the predominant metabolic compounds found during the fermentation process. Komagataeibacter medellinensis, Lactobacillus acetotolerans, Saccharomycopsis fibuligera, Sterigmatomyces halophilus, and Yarrowia lipolytica were the dominant microorganisms during the traditional brewing of Monascus vinegar. Furthermore, based on Spearman's correlation analysis, K. medellinensis showed a positive correlation with acetic acid, acetoin, benzaldehyde, phenethyl acetate, 4-ethylphenol, proline, threonine, and isoleucine. Saccharomyces cerevisiae was positively associated with the production of acetoin, benzeneacetaldehyde, 2,3,5-trimethylpyrazine, proline, threonine, and isoleucine. Bacillus velezensis and Yarrowia lipolytica were positively correlated with esters and alcohols, implying that these microorganisms might make a significant contribution to the flavor of vinegar. These findings demonstrated that some microorganisms may play important roles in improving the aromatic quality of Monascus vinegar.
Display omitted
•Volatile compounds in Monascus vinegar were identified.•Amino acids and organic acids in Monascus vinegar were investigated.•Flavor and dominant microflora network analysis in vinegar were explored.
Stroke is the leading cause of death and disability among people in China, and it leads to heavy burdens for patients, their families and society. An accurate prediction of the risk of stroke has ...important implications for early intervention and treatment. In light of recent advances in machine learning, the application of this technique in stroke prediction has achieved plentiful promising results. To detect the relationship between potential factors and the risk of stroke and examine which machine learning method significantly can enhance the prediction accuracy of stroke. We employed six machine learning methods including logistic regression, naive Bayes, decision tree, random forest, K-nearest neighbor and support vector machine, to model and predict the risk of stroke. Participants were 233 patients from Sichuan and Chongqing. Four indicators (accuracy, precision, recall and F1 metric) were examined to evaluate the predictive performance of the different models. The empirical results indicate that random forest yields the best accuracy, recall and F1 in predicting the risk of stroke, with an accuracy of .7548, precision of .7805, recall of .7619 and F1 of .7711. Additionally, the findings show that age, cerebral infarction, PM 8 (an anti-atrial fibrillation drug), and drinking are independent risk factors for stroke. Further studies should adopt a broader assortment of machine learning methods to analyze the risk of stroke, by which better accuracy can be expected. In particular, RF can successfully enhance the forecasting accuracy for stroke.
•Ovalbumin (OVA)-EGCG conjugates were fabricated by an ultrasound-assisted method.•OVA-EGCG conjugates were studied by experimental assays and computer simulations.•The interaction of OVA and EGCG ...altered the protein conformation.•The emulsifying property of the conjugates was better than that of native OVA.•Conjugates induced by ultrasound-assisted method showed superiority in antioxidant properties.
The influence of ultrasound-assisted free radical modification on the structure and functional properties of ovalbumin-epigallocatechin gallate (OVA-EGCG) conjugates was investigated by experimental measurements and computer simulations. Compared with the traditional free radical condition, the ultrasonic-assisted processing significantly increased the conjugating efficiency of OVA and EGCG and shortened the conjugating from 24 h to 1 h without affecting the equivalent amount of EGCG conjugating. The sodium dodecyl sulfate–polyacrylamide gel electrophoresis and multi-spectroscopy analysis (Fourier transform infrared spectroscopy, intrinsic fluorescence spectroscopy, and UV spectroscopy) indicated that the covalent conjugates could be formed between OVA and EGCG. And modification in the conformation of OVA was induced by EGCG. Furthermore, molecular docking results demonstrated the possession of high-affinity EGCG binding location on OVA, supporting and clarifying the experimental results. In addition, the functional properties of OVA including emulsification (emulsifying activity and emulsion stability) and antioxidant properties (DPPH scavenging capacity and ABTS scavenging capacity) were significantly improved after conjugation with EGCG, especially in ultrasound-assisted conditions. Overall, OVA-EGCG conjugates produced by ultrasound-assisted free radical treatment could be applied as a potential emulsifier and antioxidant, thereby expanding the application of OVA as a dual-functional ingredient.
Display omitted
•Solubility and stability efficacy of dihydromyricetin (DYM) were improved by SMEDDS.•SMEDDS significantly increased the in vitro release of DYM.•SMEDDS showed superiority in ...delivering DYM.•DYM-SMEDDS exhibited superior anti-inflammatory and hepatoprotective effects.
To enhance the stability and anti-inflammatory efficacy of dihydromyricetin (DYM), suitable excipients were selected for the development of a self-microemulsifying drug delivery system (SMEDDS). The formulated SMEDDS exhibited remarkable drug loading (117.47 ± 4.5 mg/g) and encapsulation rates (93.98 ± 3.6 %). Transmission electron microscope (TEM) revealed the nanoscale and spherical morphology of DYM-SMEDDS. Stability assessments demonstrated that DYM-SMEDDS maintained a consistent uniform small particle size after various cycles of exposure. In vitro release curve exhibited that DYM-SMEDDS released 91.27 ± 1.44 % of DYM within 24 h, surpassing the suspension by 2-fold. Furthermore, in vivo studies indicated that DYM-SMEDDS significantly inhibited the levels of pro-inflammatory factors, while promoting the activity of antioxidant enzymes (p < 0.05). These findings underscore the preventive effects of DYM-SMEDDS against inflammation induced by lipopolysaccharide in mice. In conclusion, SMEDDS exhibits promising potential for oral administration, providing an effective platform for enhancing the efficacy of poorly soluble flavonoids.
•GA could be used as sole shell material for preparing curcumin loaded nanoparticle by the self-assembly effect.•The photostability of curcumin loaded in GA nanoparticle are greatly higher than free ...curcumin.•The bioavaibility of the curcumin can be significantly enhanced after loading in GA nanoparticle.
In this study, a kind of nanoparticle prepared using gum arabic as a sole wall material for loading curcumin was obtained. The properties and digestive characteristics of the curcumin-loaded nanoparticle were determined. Results showed that the maximum loading amount of the nanoparticle was 0.51 µg/mg with an approximately 500 nm size. The Fourier transform infrared (FTIR) spectrum showed that the complexation was mainly related to the -CO, –CH, and -COC- groups. The curcumin-loaded nanoparticle exhibited good stability under highly concentrated salinity stress, and the stability of the curcumin loaded in nanoparticles was significantly higher than that of free curcumin under ultraviolet radiation. The curcumin loaded in nanoparticle was released mainly in the intestinal digestion stage, and the release process was sensitive to the pH changes rather than protease. In conclusion, these nanoparticles can be a potential nanocarrier for enhancing the stability of curcumin which can be applied in the salt-containing food system.
•Blackberry polysaccharide (BP) was extracted and the composition was analyzed.•Flavor characteristics of chicken breast were improved by addition of BP.•The stability and hardness of chicken breast ...were improved by BP.
Blackberry polysaccharide was isolated from blackberry powder with 70% ethanol. The crude polysaccharide was composed of 95.44% glucose, 2.01% arabinose, 1.81% galactose and 0.74% glucuronic acid. Chicken breast meat was only marinated with different concentrations of the isolated blackberry polysaccharide (1 g/kg, 3 g/kg) for 24 h at a ratio of material to liquid of 1:3, and boiled at 80℃ for 1 h. The differences in texture, water distribution and volatile flavor components among different groups （adding 0,1,3 g/kg blackberry polysaccharide) were investigated. The results showed that the addition of blackberry polysaccharide could significantly improve the hardness of chicken breast, the transformation of free water to bound water, the overall flavor characteristics of the control group and the addition of different concentrations of blackberry polysaccharide were significantly different, and the concentration of volatile flavor substances in boiled chicken breast was reduced.
The study of circulating cells in the blood stream is critical, as it covers many fields of biomedicine, including immunology, cell biology, oncology, and reproductive medicine. In-vivo flow ...cytometry (IVFC) is a new tool to monitor and count cells in real time for long durations in their native biological environment. This review describes two main categories of IVFC, i.e., labeled and label-free IVFC. It focuses on label-free IVFC and introduces its technological development and related biological applications. Because cell recognition is the basis of flow cytometry counting, this review also describes various methods for the classification of unlabeled cells, including the latest machine learning-based technologies.
The adherence to secondary prevention treatment in patients with coronary heart disease (CHD) is low. Digital therapeutics (DTx) refers to an emerging branch of medicine that delivers medical ...interventions directly to patients using evidence-based, clinically evaluated, technology-based software algorithms or apps to facilitate disease management, which may be an efficient tool to optimize adherence.
This paper aims to investigate the effect of mobile app-based self-management DTx on long-term use of secondary prevention medications in patients with CHD in China.
This pilot study was a parallel-designed, open-labeled, single-center, randomized controlled trial. Hospitalized patients with CHD admitted to Peking University First Hospital between April 2016 and June 2017 were randomized before discharge on a 1:1 ratio. The intervention group received regular follow-up combined with DTx, which is a self-management mobile app already installed on an Android 5 (Mi Pad 1, Xiaomi Corporation) tablet. Structured data from the hospital informatics system were integrated automatically, and medication, lifestyle intervention plan, follow-up protocol, and patient education materials were also provided according to the diagnosis. Participants could use DTx for self-management at home. The control group was under conventional hospital-based follow-up care. Patients were followed up for 1 year, and the primary end point was the percentage of all guideline-recommended medications at 12 months. The secondary end points included the percentage adhered to standard secondary prevention medications at 6 months, the control rate of lipid profile, and blood pressure at 6 months and 1 year.
Among 300 randomized patients with CHD, 290 (96.7%) were included in the final analysis, including 49.3% (143/290) and 50.7% (147/290) of patients from the intervention and control groups, respectively. Baseline characteristics were similar between the 2 groups. There was a statistically significant improvement in the percentage of all guideline-recommended medications at 12 months in the intervention group compared with the control group (relative risk RR 1.34, 95% CI 1.12-1.61; P=.001), and there was no interaction with baseline characteristics. The intervention group had a significantly higher proportion of patients achieving blood pressure under control (systolic blood pressure <140 mm Hg and diastolic blood pressure <90 mm Hg) and low-density lipoprotein cholesterol <1.8 mmol/L (RR 1.45, 95% CI 1.22-1.72; P<.001 and RR 1.40, 95% CI 1.11-1.75; P=.004, respectively) at 12 months. Furthermore, on logistic regression, the intervention group had a lower risk of withdrawing from guideline-recommended medications (odds ratio 0.46, 95% CI 0.27-0.78; P=.004).
Among patients with CHD, using a mobile app-based self-management DTx in addition to traditional care resulted in a significant improvement in guideline-recommended medication adherence at 12 months. The results of the trial will be applicable to primary care centers, especially in rural areas with less medical resources.
ClinicalTrials.gov NCT03565978; https://clinicaltrials.gov/ct2/show/NCT03565978.
Attributed graph clustering is a fundamental task in complex network analysis. Many existing graph clustering methods utilize graph representation learning techniques to learn node representations, ...subsequently applying K-means for clustering. Despite the significant attention and promising outcomes of graph contrastive learning in graph representation learning, we find two essential problems that need to be solved. (1) How to achieve augmentation for contrast that preserves the cluster structure of a given graph? (2) How to design an effective contrastive learning mechanism that collaborates with clustering? Therefore, we propose an attributed graph clustering method under the contrastive mechanism with cluster-preserving augmentation, integrating node representation learning and clustering into a unified framework. Specifically, we construct a contrasting view based on a generated kNN graph and edge betweenness centrality to preserve the cluster structure in the original graph. Meanwhile, a multilevel contrast mechanism based on pseudo-label-guided negative sampling is proposed to maximize the agreement between node representations in multiple latent spaces. We jointly optimize a specific clustering objective during the contrastive process, leading to refined cluster distribution directly in training. Extensive experiments on several datasets demonstrate that our proposed model consistently outperforms existing state-of-the-art methods on clustering.
•An attributed graph clustering method under the contrastive mechanism is proposed.•A cluster-aware contrasting view based on EBC and kNN graph is built.•Multilevel contrast and self-supervised clustering are jointly optimized.•Extensive experiments demonstrate the superiority of the model in clustering.
PDF
