Unraveling the Ligand-Binding Sites of CYP3A4 by Molecular Dynamics Simulations with Solvent Probes.

Cytochrome P450 3A4 (CYP3A4) is one of the most important drug-metabolizing enzymes in the human body and is well known for its complicated, atypical kinetic characteristics. The existence of multiple ligand-binding sites in CYP3A4 has been widely recognized as being capable of interfering with the active pocket through allosteric effects. The identification of ligand-binding sites other than the canonical active site above the heme is especially important for understanding the atypical kinetic characteristics of CYP3A4 and the intriguing association between the ligand and the receptor. In this study, we first employed mixed-solvent molecular dynamics (MixMD) simulations coupled with the online computational predictive tools to explore potential ligand-binding sites in CYP3A4. The MixMD approach demonstrates better performance in dealing with the receptor flexibility compared with other computational tools. From the sites identified by MixMD, we then picked out multiple sites for further exploration using ensemble docking and conventional molecular dynamics (cMD) simulations. Our results indicate that three extra sites are suitable for ligand binding in CYP3A4, including one experimentally confirmed site and two novel sites.

Evaluation of machine learning models for cytochrome P450 3A4, 2D6, and 2C9 inhibition.

Cytochrome P450 (CYP) enzymes are involved in the metabolism of approximately 75% of marketed drugs. Inhibition of the major drug-metabolizing P450s could alter drug metabolism and lead to undesirable drug-drug interactions. Therefore, it is of great significance to explore the inhibition of P450s in drug discovery. Currently, machine learning including deep learning algorithms has been widely used for constructing in silico models for the prediction of P450 inhibition. These models exhibited varying predictive performance depending on the use of machine learning algorithms and molecular representations. This leads to the difficulty in the selection of appropriate models for practical use. In this study, we systematically evaluated the conventional machine learning and deep learning models for three major P450 enzymes, CYP3A4, CYP2D6, and CYP2C9 from several perspectives, such as algorithms, molecular representation, and data partitioning strategies. Our results showed that the XGBoost and CatBoost algorithms coupled with the combined fingerprint/physicochemical descriptor features exhibited the best performance with Area Under Curve (AUC)  of 0.92, while the deep learning models were generally inferior to the conventional machine learning models (average AUC reached 0.89) on the same test sets. We also found that data volume and sampling strategy had a minor effect on model performance. We anticipate that these results are helpful for the selection of molecular representations and machine learning/deep learning algorithms in the P450 model construction and the future model development of P450 inhibition.

A macrophage cell membrane-coated cascade-targeting photothermal nanosystem for combating intracellular bacterial infections.

Current antibacterial interventions encounter formidable challenges when confronting intracellular bacteria, attributable to their clustering within phagocytes, particularly macrophages, evading host immunity and resisting antibiotics. Herein, we have developed an intelligent cell membrane-based nanosystem, denoted as MM@DAu NPs, which seamlessly integrates cascade-targeting capabilities with controllable antibacterial functions for the precise elimination of intracellular bacteria. MM@DAu NPs feature a core comprising D-alanine-functionalized gold nanoparticles (DAu NPs) enveloped by a macrophage cell membrane (MM) coating. Upon administration, MM@DAu NPs harness the intrinsic homologous targeting ability of their macrophage membrane to infiltrate bacteria-infected macrophages. Upon internalization within these host cells, exposed DAu NPs from MM@DAu NPs selectively bind to intracellular bacteria through the bacteria-targeting agent, D-alanine present on DAu NPs. This intricate process establishes a cascade mechanism that efficiently targets intracellular bacteria. Upon exposure to near-infrared irradiation, the accumulated DAu NPs surrounding intracellular bacteria induce local hyperthermia, enabling precise clearance of intracellular bacteria. Further validation in animal models infected with the typical intracellular bacteria, Staphylococcus aureus, substantiates the exceptional cascade-targeting efficacy and photothermal antibacterial potential of MM@DAu NPs in vivo. Therefore, this integrated cell membrane-based cascade-targeting photothermal nanosystem offers a promising approach for conquering persistent intracellular infections without drug resistance risks. STATEMENT OF SIGNIFICANCE: Intracellular bacterial infections lead to treatment failures and relapses because intracellular bacteria could cluster within phagocytes, especially macrophages, evading the host immune system and resisting antibiotics. Herein, we have developed an intelligent cell membrane-based nanosystem MM@DAu NPs, which is designed to precisely eliminate intracellular bacteria through a controllable cascade-targeting photothermal antibacterial approach. MM@DAu NPs combine D-alanine-functionalized gold nanoparticles with a macrophage cell membrane coating. Upon administration, MM@DAu NPs harness the homologous targeting ability of macrophage membrane to infiltrate bacteria-infected macrophages. Upon internalization, exposed DAu NPs from MM@DAu NPs selectively bind to intracellular bacteria through the bacteria-targeting agent, enabling precise clearance of intracellular bacteria through local hyperthermia. This integrated cell membrane-based cascade-targeting photothermal nanosystem offers a promising avenue for conquering persistent intracellular infections without drug resistance risks.

1D Chiral Enantiomer Lead-Free Perovskites Induced Chiralopical Activity and Photoelectric Response.

Chirality is a fascinating geometrical concept with widespread applications in biology, chemistry, and materials. Incorporating chirality into hybrid perovskite materials can induce novel physical properties (chiral optical activity, nonlinear optics, etc.). Hybrid lead-free or lead-substituted perovskite materials, as representatives of perovskites, have been widely used in fields such as photovoltaics, sensors, catalysis, and detectors. However, the successful introduction of chirality into hybrid lead-free perovskites, which can enable their potential applications in areas such as circularly polarized light photodetectors, memories, and spin transistors, remains a challenging research topic. Here, we synthesized two new chiral lead-free perovskites, [(R)-2-methylpiperazine][BiI5] and [(S)-2-methylpiperazine][BiI5]. The material possesses a perovskite structure with a one-dimensional (1D) arrangement, denoted as ABX5. This structure is composed of chiral cations, specifically methylpiperazine, and endless chains of [BiI3] along the a-axis. These chains are assembled from distorted coplanar [BiI5]2- octahedra. The testing results revealed that (R)-1 and (S)-1 have narrow band gaps (Eg-R = 2.016 eV, Eg-S = 1.964 eV), high photoelectric response, and long carrier lifetime [R = 4.94 µs (τ), S = 7.85 µs (τ)]. It is worth noting that 1D chiral lead-free perovskites (R)-1 and (S)-1, which are synthesized in this study with narrow band gaps, high photoelectric response, and long carrier lifetime, have the potential to serve as alternative materials for the perovskite layer in future iterations of lead-free perovskite solar cells. Moreover, this research will inspire the preparation of multifunctional, lead-free perovskites.

Prediction of Sites of Metabolism of CYP3A4 Substrates Utilizing Docking-Derived Geometric Features.

Cytochrome P450 3A4 (CYP3A4) is one of the major drug-metabolizing enzymes in the human body and is responsible for the metabolism of ∼50% of clinically used drugs. Therefore, the identification of the compound's sites of metabolism (SOMs) mediated by CYP3A4 is of utmost importance in the early stage of drug discovery and development. Herein, docking-based approaches incorporating geometric features were used for SOMs prediction of CYP3A4 substrates. The cross-docking poses of a relatively large data set containing 474 substrates were analyzed in depth, and a widely observed geometric pattern called the close proximity of SOMs was derived from the poses. On the basis of the close proximity, several structure-based models have been constructed, which demonstrated better performance than those structure-based models using the criterion of Fe-SOM distance. For further improving the prediction performance, the structure-based models were also combined with the well-known ligand-based model SMARTCyp. One combined model exhibited good performance on the SOMs prediction of an external substrate set containing kinase inhibitors, PROTACs, approved drugs, and some lead compounds.

Recent Advances in Pickering Double Emulsions and Potential Applications in Functional Foods: A Perspective Paper.

Double emulsions are complex emulsion systems with a wide range of applications across different fields, such as pharmaceutics, food and beverage, materials sciences, personal care, and dietary supplements. Conventionally, surfactants are required for the stabilization of double emulsions. However, due to the emerging need for more robust emulsion systems and the growing trends for biocompatible and biodegradable materials, Pickering double emulsions have attracted increasing interest. In comparison to double emulsions stabilized solely by surfactants, Pickering double emulsions possess enhanced stability due to the irreversible adsorption of colloidal particles at the oil/water interface, while adopting desired environmental-friendly properties. Such advantages have made Pickering double emulsions rigid templates for the preparation of various hierarchical structures and as potential encapsulation systems for the delivery of bioactive compounds. This article aims to provide an evaluation of the recent advances in Pickering double emulsions, with a special focus on the colloidal particles employed and the corresponding stabilization strategies. Emphasis is then devoted to the applications of Pickering double emulsions, from encapsulation and co-encapsulation of a wide range of active compounds to templates for the fabrication of hierarchical structures. The tailorable properties and the proposed applications of such hierarchical structures are also discussed. It is hoped that this perspective paper will serve as a useful reference on Pickering double emulsions and will provide insights toward future studies in the fabrication and applications of Pickering double emulsions.

Dental Materials for Oral Microbiota Dysbiosis: An Update.

The balance or dysbiosis of the microbial community is a major factor in maintaining human health or causing disease. The unique microenvironment of the oral cavity provides optimal conditions for colonization and proliferation of microbiota, regulated through complex biological signaling systems and interactions with the host. Once the oral microbiota is out of balance, microorganisms produce virulence factors and metabolites, which will cause dental caries, periodontal disease, etc. Microbial metabolism and host immune response change the local microenvironment in turn and further promote the excessive proliferation of dominant microbes in dysbiosis. As the product of interdisciplinary development of materials science, stomatology, and biomedical engineering, oral biomaterials are playing an increasingly important role in regulating the balance of the oral microbiome and treating oral diseases. In this perspective, we discuss the mechanisms underlying the pathogenesis of oral microbiota dysbiosis and introduce emerging materials focusing on oral microbiota dysbiosis in recent years, including inorganic materials, organic materials, and some biomolecules. In addition, the limitations of the current study and possible research trends are also summarized. It is hoped that this review can provide reference and enlightenment for subsequent research on effective treatment strategies for diseases related to oral microbiota dysbiosis.

Cation-Gated Ion Transport at Nanometer Scale for Tunable Power Generation.

Gated ion channels in biological cell membranes allow efficient tuning of cross-membrane ion transport with enhanced permeation and selectivity, converting ionic signals into various forms of electrical signals and energies on demands, which functionalities though are still difficult to achieve in artificial membranes. Here, we report cation-gated ion transport through synthesized porous aromatic films containing nanometer-scale ionic channels together with -NH2 groups at interiors. Ion selectivity and permeability is greatly tuned by gating cations, up to 2 orders of magnitude, and as a consequence, the membrane efficiently produces switchable electricity output from salinity gradients. The results are attributed to positively charged cations binding at -NH2 groups, which screens the intrinsic negative surface charge at channels' interiors and inverts charge polarity there. Our work adds understanding to ion gating effects at nanoscale and offers strategies of developing smart membranes and their heterostructures for separation, energy conversion, cell membrane mimics, and related technologies.

Anti-obesity effects of Chenpi: an artificial gastrointestinal system study.

The gut microbiota plays a significant role in human health; however, the complex relationship between gut microbial communities and host health is still to be thoroughly studied and understood. Microbes in the distal gut contribute to host health through the biosynthesis of vitamins and essential amino acids and the generation of important metabolic by-products from dietary components that are left undigested by the small intestine. Aged citrus peel (Chenpi) is used in traditional Chinese medicine to lower cholesterol, promote weight loss and treat various gastrointestinal symptoms. This study investigated how the microbial community changes during treatment with Chenpi using the Simulator of the Human Intestinal Microbial Ecosystem (SHIME). Two preparations of Chenpi extract were tested: Chenpi suspended in oil only and Chenpi in a viscoelastic emulsion. Short-chain fatty acids (SCFAs) were measured during treatment to monitor changes in the microbial community of the colon presenting a decrease in production for acetic, propionic and butyric acid (ANOVA (P < 0.001) during the 15 days of treatment. 16S rRNA sequencing of microbial samples showed a clear difference between the two treatments at the different sampling times (ANOSIM P < 0.003; ADOSIM P < 0.002 [R2 = 69%]). Beta diversity analysis by PcoA showed differences between the two Chenpi formulations for treatment day 6. These differences were no longer detectable as soon as the Chenpi treatment was stopped, showing a reversible effect of Chenpi on the human microbiome. 16S rRNA sequencing of microbial samples from the descending colon showed an increase in Firmicutes for the treatment with the viscoelastic emulsion. At the genus level, Roseburia, Blautia, Subdoligranulum and Eubacterium increased in numbers during the viscoelastic emulsion treatment. This study sheds light on the anti-obesity effect of a polymethoxyflavone (PMFs)-enriched Chenpi extract and creates a foundation for the identification of 'obesity-prevention' biomarkers in the gut microbiota.

Multi-vehicle interaction safety of connected automated vehicles in merging area: A real-time risk assessment approach.

The risky lane-changing manoeuvre of vehicles often occurs at expressway entrances, which would result in a high crash risk in the freeway system and significantly impact its safety. The highly anticipated environment of connected and autonomous vehicles (CAVs) is expected to reduce the associated crash risk of lane changing by offering various types of driving support, which utilise surrounding traffic information. The modelling crash risk under the environment of CAV driving during mandatory lane changing in merging areas faces new challenges due to the novelty of CAVs and subsequent shortage of data. To explore such risk situation of multi-vehicle interaction at expressway entrances, this study proposed a supervised learning algorithm and a Bayesian hierarchical model to assess risk levels and predict the probability of risk occurrence at different risk levels of interactive vehicles in real time of mandatory driving behaviour during the merging process. The learning algorithm, based on XGBoost, was exploited to classify risk levels. The Bayesian hierarchical model was used to analyse the probability of real-time risk comprising vehicle physical state layer, multi-vehicle interaction layer and risk probability layer. The probabilistic model parameters were calibrated using Markov Chain Monte Carlo (MCMC) Gibbs sampling method. The K-fold cross validation method was used to validate the proposed model of risk level. The probabilistic model validity was tested through posterior prediction of P-value. The quantitative risk estimation of CAVs through a few merging cases was conducted. Results show that the identification accuracy of slight, low, moderate and high risk is 94.24%, 85.82%, 84.16% and 79.69%, respectively. The P-value of Durbin-Watson's posterior, normal hypothesis, test distribution symmetry and kurtosis are all close to 0.5. Therefore, the method of real-time risk assessment is convergent and has good fitting. This research can promote cautious driving behaviours and provide reference for driver's decision making in the long term under the environment of CAVs.

Development of organogel-based emulsions to enhance the loading and bioaccessibility of 5-demethylnobiletin.

5-Demethylnobiletin (5-DMN), identified in the aged citrus peels, has received increasing attentions due to its outstanding bioactivity among citrus polymethoxyflavones (PMFs). However, the poor water solubility and high crystallinity limit its oral bioavailability. Besides, the solubility of 5-DMN in the oil is very limited, which restricts its loading capacity in emulsions for bioavailability enhancement. In this study, an organogel formulation was developed to improve the solubility of 5-DMN in medium-chain triacylglycerols by 3.5 times higher without crystal formation during 5-day storage at room temperature. Increasing the gelator (i.e., sugar ester) concentration led to the increase of viscosity and a gel-like structure of the organogel. The ternary phase diagram of organogel-based emulsions was explored, and 40% organogel was selected as the oil phase for emulsion preparation. Increasing the concentration of Tween 80 from 0% to 6% decreased the droplet size and viscoelasticity of the emulsions. Two in vitro models, the pH-stat lipolysis model and TNO gastro-intestinal model (TIM-1), were applied to investigate the bioaccessibility of 5-DMN in different delivery systems. Compared with the conventional emulsion and oil suspension, the pH-stat lipolysis demonstrated that the organogel-based emulsion was the most efficient tool to enhance 5-DMN bioacccessibility. Moreover, TIM-1 digestive study indicated that 5-DMN bioaccessibility delivered by organogel-based emulsions was about 3.26-fold higher than that of oil suspension. Our results suggested that the organogel-based emulsion was an effective delivery route to enhance the loading and bioaccessibility of lipophilic compounds of high crystallinity.

Bidirectional interaction of nobiletin and gut microbiota in mice fed with a high-fat diet.

Nobiletin is abundant in citrus peels and demonstrates good anti-obesity bioactivity. However, its anti-obesity mechanisms still remain unclear. This study aims to explore the bidirectional interaction between nobiletin and gut microbiota in mice fed with a high-fat diet. For the colonic bioconversion, more demethylated metabolites with higher biological activity were found in feces than nobiletin in the 48 h excretion study and 8 week consecutive dosing study. Moreover, long-term oral intake of nobiletin would modify the gut microbiota with improved demethylation ability and enhanced production of short chain fatty acids. The comparison of metabolite profiles in mouse liver and feces indicated that gut microbiota might have a higher biotransformation activity on nobiletin than the host. Two bacteria at the genus level, Allobaculum and Roseburia, remained enriched by nobiletin after the 4- and 8-week feedings. They might correlate with the enhanced nobiletin biotransformation and actively contribute to the health benefits of nobiletin in vivo. These results suggested that the bidirectional interaction of nobiletin and gut microbiota played an important role on the anti-obesity effect of nobiletin.

Left-turn conflict identification at signal intersections based on vehicle trajectory reconstruction under real-time communication conditions.

Connected vehicle (CV)technologies offer promising solutions to several problems in transportation systems. The trajectory data generated from CV technology can be used to identify real-time conflicts in intersections. To perform such identification, accurate vehicle localisation should be obtained to clearly recognise the conflicts between left-turning vehicles and straight-through vehicles in the opposite direction at the signal control intersection. This study presents a CV framework that uses the two-way time of arrival to locate the vehicles on the basis of the Intelligent Vehicle Infrastructure Cooperative Environment. Kalman Filter (KF) is used to improve the accuracy of the vehicle location, and the corresponding algorithm is used to estimate the vehicle trajectory to obtain the vehicle kinematics information via the on-board system. The traffic conflict areas of the left-turning vehicles and straight-through vehicles in the opposite direction are determined through vehicle trajectory extrapolation, and the left-turn collision at the signal intersection is identified using the post-encroachment time algorithm and vehicle movement information. In addition, Anderson-Darling and modified Kolmogorov-Smirnov tests are performed to verify the goodness of fit of the data. Results show that the vehicle speed and localisation errors of the proposed method decreased by 66.67 % and 83.33 % compared with the results before filtering, respectively. Moreover, the results of the conflict recognition method based on CV trajectory reconstruction is consistent for both goodness of fit tests under real-time communication conditions. This study can provide driving decision for drivers of left-turning vehicles under the Intelligent Vehicle Infrastructure Cooperative Environment and provide technical support for the research and development of left-turn anti-collision systems.

Spectral sensitivity estimation of trichromatic camera based on orthogonal test and window filtering.

The three-channel spectral sensitivity of a trichromatic camera represents the characteristics of system color space. It is a mapping bridge from the spectral information of a scene to the response value of a camera. In this paper, we propose an estimation method for three-channel spectral sensitivity of a trichromatic camera. It includes calibration experiment by orthogonal test design and the data processing by window filtering. The calibration experiment was first designed by an orthogonal table of the 9-level and 3-factor. A rough estimation model of spectral sensitivity is established on the data pairs of the system input and output in calibration experiments. The data of rough estimation is then modulated by two window filters on frequency and spatial domain. The Luther-Ives condition and the smoothness condition are introduced to design the window, and help to achieve the optimal estimation of the system spectral sensitivity. Finally, the proposed method is verified by some comparison experiments. The results show that the estimated spectral sensitivity is basically consistent with the measured results of the monochromator experiments, the relative full-scale errors of the RGB three-channel is obviously lower than the Wiener filtering method and the Fourier band-limitedness method. The proposed method can estimate the spectral sensitivity of the trichromatic digital camera very well, which is of great significance for the colorimetric characterization and evaluation of imaging systems.

An evaluation method of fragile states index based on climate shock: A case of Bangladesh.

Fragile states index reflects a country's ability to maintain stability. The main objective of this study is to analyze how climate change influences fragile states index. Firstly, we aim to modify the fragile states index. We devise an index system of climate shocks (MCS), which measures not climate change but also governance capacity. Meanwhile, a three-class index system is formulated to measure fragility of states (MCFS). Afterwards, we utilize MCS to modify the initial index system based on multiplication model. Furthermore, the weights of MCS are obtained by Delphi method while the weights in the third level of MCFS are gotten by CRITIC Weighting Model. The weights in the second level of MCFS then are determined by Entropy Weighting Model and Group Making Method. Finally, the classification standard of measuring fragility of states is calculated through System Clustering Model. And then Bangladesh is chosen to show the variation tendency of fragility based on the data between 2000 and 2015. To further predict the fragility of Bangladesh, Cascaded Neural Network Model (CNN) is adopted to predict MCFS from 2016 to 2030. Eventually we determine and define tipping points into 2 types-amelioration tipping points and deterioration tipping points. The result show that Bangladesh reached the deterioration tipping points in 2016.

Aged citrus peel (chenpi) extract causes dynamic alteration of colonic microbiota in high-fat diet induced obese mice.

Aged citrus peels (chenpi) have been used as a dietary supplement for gastrointestinal health maintenance in China. Recently, it was reported to exhibit anti-obesity activity. However, the relationship between the modulation effect of chenpi on gut microbiota and obesity prevention is not clearly understood. In this study, mice were fed with a high-fat diet (HFD), HFD supplemented with 0.25%- and 0.5%-chenpi extract, and normal diet, respectively, for 11 weeks. Chenpi extract significantly increased fecal short chain fatty acids by 43% for acetic acid and 86% for propionic acid. In addition, chenpi could decrease the prevalence of Proteobacteria and the ratio of Firmicutes to Bacteroidetes by about 88% and 70%, respectively. Moreover, this study was the first work to demonstrate the dynamics of two beneficial bacteria-Akkermansia spp. and Allobaculum spp. in a dose- and time-dependent manner for chenpi treatment via monitoring the dynamic change of the gut microbiota. Metagenomic analysis of the gut microbiota showed that several pathways, such as a two-component system, a tight junction, Staphylococcus aureus infection and others, were enhanced dynamically. The improved biological process of metabolism especially in benzoate derivatives might refer to the increased metabolic transformation of polymethoxyflavones from chenpi in the colon. Our study indicated that the modulation effect of chenpi on the gut microbiota may be an important pathway for its anti-obesity mechanisms.

Applications and delivery mechanisms of hyaluronic acid used for topical/transdermal delivery - A review.

The purpose of this review is to introduce the functionalities of hyaluronic acid (HA) and its potential application as an effective carrier for topical/transdermal delivery. Specifically, several delivery mechanisms of HA were summarized here in order to explain its potential permeation-enhancing roles for the skin, which includes receptor-based delivery pathway, skin hydration, hydrophobic interaction with stratum corneum, bioadhesive properties, and viscoelastic properties. To achieve the optimum delivery efficacy for bioactive compounds at different target layers of the skin, HA with various molecular weights and chemical modifications were applied to design different delivery systems, including hydrogel, nanoemulsion, microemulsion, prodrug, microneedle, liposome/hyalurosome. Delivery efficacy has been evaluated using in vitro Franz Cell Diffusion method and/or in vivo animal models. Throughout this review, it was confirmed that HA could be an effective carrier for both topical and transdermal deliveries due to its unique viscoelasticity, biocompatibility, biodegradability, non-immunogenicity, and biomedical benefits for the skin.

[Characteristics of clinical effectiveness of bloodletting and proposed ways of mechanism research].

According to the operative characteristics, the stimulated site and the curative effect-emerged site of bloodletting therapy, its clinical characteristics may be divided into three categories: a) local stimulation induced focus-local effect, b) local stimulation induced effect of the distal target organ (point-to-point distal effect), and c) special point stimulation induced broader effect of the whole body. Accordingly, the underlying mechanisms of clinical outcomes mainly involve the improvement of the local microcirculation and secondary changes of inflammatory substances for the first category (local focus). The point-to-point distal effect might mainly involve the innervation of nerve segments, while the broad effect of specific acupoint stimulation might involve multiple levels of the neuro-endocrine-immune system. The future research on the mechanisms of bloodletting should starts from its specific effects and the type of disease, which should not be generalized.

Evaluation of Oral Bioaccessibility of Aged Citrus Peel Extracts Encapsulated in Different Lipid-Based Systems: A Comparison Study Using Different in Vitro Digestion Models.

The oral delivery efficiency of aged citrus peel extract containing polymethoxyflavones and 5-demethylated polymethoxyflavones (PMFs) in three different systems, including a pure oil phase, a Tween 80-stabilized nanoemulsion, and a milled-cellulose-particles-stabilized Pickering emulsion, was investigated using two typical in vitro digestion models. The digestion profiles and release of PMFs in these emulsions and bulk oil in the human upper gastrointestinal (GI) tract were evaluated using the pH-stat lipolysis model and TNO's gastrointestinal model (TIM-1). Compared to the bulk oil sample, the bioaccessibilities of PMFs in the nanoemulsion and Pickering emulsion were both increased by around 14 fold when the pH-stat lipolysis model was used. However, the results from the TIM-1 system indicated that the bioaccessibilities of PMFs in the nanoemulsion and Pickering emulsion were around two and four times that in bulk oil, respectively. The results from this work would provide valuable information for the rational design and evaluation of lipid-based delivery systems for lipophilic bioactive compounds.

Ovotransferrin fibril-stabilized Pickering emulsions improve protection and bioaccessibility of curcumin.

The present study aimed to investigate protection and bioaccessibility of curcumin in ovotransferrin (OVT) fibril-stabilized Pickering emulsions. Curcumin protection of OVT fibril-stabilized emulsions against ultraviolet light exposure was studied. OVT fibril-stabilized Pickering emulsion at an ionic strength of 1000 mM provided the best curcumin protection. OVT fibril-stabilized Pickering emulsion at pH 6 provided better curcumin protection than those at pH 2 and 4. Afterwards, digestion of OVT fibril-stabilized curcumin emulsion was investigated in both TNO dynamic digestion model (TIM-1) and pH-stat static digestion model. In terms of TIM-1 result, curcumin bioaccessibility in OVT fibril-stabilized emulsion increased by 129% when compared with that in bulk oil. In pH-stat digestion model, curcumin bioaccessibility increased by 114% after formulated into OVT fibril-stabilized droplets, which was due to higher extent of lipolysis. Interestingly, both TIM-1 and pH-stat digestion models gave almost consistent measurements of improved percentage in curcumin bioaccessibility. Curcumin bioaccessibility of the emulsion in TIM-1 and pH-stat model was 15.3% and 33.8% respectively, indicating bioaccessibility overestimation in pH-stat model. The novel findings in this work could facilitate designing food-grade Pickerinng emulsion with excellent nutraceutical protection and enhanced nutraceutical bioaccessibility.