Mechanism of l-cysteine-induced fibrous structural changes of soybean protein at different high-moisture extrusion zones.

In this study, the fibrous structure formation mechanism of soybean protein during high moisture extrusion processing was investigated using a dead-stop operation, and based on the interaction between soybean protein concentrate (SPC) and L-cysteine (CYS). The thermal properties, SDS-PAGE and particle size distribution of the samples from different extrusion zones were investigated. It was revealed that the addition of a moderate amount of CYS (0.1 %) promoted the fibrous structure formation in the SPC extrudates and optimised the textural properties of the SPC extrudates. In the extruder barrel, addition of CYS (0.1 %) promoted protein depolymerisation and unfolding in the mixing and cooking zones, and facilitated protein aggregation in the die and cooling zones. Protein solubility and raman spectroscopy revealed that disulfide bonds were principally responsible for fibrous structure formation; favoured when the intermolecular disulfide bonds (t-g-t mode) was increased. Finally, the transformation of protein conformation was revealed by secondary structure and surface hydrophobicity, which confirmed that the effect of CYS on protein conformation mainly occurred in the cooling zone. This study provides a theoretical basis for the application of CYS to regulate the fibrous structure of meat analogues.

Microscopic-Level Insights into P-O-Induced Strong Electronic Coupling Over Nickel Phosphide with Efficient Benzyl Alcohol Electrooxidation.

Electrooxidation of biomass into fine chemicals coupled with energy-saving hydrogen production for a zero-carbon economy holds great promise. Advanced anode catalysts determine the cell voltage and electrocatalytic efficiency greatly, further the rational design and optimization of their active site coordination remains a challenge. Herein, a phosphorus-oxygen terminals-rich species (Ni2 P-O-300) via an anion-assisted pyrolysis strategy is reported to induce strong electronic coupling and high valence state of active nickel sites over nickel phosphide. This ultimately facilitates the rapid yet in-situ formation of high-valence nickel with a high reaction activity under electrochemical conditions, and exhibits a low potential of 1.33 V vs. RHE at 10 mA cm-2 , exceeding most of reported transition metal-based catalysts. Advanced spectroscopy, theoretical calculations, and experiments reveal that the functional P-O species can induce the favorable local bonding configurations for electronic coupling, promoting the electron transfer from Ni to P and the adsorption of benzyl alcohol (BA). Finally, the hydrogen production efficiency and kinetic constant of BA electrooxidation by Ni2 P-O-300 are increased by 9- and 2.8- fold compared with the phosphorus-oxygen terminals-deficient catalysts (Ni2 P-O-500). This provides an anion-assisted pyrolysis strategy to modulate the electronic environment of the Ni site, enabling a guideline for Ni-based energy/catalysis systems.

Effect and mechanism of freezing on the quality and structure of soymilk gel induced by different salt ions.

BACKGROUND: The increasing attention toward frozen soy-based foods has sparked interest. Variations exist in the quality and structure of soymilk gels induced by different salt ions, leading to diverse changes post-freezing. This study compared and analyzed the effects of calcium chloride (CC), magnesium chloride (MC) and calcium sulfate (CS) on the quality characteristics and protein structure changes of soymilk gels (CC-S, MC-S and CS-S) before and after freezing, and clarified the mechanisms of freezing on soymilk gel. RESULTS: The formation rate of soymilk gel is influenced by the type of salt ions. In comparison to CS and MC, soymilk gel induced by CC exhibited the fastest formation rate, highest gel hardness, lowest moisture content, and smaller gel pores. However, freezing treatment deteriorated the quality of soymilk gel induced by different salt ions, leading to a decline in textural properties (hardness and chewiness). Among these, the textual state of CC-induced soymilk gel remained optimal, exhibiting the least apparent damage and minimal cooking loss. Freezing treatments prompt a transition of soymilk gel secondary structure from ß-turns to ß-sheets, disrupting the protein's tertiary structure. Furthermore, freezing treatments also fostered the crosslinking between soymilk gel protein, increasing the content of disulfide bonds. CONCLUSION: The quality of frozen soymilk gel is influenced by the rate of gel formation induced by salt ions. After freezing, soymilk gel with faster gelation rates exhibited a greater tendency for the transformation of protein-water interactions into protein-protein interactions. They showed a higher degree of disulfide bond formation, resulting in a more tightly knit and firm frozen gel network structure with denser and more uniformly distributed pores. © 2024 Society of Chemical Industry.

Investigation of the effect and mechanism of nanocellulose on soy protein isolate- konjac glucomannan composite hydrogel system.

To enrich the application of nanocomposite hydrogels, we introduced two types of nanocellulose (CNC, cellulose nanocrystals; CNF, cellulose nanofibers) into the soy protein isolate(SPI)- konjac glucomannan (KGM) composite hydrogel system, respectively. The similarities and differences between the two types of nanocellulose as textural improvers of composite gels were successfully explored, and a model was developed to elaborate their interaction mechanisms. Appropriate levels of CNC (1.0 %) and CNF (0.75 %) prolonged SPI denaturation within the system, exposed more buried functional groups, improved molecular interactions, and strengthened the honeycomb structural skeleton formed by KGM. The addition of CNC resulted in greater gel strength (SKC1 2708.53 g vs. Control 810.35 g), while the addition of CNF improved the elasticity (SKF0.75 1940.24 g vs. Control 405.34 g). This was mainly attributed to the reinforcement of the honeycomb-structured, water binding and trapping, and the synergistic effect of covalent (disulfide bonds) and non-covalent interactions (hydrogen bonds, ionic bonds) within the gel network. However, the balance and interactions between proteins and polysaccharides were disrupted in the composite system with excessive CNF addition (≥0.75 %), which broken the stability of the honeycomb-like structure. We expect this study will draw attention on potential applications of CNC and CNF in protein-polysaccharide binary systems and facilitate the creation of novel, superior, mechanically strength-regulated nanofiber composite gels.

Self-powered biosensor using photoactive ternary nanocomposite: Testing the phospholipid content in rhodotorula glutinis oil.

In the field of oil refining, the presence of excessive residual phosphorus in crude oil can significantly impact its quality, thereby emphasizing the necessity for compact and convenient testing equipment. This study primarily focuses on developing of self-powered biosensor (SPB) using immobilizing Choline Oxidase with a photoactive ternary nanocomposite complex (CHOx-BiOI-rGO-Fe3O4 NPs-ITO) as the anode and utilizing a Pt electrode as the cathode. The successful preparation of the ternary composite photoelectrode for the anode was confirmed through a range of characterization techniques, including X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Transmission electron microscopy (TEM), Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), N2 absorption/desorption, Dynamic light scattering (DLS), and Ultraviolet-visible diffuse reflection spectrometer (UV-vis DRS). The electrochemical and photoelectrochemical properties were assessed using an electrochemical workstation, revealing a significant enhancement photoelectrical responsiveness attributed to the formation of heterojunction structures. The SPB exhibited a remarkable linear relationship between the instantaneous photocurrent and phosphatidylcholine (PC) concentration, with a regression equation of I (µA) = 39.62071C (mM) + 3.47271. The linear range covered a concentration range of 0.01-10 mM, and the detection limit (S/N = 3) was determined to be 0.008 mM. It demonstrated excellent reproducibility and storage stability, positioning it a promising alternative to High-performance liquid chromatography (HPLC) for accurate quantification of PC content in rhodotorula glutinis oil. The standard recovery PC content ranged from 98.48% to 103.53%, with a relative standard deviation (RSD) ranging from 1.4% to 2.4%. This research presents a convenient and precise detection device that has the potential to address the issue of lagging detection in the oil refining process.

Effect of ultrasound treatment on thawing process of frozen tofu prepared with different salt coagulants.

This study investigated the effects of ultrasound-assisted water thawing (UWT) at different power levels (0, 100, 150, 200, and 250 W) on the thawing rate and gel properties of frozen tofu made using three different salt coagulants (CaCl2, CaSO4, and MgCl2). Tofu produced with CaCl2 and CaSO4 elicited gel structures with dense and homogeneous networks, while that with MgCl2 had rough pores and irregular networks. UWT treatment significantly decreased thawing time by 30.9-53.5% compared to the control. Water holding capacity and scanning electron microscopy analyses demonstrated that UWT-100, UWT-150, and UWT-200 should be used to increase the amount of fixed water for CaCl2, CaSO4, and MgCl2. These findings suggest that appropriate ultrasonic treatment could improve the water retention capacity of the tofu network and make the gel network structure more compact. Additionally, protein structural analysis showed a decrease in the exposure of hydrophobic groups and reduced protein denaturation when tofu prepared with all the coagulants were thawed with UWT energies of 100-200 W ultrasonication. These findings offer theoretical support for improving the frozen tofu thawing process while ensuring optimal final product quality.

Effect of Na+ and Ca2+ on the texture, structure and microstructure of composite protein gel of mung bean protein and wheat gluten.

To investigate the change of ionic strength on the gel characteristics during the processing of mung bean protein-based foods, the effects of NaCl and CaCl2 at different concentrations (0-0.005 g/mL) on the properties of mung bean protein (MBP) and wheat gluten (WG) composite protein gel were studied. The results showed that low concentration (0.001-0.002 g/mL) could significantly improve the water holding capacity (WHC), storage modulus (G') and texture properties of composite protein gel (MBP/WG), while the surface hydrophobicity (H0) and solubility were significantly decreased (P < 0.05). With the increase of ion concentration, the secondary structures of MBP/WG shifted from α-helix to ß-sheet, and the fluorescence spectra also showed fluorescence quenching phenomenon. By analyzing the intermolecular forces of MBP/WG, it was found that with the addition of salt ions, the hydrogen bonds was weakened and the electrostatic interactions, hydrophobic interactions and disulfide bonds were enhanced, which in turn the aggregation behavior of MBP/WG composite protein gel was affected and larger aggregates between the proteins were formed. It could be also demonstrated that the gel network was denser due to the addition of these large aggregates, thus the gel properties of MBP/WG was improved. However, too many salt ions could disrupt the stable network structure of protein gel. This study can provide theoretical support to expand the development of new mung bean protein products.

The pharmacological actions of Danzhi-xiaoyao-San on depression involve lysophosphatidic acid and microbiota-gut-brain axis: novel insights from a systems pharmacology analysis of a double-blind, randomized, placebo-controlled clinical trial.

Danzhi-xiaoyao-San (DZXYS), a Traditional Chinese Medicine, plays an essential role in the clinical treatment of depression, but its mechanisms in humans remain unclear. To investigate its pharmacological effects and mechanisms as an add-on therapy for depression, we conducted a double-blind, placebo-controlled trial with depressed patients receiving selective serotonin reuptake inhibitors (SSRIs). Serum and fecal samples were collected for metabolomic and microbiome analysis using UHPLC-QTRAP-MS/MS and 16S rRNA gene sequencing technologies, respectively. Depression symptoms were assessed using the 24-item Hamilton Depression Scale. We employed network pharmacology, metabolomics, and molecular docking to identify potential targets associated with DZXYS. We also examined the correlation between gut microbes and metabolites to understand how DZXYS affects the microbiota-gut-brain axis. The results showed that DZXYS combined with SSRIs was more effective than SSRIs alone in improving depression. We identified 39 differential metabolites associated with DZXYS treatment and found seven upregulated metabolic pathways. The active ingredients quercetin and luteolin were docked to targets (AVPR2, EGFR, F2, and CDK6) associated with the enriched pathways 'pancreatic cancer' and 'phospholipase D signaling pathway', which included the metabolite lysophosphatidic acid [LPA(0:0/16:0)]. Additionally, we identified 32 differential gut microbiota species related to DZXYS treatment, with Bacteroides coprophilus and Ruminococcus gnavus showing negative correlations with specific metabolites such as L-2-aminobutyric acid and LPA(0:0/16:0). Our findings indicate that DZXYS's antidepressant mechanisms involve multiple targets, pathways, and the regulation of LPA and the microbiota-gut-brain axis. These insights from our systems pharmacology analysis contribute to a better understanding of DZXYS's potential pharmacological mechanisms in depression treatment.Communicated by Ramaswamy H. Sarma.

HIGHLIGHTSThis study presents a double-blind, randomized, placebo-controlled clinical trial comparing the clinical effects of Danzhi-xiaoyao-San (DZXYS) plus selective serotonin reuptake inhibitors (SSRIs) and SSRIs alone.This study is the first system pharmacology approach to integrate multi-omics and network pharmacology and examine the clinical pharmacological mechanisms of DZXYS as an add-on therapy for depression.This study highlights that regulation of lysophosphatidic acid (LPA) and the microbiota-gut-brain axis by DZXYS plays an essential role in its antidepressant mechanisms.

Bibliometric analysis of global research on the role of apolipoprotein E in Alzheimer's disease.

Alzheimer's disease (AD) has attracted considerable attention from the public and scientific researchers, leading to a rapid growth in relevant research on this disorder in the last 10 years. The present study aimed to conduct a bibliometric analysis to elucidate the trends of global research on the role of apolipoprotein E in AD in the past decade. Three bibliometric software (CiteSpace, VOSviewer, and R Bibliometrix) were used to analyze the active journals, countries/regions, institutes, authors, co-cited references, and keywords in this field. The USA was the most influential country, and the University of California was the most productive institute. Zetterberg H contributed the highest number of publications, and Petersen RC was the most cited author in this field. On the basis of the co-cited reference analysis, knowledge base on biomarkers, risk factors, and mechanisms were updated in the past decade. Current research hotspots are shifting to tau-related mechanisms and identification of genetic risk factors. Our study provides insights into the developing knowledge base and trends related to research on apolipoprotein E in AD, which may provide new directions for further research in this field.

Rationale, Design and Methodology of a Population-Based Ocular Study in a Suburbanization Region in Tianjin, China: The Beichen Eye Study.

PURPOSE: The urbanization of suburbs has a significant impact on ocular health, however, the effect of this phenomenon on the epidemiology of eye diseases in the sub-urbanization region of China remains unclear. In this context, the population-based Beichen Eye Study (BCES) was conducted in the Beichen District of Tianjin, China. This article aims to summarize the background, design scheme and operation process of the study. The Chinese Clinical Trial Registry number was ChiCTR2000032280. METHODS: In total, 8218 participants were randomly selected by a multi-stage sampling method. After their qualification was confirmed, participants were mainly invited to a centralized clinic via telephone interviews after promotion of the study in the community. Examinations included a standardized interview, anthropometric assessment, autorefraction, ocular biometry, visual acuity, anterior and posterior segment examinations, dry eye disease (DED), intra-ocular pressure, visual field testing, gonioscopy, and imaging of anterior segment, posterior segment, fundus, and optic disc. A peripheral venous blood sample was also collected for biochemical testing. For observational purposes, a community-based type II diabetes mellitus management mode was created and assessed for its effect in preventing the progression of diabetic retinopathy (DR). RESULTS: Of the 8,218 residents, 7,271 were eligible for inclusion, and 5,840 (80.32%) subjects were enrolled in the BCES. Most of the participants were female (64.38%) with a median age of 63 years, and 98.23% representing Han Chinese descent. Conclusions: This study provides insights into the epidemiological characteristics of major ocular diseases and their moderators in a suburbanized region of China.

Use of soybean oil to modulate the gel properties of soybean protein isolation-wheat gluten composite with or without CaCl2.

BACKGROUND: Plant protein is widely used in the study of animal protein substitutes and healthy sustainable products. The gel properties are crucial for the production of plant protein foods. Therefore, the present study investigated the use of soybean oil to modulate the gel properties of soybean protein isolation-wheat gluten composite with or without CaCl2 . RESULTS: Oil droplets filled protein network pores under the addition of soybean oil (1-2%). This resulted in an enhanced gel hardness and water holding capacity. Further addition of soybean oil (3-4%), oil droplets and some protein-oil compounds increased the distance between the protein molecule chain. The results of Fourier transform infrared spectroscopy and intermolecular interaction also showed that the disulfide bond and ß-sheet ratio decreased in the gel system, which damaged the overall structure of the gel network. Compared with the addition of 0 m CaCl2 , salt ion reduced the electrostatic repulsion between proteins, and local protein cross-linking was more intense at 0.005 m CaCl2 concentration. In the present study, structural properties and rheological analysis showed that the overall strength of the gel was weakened after the addition of CaCl2 . CONCLUSION: The presence of appropriate amount of soybean oil can fill the gel pores and improve the texture properties and network structure of soy protein isolate-wheat gluten (SPI-WG) composite gel. Excessive soybean oil may hinder protein-protein interaction and adversely affect protein gel. In addition, the presence or absence of CaCl2 significantly affected the gelling properties of SPI-WG composite protein gels. © 2023 Society of Chemical Industry.

Impact of Insoluble Dietary Fiber and CaCl2 on Structural Properties of Soybean Protein Isolate-Wheat Gluten Composite Gel.

The effect and mechanism of soybean insoluble dietary fiber (SIDF) (0~4%) and CaCl2 (0~0.005 M) on the properties of soybean protein isolate (SPI)-wheat gluten (WG) composite gel were studied. It was revealed that the addition of insoluble dietary fiber (1~2%) increased the strength and water-holding capacity (WHC) of the composite gel (p < 0.05) and enhanced the gel network structure compared with the control. WHC and LF-NMR showed that the water-binding ability of the gel system with only 2% SIDF was the strongest. The addition of excessive SIDF increased the distance between protein molecules, impeded the cross-linking of protein, and formed a three-dimensional network with low gel strength. The infrared spectrum and intermolecular force indicated that the interaction between SIDF and SPI were mainly physical, and the hydrophobic interaction and disulfide bond were the main forces in the gel system. The addition of CaCl2 can increase the critical content of gel texture destruction caused by SIDF, and the gel strength attained its peak at 3% SIDF, indicating that appropriate CaCl2 improved gel structure weakening caused by excessive SIDF. This study provides insights in enhancing the production of multi-component composite gel systems.

Risk of diabetic retinopathy and retinal neurodegeneration in individuals with type 2 diabetes: Beichen Eye Study.

Objective: Our aim was to evaluate associations of different risk factors with odds of diabetic retinopathy (DR) diagnosis and retinal neurodegeneration represented by macular ganglion cell-inner plexiform layer (mGCIPL). Methods: This cross-sectional study analyzed data from individuals aged over 50 years examined between June 2020 and February 2022 in the community-based Beichen Eye Study on ocular diseases. Baseline characteristics included demographic data, cardiometabolic risk factors, laboratory findings, and medications at enrollment. Retinal thickness in both eyes of all participants was measured automatically via optical coherence tomography. Risk factors associated with DR status were investigated using multivariable logistic regression. Multivariable linear regression analysis was performed to explore associations of potential risk factors with mGCIPL thickness. Results: Among the 5037 included participants with a mean (standard deviation, SD) age of 62.6 (6.7) years (3258 women [64.6%]), 4018 (79.8%) were control individuals, 835 (16.6%) were diabetic individuals with no DR, and 184 (3.7%) were diabetic individuals with DR. The risk factors significantly associated with DR status were family history of diabetes (odds ratio [OR], 4.09 [95% CI, 2.44-6.85]), fasting plasma glucose (OR, 5.88 [95% CI, 4.66-7.43]), and statins (OR, 2.13 [95% CI, 1.03-4.43]) relative to the control individuals. Compared with the no DR, diabetes duration (OR, 1.17 [95% CI, 1.13-1.22]), hypertension (OR, 1.60 [95% CI, 1.26-2.45]), and glycated hemoglobin A1C (HbA1c) (OR, 1.27 [95% CI, 1.00-1.59]) were significantly correlated with DR status. Furthermore, age (adjusted ß = -0.19 [95% CI, -0.25 to -0.13] µm; P < 0.001), cardiovascular events (adjusted ß = -0.95 [95% CI, -1.78 to -0.12] µm; P = 0.03), and axial length (adjusted ß = -0.82 [95% CI, -1.29 to -0.35] µm; P = 0.001) were associated with mGCIPL thinning in diabetic individuals with no DR. Conclusion: Multiple risk factors were associated with higher odds of DR development and lower mGCIPL thickness in our study. Risk factors affecting DR status varied among the different study populations. Age, cardiovascular events, and axial length were identified as potential risk factors for consideration in relation to retinal neurodegeneration in diabetic patients.

Effect of polysaccharides on the rheological behaviour of soy-wheat protein aggregation and conformational changes during high-moisture extrusion.

BACKGROUND: Due to the extrusion black box effect, polysaccharides determine the formation of meat-like fibrous structures by modulating the flow behaviour and structural changes of plant proteins under high-moisture extrusion conditions. However, there is limited knowledge on the mechanism of resolution. This study simulated the rheological properties of soy protein-wheat protein under 57% moisture conditions with addition of 4% sodium alginate (SA), 2% xanthan gum (XG), and 2% maltodextrin (MD). The effect of these polysaccharides on the aggregation behaviour and conformation of raw protein during high-moisture extrusion was investigated. RESULTS: It was revealed that the three polysaccharides were effective in increasing the interaction between proteins and between proteins and water. Among them, 4% SA elicited a significantly stronger storage modulus (gelation behaviour) compared to the control. Analysis of different zones of extrudates by protein electrophoresis, particle size, and turbidity showed that SA-4% was able to form more high molecular protein aggregates (> 245 kDa) and promoted crosslinking of low molecular subunits (< 48 kDa), resulting in moderately sized protein aggregated particles. Fluorescence and ultraviolet spectra showed the transformation of protein tertiary structures in different extrusion zones, confirming that the key extrusion zone for protein conformational transformation by polysaccharides is the die-cooling zone. Furthermore, stretching of polypeptide chains and accelerated protein rearrangement facilitated the formation of more fibrillar structures. CONCLUSION: Theoretical support for polysaccharide modulation of plant protein quality in high moisture extruded products is provided by this study. © 2023 Society of Chemical Industry.

Effect of high-pressure homogenization on Ca2+ -induced gel formation of soybean 11 S globulin.

BACKGROUND: High-pressure homogenization (HPH) is commonly used as a non-thermal processing technique for soybean and soy protein products, and the preparation of soy protein gel products often requires the synergistic effect of HPH and heat treatment. The dissociative association behavior of 11 S is the key to the protein gel formation state. In this study, therefore, 11 S thermal gels were prepared by high-pressure homogenization and co-induction (90 °C, 30 min) (adding Ca2+ to promote gel formation before heat treatment), and the effects of different high-pressure homogenization pressures (0-100 MPa) and co-treatment on the dissociative association behavior of 11 S protein, gel properties, and microstructure of 11 S gels were investigated. RESULTS: The results showed that HPH at higher pressures led to the breaking of disulfide bonds of aggregates and disrupted non-covalent interactions in protein aggregates, leading to collisions between protein aggregates and the reduction of large protein aggregates. High-pressure homogenization treatment at 60 MPa improved the gel properties of 11 S more. The HPH combined with heating changed the binary and tertiary structure of 11 S soy globulin and enhanced the hydrophobic interaction between 11 S molecules, thus improving the gel properties of 11 S. The change in intermolecular forces reflected the positive effect of HPH treatment on the formation of denser and more homogeneous protein gels. CONCLUSION: In conclusion, high-pressure homogenization combined with heating can improve the properties of 11 S gels by changing the structure of 11 S protein, providing data and theoretical support for soy protein processing and its further applications. © 2022 Society of Chemical Industry.

Effect of maltodextrin on the oxidative stability of ultrasonically induced soybean oil bodies microcapsules.

Introduction: Encapsulation of soybean oil bodies (OBs) using maltodextrin (MD) can improve their stability in different environmental stresses and enhance the transport and storage performance of OBs. Methods: In this study, the effects of different MD addition ratios [OBs: MD = 1:0, 1:0.5, 1:1, 1:1.5, and 1:2 (v/v)] on the physicochemical properties and oxidative stability of freeze-dried soybean OBs microcapsules were investigated. The effect of ultrasonic power (150-250 W) on the encapsulation effect and structural properties of oil body-maltodextrin (OB-MD) microcapsules were studied. Results: The addition of MD to OBs decreased the surface oil content and improved the encapsulation efficiency and oxidative stability of OBs. Scanning electron microscopy images revealed that the sonication promoted the adsorption of MD on the surface of OBs, forming a rugged spherical structure. The oil-body-maltodextrin (OB-MD) microcapsules showed a narrower particle size distribution and a lower-potential absolute value at an MD addition ratio of 1:1.5 and ultrasonic power of 250 W (32.1 mV). At this time, MD-encapsulated OBs particles had the highest encapsulation efficiency of 85.3%. Ultrasonic treatment improved encapsulation efficiency of OBs and increased wettability and emulsifying properties of MD. The encapsulation of OBs by MD was improved, and its oxidative stability was enhanced by ultrasound treatment, showing a lower hydrogen peroxide value (3.35 meq peroxide/kg) and thiobarbituric acid value (1.65 µmol/kg). Discussion: This study showed that the encapsulation of soybean OBs by MD improved the stability of OBs microcapsules and decreased the degree of lipid oxidation during storage. Ultrasonic pretreatment further improved the encapsulation efficiency of MD on soybean OBs, and significantly enhanced its physicochemical properties and oxidative stability.

Structural Analysis and Study of Gel Properties of Thermally-Induced Soybean Isolate-Potato Protein Gel System.

Heat-induced composite gel systems consisting of different soybean protein isolate (SPI) and potato protein (PP) mixtures were studied to elucidate their "backbone" and property changes. This was achieved by comparing the ratio of non-network proteins, protein subunit composition, and aggregation of different gel samples. It was revealed that SPI was the "gel network backbone" and PP played the role of "filler" in the SPI-PP composite gel system. Compared with the composite gels at the same ratio, springiness and WHC decrease with PP addition. For hardness, PP addition showed a less linear trend. At the SPI-PP = 2/1 composite gel, hardness was more than doubled, while springiness and WHC did not decrease too much and increased the inter-protein binding. The hydrophobic interactions and electrostatic interactions and hydrogen bonding of the SPI gel system were enhanced. The scanning electron microscopy results showed that the SPI-based gel system was able to form a more compact and compatible gel network. This study demonstrates the use of PP as a potential filler that can effectively improve the gelling properties of SPI, thus providing a theoretical basis for the study of functional plant protein foods.

Machine learning advances the integration of covariates in population pharmacokinetic models: Valproic acid as an example.

Background and Aim: Many studies associated with the combination of machine learning (ML) and pharmacometrics have appeared in recent years. ML can be used as an initial step for fast screening of covariates in population pharmacokinetic (popPK) models. The present study aimed to integrate covariates derived from different popPK models using ML. Methods: Two published popPK models of valproic acid (VPA) in Chinese epileptic patients were used, where the population parameters were influenced by some covariates. Based on the covariates and a one-compartment model that describes the pharmacokinetics of VPA, a dataset was constructed using Monte Carlo simulation, to develop an XGBoost model to estimate the steady-state concentrations ( C s s ) of VPA. We utilized SHapley Additive exPlanation (SHAP) values to interpret the prediction model, and calculated estimates of VPA exposure in four assumed scenarios involving different combinations of CYP2C19 genotypes and co-administered antiepileptic drugs. To develop an easy-to-use model in the clinic, we built a simplified model by using CYP2C19 genotypes and some noninvasive clinical parameters, and omitting several features that were infrequently measured or whose clinically available values were inaccurate, and verified it on our independent external dataset. Results: After data preprocessing, the finally generated combined dataset was divided into a derivation cohort and a validation cohort (8:2). The XGBoost model was developed in the derivation cohort and yielded excellent performance in the validation cohort with a mean absolute error of 2.4 mg/L, root-mean-squared error of 3.3 mg/L, mean relative error of 0%, and percentages within ± 20% of actual values of 98.85%. The SHAP analysis revealed that daily dose, time, CYP2C19*2 and/or *3 variants, albumin, body weight, single dose, and CYP2C19*1*1 genotype were the top seven confounding factors influencing the C s s of VPA. Under the simulated dosage regimen of 500 mg/bid, the VPA exposure in patients who had CYP2C19*2 and/or *3 variants and no carbamazepine, phenytoin, or phenobarbital treatment, was approximately 1.74-fold compared to those with CYP2C19*1/*1 genotype and co-administered carbamazepine + phenytoin + phenobarbital. The feasibility of the simplified model was fully illustrated by its performance in our external dataset. Conclusion: This study highlighted the bridging role of ML in big data and pharmacometrics, by integrating covariates derived from different popPK models.

An interpretable stacking ensemble learning framework based on multi-dimensional data for real-time prediction of drug concentration: The example of olanzapine.

Background and Aim: Therapeutic drug monitoring (TDM) has evolved over the years as an important tool for personalized medicine. Nevertheless, some limitations are associated with traditional TDM. Emerging data-driven model forecasting [e.g., through machine learning (ML)-based approaches] has been used for individualized therapy. This study proposes an interpretable stacking-based ML framework to predict concentrations in real time after olanzapine (OLZ) treatment. Methods: The TDM-OLZ dataset, consisting of 2,142 OLZ measurements and 472 features, was formed by collecting electronic health records during the TDM of 927 patients who had received OLZ treatment. We compared the performance of ML algorithms by using 10-fold cross-validation and the mean absolute error (MAE). The optimal subset of features was analyzed by a random forest-based sequential forward feature selection method in the context of the top five heterogeneous regressors as base models to develop a stacked ensemble regressor, which was then optimized via the grid search method. Its predictions were explained by using local interpretable model-agnostic explanations (LIME) and partial dependence plots (PDPs). Results: A state-of-the-art stacking ensemble learning framework that integrates optimized extra trees, XGBoost, random forest, bagging, and gradient-boosting regressors was developed for nine selected features [i.e., daily dose (OLZ), gender_male, age, valproic acid_yes, ALT, K, BW, MONO#, and time of blood sampling after first administration]. It outperformed other base regressors that were considered, with an MAE of 0.064, R-square value of 0.5355, mean squared error of 0.0089, mean relative error of 13%, and ideal rate (the percentages of predicted TDM within ± 30% of actual TDM) of 63.40%. Predictions at the individual level were illustrated by LIME plots, whereas the global interpretation of associations between features and outcomes was illustrated by PDPs. Conclusion: This study highlights the feasibility of the real-time estimation of drug concentrations by using stacking-based ML strategies without losing interpretability, thus facilitating model-informed precision dosing.

Integrating machine learning with electronic health record data to facilitate detection of prolactin level and pharmacovigilance signals in olanzapine-treated patients.

Background and aim: Available evidence suggests elevated serum prolactin (PRL) levels in olanzapine (OLZ)-treated patients with schizophrenia. However, machine learning (ML)-based comprehensive evaluations of the influence of pathophysiological and pharmacological factors on PRL levels in OLZ-treated patients are rare. We aimed to forecast the PRL level in OLZ-treated patients and mine pharmacovigilance information on PRL-related adverse events by integrating ML and electronic health record (EHR) data. Methods: Data were extracted from an EHR system to construct an ML dataset in 672×384 matrix format after preprocessing, which was subsequently randomly divided into a derivation cohort for model development and a validation cohort for model validation (8:2). The eXtreme gradient boosting (XGBoost) algorithm was used to build the ML models, the importance of the features and predictive behaviors of which were illustrated by SHapley Additive exPlanations (SHAP)-based analyses. The sequential forward feature selection approach was used to generate the optimal feature subset. The co-administered drugs that might have influenced PRL levels during OLZ treatment as identified by SHAP analyses were then compared with evidence from disproportionality analyses by using OpenVigil FDA. Results: The 15 features that made the greatest contributions, as ranked by the mean (|SHAP value|), were identified as the optimal feature subset. The features were gender_male, co-administration of risperidone, age, co-administration of aripiprazole, concentration of aripiprazole, concentration of OLZ, progesterone, co-administration of sulpiride, creatine kinase, serum sodium, serum phosphorus, testosterone, platelet distribution width, α-L-fucosidase, and lipoprotein (a). The XGBoost model after feature selection delivered good performance on the validation cohort with a mean absolute error of 0.046, mean squared error of 0.0036, root-mean-squared error of 0.060, and mean relative error of 11%. Risperidone and aripiprazole exhibited the strongest associations with hyperprolactinemia and decreased blood PRL according to the disproportionality analyses, and both were identified as co-administered drugs that influenced PRL levels during OLZ treatment by SHAP analyses. Conclusions: Multiple pathophysiological and pharmacological confounders influence PRL levels associated with effective treatment and PRL-related side-effects in OLZ-treated patients. Our study highlights the feasibility of integration of ML and EHR data to facilitate the detection of PRL levels and pharmacovigilance signals in OLZ-treated patients.