eLIMS: Ensemble Learning-Based Spatial Segmentation of Mass Spectrometry Imaging to Explore Metabolic Heterogeneity.

Spatial segmentation is an essential processing method for image analysis aiming to identify the characteristic suborgans or microregions from mass spectrometry imaging (MSI) data, which is critical for understanding the spatial heterogeneity of biological information and function and the underlying molecular signatures. Due to the intrinsic characteristics of MSI data including spectral nonlinearity, high-dimensionality, and large data size, the common segmentation methods lack the capability for capturing the accurate microregions associated with biological functions. Here we proposed an ensemble learning-based spatial segmentation strategy, named eLIMS, that combines a randomized unified manifold approximation and projection (r-UMAP) dimensionality reduction module for extracting significant features and an ensemble pixel clustering module for aggregating the clustering maps from r-UMAP. Three MSI datasets are used to evaluate the performance of eLIMS, including mouse fetus, human adenocarcinoma, and mouse brain. Experimental results demonstrate that the proposed method has potential in partitioning the heterogeneous tissues into several subregions associated with anatomical structure, i.e., the suborgans of the brain region in mouse fetus data are identified as dorsal pallium, midbrain, and brainstem. Furthermore, it effectively discovers critical microregions related to physiological and pathological variations offering new insight into metabolic heterogeneity.

Characterization of wheat dough and Chinese steamed bread using mealworm powder formulated with medium-gluten and whole wheat flour.

BACKGROUND: Mealworm (Tenebrio molitor) larvae are nutritious edible insects and exhibit the potential to act as protein substitutes in food products. In this study, we added mealworm powder as a substitute to medium-gluten wheat and whole wheat flours to enhance the quality of baked products. We compared the pasting, farinograph and extensograph properties of medium-gluten wheat and whole wheat flours replaced with different concentrations of mealworm powder to explore the interactions between flour and mealworm powder. RESULTS: Mealworm powder changed the pasting characteristics of medium-gluten wheat and whole wheat flours. After adding 20% mealworm powder, the pasting temperature of the medium-gluten wheat flour remained unchanged (approximately 89.9 °C), while the pasting temperature of whole wheat flour increased from 88.83 to 90.27 °C. Water absorption of medium-gluten and whole wheat flours exhibited a decreasing trend with increasing mealworm powder concentrations. Mealworm powder substitution resulted in stronger medium-gluten dough but exerted an opposite effect on the farinograph properties of whole wheat dough. Mealworm powder substitution decreased the stretching resistance of medium-gluten dough but increased that of whole wheat dough. With an increase in the concentration of mealworm powder, the specific volume of medium-gluten wheat steamed bread significantly increased from 1.69 mL g-1 (M0) to 3.31 mL g-1 (M10) whereas that of whole wheat steamed bread increased from 1.64 mL g-1 (M0) to 2.34 mL g-1 (M15). The addition of mealworm powder increased the protein, dietary fiber, lipid and sodium contents of steamed bread samples. CONCLUSIONS: This study provides a reference for the rheological properties of medium-gluten wheat and whole wheat flours substituted with mealworm powder and supports the addition of insects as a protein source in food products. © 2023 Society of Chemical Industry.

Effect of Adding Different Commercial Propylene Glycol Alginates on the Properties of Mealworm-Flour-Formulated Bread and Steamed Bread.

Mealworm-flour-formulated flour-based products have gained increasing attention; however, their textural properties need to be improved. Propylene glycol alginate (PGA) is a commercial food additive with excellent emulsifying and stabilizing capabilities. We evaluated the effects of adding three commercially available PGAs (0.3% w/w, as food additive) on the properties of 10% concentration of mealworm-flour-formulated bread and steamed bread. The results showed that, compared with the control (2.17 mL/g), three PGA brands (Q, M, and Y) significantly increased the specific volume of the bread to 3.34, 3.40, and 3.36 mL/g, respectively. Only PGA from brand Q significantly improved the specific volumes of bread and steamed bread. The color of the bread was affected by the Maillard reaction. The addition of PGAs also augmented the moisture content of the fresh bread crumbs and steamed bread crumbs. All three PGAs improved the textural properties of bread and steamed bread. During storage, PGA addition delayed the staling of bread and steamed bread. In summary, our study showed that the addition of 0.3% PGA from three different producers improved bread properties, with PGA from brand Q having the most substantial effect. PGA had a more substantial effect on bread than steamed bread. Our results provide a theoretical basis to guide the development of insect-formulated flour-based products.

Differential Correlations Informed Metabolite Set Enrichment Analysis to Decipher Metabolic Heterogeneity of Disease.

Metabolic pathways are regarded as functional and basic components of the biological system. In metabolomics, metabolite set enrichment analysis (MSEA) is often used to identify the altered metabolic pathways (metabolite sets) associated with phenotypes of interest (POI), e.g., disease. However, in most studies, MSEA suffers from the limitation of low metabolite coverage. Random walk (RW)-based algorithms can be used to propagate the perturbation of detected metabolites to the undetected metabolites through a metabolite network model prior to MSEA. Nevertheless, most of the existing RW-based algorithms run on a general metabolite network constructed based on public databases, such as KEGG, without taking into consideration the potential influence of POI on the metabolite network, which may reduce the phenotypic specificities of the MSEA results. To solve this problem, a novel pathway analysis strategy, namely, differential correlation-informed MSEA (dci-MSEA), is proposed in this paper. Statistically, differential correlations between metabolites are used to evaluate the influence of POI on the metabolite network, so that a phenotype-specific metabolite network is constructed for RW-based propagation. The experimental results show that dci-MSEA outperforms the conventional RW-based MSEA in identifying the altered metabolic pathways associated with colorectal cancer. In addition, by incorporating the individual-specific metabolite network, the dci-MSEA strategy is easily extended to disease heterogeneity analysis. Here, dci-MSEA was used to decipher the heterogeneity of colorectal cancer. The present results highlight the clustering of colorectal cancer samples with their cluster-specific selection of differential pathways and demonstrate the feasibility of dci-MSEA in heterogeneity analysis. Taken together, the proposed dci-MSEA may provide insights into disease mechanisms and determination of disease heterogeneity.

Application of Band-Selective HSQC NMR in Species Discrimination and Adulteration Identification of Panax Linn.

The quality of Panax Linn products available in the market is threatened by adulteration with different Panax species, such as Panax quinquefolium (PQ), Panax ginseng (PG), and Panax notoginseng (PN). In this paper, we established a 2D band-selective heteronuclear single quantum coherence (bs-HSQC) NMR method to discriminate species and detect adulteration of Panax Linn. The method involves selective excitation of the anomeric carbon resonance region of saponins and non-uniform sampling (NUS) to obtain high-resolution spectra in less than 10 min. The combined strategy overcomes the signal overlap limitation in 1H NMR and the long acquisition time in traditional HSQC. The present results showed that twelve well-separated resonance peaks can be assigned in the bs-HSQC spectra, which are of high resolution, good repeatability, and precision. Notably, the identification accuracy of species was found to be 100% for all tests conducted in the present study. Furthermore, in combination with multivariate statistical methods, the proposed method can effectively determine the composition proportion of adulterants (from 10% to 90%). Based on the PLS-DA models, the identification accuracy was greater than 80% when composition proportion of adulterants was 10%. Thus, the proposed method may provide a fast, practical, and effective analysis technique for food quality control or authenticity identification.

Concordance-Based Batch Effect Correction for Large-Scale Metabolomics.

For a large-scale metabolomics study, sample collection, preparation, and analysis may last several days, months, or even (intermittently) over years. This may lead to apparent batch effects in the acquired metabolomics data due to variability in instrument status, environmental conditions, or experimental operators. Batch effects may confound the true biological relationships among metabolites and thus obscure real metabolic changes. At present, most of the commonly used batch effect correction (BEC) methods are based on quality control (QC) samples, which require sufficient and stable QC samples. However, the quality of the QC samples may deteriorate if the experiment lasts for a long time. Alternatively, isotope-labeled internal standards have been used, but they generally do not provide good coverage of the metabolome. On the other hand, BEC can also be conducted through a data-driven method, in which no QC sample is needed. Here, we propose a novel data-driven BEC method, namely, CordBat, to achieve concordance between each batch of samples. In the proposed CordBat method, a reference batch is first selected from all batches of data, and the remaining batches are referred to as "other batches." The reference batch serves as the baseline for the batch adjustment by providing a coordinate of correlation between metabolites. Next, a Gaussian graphical model is built on the combined dataset of reference and other batches, and finally, BEC is achieved by optimizing the correction coefficients in the other batches so that the correlation between metabolites of each batch and their combinations are in concordance with that of the reference batch. Three real-world metabolomics datasets are used to evaluate the performance of CordBat by comparing it with five commonly used BEC methods. The present experimental results showed the effectiveness of CordBat in batch effect removal and the concordance of correlation between metabolites after BEC. CordBat was found to be comparable to the QC-based methods and achieved better performance in the preservation of biological effects. The proposed CordBat method may serve as an alternative BEC method for large-scale metabolomics that lack proper QC samples.

iMSEA: A Novel Metabolite Set Enrichment Analysis Strategy to Decipher Drug Interactions.

Drug combinations are commonly used to treat various diseases to achieve synergistic therapeutic effects or to alleviate drug resistance. Nevertheless, some drug combinations might lead to adverse effects, and thus, it is crucial to explore the mechanisms of drug interactions before clinical treatment. Generally, drug interactions have been studied using nonclinical pharmacokinetics, toxicology, and pharmacology. Here, we propose a complementary strategy based on metabolomics, which we call interaction metabolite set enrichment analysis, or iMSEA, to decipher drug interactions. First, a digraph-based heterogeneous network model was constructed to model the biological metabolic network based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Second, treatment-specific influences on all detected metabolites were calculated and propagated across the whole network model. Third, pathway activity was defined and enriched to quantify the influence of each treatment on the predefined functional metabolite sets, i.e., metabolic pathways. Finally, drug interactions were identified by comparing the pathway activity enriched by the drug combination treatments and the single drug treatments. A data set consisting of hepatocellular carcinoma (HCC) cells that were treated with oxaliplatin (OXA) and/or vitamin C (VC) was used to illustrate the effectiveness of the iMSEA strategy for evaluation of drug interactions. Performance evaluation using synthetic noise data was also performed to evaluate sensitivities and parameter settings for the iMSEA strategy. The iMSEA strategy highlighted synergistic effects of combined OXA and VC treatments including the alterations in the glycerophospholipid metabolism pathway and glycine, serine, and threonine metabolism pathway. This work provides an alternative method to reveal the mechanisms of drug combinations from the viewpoint of metabolomics.

Protocol for metabolic synergy analysis of multi-organs in mice using iMS2Net.

Biomolecule regulation and communication between cells and organs show specific network and regional features and play an important role in disease progression. Here, we describe steps for in situ detection of biomolecules with detailed spatial distribution using imaging mass spectrometry (iMS). Using the information on inter-cells and inter-organs metabolic interactions provided by iMS, we detail the establishment of an iMS-dataset-sourced multiscale network strategy and present steps for exploring metabolic responses in environmental-exposure-induced disease model. For complete details on the use and execution of this protocol, please refer to Dong et al. (2022).1.

Effects of Physical Properties of Konjac Glucomannan on Appetite Response of Rats.

Dietary fiber has been widely used in designing foods with a high satiating capacity, as the use of satiety-enhancing food is considered to be a promising strategy for combating obesity and the overweight condition. In the present study, partially degraded konjac glucomannan (DKGM) diets with different water-holding capacities, swelling capacities, and viscosities were used to feed rats to investigate the effects of the fiber's physical properties in regulating the appetite response of the animals. The results showed that the mass and water content of the gastrointestinal chyme increased as the diet's physical properties were enhanced by the DKGM, which increased the stomach distention of the rats and promoted satiation. Besides, the hydrated DKGM elevated the chyme's viscosity, and the retention time of the digesta in the small intestine was prolonged significantly, which resulted in an increased concentration of cholecystokinin-8, glucagon-like peptide 1, and peptide tyrosine-tyrosine in the plasma, thus helping to maintain the satiety of rats. Furthermore, the results of the behavioral satiety sequence and meal pattern analysis showed that DKGM in the diets is more likely to reduce the food intake of rats by enhancing satiety rather than satiation, and will finally inhibit excessive weight gain. In conclusion, the physical properties of dietary fiber are highly related to the appetite response, which is a powerful tool in designing food with a high satiating capacity.

Influence of the Maillard Reaction on Properties of Air-Assisted Electrospun Gelatin/Zein/Glucose Nanofibers.

To develop biodegradable, sustainable, and environment-friendly functional food-packaging materials, gelatin/zein/glucose nanofibers were fabricated through air-assisted electrospinning and then crosslinked by the Maillard reaction under mild conditions (60 °C and 50% relative humidity) in this study. Compared to traditional electrospinning, air-assisted electrospinning increased the yield of nanofibers by 10 times, and the average diameter from 263 nm to 664 nm, while the airflow facilitated uniform and smooth nanofiber formation. During the Maillard reaction in 0-5 days, the gelatin/zein/glucose showed no morphology change. Fourier transform infrared spectra analysis indicated that gelatin interacted with zein through hydrogen bonding and the occurrence of the Maillard reaction among the protein and glucose molecules. After four days of Maillard reaction, the nanofibers presented higher thermal stability, the most hydrophobic surface (water contact angle: 133.6°), and stiffer network structure (elastic modulus of 38.63 MPa, tensile strength of 0.85 MPa). Overall, Maillard-reaction-crosslinked gelatin/zein/glucose nanofibers showed favorable physical properties, which suggests their potential for application in food-active packaging.

Effect of Mealworm Powder Substitution on the Properties of High-Gluten Wheat Dough and Bread Based on Different Baking Methods.

Mealworms (Tenebrio molitor) are protein-rich edible insects that have been regarded as novel food ingredients. In this study, high-gluten wheat flour was formulated with dried mealworm powder at various levels (0%, 5%, 10%, 15%, and 20%) to study its influence on the pasting, farinograph, and extensograph properties and microstructure of the dough. A subsequent decrease in the pasting parameters was observed due to starch dilution. The water absorption, dough development time, and dough stability time decreased gradually from 71.9% to 68.67%, 13.6 min to 10.43 min, and 14.1 min to 5.33 min, respectively, with the increase in the substitution of mealworm powder from 0% to 20%. The farinograph characteristics corresponded to a weak gluten network formed through the dilution of gluten by the replacement of wheat flour with a non-gluten ingredient. The stretch ratio of the high-gluten dough increased gradually from 4.37 (M0) to 6.33 (M15). The increased stretching resistance and extensibility of the dough with 5% and 10% mealworm powder indicated that mealworm powder can act as a plasticizer in the gluten network, which might contribute to the decreased strength and increased elasticity and flexibility of the dough network. The bread made with three different baking methods showed similar increases in specific volume and decreased hardness up to the 10% substitution level, owing to the increased elasticity and flexibility of the dough. The GB/T 35869-2018 Rapid-baking method, GB/T 14611-2008 Straight dough method, and automatic bread maker method exhibited the highest specific volumes of 3.70 mL/g, 3.79 mL/g, and 4.14 mL/g when the wheat flour was substituted with 10% mealworm powder. However, 15% and 20% mealworm powder substitution markedly reduced the bread quality owing to the dilution effect and mealworm powder phase separation. These results provide a perspective on the relationship between the rheological properties of mealworm powder-substituted high-gluten dough and application suggestions for insect food development in the food industry.

Molecular network strategy in multi-omics and mass spectrometry imaging.

Human physiological activities and pathological changes arise from the coordinated interactions of multiple molecules. Mass spectrometry (MS)-based multi-omics and MS imaging (MSI)-based spatial omics are powerful methods used to investigate molecular information related to the phenotype of interest from homogenated or sliced samples, including the qualitative, relative quantitative and spatial distributions. Molecular network strategy provides efficient methods to help us understand and mine the biological patterns behind the phenotypic data. It illustrates and combines various relationships between molecules, and further performs the molecule identification and biological interpretation. Here, we describe the recent advances of network-based analysis and its applications for different biological processes, such as, obesity, central nervous system diseases, and environmental toxicology.

iMS2Net: A multiscale networking methodology to decipher metabolic synergy of organism.

The metabolic responses of organism to external stimuli are characterized by the multicellular- and multiorgan-based synergistic regulation. Network analysis is a powerful tool to investigate this multiscale interaction. The imaging mass spectrometry (iMS)-based spatial omics provides multidimensional and multiscale information, thus offering the possibility of network analysis to investigate metabolic response of organism to environmental stimuli. We present iMS dataset-sourced multiscale network (iMS2Net) strategy to uncover prenatal environmental pollutant (PM2.5)-induced metabolic responses in the scales of cell and organ from metabolite abundances and metabolite-metabolite interaction using mouse fetal model, including metabotypic similarity, metabolic vulnerability, metabolic co-variability and metabolic diversity within and between organs. Furthermore, network-based analysis results confirm close associations between lipid metabolites and inflammatory cytokine release. This networking methodology elicits particular advantages for modeling the dynamic and adaptive processes of organism under environmental stresses or pathophysiology and provides molecular mechanism to guide the occurrence and development of systemic diseases.

Evaluation of prediction effect of perfusion index for supraclavicular brachial plexus block in children: protocol for a randomized trial.

BACKGROUND: Pulse perfusion index (PI) reflects blood perfusion. It has been reported that PI can be used to evaluate the effect of nerve block, but currently, it is mainly focused on awake adults. In pediatric general anesthesia, it has been reported that PI can evaluate the effect of the sacral block. Still, there is a lack of relevant research on the impact of brachial plexus blocks. Our objective is to assess the prediction effects of PI on the success of supraclavicular brachial plexus block in pediatric patients under sevoflurane or propofol general anesthesia. METHODS/DESIGN: This is a mono-center, parallel, 2-arm randomized superiority trial. One hundred four children aged 1 month to 12 years who undergo upper limb surgery will be enrolled in this study. According to anesthesia induction and maintenance medication, they will be divided into sevoflurane and propofol groups. The PI values of the index and little finger will be recorded on the blocked and non-blocked sides of supraclavicular brachial plexus block (SCB) in all children. The primary outcome is to assess the effects of PI on the success of supraclavicular brachial plexus block in pediatric patients under sevoflurane or propofol general anesthesia. The secondary outcome includes mean arterial blood pressure (MAP), heart rate (HR), and correlation between baseline PI and 10 min after SCB (PI ratio). DISCUSSION: This trial will provide evidence on the changes in PI after SCB in sevoflurane or propofol anesthesia in children. SCB may lead to changes in PI values under sevoflurane or propofol anesthesia. After the children wake up at the end of the surgery, the changes in PI values on the block side and non-block side may be helpful to judge the effect of nerve block when excluding the influence of anesthetics. TRIAL REGISTRATION: ClinicalTrials.gov NCT04216823 . Registered on 15 July 2020.

Effect of Partial Substitution of Flour with Mealworm (Tenebrio molitor L.) Powder on Dough and Biscuit Properties.

Mealworm (Tenebrio molitor L.) is a type of edible insect rich in protein that has become popular as a protein-alternative ingredient in flour-based products to improve the nutritional properties of baking products. The mealworm powder substitution affected the pasting, farinograph, extensograph properties of wheat flour and the texture, nutritional, and sensory properties of the resulting soda biscuit. The pasting parameters (peak viscosity, trough viscosity, breakdown viscosity, final viscosity, and setback viscosity) and the water absorption decreased with the increased mealworm powder substitution level, which was ascribed to the dilution effect of mealworm powder. The farinograph parameters remained similar up to 15% substitution level. The extensograph results showed that mealworm powder substitution decreased the elastic properties of wheat dough as indicated by the consistently decreased extensibility, stretching energy, and stretching resistance, resulting in a significantly decreased baking expansion ratio of the soda biscuit. The protein, lipid, and dietary fiber content of the biscuits increased accordingly with the increased mealworm powder substitution level. The protein content of the soda biscuit was gradually increased from 9.13/100 g for the control (M0) to 16.0/100 g for that supplemented with 20% mealworm powder (M20), accompanied with the significantly increased essential amino acid content. Meanwhile, the fat and dietary fiber content of M20 exhibited 20.5 and 21.7% increase compared to those of M0. The score of the sensory attributes showed no significant difference up to 15% substitution level. The results demonstrated the 15% mealworm powder substitution level would not significantly affect the farinograph property, microstructure of wheat dough, and sensory acceptability.

Impact of glycation on physical properties of composite gluten/zein nanofibrous films fabricated by blending electrospinning.

In this study, the gluten/zein nanofibrous films were fabricated by blending electrospinning and then glycated with xylose via Maillard reaction. The average fiber diameter of the gluten film decreased from 551 to 343 nm with the increasing ratio of zein, but increased significantly to a range of 717-521 nm after glycation, which induced a higher thermal stability of the nanofibers with an order to disorder transition. The glycated composite films showed the reduced water vapor permeability and improved water stability with a stiffer and more elastic network structure, due to the enhanced intermolecular entanglements and interactions between polymer chains. The results from this work suggested that the composite gluten/zein electrospun films may be glycated via Maillard reaction to obtain desirable physical properties for active food-packaging applications.

Current Progress in the Utilization of Soy-Based Emulsifiers in Food Applications-A Review.

Soy-based emulsifiers are currently extensively studied and applied in the food industry. They are employed for food emulsion stabilization due to their ability to absorb at the oil-water interface. In this review, the emulsifying properties and the destabilization mechanisms of food emulsions were briefly introduced. Herein, the effect of the modification process on the emulsifying characteristics of soy protein and the formation of soy protein-polysaccharides for improved stability of emulsions were discussed. Furthermore, the relationship between the structural and emulsifying properties of soy polysaccharides and soy lecithin and their combined effect on the protein stabilized emulsion were reviewed. Due to the unique emulsifying properties, soy-based emulsifiers have found several applications in bioactive and nutrient delivery, fat replacer, and plant-based creamer in the food industry. Finally, the future trends of the research on soy-based emulsifiers were proposed.

Fabrication and characterization of dextran/zein hybrid electrospun fibers with tailored properties for controlled release of curcumin.

BACKGROUND: In recent years, there has been considerable interest in the use of biopolymer electrospun nanofibers for various food applications due to the biocompatibility, biodegradability, and high loading capacity. Herein, we fabricated and characterized novel hybrid electrospun fibers from dextran (50%, w/v) and zein (0-30%, w/v) solutions, and the effects of various zein concentrations on the properties of the hybrid electrospun fibers were investigated. RESULTS: When zein was added at low concentrations (5% and 10%), dextran and zein showed poor miscibility, as reflected by significantly decreased viscosity of the solutions, and the poor mechanical properties of the derived fiber membranes. When zein was added at medium concentrations (15-25%), hydrogen bonds were formed between dextran and zein molecules, as indicated by the red shift of Fourier-transform infrared bands and ß-sheet to α-helix structural transformations. The fiber membranes electrospun from a solution with 25% zein showed the most hydrophobic surface, with a water contact angle of 116.9°. The homogenous dispersion of dextran and zein resulted in improved mechanical properties for fibers electrospun from a solution with 30% zein. Curcumin encapsulating dextran/zein electrospun fibers exhibited effective radical scavenging activity and ferric reducing power, along with the desired controlled release behavior for curcumin delivery. CONCLUSION: Food grade dextran/zein hybrid electrospun fibers demonstrated tunable properties, and appear to be promising as delivery systems for bioactive and edible antimicrobial food packaging. © 2021 Society of Chemical Industry.

Sparse PLS-Based Method for Overlapping Metabolite Set Enrichment Analysis.

Metabolite set enrichment analysis (MSEA) has gained increasing research interest for identification of perturbed metabolic pathways in metabolomics. The method incorporates predefined metabolic pathways information in the analysis where metabolite sets are typically assumed to be mutually exclusive to each other. However, metabolic pathways are known to contain common metabolites and intermediates. This situation, along with limitations in metabolite detection or coverage leads to overlapping, incomplete metabolite sets in pathway analysis. For overlapping metabolite sets, MSEA tends to result in high false positives due to improper weights allocated to the overlapping metabolites. Here, we proposed an extended partial least squares (PLS) model with a new sparse scheme for overlapping metabolite set enrichment analysis, named overlapping group PLS (ogPLS) analysis. The weight vector of the ogPLS model was decomposed into pathway-specific subvectors, and then a group lasso penalty was imposed on these subvectors to achieve a proper weight allocation for the overlapping metabolites. Two strategies were adopted in the proposed ogPLS model to identify the perturbed metabolic pathways. The first strategy involves debiasing regularization, which was used to reduce inequalities amongst the predefined metabolic pathways. The second strategy is stable selection, which was used to rank pathways while avoiding the nuisance problems of model parameter optimization. Both simulated and real-world metabolomic datasets were used to evaluate the proposed method and compare with two other MSEA methods including Global-test and the multiblock PLS (MB-PLS)-based pathway importance in projection (PIP) methods. Using a simulated dataset with known perturbed pathways, the average true discovery rate for the ogPLS method was found to be higher than the Global-test and the MB-PLS-based PIP methods. Analysis with a real-world metabolomics dataset also indicated that the developed method was less prone to select pathways with highly overlapped detected metabolite sets. Compared with the two other methods, the proposed method features higher accuracy, lower false-positive rate, and is more robust when applied to overlapping metabolite set analysis. The developed ogPLS method may serve as an alternative MSEA method to facilitate biological interpretation of metabolomics data for overlapping metabolite sets.

Fabrication and characterization of fast dissolving glycerol monolaurate microemulsion encapsulated gelatin nanofibers with antimicrobial activity.

BACKGROUND: Electrospun fibers are a good candidate for the delivery of bioactive compounds in the food industry because of their advantages that include a tunable diameter, high porosity and a high specific surface area. In the present study, we fabricated gelatin/glycerol monolaurate (GML) microemulsion nanofibers by solubilizing GML in Tween-80 followed by mixing with gelatin solution for electrospinning. We hypothesized that the addition of GML microemulsions affects the properties of the gelatin solution and modifies the physical and antimicrobial properties of the resulting nanofibers. RESULTS: Both pure gelatin solution and gelatin/GML microemulsions showed shear-thinning behavior. However, electrospinnability was not affected by the addition of GML microemulsions. A significantly higher average diameter of nanofibers (1147 nm) with 5% GML was observed compared to the gelatin fiber diameter of 560 nm. Fourier transform infrared spectroscopy showed hydrogen bonding between gelatin molecules and GML microemulsions. Thermal analysis and X-ray diffraction indicated an amorphous structure of gelatin/GML microemulsion nanofibers, although a small amount of crystalline GML existed in the nanofibers with high GML content. Gelatin/GML microemulsion nanofibers showed high thermal stability and improved hydrophilicity. Nanofibers with 5% GML (weight with respect to nanofiber) (D64 nanofibers) showed effective antimicrobial activity against Escherichia coli and Staphylococcus aureus. CONCLUSION: Gelatin/GML microemulsion nanofibrous films demonstrate superhydrophilicity and fast dissolution properties as a result of the high surface-to-volume ratio, amorphous structure and improved hydrophilicity of the nanofiber surface. The results indicate the potential application of gelatin/GML microemulsion nanofibrous films as edible antimicrobial food packaging. © 2021 Society of Chemical Industry.