Comparative pharmacokinetics of six components in normal and rheumatoid arthritis rats after intragastrical administration of Qianghuo Shengshi Decoction granules by LC-MS/MS.

Objective: To investigate the plasma pharmacokinetics of six representative components (nodakenin, osthole, 5-O-methylvisammioside, ferulic acid, liquiritigenin, and liquiritin), which were the ingredients of Qianghuo Shengshi Decoction (QSD) granules, in normal and rheumatoid arthritis (RA) rats administrated QSD granules intragastrically. Methods: A rapid and accurate ultra-high performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed for the simultaneous determination of six components in plasma, and it showed a good specificity, linearity, intra-day and inter-day precision, intra-day and inter-day accuracy, extraction recovery, stability, and the less matrix effect. Results: The validated LC-MS/MS method was successfully used to compare the plasma pharmacokinetics of six ingredients between normal and RA rats after intragastrical administration of QSD granules and differences in the pharmacokinetics were found in two types of rats. The absorption rate in the RA rats was lower for nodakenin, osthole, 5-O-methylvisammioside, liquiritigenin and liquiritin than in the normal group, while the absorption rate of ferulic acid remained constant in two groups. In comparison with the normal rats, the exposure concentration of nodakenin was higher and that of other five components except for nodakenin was lower under pathological conditions. Additionally, the absorptive amount of nodakenin, osthole, 5-O-methylvisammioside and liquiritin was increased and that of ferulic acid and liquiritigenin was reduced in the RA rats than in the normal rats. Compared with the normal rats, the retention time of nodakenin, ferulic acid and liquiritin was reduced in vivo, whereas the retention time of osthole, 5-O-methylvisammioside and liquiritigenin was raised in the body for the RA rats. In contrast to the normal rats, the data demonstrated an increase in the elimination velocity of nodakenin and a decrease in the elimination velocity of the other five components except for nodakenin in the pathological state. Conclusion: This study showed that the pharmacokinetic behavior of the six components, nodakenin, osthole, 5-O-methylvisammioside, ferulic acid, liquiritigenin, and liquiritin, is different in vivo between normal and pathological states of rats, and this research provided the necessary experimental data to explain the pharmacokinetics of QSD granules in both normal and pathological states and provide some references for its clinical application at some level.

Transcriptome Reveals the Key Genes Related to the Metabolism of Volatile Sulfur-Containing Compounds in Lentinula edodes Mycelium.

Lentinula edodes (L. edodes) is a globally popular edible mushroom because of its characteristic sulfur-containing flavor compounds. However, the formation of the volatile sulfur-containing compounds in the mycelium of L. edodes has not been studied. We found that there were also sulfur-containing aroma compounds in the mycelium of L. edodes, and the content and composition varied at different stages of mycelial growth and development. The γ-glutamyl-transpeptidase (GGT) and cysteine sulfoxide lyase (C-S lyase) related to the generation of sulfur compounds showed the highest activities in the 15-day sample. Candidate genes for the metabolism of volatile sulfur compounds in mycelium were screened using transcriptome analysis, including encoding the GGT enzyme, C-S lyase, fatty acid oxidase, HSP20, and P450 genes. The expression patterns of Leggt3 and Leccsl3 genes were consistent with the measured activities of GGT and C-S lyase during the cultivation of mycelium and molecular dynamics simulations showed that they could stably bind to the substrate. Our findings provide insights into the formation of sulfur-containing flavor compounds in L. edodes. The mycelium of L. edodes is suggested for use as material for the production of sulfur-containing flavor compounds.

Preparation of chitosan/Tenebrio molitor larvae protein/curcumin active packaging film and its application in blueberry preservation.

With growing concerns about postharvest spoilage of fruits, higher requirements have been placed on high-performance and sustainable active packaging materials. In this study, we prepared curcumin-based functional composite films using chitosan (CS) and Tenebrio molitor larvae protein (TMP) as the substrates. The effects of curcumin concentration on the structural and physicochemical properties of the composite films were determined. Curcumin was equally distributed in the polymer film through physical interactions. Furthermore, the curcumin composite film with 0.3 % addition exhibited a 27.39 % increase in elongation at break (EBA), a 37.04 % increase in the water vapor barrier, and strong UV-blocking properties and antioxidant activity compared with the control film (CS/TMP). The degradation experiment of the composite film on natural soil revealed that the composite film exhibited good biodegradability and environmental protection. Furthermore, the applicability of functional composite films for preserving blueberries was investigated. Compared with the control film and polyethylene (PE) films, the prepared composite films packaging treatment reduced the decay rate and weight loss rate of blueberries during storage, delayed softening and aging, and maintained the quality of blueberries. Using sustainable protein resources (TMP) and natural polysaccharides as packaging materials provides an economically, feasible and sustainable way to achieve the functional preservation of biomass materials.

The combined effects of ultrasound and plasma-activated water on silkworm pupae:Physicochemical properties, microbiological diversity and ultrastructure.

A novel technique was proposed for processing silkworm pupae by combining plasma- activated water (PAW) with ultrasound (US). The microbial diversity and quality characteristics of the silkworm pupae were also evaluated. The results of the microbial diversity analysis indicated that PAW combined with US treatment significantly reduced the relative abundance of Streptococcaceae, Leuconostocaceae, and Acetobacteraceae from 32%, 18% and 16% to 27%, 11% and 11%, respectively. Microstructural analysis demonstrated that the collapse of the internal structure of chitin in silkworm pupae facilitated the release of nutrients and flavour compounds including fatty acids, water-soluble proteins (WSP), amino acids, phenolics, and volatile compounds. Furthermore, the increase in antioxidant capacity and the decrease in catalase activity and malondialdehyde content confirmed the mechanism of quality change. These findings provide new insights into the possible mechanism of PAW combined with US to improve the quality of edible insects.

Discovery of potential anti- Staphylococcus aureus natural products and their mechanistic studies using machine learning and molecular dynamic simulations.

The structure-activity analysis (SAR) and machine learning were used to investigate potential anti-S. aureus agents in a faster method. In this study, 24 oxygenated benzene ring components with S. aureus inhibition capacity were confirmed by literature exploring and in-house experiments, and the SAR analysis suggested that the hydroxyl group position may affect the anti-S. aureus activity. The 2D-MLR-QSAR model with 9 descriptors was further evaluated as the best model among the 21 models. After that, hesperetic acid and 2-HTPA were further explored and evaluated as the potential anti-S. aureus agents screening in the natural product clustering library through the best QSAR model calculation. The antibacterial capacities of hesperetic acid and 2-HTPA had been investigated and proved the similar predictive pMIC value resulting from the QSAR model. Besides, the two novel components were able to inhibit the growth of S. aureus by disrupting the cell membrane through the molecular dynamics simulation (MD), which further evidenced by scanning electron microscopy (SEM) test and PI dye results. Overall, these results are highly suggested that QSAR can be used to predict the antibacterial agents targeting S. aureus, which provides a new paradigm to research the molecular structure-antibacterial capacity relationship.

Exploring the effect of high-pressure processing conditions on the deaggregation of natural major royal jelly proteins (MRJPs) fibrillar aggregates.

High pressure processing is a safe and green novel non-thermal processing technique for modulating food protein aggregation behavior. However, the systematic relationship between high pressure processing conditions and protein deaggregation has not been sufficiently investigated. Major royal jelly proteins, which are naturally highly fibrillar aggregates, and it was found that the pressure level and exposure time could significantly promote protein deaggregation. The 100-200 MPa treatment favoured the deaggregation of proteins with a significant decrease in the sulfhydryl group content. Contrarily, at higher pressure levels (>400 MPa), the exposure time promoted the formation of disordered agglomerates. Notably, the inter-conversion of α-helix and ß-strands in major royal jelly proteins after high pressure processing eliminates the solvent-free cavities inside the aggregates, which exerts a 'collapsing' effect on the fibrillar aggregates. Furthermore, the first machine learning model of the high pressure processing conditions and the protein deaggregation behaviour was developed, which provided digital guidance for protein aggregation regulation.

EEG-based emotion recognition using a temporal-difference minimizing neural network.

Electroencephalogram (EEG) emotion recognition plays an important role in human-computer interaction. An increasing number of algorithms for emotion recognition have been proposed recently. However, it is still challenging to make efficient use of emotional activity knowledge. In this paper, based on prior knowledge that emotion varies slowly across time, we propose a temporal-difference minimizing neural network (TDMNN) for EEG emotion recognition. We use maximum mean discrepancy (MMD) technology to evaluate the difference in EEG features across time and minimize the difference by a multibranch convolutional recurrent network. State-of-the-art performances are achieved using the proposed method on the SEED, SEED-IV, DEAP and DREAMER datasets, demonstrating the effectiveness of including prior knowledge in EEG emotion recognition.

Efficient degradation of imidacloprid by surface discharge cold plasma: Mechanism of interaction between ROS and molecular structure and evaluation of residual toxicity.

Incorrect use of neonicotinoid pesticides poses a serious threat to human and pollinator health, as these substances are commonly present in bee products and even drinking water. To combat this threat, the study developed a new method of degrading the pesticide imidacloprid using surface discharge cold plasma oxidation technology. The study showed that this method achieved a very high efficiency of imidacloprid degradation of 91.4%. The main reactive oxygen species (H2O2, O3, ·OH, O2-, 1O2) effectively participated in the decomposition reaction of imidacloprid. Reactive oxygen species were more sensitive to the structure of the nitroimine group. Density functional theory (DFT) further explored the sites of reactive oxygen species attack on imidacloprid and revealed the process of energy change of attacking imidacloprid. In addition, a degradation pathway for imidacloprid was proposed, mainly involving reactive oxygen species chemisorption, a ring-opening intermediate, and complete cleavage of the nitroimine group structure. Model predictions indicated that acute oral and developmental toxicity were significantly reduced after cold plasma treatment, as confirmed by insect experiments. Animal experiments have shown that plasma treatment reduces imidacloprid damage to mice hippocampal tissue structure and inhibits the reduction of brain-derived neurotrophic factor content, thus revealing the detoxification mechanism of the body.

Fusing the spatial structure of electroencephalogram channels can increase the individualization of the functional connectivity network.

An electroencephalogram (EEG) functional connectivity (FC) network is individualized and plays a significant role in EEG-based person identification. Traditional FC networks are constructed by statistical dependence and correlation between EEG channels, without considering the spatial relationships between the channels. The individual identification algorithm based on traditional FC networks is sensitive to the integrity of channels and crucially relies on signal preprocessing; therefore, finding a new presentation for FC networks may help increase the performance of the identification algorithms. EEG signals are smooth across space owing to the volume conduction effect. Considering such spatial relationships among channels can provide a more accurate representation of FC networks. In this study, we propose an EEG FC network with virtual nodes that combines the spatial relationships and functional connectivity of channels. The comparison results for individual identification show that the novel EEG network is more individualized and achieves an accuracy of 98.64% for data without preprocessing. Furthermore, our algorithm is more robust in reducing the number of channels and can perform well even when a large area of channels is removed.

Application of hyaluronic acid-based nanoparticles for cancer combination therapy.

Cancer is a significant public health problem in the world. The treatment methods include surgery, chemotherapy, phototherapy, and immunotherapy. Due to their respective limitations, the treatment effect is often unsatisfactory, laying hidden dangers for metastasis and recurrence. Since their exceptional biocompatibility and excellent targeting capabilities, hyaluronic acid-based biomaterials have generated great interest as drug delivery methods for tumor therapy. Moreover, modified HA can self-assemble into hydrogels or nanoparticles (NPs) for precise drug administration. This article summarizes the application of HA-based NPs in combination therapy. Ultimately, it is anticipated that this research will offer guidance for creating various HA-based NPs utilized in numerous cancer therapies.

Self-assembled condensed tannins supramolecular system can adsorb cholesterol micelles to promote cholesterol excretion.

In this study, the cholesterol (CH)-lowering behavioral mechanisms and drivers of condensed tannins (CTs) were revealed using a molecular aggregation theoretical model combined with in vitro experiments, as well as the CH-lowering effects of CTs validated based on animal experiments. Theoretical model results indicated that CTs can spontaneously aggregate to form supramolecular systems, can break CH micelles and form larger aggregates, a behavior driven by van der Waals forces and hydrogen bonds; DLS and TEM results confirmed that the presence of CH leads to a larger particle size of CTs and the formation of large aggregates; thermodynamic analysis and ITC revealed that the adsorption of CH by CTs is a spontaneous reaction driven by hydrogen bonds and hydrophobic forces; Animal experiments and fecal biochemical parameters further confirmed that the intake of CTs can reduce CH absorption and promotes CH excretion. Overall, this study reveals the CH-lowering behavioral mechanism of CTs from the perspective of molecular aggregation behavior.

Virtual screening strategy for anti-DPP-IV natural flavonoid derivatives based on machine learning.

Flavonoids, especially their inhibitory effect on DPP-IV activity, have been widely recognized for their antidiabetic effects. However, the variety of natural flavonoid derivatives is very rich, and even subtle structural differences can lead to several orders of magnitude differences in their inhibitory activities against DPP-IV, which makes it challenging to find novel and potent anti-DPP-IV flavonoid derivatives experimentally. Therefore, there is an urgent need to develop an efficient screening pipeline that targets active natural products. Here, we propose a fusion strategy based on a QSAR model, and to simplify this process, it was applied to the discovery of flavonoid derivatives with potent anti-DPP-IV activity. First, the high-quality QSAR model (Rtest2 = 0.816, MAEtest = 0.14, MSEtest = 0.026) was composed of seven key molecular property parameters, which were constructed with the genetic algorithm (GA) and passed the leave-one-out cross-validation evaluation. A total of 1,668 flavonoid derivatives were obtained from the natural product enriched by NPCD based on molecular fingerprint similarity (> 0.8). Further, the enriched flavonoid derivatives were further predicted and screened using the QED score combined with the QSAR model, and a total of 33 flavonoid derivatives (IC50pre < 6.5 µM) were found. Subsequently, three flavonoid derivatives (5,7,3',5'-tetrahydroxyflavone, 3,7-dihydroxy-5,3',4'-trimethoxyflavone, and 5,7,2',5'-tetrahydroxyflavone) with highly effective anti-DPP-IV activity were obtained by ADMET analysis. Finally, the DPP-IV inhibitory potential of these three flavonoid derivatives was verified by 100 ns MD simulation and MM/PB(GB)SA.Communicated by Ramaswamy H. Sarma.

Comprehensive study of volatile compounds of rare Leucosceptrum canum Smith honey: Aroma profiling and characteristic compound screening via GC-MS and GC-MS/MS.

Monofloral honeys are highly valued for their unique flavors and potential health benefits. In this study, the aromatic attributes of rare Leucosceptrum canum Smith honey (LCH) were characterized by GC-MS coupled with GC-MS/MS. Based on their odor contribution rates (OCRs), linalool (74.22%), 3-methyl-1-butanol (18.19%), benzeneacetaldehyde (1.31%) and lilac aldehyde B (2.78%) were largely responsible for the unique and complex flavor of LCH - flowery, spicy, sweet, fruity and fresh. Compared to other tested honeys, linalool (0.18 mg/kg), which has known antibacterial properties, was higher in LCH. However, it was not the main antibacterial compound in LCH, suggesting as of now unknown antibacterial compounds. This study provides the first aromatic profile of LCH, which will be useful for the authentication of LCH and for uncovering the mechanisms behind its perceived health benefits.

Effects of Major Royal Jelly Proteins on the Immune Response and Gut Microbiota Composition in Cyclophosphamide-Treated Mice.

Increasing evidence suggests that royal jelly (RJ) has exceptional biological properties, and that major royal jelly proteins (MRJPs) are the key active factors in RJ. The objective of this study was to compare the difference in the protein content between RJ and MRJPs using non-labeled, quantitative proteomics technology, and to investigate the adjustment features and mechanisms of MRJPs on murine immune functions and the composition of intestinal flora in cyclophosphamide-treated mice. Results showed that, during the process of extracting MRJPs, the ratio of the protein types in the main protein and other proteins decreased significantly, except for MRJP1 and MRJP7, which demonstrated that an enriching effect of MRJP1 and MRJP7 was present during the extraction process. Cyclophosphamide-induced mice were orally administered MRJPs. Results showed that the middle-dose group, which received 0.25 g/(kg·bw) of royal jelly main protein, demonstrated a clear impact on the development of the spleen and liver, the quantity of peripheral blood leukocytes, immunoglobulin content, immune factor level, and the proliferation ability of spleen lymphocytes. A 16S rRNA high-throughput sequencing technology analysis showed that MRJPs could improve the component and richness of intestinal flora and raise the immunity of mice. The above-mentioned results indicated that the application of MRJPs is very likely to have an advantage effect on murine immune functions.

Identification of the maturity of acacia honey by an endogenous oligosaccharide: A preliminary study.

Mature honeys that brew naturally in the hive develop distinct bioactive components, and thus carry a higher premium due to their superior quality. However, how to identify mature honeys remains difficult. Trace oligosaccharides are a likely source of biomarkers to indicate maturity. Here, we profiled trace oligosaccharides in acacia honey by GC-MS and used a metabolomics strategy to screen oligosaccharides that distinguish honeys with different maturities. Turanose content increased gradually in acacia honey samples and was closely related to the days stored in the hive (p < 0.05). To accurately quantify turanose, a UPLC-ELSD method was developed. Using the established method, honeys with ≥1.20 g/100 g of turanose could be classified as mature acacia honey. Based on the preliminary study, 500 commercial acacia honeys were analyzed, and only 77.2 % of these samples had a satisfactory level of turanose. This work offers a potential method to evaluate the quality of honeys.

Honeybee (Apis mellifera) resistance to deltamethrin exposure by Modulating the gut microbiota and improving immunity.

Honeybees (Apis mellifera) are important economic insects and play important roles in pollination and maintenance of ecological balance. However, the use of pesticides has posed a substantial threat to bees in recent years, with the more widely used deltamethrin being the most harmful. In this study, we found that deltamethrin exposure significantly reduced bee survival in a dose-dependent manner (p = 0.025). In addition, metagenomic sequencing further revealed that DM exposure significantly reduced the diversity of the bee gut microbiota (Chao1, p < 0.0001; Shannon, p < 0.0001; Simpson, p < 0.0001) and decreased the relative abundance of core species of the gut microbiota. Importantly, in studies of GF-bees, we found that the colonization of important gut bacteria such as Gilliamella apicola and Lactobacillus kunkeei significantly increased bee resistance to DM (survival rate increased from 16.7 to 66.7%). Interestingly, we found that the immunity-genes Defensin-2 and Toll were significantly upregulated in bees after the colonization of gut bacteria. These results suggest that gut bacteria may protect against DM stress by improving host immunity. Our findings provide an important rationale for protecting honeybees from pollutants from the perspective of gut microbes.

Effects of hot-air drying temperature on drying characteristics and color deterioration of rape bee pollen.

The effects of different hot-air drying (HAD) temperature (40, 50, 60, and 70 °C) on the drying characteristics, color changes, the contents of α-dicarbonyl compounds (α-DCs), 5-hydroxymethyl furfural (5-HMF) and carotenoids of rape bee pollen were investigated in the study. The results showed that increasing the drying temperature from 40 to 70 °C shortened the drying time by 65 %. HAD caused lower L* and b* values, as well as higher a* values. Browning index and 5-HMF content increased with increasing drying temperature. The relative content of antheraxanthin increased 230 % at 70 °C while lutein and zeaxanthin decreased by 74 and 81 % than that of fresh (non-heated) pollen. The contents of 3-deoxyglucosone, 1-deoxy-2,3-pentosulose, antheraxanthin, and lutein were related to the color deterioration in HAD process in rape bee pollen. This work is of great practical significance to provide scientific basis for quality optimization of bee pollen in the drying process.

Applying Multiple Functional Connectivity Features in GCN for EEG-Based Human Identification.

EEG-based human identification has gained a wide range of attention due to the further increase in demand for security. How to improve the accuracy of the human identification system is an issue worthy of attention. Using more features in the human identification system is a potential solution. However, too many features may cause overfitting, resulting in the decline of system accuracy. In this work, the graph convolutional neural network (GCN) was adopted for classification. Multiple features were combined and utilized as the structure matrix of the GCN. Because of the constant signal matrix, the training parameters would not increase as the structure matrix grows. We evaluated the classification accuracy on a classic public dataset. The results showed that utilizing multiple features of functional connectivity (FC) can improve the accuracy of the identity authentication system, the best results of which are at 98.56%. In addition, our methods showed less sensitivity to channel reduction. The method proposed in this paper combines different FCs and reaches high classification accuracy for unpreprocessed data, which inspires reducing the system cost in the actual human identification system.

Insight into the Influence of Lactic Acid Bacteria Fermentation on the Variations in Flavor of Chickpea Milk.

This study aimed to evaluate the influence of fermentation on the levels of free amino acids (FAAs) and variations of volatile odorants in four groups of chickpea milk. Electronic nose (E-nose) and gas chromatography-mass spectrometry (GC-MS) data were subjected to mutual validation. W2S and W3S sensors of E-nose were sensitive to volatile constituents in the four groups of unfermented and fermented specimens. After fermentation, the levels of FAAs in the four groups of specimens decreased to varying degrees. Additionally, there were remarkable differences in the types and contents of volatile odor substances in all specimens before and after fermentation. The principal component analysis findings based on E-nose identified the changes of volatile odorants in all specimens before and after fermentation. GC-MS identified 35 and 55 volatile flavor substances in unfermented and fermented specimens, respectively. The varieties of volatile odor substances in fermented chickpea milk (FCM) with papain treatment plus yam addition (38) were more than those in FCM (24), indicating that the coupled treatment of enzymolysis and yam addition could enrich the volatile odorants in fermented specimens. After probiotic fermentation, the contents of off-flavor substances decreased to a certain extent, and key aroma substances such as 2,3-pentanedione, 2,3-butanedione, and heptyl formate were detected. These results demonstrated that lactic acid bacterial fermentation on the basis of enzymolysis and yam addition could be utilized as a feasible approach to improve the flavor of plant-based products adopting chickpea as the original ingredient.

Royal Jelly Protected against Dextran-Sulfate-Sodium-Induced Colitis by Improving the Colonic Mucosal Barrier and Gut Microbiota.

Royal jelly (RJ) is a natural bee product that contains a variety of biologically active ingredients and has antitumor, antiallergic, antibacterial and immune-regulating effects. Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the intestine that can cause abdominal pain and diarrhea. With this study, we aimed to explore the protective effect of RJ on DSS-induced colitis in mice. The physiochemical parameters (water, protein, 10-hydroxy-2-decenoic acid, total sugar, starch, ash and acidity) of the RJ samples used in this study met the requirements of the international and Chinese national standards. Treatment with RJ improved symptoms and colonic cell apoptosis and decreased intestinal permeability by increasing the expression of tight-junction protein, goblet cells and their secretion mucin, MUC2, in DSS-induced ulcerative colitis mice. RJ also reduced the expression of proinflammatory cytokine IL-6 and increased the expression of anti-inflammatory cytokine IL-10 and sIgA. DSS resulted in an increase in the relative abundance of Parabacteroides, Erysipelotrichaceae, Proteobacteria (Gammaproteobacteria, Enterobacteriales and Enterobacteriaceae) and Escherichia Shigella in the colon and a decrease in the relative abundance of Muribaculum. In the RJ treatment group, the relative abundance of the above intestinal flora was improved by treatment with 2.0 g/kg RJ. These results suggested that RJ alleviated DSS-induced colitis by improving the colonic mucosal barrier.