Structure of human MDM2 complexed with RPL11 reveals the molecular basis of p53 activation.

The central region of MDM2 is critical for p53 activation and tumor suppression. Upon ribosomal stress, this region is bound by ribosomal proteins, particularly ribosomal protein L11 (RPL11), leading to MDM2 inactivation and subsequent p53 activation. Here, we solved the complex structure of human MDM2-RPL11 at 2.4 Å. MDM2 extensively interacts with RPL11 through an acidic domain and two zinc fingers. Formation of the MDM2-RPL11 complex induces substantial conformational changes in both proteins. RPL11, unable to bind MDM2 mutants, fails to induce the activation of p53 in cells. MDM2 mimics 28S rRNA binding to RPL11. The C4 zinc finger determines RPL11 binding to MDM2 but not its homolog, MDMX. Our results highlight the essential role of the RPL11-MDM2 interaction in p53 activation and tumor suppression and provide a structural basis for potential new anti-tumor drug development.

Structural and Interfacial Engineering of Ni2P/Fe3O4 Porous Nanosheet Arrays for Efficient Oxygen Evolution Reaction.

Rational design of transition-metal phosphide (TMPs)-based electrocatalysts can effectively promote oxygen evolution reaction (OER). Herein, the novel efficient Ni2P/Fe3O4 porous nanosheets arrays supported on Ni foam (Ni2P/Fe3O4/NF) as alkaline OER catalysts were synthesized using structural and interfacial engineering. The three-dimensional (3D) porous hierarchical structure of Ni2P/Fe3O4/NF provides abundant active sites for OER and facilitates the electrolyte diffusion of ions and O2 liberation. Furthermore, the strong interfacial coupling and synergistic effect between Ni2P and Fe3O4 modify the electronic structure, resulting in the enhanced intrinsic activity. Consequently, the optimized Ni2P/Fe3O4/NF exhibits excellent OER performance with low overpotentials of 213 and 240 mV at 60 and 100 mA cm-2 in 1.0 M KOH, respectively, better than the RuO2/NF and most Ni/Fe-based OER catalysts. Impressively, it can maintain its catalytic activity for at least 20 h at 60 mA cm-2. In addition, the relationship between the structure and performance is fully elucidated by the experimental characterizations, indicating that the metal oxyhydroxides in situ generated on the surface of catalysts are responsible for the high OER activity.

Nickel sulfide nanoworm network architecture as a binder-free high-performance non-enzymatic glucose sensor.

Nickel sulfide nanoworm (Ni3S2 NW) network architecture was directly grown on the poly (3,4-ethylenedioxythiophene)-reduced graphene oxide hybrid films (PEDOT-rGO HFs) modified on glassy carbon electrode (GCE), acting as a binder-free sensor for high-performance non-enzymatic glucose monitoring. The sensor exhibited the satisfactory sensitivity (2123 µA mM-1 cm-2), wide linear range (15~9105 µM), low detection limit (0.48 µM), and rapid response time (< 1.5 s) at a potential of 0.5 V (vs. SCE) in 0.1 M NaOH and possessed good selectivity, reproducibility, and stability. The enhanced electrocatalytic activity of the sensor towards glucose oxidation was attributed to the particular morphology, satisfying hydrophilic nature, strong combination between Ni3S2 NWs, PEDOT-rGO, and bare GCE. Moreover, it can be used for assaying glucose in human serum samples without dilution, indicating potential for clinical diagnostic applications. Graphical abstract Nickel sulfide nanoworms (Ni3S2 NWs)/poly (3,4-ethylenedioxythiophene)-reduced graphene oxide hybrid films (PEDOT-rGO HFs) were used to construct a binder-free high-performance non-enzymatic glucose sensor with satisfactory sensitivity, wide linear range, low detection limit, good selectivity, amazing reproducibility, and stability.

Ultrathin Mn Doped Ni-MOF Nanosheet Array for Highly Capacitive and Stable Asymmetric Supercapacitor.

In this study, we demonstrate that an Mn-doped ultrathin Ni-MOF nanosheet array on nickel foam (Mn0.1 -Ni-MOF/NF) serves as a highly capacitive and stable supercapacitor positive electrode. The Mn0.1 -Ni-MOF/NF shows an areal capacity of 6.48 C cm-2 (specific capacity C: 1178 C g-1 ) at 2 mA cm-2 in 6.0 m KOH, outperforming most reported MOF-based materials. More importantly, it possesses excellent cycle stability to maintain 80.6 % capacity after 5000 cycles. An asymmetric supercapacitor device utilizing Mn0.1 -Ni-MOF/NF as the positive electrode and activated carbon as the negative electrode attains a high energy density of 39.6 Wh kg-1 at 143.8 Wkg-1 power density with a capacitance retention of 83.6 % after 5000 cycles.

Lactobacillus gasseri JM1 with potential probiotic characteristics alleviates inflammatory response by activating the PI3K/Akt signaling pathway in vitro.

Lactobacillus gasseri JM1, a novel strain isolated from infant feces, exhibited common probiotic properties such as high acid tolerance, bile salt tolerance, and adhesion to epithelial Caco-2 cells, suggesting its ability to survive in the gastrointestinal tract and confer potential probiotic action on the host. In the current study, we aimed to evaluate the immunomodulatory activity of L. gasseri JM1 and explore the underlying signaling pathways in vitro. The results showed that pretreatment with L. gasseri JM1 alleviated lipopolysaccharide-induced inflammatory response, as evidenced by downregulation of genes encoding proinflammatory cytokines [IL1B, IL6, IL8, and tumor necrosis factor-α (TNFA)] and upregulation of genes encoding anti-inflammatory cytokines [IL4, IL10, transforming growth factor-ß3 (TGFB3), and IFNG]. A high level of gene expression was noted for toll-like receptor 2 and NOD-like receptor 2. Meanwhile, transcriptomic sequencing obtained 84 differentially expressed genes. Kyoto Encyclopedia of Genes and Genomes analysis revealed the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway was activated by L. gasseri JM1 in Caco-2 cells. Inhibitor of PI3K/Akt played various roles in the release of cytokines, indicating that the pathway was involved in protecting the host against lipopolysaccharide stress. Moreover, whole-genome sequencing revealed fundamental genetic properties of L. gasseri JM1 and provided clues for probiotic characteristics. In summary, the strain could exert immunomodulatory effects via the toll-like receptor 2 and NOD2-mediated PI3K/Akt signaling pathway and be regarded as a potential probiotic.

Hepatoprotective effects of kombucha tea: identification of functional strains and quantification of functional components.

BACKGROUND: Kombucha tea (KT), a traditional health beverage containing potential hepatoprotective agents, is fermented from sugared tea by a symbiotic culture of yeast and bacteria for 8 days. However, the functional strains that produce components for the hepatoprotective property of KT remain unclear. Multiple strains are involved in traditional KT production. Therefore, KT has not been standardized or produced commercially. This study aimed to identify the functional strains and quantify the functional components with hepatoprotective effects in kombucha tea. RESULTS: Gluconacetobacter sp. A4 was one of the microorganisms in KT in which the D-saccharic acid-1,4-lactone (DSL) produced by G. sp. A4 was significantly higher than that produced by original tea fungus at 8 days of fermentation. Traditional KT (TKT, tea broth fermented by mixed tea fungus), modified KT (MKT, fermented by single G. sp. A4), and DSL significantly inhibited the acetaminophen-induced increase of alanine aminotransferase, alkaline phosphatase, triglyceride and malondialdehyde, as well as facilitating the reduction of total antioxidant capacity in mice. Furthermore, MKT and TKT are both similar to DSL in terms of protection against acetaminophen-induced liver injury in mice. These results suggested a positive relationship between DSL content and the hepatoprotective effect of TKT, MKT and DSL groups. CONCLUSION: G. sp. A4 was concluded to be a potential functional strain and DSL might be the key functional component for the hepatoprotective property in KT. The stronger capability of G. sp. A4 in producing DSL makes it a better choice for the commercial production of KT.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.