Inhibitory Effects of Myriocin on Non-Enzymatic Glycation of Bovine Serum Albumin

Advanced glycation end products (AGEs) are the compounds produced by non-enzymatic glycation of proteins, which are involved in diabetic-related complications. To investigate the potential anti-glycation activity of Myriocin (Myr), a fungal metabolite of Cordyceps, the effect of Myr on the formation of AGEs resulted from the glycation of bovine serum albumin (BSA) and the interaction between Myr and BSA were studied by multiple spectroscopic techniques and computational simulations. We found that Myr inhibited the formation of AGEs at the end stage of glycation reaction and exhibited strong anti-fibrillation activity. Spectroscopic analysis revealed that Myr quenched the fluorescence of BSA in a static process, with the possible formation of a complex (approximate molar ratio of 1:1). The binding between BSA and Myr mainly depended on van der Waals interaction, hydrophobic interactions and hydrogen bond. The synchronous fluorescence and UV-visible (UV-vis) spectra results indicated that the conformation of BSA altered in the presence of Myr. The fluorescent probe displacement experiments and molecular docking suggested that Myr primarily bound to binding site 1 (subdomain IIA) of BSA. These findings demonstrate that Myr is a potential anti-glycation agent and provide a theoretical basis for the further functional research of Myr in the prevention and treatment of AGEs-related diseases.     

High-Throughput Preparation and Machine Learning Screening of a Blue-Phase Liquid Crystal Based on Inkjet Printing

Blue-phase liquid crystal (BPLC) is considered as the next-generation liquid crystal display material, but its practical application is seriously affected by a narrow temperature range and a long research period. In this paper, we used inkjet printing technology to prepare BPLC materials with high throughput, and try to use machine vision technology to test BPLC with high throughput. The “standard curve method” for establishing each printing channel and the “vector matching method” for searching the chromaticity value of the minimum distance were proposed to improve the accuracy of inkjet printing BPLC materials. For a large number of sample-phase images, we propose a machine learning method to identify the liquid crystal phase. In this paper, for the first time, the high-throughput preparation and high-throughput detection of 1080 BPLC samples with five common components by a comprehensive experimental method has been successfully realized. The results are helpful to improve the research efficiency of blue-phase materials and provide a theoretical basis and practical guidance for rapid screening of multi-component BPLC materials.     

DAD-Net: Classification of Alzheimer’s Disease Using ADASYN Oversampling Technique and Optimized Neural Network

Alzheimer’s Disease (AD) is a neurological brain disorder that causes dementia and neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a kind of Artificial Intelligence (AI), has paved the way for new AD detection and automation methods. The DL model’s prediction accuracy depends on the dataset’s size. The DL models lose their accuracy when the dataset has an imbalanced class problem. This study aims to use the deep Convolutional Neural Network (CNN) to develop a reliable and efficient method for identifying Alzheimer’s disease using MRI. In this study, we offer a new CNN architecture for diagnosing Alzheimer’s disease with a modest number of parameters, making it perfect for training a smaller dataset. This proposed model correctly separates the early stages of Alzheimer’s disease and displays class activation patterns on the brain as a heat map. The proposed Detection of Alzheimer’s Disease Network (DAD-Net) is developed from scratch to correctly classify the phases of Alzheimer’s disease while reducing parameters and computation costs. The Kaggle MRI image dataset has a severe problem with class imbalance. Therefore, we used a synthetic oversampling technique to distribute the image throughout the classes and avoid the problem. Precision, recall, F1-score, Area Under the Curve (AUC), and loss are all used to compare the proposed DAD-Net against DEMENET and CNN Model. For accuracy, AUC, F1-score, precision, and recall, the DAD-Net achieved the following values for evaluation metrics: 99.22%, 99.91%, 99.19%, 99.30%, and 99.14%, respectively. The presented DAD-Net outperforms other state-of-the-art models in all evaluation metrics, according to the simulation results.     

Tannin-Derived Hard Carbon for Stable Lithium-Ion Anode

Graphite anodes are well established for commercial use in lithium-ion battery systems. However, the limited capacity of graphite limits the further development of lithium-ion batteries. Hard carbon obtained from biomass is a highly promising anode material, with the advantage of enriched microcrystalline structure characteristics for better lithium storage. Tannin, a secondary product of metabolism during plant growth, has a rich source on earth. But the mechanism of hard carbon obtained from its derivation in lithium-ion batteries has been little studied. This paper successfully applied the hard carbon obtained from tannin as anode and illustrated the relationship between its structure and lithium storage performance. Meanwhile, to further enhance the performance, graphene oxide is skillfully compounded. The contact with the electrolyte and the charge transfer capability are effectively enhanced, then the capacity of PVP-HC is 255.5 mAh g⁻¹ after 200 cycles at a current density of 400 mA g⁻¹, with a capacity retention rate of 91.25%. The present work lays the foundation and opens up ideas for the application of biomass-derived hard carbon in lithium anodes.     

Selective Conversion of Glycerol to Methanol over CaO-Modified HZSM-5 Zeolite

Biodiesel is generally produced from vegetable oils and methanol, which also generates glycerol as byproduct. To improve the overall economic performance of the process, the selective formation of methanol from glycerol is important in biodiesel production. In the present study, a CaO modified HZSM-5 zeolite was prepared by an impregnation method and used for the conversion of glycerol to methanol. We found that the 10%CaO/HZSM-5 with Si/Al ratio of 38 exhibited highest selectivity to methanol of 70%, with a glycerol conversion of 100% under 340 ℃ and atmospheric pressure. The characterization results showed that the introduction of a small amount of CaO into the HZSM-5 did not affect the structure of zeolite. The incorporation of HZSM-5 as an acidic catalyst and CaO as a basic catalyst in a synergistic catalysis system led to higher conversion of glycerol and selectivity of methanol.     

Radical-Induced Cascade Annulation/Hydrocarbonylation for Construction of 2-Aryl-4H-chromen-4-ones

A robust metal- and solvent-free cascade radical-induced C-N cleavage/intramolecular 6-endo-dig annulation/hydrocarbonylation for the synthesis of the valuable 2-aryl-4H-chromen-4-ones is described. This practical synthesis strategy utilizes propargylamines and air as the oxygen source and green carbonylation reagent, in which propargylamines are activated by the inexpensive and available dimethyl 2,2′-azobis(2-methylpropionate) (AIBME) and (PhSe)₂ as the radical initiators. This simple and green protocol features wide substrate adaptability, good functional group tolerance, and amenability to scaling up and derivatizations.     

Oxidative Desulfurization Activity of NIT Nitroxide Radical Modified Metallophthalocyanine

In the present study, metallophthalocyanines were modified with NIT nitroxide radicals through chemical bonds to prepare a series of metallophthalocyanines–NIT catalysts (MPcTcCl₈-NIT, M=Mn²⁺, Fe²⁺, Co²⁺, Ni²⁺, Cu²⁺ and Zn²⁺) applied for oxidative desulfurization of thiophene (T) in model fuel. The MPcTcCl₈-NIT catalysts were characterized by FTIR, UV-Vis, ESR, and XPS spectra. The oxidative desulfurization activity of MPcTcCl₈-NIT catalysts was studied in a biomimetic catalytic system using molecular O₂ as the oxidant. The MPcTcCl₈-NIT catalysts exhibited high catalytic activities for the oxidation of thiophene in model fuel. The desulfurization rate of ZnPcTcCl₈-NIT for thiophene reached to 99.61%, which was 20.53% higher than that of pure ZnPcTcCl₈ (79.08%) under room temperature and natural light. The results demonstrated that MPcTcCl₈-NIT catalysts could achieve more effective desulfurization rate under milder conditions than that of the metallophthalocyanines. The NIT nitroxide radicals also could improve the catalytic activity of metallophthalocyanine based on the synergistic oxidation effect. The stability experiments for ZnPcTcCl₈-NIT showed that the catalyst still had a high desulfurization rate of 92.37% after five times recycling. All these findings indicate that the application of MPcTcCl₈-NIT catalysts provides a potential new way for the desulfurization performance of thiophene in fuel.     

Concurrent Determination of Tigecycline,Tetracyclines and Their 4-Epimer Derivatives in Chicken Muscle Isolated from a Reversed-Phase Chromatography System Using Tandem Mass Spectrometry

A quantitative and qualitative method using a high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) detection approach was developed and validated for the analysis of tigecycline, four tetracyclines and their three 4-epimer derivatives in chicken muscle. Samples were extracted repeatedly with 0.1 mol/L Na₂EDTA–McIlvaine buffer solution. After vortexing, centrifugation, solid-phase extraction, evaporation and reconstitution, the aliquots were separated using a C8 reversed-phase column (50 mm × 2.1 mm, 5 µm) with a binary solvent system consisting of methanol and 0.01 mol/L trichloroacetic acid aqueous solution. The typical validation parameters were evaluated in accordance with the acceptance criteria detailed in the guidelines of the EU Commission Decision 2002/657/EC and the U.S. Food and Drug Administration Bioanalytical Method Validation 05/24/18. The matrix-matched calibration curve was linear over the concentration range from the limit of quantitation (LOQ) to 400 μg/kg for doxycycline, and the calibration graphs for tetracycline, chlortetracycline, oxytetracycline, their 4-epimer derivatives and tigecycline showed a good linear relationship within the concentration range from the LOQ to 200 μg/kg. The limits of detection (LODs) for the eight targets were in the range of 0.06 to 0.09 μg/kg, and the recoveries from the fortified blank samples were in the range of 89% to 98%. The within-run precision and between-run precision, which were expressed as the relative standard deviations, were less than 5.0% and 6.9%, respectively. The applicability was successfully demonstrated through the determination of residues in 72 commercial chicken samples purchased from different sources. This approach provides a novel option for the detection of residues in animal-derived food safety monitoring.     

Cold Sintering of Li6.4La3Zr1.4Ta0.6O12/PEO Composite Solid Electrolytes

Ceramic/polymer composite solid electrolytes integrate the high ionic conductivity of in ceramics and the flexibility of organic polymers. In practice, ceramic/polymer composite solid electrolytes are generally made into thin films rather than sintered into bulk due to processing temperature limitations. In this work, Li_6.4La₃Zr_1.4Ta_0.6O₁₂ (LLZTO)/polyethylene-oxide (PEO) electrolyte containing bis(trifluoromethanesulfonyl)imide (LiTFSI) as the lithium salt was successfully fabricated into bulk pellets via the cold sintering process (CSP). Using CSP, above 80% dense composite electrolyte pellets were obtained, and a high Li-ion conductivity of 2.4 × 10⁻⁴ S cm^–1 was achieved at room temperature. This work focuses on the conductivity contributions and microstructural development within the CSP process of composite solid electrolytes. Cold sintering provides an approach for bridging the gap in processing temperatures of ceramics and polymers, thereby enabling high-performance composites for electrochemical systems.     

Probe-Integrated Label-Free Electrochemical Immunosensor Based on Binary Nanocarbon Composites for Detection of CA19-9

Convenient and sensitive detection of tumor biomarkers is crucial for the early diagnosis and treatment of cancer. Herein, we present a probe-integrated and label-free electrochemical immunosensor based on binary nanocarbon composites and surface-immobilized methylene blue (MB) redox probes for detection of carbohydrate antigen 199 (CA19-9), which is closely associated with gastric malignancies. Nanocarbon composites consisting of electrochemically reduced graphene oxides and carbon nanotubes (ErGO-CNT) are electrodeposited onto an indium tin oxide (ITO) electrode surface to form a 3D nanocomposite film, which could provide high surface area to immobilize abundant MB probes, facilitate the electron transfer of MB, and therefore, improve sensitivity. Polydopamine (PDA) served as a bifunctional linker is able to immobilize anti-CA19-9 antibodies and stabilize the inner probe, conferring the sensing interface with specific recognition capacity. Electrochemical detection of CA19-9 is achieved based on the decrease of the redox signal of MB after specific binding of CA19-9 with a wide linear range of 0.1 mU/mL to 100 U/mL and a limit of detection (LOD) of 0.54 nU/mL (S/N = 3). The constructed electrochemical immunosensor has good selectivity, repeatability, reproducibility, and stability. Furthermore, determination of CA19-9 in human serum samples is also realized.