Construction of Bicyclo[2.2.2]diazaoctane Scaffolds via Intermolecular Diels-Alder: Synthesis of (±)-Brevianamide B and Progress Toward (+)-Serantrypinone

This thesis outlines investigations into utilizing an intermolecular Diels-Alder approach to access the bicyclo[2.2.2]diazaoctane motif in natural products. A stereodivergent synthesis of prenylated indole alkaloid scaffolds from a common diene precursor, and a revised synthetic strategy to (±)-brevianamide B was a result of improved understanding of regioselectivity and stereoselectivity of intermolecular [4+2] between pyrazinone-type dienes and fumarate and maleic anhydride type dienophiles. This observed selectivity was also exploited in the synthesis of (+) serantrypinone, as the key Diels-Alder reaction between a chiral-nonracemic diene and an isatin derived dienophile proceeded with endo preference and exclusive regioselectivity. Progress of downstream elaborations from the cycloadduct towards (+)-serantrypinone is also reported

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As a traditional Mongolian medicine, Sendeng-4 (SD) has been widely used to treat rheumatoid arthritis (RA) in Inner Mongolia and exhibits a good curative effect. Unfortunately, due to geographical factors, it is difficult to popularize this drug throughout the whole country, and the mechanism of action of SD has been unclear. In this study, a serum metabolite profile analysis was performed to identify potential biomarkers associated with adjuvant-induced RA and investigate the mechanism of action of SD. Ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was performed for the metabonomics analysis. K nearest neighbor (KNN) models were established in both positive and negative spectra for classifying data from the control, model, and SD administration groups. Accuracy rate for classification was 95.8% in positive ion mode and 91.7% in negative ion mode. Orthogonal partial least squares discriminant analysis (OPLS-DA) enabled the identification of 12 metabolites as potential biomarkers of adjuvant-induced RA. After treatment with SD, the levels of uridine triphosphate, calcitroic acid, dynorphin B (6-9), and docosahexaenoic acid were restored to normal, indicating that SD likely ameliorated RA by regulating the levels of these biomarkers. This study identified early biomarkers of RA and elucidated the underlying mechanism of action of SD, which is worth further investigation for development as a clinical therapy

Analyzing the Therapeutic Mechanism of Mongolian Medicine Zhonglun-5 in Rheumatoid Arthritis Using a Bagging Algorithm with Serum Metabonomics

Rheumatoid arthritis (RA) is a complex autoimmune disorder. Zhonglun-5 (ZL), a traditional Mongolian medicine, exhibits an excellent clinical effect on RA; however, its molecular mechanism remains unclear. In this study, rat serum metabolomic analysis was performed to identify potential biomarkers for RA and investigate its treatment mechanism. A Dionex Ultimate 3000 ultrahigh-performance liquid chromatography system coupled with a Q-Exactive Focus Orbitrap mass spectrometer was used for metabonomics analysis. Bootstrap aggregation (bagging) classification algorithm was applied to process data from control (CG), model (MG), and treatment administration groups. The classification accuracy was 100.00% (6/6) in the decision tree model and 83.33% (5/6) in the K-nearest neighbor (KNN) model, accompanied by 18 training samples and 6 testing samples. Using volcanic map analysis, 24 biomarkers were identified between CG and MG, including those related to glycosphingolipid biosynthesis, arachidonic acid, fatty acids, amino acids, bile acids, vitamins, and sphingolipids. A set diagram of the heatmap and drug-biomarker network of potential biomarkers was constructed. After ZL administration, the levels of these biomarkers returned to normal, indicating that ZL had a therapeutic effect in rats with RA. This study established a solid theoretical foundation to promote further research on the clinical applicability of ZL

A High Dynamic Weak Spread Spectrum Signal Acquisition Strategy Based on Iterative Local Search

To solve the acquisition problem of the satellite-ground microwave link ranging of the China Space Station, iterative local search (ILS) is proposed. In this paper, an iterative-local-search-based acquisition strategy is presented, and a Doppler frequency and code phase transfer model is designed, which can accomplish acquisition by multiple rounds of two-dimensional search. The adaptability of the ILS improved traditional acquisition algorithm to a high dynamic and low signal-to-noise ratio (SNR) environment can be significantly improved without relying on prior information. For the classical parallel code phase acquisition algorithm, the performance of the ILS acquisition strategy was experimentally evaluated for high dynamic weak signals, and the results demonstrated the superiority of the proposed strategy. The computational complexity of the ILS improved parallel code phase acquisition algorithm was greatly reduced. The sensitivity of the parallel code phase acquisition algorithm improved by the ILS strategy to the acquisition of weak signals in a dynamic environment was significantly improved

Diagnosis of Breast Hyperplasia and Evaluation of RuXian-I Based on Metabolomics Deep Belief Networks

Breast cancer is estimated to be the leading cancer type among new cases in American women. Core biopsy data have shown a close association between breast hyperplasia and breast cancer. The early diagnosis and treatment of breast hyperplasia are extremely important to prevent breast cancer. The Mongolian medicine RuXian-I is a traditional drug that has achieved a high level of efficacy and a low incidence of side effects in its clinical use. However, for detecting the efficacy of RuXian-I, a rapid and accurate evaluation method based on metabolomic data is still lacking. Therefore, we proposed a framework, named the metabolomics deep belief network (MDBN), to analyze breast hyperplasia metabolomic data. We obtained 168 samples of metabolomic data from an animal model experiment of RuXian-I, which were averaged from control groups, treatment groups, and model groups. In the process of training, unlabelled data were used to pretrain the Deep Belief Networks models, and then labelled data were used to complete fine-tuning based on a limited-memory Broyden Fletcher Goldfarb Shanno (L-BFGS) algorithm. To prevent overfitting, a dropout method was added to the pretraining and fine-tuning procedures. The experimental results showed that the proposed model is superior to other classical classification methods that are based on positive and negative spectra data. Further, the proposed model can be used as an extension of the classification method for metabolomic data. For the high accuracy of classification of the three groups, the model indicates obvious differences and boundaries between the three groups. It can be inferred that the animal model of RuXian-I is well established, which can lay a foundation for subsequent related experiments. This also shows that metabolomic data can be used as a means to verify the effectiveness of RuXian-I in the treatment of breast hyperplasia

A multifunctional ‘golden cicada’ nanoplatform breaks the thermoresistance barrier to launch cascade augmented synergistic effects of photothermal/gene therapy

Abstract Background Photothermal therapy (PTT) is taken as a promising strategy for cancer therapy, however, its applicability is hampered by cellular thermoresistance of heat shock response and insufficient accumulation of photothermal transduction agents in the tumor region. In consideration of those limitations, a multifunctional “Golden Cicada” nanoplatform (MGCN) with efficient gene delivery ability and excellent photothermal effects is constructed, overcoming the thermoresistance of tumor cells and improving the accumulation of indocyanine green (ICG). Results Down-regulation of heat shock protein 70 (HSP70) makes tumor cells more susceptible to PTT, and a better therapeutic effect is achieved through such cascade augmented synergistic effects. MGCN has attractive features with prolonged circulation in blood, dual-targeting capability of CD44 and sialic acid (SA) receptors, and agile responsiveness of enzyme achieving size and charge double-variable transformation. It proves that, on the one hand, MGCN performs excellent capability for HSP70-shRNA delivery, resulting in breaking the cellular thermoresistance mechanism, on the other hand, ICG enriches in tumor site specifically and possesses a great thermal property to promoted PTT. Conclusions In short, MGCN breaks the protective mechanism of cellular heat stress response by downregulating the expression of HSP70 proteins and significantly augments synergistic effects of photothermal/gene therapy via cascade augmented synergistic effects

Further Investigation of the Intermolecular Diels–Alder Cycloaddition for the Synthesis of Bicyclo[2.2.2]diazaoctane Alkaloids

The convergent synthesis of bicyclo[2.2.2]­diazaoctane structures using an intermolecular Diels–Alder cycloaddition between a pyrazinone and commercially available fumarate or maleate precursors is reported. High reactivity and stereoselection is observed with both dienophile substrates. Structure validation was achieved by conversion of cycloadducts into known [2.2.2]­diazabicyclic compounds or into crystalline derivatives suitable for X-ray analysis. The cycloadduct derived from reaction of pyrazinone and maleic anhydride underwent selective anhydride ring opening and intersected an established precursor in the synthesis of brevianamide B