Gaussian mixture model-based target feature extraction and visualization

Journal of Visualization - Effective extraction and visualization of complex target features from volume data are an important task, which allows the user to analyze and get insights of the complex...     

Local Intrinsic Dimensionality,Entropy and Statistical Divergences

Properties of data distributions can be assessed at both global and local scales. At a highly localized scale, a fundamental measure is the local intrinsic dimensionality (LID), which assesses growth rates of the cumulative distribution function within a restricted neighborhood and characterizes properties of the geometry of a local neighborhood. In this paper, we explore the connection of LID to other well known measures for complexity assessment and comparison, namely, entropy and statistical distances or divergences. In an asymptotic context, we develop analytical new expressions for these quantities in terms of LID. This reveals the fundamental nature of LID as a building block for characterizing and comparing data distributions, opening the door to new methods for distributional analysis at a local scale.     

Design and Embedded Implementation of Secure Image Encryption Scheme Using DWT and 2D-LASM

In order to further improve the information effectiveness of digital image transmission, an image-encryption algorithm based on 2D-Logistic-adjusted-Sine map (2D-LASM) and Discrete Wavelet Transform (DWT) is proposed. First, a dynamic key with plaintext correlation is generated using Message-Digest Algorithm 5 (MD5), and 2D-LASM chaos is generated based on the key to obtain a chaotic pseudo-random sequence. Secondly, we perform DWT on the plaintext image to map the image from the time domain to the frequency domain and decompose the low-frequency (LF) coefficient and high-frequency (HF) coefficient. Then, the chaotic sequence is used to encrypt the LF coefficient with the structure of “confusion-permutation”. We perform the permutation operation on HF coefficient, and we reconstruct the image of the processed LF coefficient and HF coefficient to obtain the frequency-domain ciphertext image. Finally, the ciphertext is dynamically diffused using the chaotic sequence to obtain the final ciphertext. Theoretical analysis and simulation experiments show that the algorithm has a large key space and can effectively resist various attacks. Compared with the spatial-domain algorithms, this algorithm has great advantages in terms of computational complexity, security performance, and encryption efficiency. At the same time, it provides better concealment of the encrypted image while ensuring the encryption efficiency compared to existing frequency-domain methods. The successful implementation on the embedded device in the optical network environment verifies the experimental feasibility of this algorithm in the new network application.     

Detecting the Critical States of Type 2 Diabetes Mellitus Based on Degree Matrix Network Entropy by Cross-Tissue Analysis

Type 2 diabetes mellitus (T2DM) is a metabolic disease caused by multiple etiologies, the development of which can be divided into three states: normal state, critical state/pre-disease state, and disease state. To avoid irreversible development, it is important to detect the early warning signals before the onset of T2DM. However, detecting critical states of complex diseases based on high-throughput and strongly noisy data remains a challenging task. In this study, we developed a new method, i.e., degree matrix network entropy (DMNE), to detect the critical states of T2DM based on a sample-specific network (SSN). By applying the method to the datasets of three different tissues for experiments involving T2DM in rats, the critical states were detected, and the dynamic network biomarkers (DNBs) were successfully identified. Specifically, for liver and muscle, the critical transitions occur at 4 and 16 weeks. For adipose, the critical transition is at 8 weeks. In addition, we found some “dark genes” that did not exhibit differential expression but displayed sensitivity in terms of their DMNE score, which is closely related to the progression of T2DM. The information uncovered in our study not only provides further evidence regarding the molecular mechanisms of T2DM but may also assist in the development of strategies to prevent this disease.     

Identification of Protosappanoside D from Caesalpinia decapetala and Evaluation of Its Pharmacokinetic,Metabolism and Pharmacological Activity

Protosappanoside D (PTD) is a new component isolated from the extract of Caesalpinia decapetala for the first time. Its structure was identified as protosappanin B-3-O-β-D-glucoside by ¹H-NMR, ¹³C-NMR, 2D-NMR and MS techniques. To date, the pharmacological activities, metabolism or pharmacokinetics of PTD has not been reported. Therefore, this research to study the anti-inflammatory activity of PTD was investigated via the LPS-induced RAW264.7 cells model. At the same time, we also used the UHPLC/Q Exactive Plus MS and UPLC-MS/MS methods to study the metabolites and pharmacokinetics of PTD, to calculate its bioavailability for the first time. The results showed that PTD could downregulate secretion of the pro-inflammatory cytokines. In the metabolic study, four metabolites were identified, and the primary degradative pathways in vivo involved the desaturation, oxidation, methylation, alkylation, dehydration, degradation and desugarization. In the pharmacokinetic study, PTD and its main metabolite protosappanin B (PTB) were measured after oral and intravenous administration. After oral administration of PTD, its T_max was 0.49 h, t_1/2z and MRT_(0–t) were 3.47 ± 0.78 h and 3.06 ± 0.63 h, respectively. It shows that PTD was quickly absorbed into plasma and it may be eliminated quickly in the body, and its bioavailability is about 0.65%.     

Biosensors Based on Ion-Sensitive Field-Effect Transistors for HLA and MICA Antibody Detection in Kidney Transplantation

This work demonstrates the ability of the Ion-Sensitive Field-Effect Transistor (ISFET)-based immunosensor to detect antibodies against the human leukocyte antigen (HLA) and the major histocompatibility complex class-I-related chain A (MICA). The sensing membrane of the ISFET devices was modified and functionalized using an APTES-GA strategy. Surface properties, including wettability, surface thickness, and surface topology, were assessed in each module of the modification process. The optimal concentrations of HLA and MICA proteins for the immobilization were 10 and 50 μg/mL. The dose-response curve showed a detection range of 1.98–40 µg/mL for anti-HLA and 5.17–40 µg/mL for anti-MICA. The analytical precision (%CV) was found to be 10.69% and 8.92% for anti-HLA and -MICA, respectively. Moreover, the electrical signal obtained from the irrelevant antibody was considerably different from that of the specific antibodies, indicating the specific binding of the relevant antibodies without noise interference. The sensitivity and specificity in the experimental setting were established for both antibodies (anti-HLA: sensitivity = 80.00%, specificity = 86.36%; anti-MICA: sensitivity = 86.67%, specificity = 88.89%). Our data reveal the potential of applying the ISFET-based immunosensor to the detection of relevant anti-HLA and -MICA antibodies, especially in the field of kidney transplantation.     

Antioxidant and Biological Activities of the Lotus Root Polysaccharide-Iron (III) Complex

In this study, the synthesis parameters of the lotus root polysaccharide iron complex (LRPF) were determined and optimized by response surface methodology. Under the optimum preparation conditions, the pH of the solution was 9, the ratio of M (trisodium citrate): m (lotus root polysaccharide) was 0.45, the reaction time was 3 h. UV spectroscopy, thermogravimetry, FT-IR spectroscopy, X-ray diffraction, CD, and NMR were used for the characterization of the LRPF. LRPF has good stability and easily releases iron ions under artificial gastrointestinal conditions. LRPF exhibited antioxidant activity in vitro and can significantly improve the antioxidant activity in vivo. In addition, LRPF has a good effect in the treatment of iron deficiency anemia in model mice, impacts the gut microbiome, and reduces the iron deficiency-induced perniciousness by regulating steroid hormone biosynthesis. Therefore, LRPF can be used as a nutritional supplement to treat and prevent iron-deficiency anemia and improve human immunity.     

The Biosynthesis Related Enzyme,Structure Diversity and Bioactivity Abundance of Indole-Diterpenes: A Review

Indole diterpenes are a large class of secondary metabolites produced by fungi, possessing a cyclic diterpenoid backbone and an indole moiety. Novel structures and important biological activity have made indole diterpenes one of the focuses of synthetic chemists. Although the discovery, identification, structural diversity, biological activity and especially structure–activity relationship of indole diterpenes have been reported in some papers in recent years, they are absent of a systematic and comprehensive analysis, and there is no elucidation of enzymes related to this kind of natural product. Therefore, it is necessary to summarize the relevant reports to provide new perspectives for the following research. In this review, for the first time, the function of related synthases and the structure–activity relationship of indole diterpenes are expounded, and the recent research advances of them are emphasized.     

Lanostane Triterpenoids and Ergostane Steroids from Ganoderma luteomarginatum and Their Cytotoxicity

Macrofungus Ganoderma luteomarginatum is one of the main species of Ganoderma fungi distributed in Hainan province of China, the fruiting bodies of which have been widely used in folk as a healthy food to prevent tumors. To explore the potential cytotoxic constituents from G. luteomarginatum, the phytochemical investigation on the ethyl acetate soluble fraction of 95% ethanolic extract from the fruiting bodies of this fungus led to the isolation of twenty-six lanostane triterpenoids (1–26), including three undescribed ones (1–3), together with eight ergostane steroids (27–34). The structures of three new lanostane triterpenoids were elucidated as lanosta-7,9(11)-dien-3β-acetyloxy-24,25-diol (1), lanosta-7,9(11)-dien-3-oxo-24,26-diol-25-methoxy (2), and lanosta-8,20(22)-dien-3,11,23-trioxo-7β,15β-diol-26-oic acid methyl ester (3) by the analysis of 1D, 2D NMR, and HRESIMS spectroscopic data. All isolates were assayed for their cytotoxic activities using three human cancer cell lines (K562, BEL-7402, and SGC-7901) and seven lanostane triterpenoids (1, 2, 7, 13, 18, 22, and 24), and one ergostane steroid (34) showed definite cytotoxicity with IC₅₀ values that ranged from 6.64 to 47.63 μg/mL. Among these cytotoxic lanostane triterpenoids, compounds 2 and 13 showed general cytotoxicity against three human cancer cell lines, while compounds 1 and 18 exhibited significant selective cytotoxicity against K562 cells with IC₅₀ values of 8.59 and 8.82 μg/mL, respectively. Furthermore, the preliminary structure–cytotoxicity relationships was proposed.     

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.