Associations between complexity of glucose time series and cognitive function in adults with type 2 diabetes.

AIMS: To characterize the comparative contributions of different glycaemic indicators to cognitive dysfunction, and further investigate the associations between the most significant indicator and cognitive function, along with related cerebral alterations. MATERIALS AND METHODS: We performed a cross-sectional study in 449 subjects with type 2 diabetes who completed continuous glucose monitoring and cognitive assessments. Of these, 139 underwent functional magnetic resonance imaging to evaluate cerebral structure and olfactory neural circuit alterations. Relative weight and Sobol's sensitivity analyses were employed to characterize the comparative contributions of different glycaemic indicators to cognitive dysfunction. RESULTS: Complexity of glucose time series index (CGI) was found to have a more pronounced association with mild cognitive impairment (MCI) compared to glycated haemoglobin, time in range, and standard deviation. The proportion and multivariable-adjusted odds ratios (ORs) for MCI increased with descending CGI tertile (Tertile 1: reference group [≥4.0]; Tertile 2 [3.6-4.0] OR 1.23, 95% confidence interval [CI] 0.68-2.24; Tertile 3 [<3.6] OR 2.27, 95% CI 1.29-4.00). Decreased CGI was associated with cognitive decline in executive function and attention. Furthermore, individuals with decreased CGI displayed reduced olfactory activation in the left orbitofrontal cortex (OFC) and disrupted functional connectivity between the left OFC and right posterior cingulate gyrus. Mediation analysis demonstrated that the left OFC activation partially mediated the associations between CGI and executive function. CONCLUSION: Decreased glucose complexity closely relates to cognitive dysfunction and olfactory brain activation abnormalities in diabetes.

Altered brain spontaneous and synchronization activity in latent autoimmune diabetes in adults: A resting-state functional MRI study.

AIMS: This study aimed to explore the clinical features and spontaneous brain activity among patients with latent autoimmune diabetes in adults (LADA) and to investigate the relationship among these characteristics. METHODS: We conducted a cross-sectional study using cognitive assessments and resting-state functional magnetic resonance imaging (rs-fMRI) to evaluate the cognitive function and brain activities of healthy controls (HCs) and patients with LADA. Functional connectivity (FC) analysis was performed on the brain regions that showed significantly different activation in regional homogeneity (ReHo) analysis between the two groups. Furthermore, a linear regression model was conducted for the association between metabolism and cognition. RESULTS: This study enrolled patients with LADA (and age-, sex-, and education-matched HCs). Patients with LADA had worse cognitive status at the general level and poorer memory than controls. Rs-fMRI analysis among patients with LADA showed decreased ReHo values in the right occipital lobe and temporal lobe and decreased seed-based FC in the right parietal lobe compared to those of controls. The seed-based FC values in the right parietal lobe were positively associated with word fluency and processing speed in patients with LADA. Furthermore, low-density lipoprotein cholesterol was negatively correlated with Montreal Cognitive Assessment scores in patients with LADA. CONCLUSIONS: Patients with LADA had worse cognitive function and decreased spontaneous brain activity in the temporal lobe and occipital lobe compared to controls. Moreover, glycolipid metabolism was closely related to brain structure and function in patients with LADA.

Second-Order Side-Channel Analysis Based on Orthogonal Transform Nonlinear Regression.

In recent years, side-channel analysis technology has been one of the greatest threats to information security. SCA decrypts the key information in the encryption device by establishing an appropriate leakage model. As one of many leakage models, the XOR operation leakage proposed by linear regression has typical representative significance in side-channel analysis. However, linear regression may have the problem of irreversibility of a singular matrix in the modeling stage of template analysis and the problem of poor data fit in the template analysis after the cryptographic algorithm is masked. Therefore, this paper proposes a second-order template analysis method based on orthogonal transformation nonlinear regression. The irreversibility of a singular matrix and the inaccuracy of the model are solved by orthogonal transformation and adding a negative direction to the calculation of the regression coefficient matrix. In order to verify the data fitting effect of the constructed template, a comparative experiment of template analysis based on regression, Gaussian, and clustering was carried out on SAKURA-G. The experimental results show that the second-order template analysis based on orthogonal transformation nonlinear regression can complete key recovery without sacrificing the performance of regression estimation. Under the condition of high noise and high order template analysis, the established template has good universality.

An Image Encryption Transmission Scheme Based on a Polynomial Chaotic Map.

Most existing chaotic systems have many drawbacks in engineering applications, such as the discontinuous range of chaotic parameters, weak chaotic properties, uneven chaotic sequence outputs, and dynamic degradation. Therefore, based on the above, this paper proposes a new method for the design of a three-dimensional chaotic map. One can obtain the desired number of positive Lyapunov exponents, and can also obtain the desired value of positive Lyapunov exponents. Simulation results show that the proposed system has complex chaotic behavior and high complexity. Finally, the method is implemented into an image encryption transmission scheme and experimental results show that the proposed image encryption scheme can resist brute force attacks, correlation attacks, and differential attacks, so it has a higher security.

Study of Generalized Chaotic Synchronization Method Incorporating Error-Feedback Coefficients.

In this paper, taking the generalized synchronization problem of discrete chaotic systems as a starting point, a generalized synchronization method incorporating error-feedback coefficients into the controller based on the generalized chaos synchronization theory and stability theorem for nonlinear systems is proposed. Two discrete chaotic systems with different dimensions are constructed in this paper, the dynamics of the proposed systems are analyzed, and finally, the phase diagrams, Lyapunov exponent diagrams, and bifurcation diagrams of these are shown and described. The experimental results show that the design of the adaptive generalized synchronization system is achievable in cases in which the error-feedback coefficient satisfies certain conditions. Finally, a chaotic hiding image encryption transmission system based on a generalized synchronization approach is proposed, in which an error-feedback coefficient is introduced into the controller.

Upregulated miR-9-5p inhibits osteogenic differentiation of bone marrow mesenchymal stem cells under high glucose treatment.

INTRODUCTION: Diabetic osteoporosis (DOP) is a chronic diabetic complication, which is attributed to high glucose (HG)-induced dysfunction of bone marrow mesenchymal stem cells (BMSCs). Studies have revealed that microRNAs (miRNAs) play critical roles in osteogenic differentiation of BMSCs in DOP. Here, the role of miR-9-5p in DOP progression was explored. MATERIALS AND METHODS: The rat model of DOP was established by intraperitoneal injection of streptozotocin (STZ). BMSCs were treated with high glucose (HG) to establish in vitro models. Gene expression in BMSCs and bone tissues of rats was tested by RT-qPCR. The degree of osteogenic differentiation of BMSCs was examined by Alizarin Red staining and ALP activity analysis. The protein levels of collagen-I (COL1), osteocalcin (OCN), osteopontin (OPN), runt-related transcription factor-2 (RUNX2), and DEAD-Box Helicase 17 (DDX17) in BMSCs were evaluated by western blotting. The interaction between miR-9-5p and DDX17 was identified by luciferase reporter assay. H&E staining was used to test morphological structure of femurs of rats with STZ treatment. RESULTS: MiR-9-5p was overexpressed in HG-treated BMSCs, while DDX17 was downregulated. Functionally, miR-9-5p knockdown promoted BMSCs osteogenic differentiation under HG condition. Mechanically, miR-9-5p targeted DDX17. DDX17 knockdown reversed the effect of miR-9-5p silencing on osteogenic differentiation of HG-treated BMSCs. In in vivo studies, miR-9-5p downregulation ameliorated the DOP condition of rats and miR-9-5p expression was negatively correlated with DDX17 expression in bone tissues of rats with STZ treatment. CONCLUSION: MiR-9-5p knockdown promotes HG-induced osteogenic differentiation BMSCs in vitro and mitigates the DOP condition of rats in vivo by targeting DDX17.

MicroRNA-577 aggravates bone loss and bone remodeling by targeting thyroid stimulating hormone receptor in hyperthyroid-associated osteoporosis.

Traditionally, hyperthyroid-associated osteoporosis has been considered to be the result of increased thyroid hormone levels. The pathogenesis of hyperthyroid-associated osteoporosis remains unclear. Thyroid stimulating hormone receptor (TSHR) is closely associated with osteoporosis. Our study aimed to explore the role of TSHR and its upstream microRNA (miRNA) in hyperthyroid-associated osteoporosis. Bioinformatics analysis (starBase and Targetscan) and a wide range of experiments including reverse-transcription quantitative polymerase chain reaction, luciferase reporter, western blot analysis of osteogenic differentiation markers including OSX, OCN, ALP, OPN, and COL1, hematoxylin and eosin staining, Alizarin Red staining assays were used to explore the function and mechanism of TSHR in hyperthyroid-associated osteoporosis. First, we observed that TSHR was downregulated in bone marrow mesenchymal stem cells (BMSCs) isolated from rats after culture in osteogenic medium for 7 days. Functionally, overexpression of TSHR accelerates BMSC osteogenic differentiation. Mechanistically, we predicted four potential miRNAs for TSHR. MiR-577 was validated to bind with TSHR. Rescue assays showed that miR-577 overexpression inhibited BMSC osteogenic differentiation via targeting TSHR. In vivo experiments showed that miR-577 aggravated bone loss and bone remodeling and our data showed that it is achieved by targeting TSHR in hyperthyroid-associated osteoporosis. This finding may deep our understanding of the pathogenesis of hyperthyroid-associated osteoporosis.

Detection and Location of Multi-Period Phenomena in Chaotic Binary Sequences.

Due to the influence of finite calculation accuracy and binary quantization method, the performance of chaotic binary sequences has been degraded in varying degrees, and some sequences emerge as multi-period phenomena. Aiming at the problem that it is difficult to accurately detect this phenomenon, this paper proposes a multi-period positioning algorithm (MPPA), which can accurately detect and locate the accurate period and local period phenomena contained in chaotic binary sequences. In order to test the effectiveness and correctness of the algorithm, the multi-period characteristics of logistic binary sequences with different calculation accuracy are analyzed. MPPA evaluates the randomness of binary sequences from a new perspective, which provides a new idea for the analysis of cryptographic security of chaotic sequences.

Image Encryption Scheme Based on Mixed Chaotic Bernoulli Measurement Matrix Block Compressive Sensing.

Many image encryption schemes based on compressive sensing have poor reconstructed image quality when the compression ratio is low, as well as difficulty in hardware implementation. To address these problems, we propose an image encryption algorithm based on the mixed chaotic Bernoulli measurement matrix block compressive sensing. A new chaotic measurement matrix was designed using the Chebyshev map and logistic map; the image was compressed in blocks to obtain the measurement values. Still, using the Chebyshev map and logistic map to generate encrypted sequences, the measurement values were encrypted by no repetitive scrambling as well as a two-way diffusion algorithm based on GF(257) for the measurement value matrix. The security of the encryption system was further improved by generating the Secure Hash Algorithm-256 of the original image to calculate the initial values of the chaotic mappings for the encryption process. The scheme uses two one-dimensional maps and is easier to implement in hardware. Simulation and performance analysis showed that the proposed image compression-encryption scheme can improve the peak signal-to-noise ratio of the reconstructed image with a low compression ratio and has good encryption against various attacks.

A Novel Color Image Encryption Algorithm Based on 5-D Hyperchaotic System and DNA Sequence.

Nowadays, it is increasingly necessary to improve the encryption and secure transmission performance of images. Therefore, in this paper, a bit-level permutation algorithm based on hyper chaos is proposed, with a newly constructed 5-D hyperchaotic system combined with DNA sequence encryption to achieve bit-wide permutation of plaintexts. The proposed 5-D hyperchaotic system has good chaotic dynamics, combining hyperchaotic sequence with bit-level permutation to enhance the pseudo-randomness of the plaintext image. We adopt a scheme of decomposing the plaintext color image into three matrices of R, G, and B, and performing block operations on them. The block matrix was DNA encoded, operated, and decoded. The DNA operation was also determined by the hyperchaotic sequence, and finally generated a ciphertext image. The result of the various security analyses prove that the ciphertext images generated by the algorithm have good distribution characteristics, which can not only resist differential attacks, but also have the advantages of large cryptographic space.

Discrete-Time Memristor Model for Enhancing Chaotic Complexity and Application in Secure Communication.

The physical implementation of the continuous-time memristor makes it widely used in chaotic circuits, whereas the discrete-time memristor has not received much attention. In this paper, the backward-Euler method is used to discretize the TiO2 memristor model, and the discretized model also meets the three fingerprints characteristics of the generalized memristor. The short period phenomenon and uneven output distribution of one-dimensional chaotic systems affect their applications in some fields, so it is necessary to improve the dynamic characteristics of one-dimensional chaotic systems. In this paper, a two-dimensional discrete-time memristor model is obtained by linear coupling of the proposed TiO2 memristor model and one-dimensional chaotic systems. Since the two-dimensional model has infinite fixed points, the stability of these fixed points depends on the coupling parameters and the initial state of the discrete TiO2 memristor model. Furthermore, the dynamic characteristics of one-dimensional chaotic systems can be enhanced by the proposed method. Finally, we apply the generated chaotic sequence to secure communication.

A Novel Color Image Encryption Scheme Based on Hyperchaos and Hopfield Chaotic Neural Network.

Problems such as insufficient key space, lack of a one-time pad, and a simple encryption structure may emerge in existing encryption schemes. To solve these problems, and keep sensitive information safe, this paper proposes a plaintext-related color image encryption scheme. Firstly, a new five-dimensional hyperchaotic system is constructed in this paper, and its performance is analyzed. Secondly, this paper applies the Hopfield chaotic neural network together with the novel hyperchaotic system to propose a new encryption algorithm. The plaintext-related keys are generated by image chunking. The pseudo-random sequences iterated by the aforementioned systems are used as key streams. Therefore, the proposed pixel-level scrambling can be completed. Then the chaotic sequences are utilized to dynamically select the rules of DNA operations to complete the diffusion encryption. This paper also presents a series of security analyses of the proposed encryption scheme and compares it with other schemes to evaluate its performance. The results show that the key streams generated by the constructed hyperchaotic system and the Hopfield chaotic neural network improve the key space. The proposed encryption scheme provides a satisfying visual hiding result. Furthermore, it is resistant to a series of attacks and the problem of structural degradation caused by the simplicity of the encryption system's structure.

FPGA-Based Implementation and Synchronization Design of a New Five-Dimensional Hyperchaotic System.

Considering the security of a communication system, designing a high-dimensional complex chaotic system suitable for chaotic synchronization has become a key problem in chaotic secure communication. In this paper, a new 5-D hyperchaotic system with high order nonlinear terms was constructed and proved to be hyperchaotic by dynamical characterization characteristics, the maximum Lyapunov exponent was close to 2, and there was a better permutation entropy index, while a valid chaotic sequence could be generated in three cycles in the FPGA (Field Programmable Gate Array)-based implementation. A multivariable nonlinear feedback synchronous controller based on FPGA was proposed to design and implement synchronization of high order complex hyperchaotic systems. The results show that the error signal converged to 0 rapidly under the effect of the nonlinear feedback synchronous controller. This lays the foundation for the synchronization of high order complex chaotic systems.

Chaos-Based Lightweight Cryptographic Algorithm Design and FPGA Implementation.

With the massive application of IoT and sensor technologies, the study of lightweight ciphers has become an important research topic. In this paper, an effective lightweight LZUC (lightweight Zu Chongzhi) cipher based on chaotic system is proposed to improve the traditional ZUC algorithm. In this method, a further algorithm is designed for the process of integrating chaos into the lightweighting of ZUC. For the first time, this design introduces the logistic chaotic system into both the LFSR (linear feedback shift register) and nonlinear F-function of the cryptographic algorithm. The improved LZUC algorithm not only achieves a certain effect in lightweighting, but also has good statistical properties and security of the output sequence. To verify the performance of the LZUC cipher, we performed NIST statistical tests and information entropy analysis on its output key streams and discussed the typical attacks on the algorithm's resistance to weak key analysis, guess-determination analysis, time-stored data trade-off analysis, and algebraic analysis. In addition, we completed the design of an image security system using the LZUC cipher. Histogram analysis and correlation analysis are used to analyze both plaintext and ciphertext data. At the end of the article, the plaintext and ciphertext images displayed by LCD can be further visualized to verify the encryption effectiveness of the LZUC cipher.

A Three-Dimensional Infinite Collapse Map with Image Encryption.

Chaos is considered as a natural candidate for encryption systems owing to its sensitivity to initial values and unpredictability of its orbit. However, some encryption schemes based on low-dimensional chaotic systems exhibit various security defects due to their relatively simple dynamic characteristics. In order to enhance the dynamic behaviors of chaotic maps, a novel 3D infinite collapse map (3D-ICM) is proposed, and the performance of the chaotic system is analyzed from three aspects: a phase diagram, the Lyapunov exponent, and Sample Entropy. The results show that the chaotic system has complex chaotic behavior and high complexity. Furthermore, an image encryption scheme based on 3D-ICM is presented, whose security analysis indicates that the proposed image encryption scheme can resist violent attacks, correlation analysis, and differential attacks, so it has a higher security level.

The Establishment and Dynamic Properties of a New 4D Hyperchaotic System with Its Application and Statistical Tests in Gray Images.

In this paper, a new 4D hyperchaotic system is generated. The dynamic properties of attractor phase space, local stability, poincare section, periodic attractor, quasi-periodic attractor, chaotic attractor, bifurcation diagram, and Lyapunov index are analyzed. The hyperchaotic system is normalized and binary serialized, and the binary hyperchaotic stream generated by the system is statistically tested and entropy analyzed. Finally, the hyperchaotic binary stream is applied to the gray image encryption. The histogram, correlation coefficient, entropy test, and security analysis show that the hyperchaotic system has good random characteristics and can be applied to the gray image encryption.

Astragaloside IV attenuates inflammatory injury and promotes odontoblastic differentiation in lipopolysaccharide-stimulated MDPC-23 cells and rat pulpitis.

BACKGROUND: Astragaloside IV (AS-IV), a natural herbal compound from Astragalus membranaceus, has inhibitory effects on receptor activator of nuclear factor-κB ligand (RANKL)-induced osteoclastogenesis, and RANKL signal helps to regulate odontoblast differentiation. However, whether and how AS-IV affects odontoblastic differentiation remains unclear. METHODS: Lipopolysaccharide (LPS)-stimulated MDPC-23 cells and rat pulpitis were treated with AS-IV, cell viability, and LDH leakage was analyzed by CCK-8 assay and LDH Leakage assay. The production of TNF-α and IL-6 was determined by ELISA and qRT-PCR assay. The expression of alkaline phosphatase (ALP) was detected using an ALP assay kit, and the expression of dentin sialophos-phoprotein (DSPP), dentin matrix protein-1 (DMP1), basic fibroblast growth factor (FGF2), and phosphorylated extracellular signal-regulated kinase (p-ERK) was determined by western blot. RESULTS: AS-IV dose dependently increased in cell viability and decreased the overproduction of TNF-α and IL-6 in LPS-stimulated MDPC-23 cells. AS-IV also counteracted LPS-induced downregulation of ALP, DSPP, and DMP1 in MDPC-23 cells. Furthermore, AS-IV significantly decreased the expression of FGF2 and p-ERK in LPS-stimulated MDPC-23 cells. More important, the addition of FGF2 partly neutralized AS-IV-mediated inhibition of FGF2/ERK signaling, abolished AS-IV-induced reduction of TNF-α and IL-6, and counteracted AS-IV-induced upregulation of DSPP and DMP-1 in these cells. Meanwhile, AS-IV inhibited the excessive production of TNF-α and IL-6, suppressed the downregulation of DSPP and DMP1, and disturbed the up-regulation of FGF2 and p-ERK in the pulp tissues of rat pulpitis model. CONCLUSIONS: AS-IV exerted anti-inflammatory and pro-differentiation effects in LPS-stimulated MDPC-23 cells and rat pulpitis via inhibiting the FGF2/ERK signaling pathway.

A Class of Quadratic Polynomial Chaotic Maps and Their Fixed Points Analysis.

When chaotic systems are used in different practical applications, such as chaotic secure communication and chaotic pseudorandom sequence generators, a large number of chaotic systems are strongly required. However, for a lack of a systematic construction theory, the construction of chaotic systems mainly depends on the exhaustive search of systematic parameters or initial values, especially for a class of dynamical systems with hidden chaotic attractors. In this paper, a class of quadratic polynomial chaotic maps is studied, and a general method for constructing quadratic polynomial chaotic maps is proposed. The proposed polynomial chaotic maps satisfy the Li-Yorke definition of chaos. This method can accurately control the amplitude of chaotic time series. Through the existence and stability analysis of fixed points, we proved that such class quadratic polynomial maps cannot have hidden chaotic attractors.

Research about the Characteristics of Chaotic Systems Based on Multi-Scale Entropy.

The logistic chaotic system, as a classical complex phenomenon of nonlinear dynamic systems, has received extensive attention in the field of secure communication. It is generally believed that the characteristics of chaos are suitable for the needs of encryption systems. In this paper, a multi-scale entropy theory analysis and statistical analysis are carried out on the chaotic sequences produced by different parameters and different initial values of logistic systems. According to the simulation results, the complexity of the chaotic system represented by the logistic system is mainly decided by parameter µ. Not all characteristic parameters of the chaotic system depend on the initial values. It is possible to make a reasonable estimation and prediction of the chaotic system from a macroscopic level. A variance estimation method for the parameter µ is proposed and applied to a logistic system and to another chaotic system, which is equally effective.

A New Two-Dimensional Map with Hidden Attractors.

The investigations of hidden attractors are mainly in continuous-time dynamic systems, and there are a few investigations of hidden attractors in discrete-time dynamic systems. The classical chaotic attractors of the Logistic map, Tent map, Henon map, Arnold's cat map, and other widely-known chaotic attractors are those excited from unstable fixed points. In this paper, the hidden dynamics of a new two-dimensional map inspired by Arnold's cat map is investigated, and the existence of fixed points and their stabilities are studied in detail.