Serum γ-glutamyltransferase levels and obesity status changes the risk of prehypertension in Chinese adults.

Objective: It's well known that γ-Glutamyltransferase (γ-GGT) and obesity plays an important role in the development of preHT. However, the effect of γ-GGT on preHT in populations with different obesity status remains unclear. Methods: From February 2014 to January 2018, a total of 20,368 participants were enrolled in this study after excluding those with hypertension and liver diseases. Fasting blood samples were collected to measure γ-GGT and blood lipid levels and glucose indices. Demographic and clinical parameters such as sex, age, height, weight, neck circumference (NC), waist circumference (WC), hip circumference (HC), and body fat ratio (BFR); and information on smoking and alcohol consumption were collected by trained medical professionals. Results: Participants were divided into three groups based on obesity status. The prevalence of preHT was 83.5 % in the obesity group was higher than that in the overweight group (58.9 %) and the normal group (47.1 %). γ-GGT in different categories of obesity indices were significantly different, and higher obesity indices were found with higher γ-GGT levels. The interaction of γ-GGT and obesity indices such as NC, WC, HC, and BFR on the prevalence of preHT was significant (P = 0.028, 0.002, 0.007, and 0.034, respectively). Serum γ-GGT was found to be positively associated with preHT in participants with normal and overweight body mass indices. Conclusion: Our results indicate that γ-GGT is a risk factor for preHT in participants who are nonobese, and that the obesity indices NC, WC, HC, BFR, and γ-GGT were contributing factors in increasing the risk of preHT.

Development and Validation of a Risk Score for Mild Cognitive Impairment in Individuals with Type 2 Diabetes in China: A Practical Cognitive Prescreening Tool.

Aim: Numerous evidence suggests that diabetes increases the risk of cognitive impairment. This study aimed to develop and validate a multivariable risk score model to identify mild cognitive impairment (MCI) in patients with type 2 diabetes mellitus (T2DM). Methods: This cross-sectional study included 1256 inpatients (age: 57.5 ± 11.2 years) with T2DM in a tertiary care hospital in China. MCI was diagnosed according to the criteria recommended by the National Institute on Aging-Alzheimer's Association Workgroup, and a MoCA score of 19-25 indicated MCI. Participants were randomly allocated into the derivation and validation sets at 7:3 ratio. Logistic regression models were used to identify predictors for MCI in the derivation set. A scoring system based on the predictors' beta coefficient was developed. Predictive ability of the risk score was tested by discrimination and calibration methods. Results: Totally 880 (285 with MCI, 32.4%) and 376 (167 with MCI, 33.8%) patients were allocated in the derivation and validation set, respectively. Age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease were identified as predictors for MCI and constituted the risk score. The AUCs (95% CI) of the risk score were 0.751 (0.717, 0.784) in derivation set and 0.776 (0.727, 0.824) in validation set. The risk score showed good apparent calibration of observed and predicted MCI probabilities and was capable of stratifying individuals into 3 risk categories by two cut-off points (low risk: ≤ 3, medium risk: 4-13, and high risk ≥ 14). Conclusion: The risk score based on age, education, HbA1c, self-reported history of severe hypoglycemia, and microvascular disease can effectively assess MCI risk in adults with T2DM at different age. It can serve as a practical prescreening tool for early detection of MCI in daily diabetes care.

Exposure to volatile organic compounds is a risk factor for diabetes retinopathy: a cross-sectional study.

Introduction: A few past experimental studies have indicated that exposure to volatile organic compounds (VOCs) might be a potential risk factor for diabetes retinopathy (DR). However, these findings lack substantial support from extensive epidemiological research. This large-scale cross-sectional study aimed to examine whether exposure to low levels of VOCs in the general population is associated with diabetes mellitus (DM) and DR. Methods: The analytical data was from the National Health and Nutrition Examination Survey (NHANES) dataset (2011-2018). To minimize the potential impact of gender and age on the findings, propensity score matching was utilized to align the data selection. Relationships between blood VOCs and DM and DR were assessed in a sample of 2,932 adults using the logistic regression models. Additionally, Bayesian kernel machine regression (BKMR) models and Weighted Quantile Sum (WQS) were conducted for mixture exposure analysis. Results: The result shows VOCs were positive associated with DM and DR in US adults, as assessed by WQS model, and the calculated odd ratios (ORs) [95% confidence interval (C.I)] were 53.91(34.11 ~ 85.22) and 7.38(3.65 ~ 14.92), respectively. Among the components of VOCs, 1,2-Dibromoethane, Carbon Tetrachloride and 2,5-Dimethylfuran were positive related with the DR, and ORs (95%C.I) were 2.91(2.29 ~ 3.70), 2.86(2.25 ~ 3.65) and 2.19(1.79 ~ 2.94), respectively. BKMR model shows that there was a dose-response relationship between combined VOCs and DR, although the relationship was non-linearly. Conclusion: This study suggested that exposure to VOCs may increase the risk of DR, which had important public health implications.

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.

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.

Enhanced artificial nitrogen fixation efficiency induced by construction of ternary TiO2/MIL-88A(Fe)/g-C3N4 Z-scheme heterojunction.

Herein, a ternary TiO2/MIL-88A(Fe)/g-C3N4 heterojunction is successfully constructed through a facile hydrothermal strategy for enhancing solar energy harvesting and efficiency of catalytic nitrogen reduction induced by enlarged light absorption range, increasing interfacial charge transfer ability and desirable stability. Under the simulated sunlight irradiation, the N2 fixation experiment shows that the yield of NH3 reaches 1084.31 µmol/(g·h) over the TiO2/MIL-88A(Fe)/g-C3N4 photocatalyst, and the yield is significantly enhanced, which is 33.68 and 13.94 times that is higher than the pure TiO2 and g-C3N4, respectively. In a mean time, the excellent performance of the photocatalytic N2 fixation over the ternary TiO2/MIL-88A(Fe)/g-C3N4 is verified based on density function theory calculation and the decisive step over the composite is investigated by calculating Gibbs free energies of nitrogen reduction paths. The performance enhancement mechanism of TiO2/MIL-88A(Fe)/g-C3N4 is speculated, which indicates that the hybridized three-component system presents a desirable Z-scheme band alignment, resulting in the improvement of separation and transfer efficiency of photoinduced charge carriers. The article shows a new and high-efficiency TiO2/MIL-88A(Fe)/g-C3N4 photocatalysis for excellent nitrogen reduction ability.

The Presence and Severity of NAFLD are Associated With Cognitive Impairment and Hippocampal Damage.

CONTEXT: Although cognitive impairment in nonalcoholic fatty liver disease (NAFLD) has received attention in recent years, little is known about detailed cognitive functions in histologically diagnosed individuals. OBJECTIVE: This study aimed to investigate the association of liver pathological changes with cognitive features and further explore the underlying brain manifestations. METHODS AND PATIENTS: We performed a cross-sectional study in 320 subjects who underwent liver biopsy. Among the enrolled participants, 225 underwent assessments of global cognition and cognitive subdomains. Furthermore, 70 individuals received functional magnetic resonance imaging scans for neuroimaging evaluations. The associations among liver histological features, brain alterations, and cognitive functions were evaluated using structural equation model. RESULTS: Compared with controls, patients with NAFLD had poorer immediate memory and delayed memory. Severe liver steatosis (odds ratio, 2.189; 95% CI, 1.020-4.699) and ballooning (OR, 3.655; 95% CI, 1.419-9.414) were related to a higher proportion of memory impairment. Structural magnetic resonance imaging showed that patients with nonalcoholic steatohepatitis exhibited volume loss in left hippocampus and its subregions of subiculum and presubiculum. Task-based magnetic resonance imaging showed that patients with nonalcoholic steatohepatitis had decreased left hippocampal activation. Path analysis demonstrated that higher NAFLD activity scores were associated with lower subiculum volume and reduced hippocampal activation, and such hippocampal damage contributed to lower delayed memory scores. CONCLUSIONS: We are the first to report the presence and severity of NAFLD to be associated with an increased risk of memory impairment and hippocampal structural and functional abnormalities. These findings stress the significance of early cognitive evaluation in patients with NAFLD.

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.

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.

Effect of Manual Lymphatic Drainage on Breast Cancer-Related Postmastectomy Lymphedema: A Meta-analysis of Randomized Controlled Trials.

BACKGROUND: Manual lymphatic drainage (MLD) is widely used in the treatment of breast cancer-related postmastectomy lymphedema (BCRL). However, the therapeutic benefit of MLD on BCRL remains controversial. OBJECTIVE: The aim of this study was to analyze the efficacy of MLD for BCRL. METHOD: Four electronic databases were systematically searched for trials comparing MLD and no MLD treatment as options for BCRL. Comparative treatment results included reduction of upper extremity limb volume with subgroup analysis by the number and duration of treatments. RESULTS: A total of 457 patients were included in the analysis. There was no significant difference in the amount of upper extremity edema between the MLD treatment and control or no MLD groups ( P = .11). However, when the treatment course was ≥20 sessions, there was a significant reduction in the upper extremity volume ( P = .03). There was also a significant reduction in the upper extremity volume when treatment duration was >2 weeks ( P = .03). CONCLUSION: Manual lymphatic drainage treatment statistically did not reduce the upper extremity limb volume of BCRL, but upper extremity volume was reduced at statistically significant levels when treatment number were ≥20 sessions or the duration of treatment was >2 weeks. IMPLICATION FOR PRACTICE: Reduction in upper limb volume is dependent on the number and duration of treatments. When treatment number were ≥20 sessions, or the duration of treatment was >2 weeks, reduction of upper limb volume was statistically achieved. Manual lymphatic drainage treatment can be clinically recommended to treat BCRL according to these parameters.

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.

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.

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.

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.

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 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.

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.