Soluble polyvinylpyrrolidone-based microneedles loaded with Sanguis draconis and Salvia miltiorrhiza for treatment of diabetic wound healing.

BACKGROUND: Nowadays, diabetic wound healing remains a crucial challenge due to their protracted and uncertain healing process. Traditional Chinese medicine (TCM) has demonstrated the therapeutic value of Sanguis draconis (SD)-Salvia miltiorrhiza (SMR) Herb Pair in diabetic wound healing. However, new administration modes are urgently needed for their convenient and wide-ranging applications. OBJECTIVE: We propose a soluble polyvinylpyrrolidone-based microneedle patch containing the herbal extracts of SD and SMR (MN-SD@SMR) for diabetic wound healing. METHODS: The herbal extracts of SD and SMR are purification and concentration via traditional lyophilization. SD endowed MN-SD@SMR with functions to improve high glycemic blood environment and migration of keratinocyte and fibroblast cells. RESULTS: SMR in MN-SD@SMR could improve blood flow velocity and microcirculation in the wound area. The effectiveness of transdermal release and mechanical strengths of MN-SD@SMR were verified. CONCLUSION: Integrating the advantages of these purified herbal compositions, we demonstrated that MN-SD@SMR had a positive healing effect on the wounds in vitro and vivo. These results indicate that soluble polyvinylpyrrolidone-based microneedle patch containing the herbal extracts of SD and SMR has a promising application value due to their superior capability to promote diabetic wound healing.

Data Fusion of Dual Foot-Mounted INS Based on Human Step Length Model.

Pedestrian navigation methods based on inertial sensors are commonly used to solve navigation and positioning problems when satellite signals are unavailable. To address the issue of heading angle errors accumulating over time in pedestrian navigation systems that rely solely on the Zero Velocity Update (ZUPT) algorithm, it is feasible to use the pedestrian's motion constraints to constrain the errors. Firstly, a human step length model is built using human kinematic data collected by the motion capture system. Secondly, we propose the bipedal constraint algorithm based on the established human step length model. Real field experiments demonstrate that, by introducing the bipedal constraint algorithm, the mean biped radial errors of the experiments are reduced by 68.16% and 50.61%, respectively. The experimental results show that the proposed algorithm effectively reduces the radial error of the navigation results and improves the accuracy of the navigation.

Measurement and Isolation of Thermal Stress in Silicon-On-Glass MEMS Structures.

The mechanical stress in silicon-on-glass MEMS structures and a stress isolation scheme were studied by analysis and experimentation. Double-ended tuning forks (DETFs) were used to measure the stress based on the stress-frequency conversion effect. Considering the coefficients of thermal expansion (CTEs) of silicon and glass and the temperature coefficient of the Young's modulus of silicon, the sensitivity of the natural frequency to temperature change was analyzed. A stress isolation mechanism composed of annular isolators and a rigid frame is proposed to prevent the structure inside the frame from being subjected to thermal stresses. DETFs without and with one- or two-stage isolation frames with the orientations <110> and <100> were designed, the stress and natural frequency variations with temperature were simulated and measured. The experimental results show that in the temperature range of -50 °C to 85 °C, the stress varied from -18 MPa to 10 MPa in the orientation <110> and -11 MPa to 5 MPa in the orientation <100>. For the 1-stage isolated DETF of <110> orientation, the measured stress variation was only 0.082 MPa. The thermal stress can be mostly rejected by a stress isolation structure, which is applicable in the design of stress-sensitive MEMS sensors and actuators.

Self-Alignment MEMS IMU Method Based on the Rotation Modulation Technique on a Swing Base.

The micro-electro-mechanical-system (MEMS) inertial measurement unit (IMU) has been widely used in the field of inertial navigation due to its small size, low cost, and light weight, but aligning MEMS IMUs remains a challenge for researchers. MEMS IMUs have been conventionally aligned on a static base, requiring other sensors, such as magnetometers or satellites, to provide auxiliary information, which limits its application range to some extent. Therefore, improving the alignment accuracy of MEMS IMU as much as possible under swing conditions is of considerable value. This paper proposes an alignment method based on the rotation modulation technique (RMT), which is completely self-aligned, unlike the existing alignment techniques. The effect of the inertial sensor errors is mitigated by rotating the IMU. Then, inertial frame-based alignment using the rotation modulation technique (RMT-IFBA) achieved coarse alignment on the swing base. The strong tracking filter (STF) further improved the alignment accuracy. The performance of the proposed method was validated with a physical experiment, and the results of the alignment showed that the standard deviations of pitch, roll, and heading angle were 0.0140 ° , 0.0097 ° , and 0.91 ° , respectively, which verified the practicality and efficacy of the proposed method for the self-alignment of the MEMS IMU on a swing base.

[Efficacy and safety of simulated artificial pancreas in modulating stress hyperglycemia in critically ill patients: a prospective randomized controlled study].

OBJECTIVE: To explore efficacy and safety of simulated artificial pancreas in modulating stress hyperglycemia in critically ill patients. METHODS: A prospective randomized controlled study was performed. Seventy-two critically ill patients with stress hyperglycemia, aged 18-85 years, acute physiology and chronic health evaluation II (APACHE II) score over 15, two consecutive random blood glucose 11.1 mmol/L or higher, glycated hemoglobin (HbA1C) below 0.065, unable to eat food for 3 days after inclusion, or only accepting parenteral nutrition, admitted to intensive care unit (ICU) in Shanghai Punan Hospital of Pudong New District from January 1st, 2015 to June 30th, 2017 were enrolled. The patients were divided into three groups according to the random number table method, high-intensity group and low-intensity group were injected Novolin R (high-intensity group 2/3 dosage, low-intensity group 1/3 dosage) to modulate stress hyperglycemia by simulated artificial pancreas. Simulated artificial pancreas consisted of Guardian real time glucose monitoring system (GRT system), close-circle control algorithm and micro-pump; subcutaneous injection of Humulin 70/30 was applied to modulate stress hyperglycemia in humulin group. Real-time glucose levels of interstitial fluid in abdominal wall, equivalent to blood glucose levels, 10 minutes each time, were monitored by using of GRT system for all patients in three groups. Fasting serum levels of stress hormones including epinephrine and cortisol and insulin resistance index (IRI) were recorded within 24 hours after inclusion. Mean blood glucose, blood glucose variation coefficient, blood glucose target-reaching rate, blood glucose target-reaching time, hypoglycemia rate and 6-month mortality were measured. Twenty healthy adults from health administration department of the hospital were recruited as healthy control group. RESULTS: A total of 60 eligible critically ill patients were included in this study, each group with 20 patients. There was no significant difference in gender, age, APACHE II scores among three groups. The levels of serum epinephrine, cortisol and IRI within 24 hours after inclusion in the three groups were significantly higher than those in healthy control group. The mean blood glucose levels of humulin group, low-intensity group, high-intensity group were decreased (mmol/L: 10.2±3.2, 8.4±2.6, 8.1±2.2), the blood glucose target-reaching rate were increased [40.2% (3 295/8 196), 71.1% (5 393/7 585), 80.4% (6 286/7 818)], the blood glucose target-reaching time were shortened (hours: 49.1±5.8, 24.6±4.6, 17.5±4.2), the hypoglycemia rates were increased respectively [1.3% (108/8 196), 2.8% (211/7 585), 4.0% (313/7 818)], with statistically significant differences (all P = 0.000). There was no significant difference in blood glucose variation coefficient and 6-month mortality among three groups [blood glucose variation coefficient: (29.4±3.7)%, (28.5±5.3)%, (26.1±4.6)%, 6-month mortality: 55.0%, 45.0%, 40.0%, all P > 0.05]. CONCLUSIONS: Simulated artificial pancreas could effectively and safely modulate stress hyperglycemia in critically ill patients, high-intensity modulation could bring about better efficacy in the regulation of hyperglycemia. High-frequency blood glucose monitoring by using GRT system could promptly identify hypoglycemia and help it to be corrected.

Modeling and Compensation of Random Drift of MEMS Gyroscopes Based on Least Squares Support Vector Machine Optimized by Chaotic Particle Swarm Optimization.

MEMS (Micro Electro Mechanical System) gyroscopes have been widely applied to various fields, but MEMS gyroscope random drift has nonlinear and non-stationary characteristics. It has attracted much attention to model and compensate the random drift because it can improve the precision of inertial devices. This paper has proposed to use wavelet filtering to reduce noise in the original data of MEMS gyroscopes, then reconstruct the random drift data with PSR (phase space reconstruction), and establish the model for the reconstructed data by LSSVM (least squares support vector machine), of which the parameters were optimized using CPSO (chaotic particle swarm optimization). Comparing the effect of modeling the MEMS gyroscope random drift with BP-ANN (back propagation artificial neural network) and the proposed method, the results showed that the latter had a better prediction accuracy. Using the compensation of three groups of MEMS gyroscope random drift data, the standard deviation of three groups of experimental data dropped from 0.00354°/s, 0.00412°/s, and 0.00328°/s to 0.00065°/s, 0.00072°/s and 0.00061°/s, respectively, which demonstrated that the proposed method can reduce the influence of MEMS gyroscope random drift and verified the effectiveness of this method for modeling MEMS gyroscope random drift.

Changes of tumor necrosis factor, surfactant protein A, and phospholipids in bronchoalveolar lavage fluid in the development and progression of coal workers' pneumoconiosis.

OBJECTIVE: To evaluate the alterations of biomarkers in the development and progression of coal workers' pneumoconiosis (CWP). METHODS: The type and number of cells, and the levels of tumor necrosis factor-alpha (TNF-alpha), pulmonary surfactant protein, phospholipids and fibronectin in bronchoalveolar lavage fluid were assayed in 14 health active coal miners, 21 coal miners without CWP and 13 miners with CWP of 0/1 to 1/1. RESULTS: Compared to active coal miners without CWP (8.23 microg/mL), TNF-alpha concentration was gradually decreased when dust exposure was stopped (5.90 microg/mL). Elevated surfactant protein A (SP-A) level and phosphatidylglycerol (PG) to phosphatidylinositol (PI) ratio were found in miners actively exposed to coal dust (6528 ng/mL for SP-A and 10. for PG/PI), and both parameters decreased when CWP progressed from CWP (0/1) (3419 microg/mL for SP-A and 5.9 for PG/PI) to CWP (1/1) (1654 microg/mL for SP-A and 5.5 for PG/PI). CONCLUSION: Biomarkers in bronchoalveolar lavage fluid can be used to screen coal miners at high risk of developing coal workers' pneumoconiosis.