Design and Optimization of MEMS Resonant Pressure Sensors with Wide Range and High Sensitivity Based on BP and NSGA-II.

With the continuous progress of aerospace, military technology, and marine development, the MEMS resonance pressure sensor puts forward the requirements of not only a wide range but also high sensitivity. However, traditional resonators are hardly compatible with both. In response, we propose a new sensor structure. By arranging the resonant beam and the sensitive diaphragm vertically in space, the new structure improves the rigidity of the diaphragm without changing the thickness of the diaphragm and achieves the purpose of increasing the range without affecting the sensitivity. To find the optimal structural parameters for the sensor sensitivity and range, and to prevent the effects of modal disturbances, we propose a multi-objective optimization design scheme based on the BP and NSGA-II algorithms. The optimization of the structure parameters not only improved the sensitivity but also increased the interference frequency to solve the issue of mode interference. The optimized structure achieves a sensitivity and range of 4.23 Hz/kPa and 1-10 MPa, respectively. Its linear influence factor is 38.07, significantly higher than that of most resonant pressure sensors. The structural and algorithmic optimizations proposed in this paper provide a new method for designing resonant pressure sensors compatible with a wide range and high sensitivity.

Use of Composite Multivariate Multiscale Permutation Fuzzy Entropy to Diagnose the Faults of Rolling Bearing.

The study focuses on the fault signals of rolling bearings, which are characterized by nonlinearity, periodic impact, and low signal-to-noise ratio. The advantages of entropy calculation in analyzing time series data were combined with the high calculation accuracy of Multiscale Fuzzy Entropy (MFE) and the strong noise resistance of Multiscale Permutation Entropy (MPE), a multivariate coarse-grained form was introduced, and the coarse-grained process was improved. The Composite Multivariate Multiscale Permutation Fuzzy Entropy (CMvMPFE) method was proposed to solve the problems of low accuracy, large entropy perturbation, and information loss in the calculation process of fault feature parameters. This method extracts the fault characteristics of rolling bearings more comprehensively and accurately. The CMvMPFE method was used to calculate the entropy value of the rolling bearing experimental fault data, and Support Vector Machine (SVM) was used for fault diagnosis analysis. By comparing with MPFE, the Composite Multiscale Permutation Fuzzy Entropy (CMPFE) and the Multivariate Multiscale Permutation Fuzzy Entropy (MvMPFE) methods, the results of the calculations show that the CMvMPFE method can extract rolling bearing fault characteristics more comprehensively and accurately, and it also has good robustness.

Design and Optimization of Hemispherical Resonators Based on PSO-BP and NSGA-II.

Although one of the poster children of high-performance MEMS (Micro Electro Mechanical Systems) gyroscopes, the MEMS hemispherical resonator gyroscope (HRG) is faced with the barrier of technical and process limits, which makes it unable to form a resonator with the best structure. How to obtain the best resonator under specific technical and process limits is a significant topic for us. In this paper, the optimization of a MEMS polysilicon hemispherical resonator, designed by patterns based on PSO-BP and NSGA-II, was introduced. Firstly, the geometric parameters that significantly contribute to the performance of the resonator were determined via a thermoelastic model and process characteristics. Variety regulation between its performance parameters and geometric characteristics was discovered preliminarily using finite element simulation under a specified range. Then, the mapping between performance parameters and structure parameters was determined and stored in the BP neural network, which was optimized via PSO. Finally, the structure parameters in a specific numerical range corresponding to the best performance were obtained via the selection, heredity, and variation of NSGAII. Additionally, it was demonstrated using commercial finite element soft analysis that the output of the NSGAII, which corresponded to the Q factor of 42,454 and frequency difference of 8539, was a better structure for the resonator (generated by polysilicon under this process within a selected range) than the original. Instead of experimental processing, this study provides an effective and economical alternative for the design and optimization of high-performance HRGs under specific technical and process limits.

Tryptophan-Modulated Nanoscale Metal-Organic Framework for Coordinated Loading of Biomolecules for Cascade Production of Reactive Oxygen and Nitrogen Species.

Owing to the high surface area and porosity, metal-organic frameworks (MOFs) could be utilized as both nanocarriers of biopharmaceuticals and nanoreactors to organize cascade biological reactions with great potential in cancer treatment. However, nanoscale MOFs suitable for biomedical applications rely on harsh preparation conditions. Here, we utilized tryptophan to modulate the morphology and optical properties of zeolitic imidazolate framework-8 (ZIF-8) as nanocarrier to efficiently encapsulate the enzyme and mRNA. Under room temperature in an aqueous solution, tryptophan would coordinate with zinc ions to form ZIF-8:Trp with a decreased size from the µm range to sub-200 nm. In addition, cargo release could be monitored in real time via fluorescence red-shift effects. Besides being used as nanocarriers of biomolecules, ZIF-8:Trp could also be utilized as nanoreactors to induce cascade reactions to produce reactive oxygen and nitrogen species. Overall, this nanosized ZIF-8:Trp could provide a new strategy for preparation of cascade bioreactions and provide new insight for gas therapy.

ICAM1-Targeting Theranostic Nanoparticles for Magnetic Resonance Imaging and Therapy of Triple-Negative Breast Cancer.

Purpose: Owing to the lack of effective biomarkers, triple-negative breast cancer (TNBC) has the worst prognosis among all subtypes of breast cancer. Meanwhile, tremendous progress has been made to identify biomarkers for TNBC. However, limited number of biomarkers still restrain the specifically targeting outcomes against TNBC. Here, to solve the obstacle, we designed and synthesized a new type of biocompatible nanoparticles to amplify the targeting effects for TNBC theranostics. Methods: To identify the biomarker of TNBC, the expression of intercellular adhesion molecule-1 (ICAM1) was assessed by real-time polymerase chain reaction and western blot among all subtypes of breast cancer and normal breast epithelium. Then, vesicular nanoparticles based on poly(ethylene glycol)-poly(ε-caprolactone) copolymers were prepared by the double emulsion method and modified with anti-ICAM1 antibodies through click chemistry to conjugate with related antigens on TNBC cell membranes and then loaded with magnetic resonance imaging (MRI) contrast agent gadolinium and chemotherapeutic drug doxorubicin. The targeting capability, diagnostic and therapeutic efficacy of this nanoparticle were validated through cell-based and tumor model-based experiments. Results: ICAM1 was expressed significantly higher on TNBC than on other subtypes of breast cancer and normal breast epithelium in both mRNA and protein level. Theranostic nanoparticle modified with anti-ICAM1 was proved to be able to specifically target to TNBC in vitro experiments. Such theranostic nanoparticle also displayed enhanced diagnostic and therapeutic efficacy by specifically targeting capability and extending circulation time in tumor models. The biocompatibility and biosafety of this nanoparticle was also confirmed in vitro and in vivo. Conclusion: Overall, this new nanoparticle has been demonstrated with effective therapeutic outcomes against TNBC, providing a promising theranostic approach for MRI-guided therapy of TNBC.

Intracellular Self-Assembly of Peptides to Induce Apoptosis against Drug-Resistant Melanoma.

Biosynthesis has been a diverse toolbox to develop bioactive molecules and materials, especially for fabricating modified peptides and their assemblies induced by enzymes. Although desired chemical structures and nanoarchitectures have been achieved, the subsequent interferences of peptide assemblies with organelles and the cellular pathways still remain unsolved important challenges. Herein, we developed a new tripeptide, phenylalanine-phenylalanine-tyrosine (Phe-Phe-Tyr, or FFY), which can be intracellularly oxidized and in situ self-assemble into nanoparticles with excellent interference capability with microtubules and ultimately reverse the drug resistance of melanoma. With the catalysis of tyrosinase, FFY was first oxidized to a melanin-like FFY dimer (mFFY) with a diquinone structure for further self-assembling into mFFY assemblies, which could inhibit the self-polymerization of tubulin to induce severe G2/M arrest (13.9% higher than control). Afterward, mitochondrial dysfunction was also induced for overproduction of cleaved caspase 3 (3.1 times higher than control) and cleaved PARP (6.3 times higher), achieving a high level of resistant reversing without chemotherapeutic drugs. In vivo studies showed that the resistant melanoma tumor volumes were reduced by 87.4% compared to control groups after FFY treatment by peritumoral injections. Overall, this tyrosinase-induced tripeptide assembly has been demonstrated with effective intrinsic apoptosis against drug-resistant melanoma, providing a new insight into utilizing biomolecules to interfere with organelles to activate certain apoptosis pathways for treatment of drug-resistant cancer.

Mitochondrial-targeting nanoprodrugs to mutually reinforce metabolic inhibition and autophagy for combating resistant cancer.

Abnormal energy metabolism is one of the hallmarks of cancer and closely linked to therapy resistance. However, existing metabolic inhibitors suffer from inefficient cell enrichment and therapeutic effects. In this work, we developed an effective strategy to mutually reinforce the metabolic inhibition and autophagy for enhanced tumor killing efficacy and combating resistant cancer. First, mitochondrial homing moiety triphenylphosphonium and metabolic inhibitor lonidamine were grafted onto polylysine. After self-assembly of this functionalized polylysine, ferrocene and glucose oxidase were immobilized to afford additional chemotherapy functions, and the final product was named as FG/T-Nanoprodrug. Effective mitochondrial targeting and metabolic inhibition were observed in resistant cancer cells. In addition, owing to the inhibited metabolism, less glucose is consumed to allow FG/T-Nanoprodrug to produce excess reactive oxygen species (ROS) by glucose oxidase and ferrocene. The enhanced chemodynamic therapy increases the mitochondrial permeability to promote the release of cytochrome c from mitochondria, ultimately induces high levels of autophagy. The FG/T-Nanoprodrug demonstrated superior mutually reinforcing of metabolic inhibition (up to 3.7-fold compared to free lonidamine) and autophagy (up to 125.3-fold compared to free lonidamine) to effectively kill resistant cancer cell both in vitro and in vivo. Overall, this strategy could pave a new way to efficient treatment of resistant cancer and other metabolically abnormal diseases.