Magnetic propelled hydrogel microrobots for actively enhancing the efficiency of lycorine hydrochloride to suppress colorectal cancer

Research and development in the field of micro/nano-robots have made significant progress in the past, especially in the field of clinical medicine, where further research may lead to many revolutionary achievements. Through the research and experiment of microrobots, a controllable drug delivery system will be realized, which will solve many problems in drug treatment. In this work, we design and study the ability of magnetic-driven hydrogel microrobots to carry Lycorine hydrochloride (LH) to inhibit colorectal cancer (CRC) cells. We have successfully designed a magnetic field driven, biocompatible drug carrying hydrogel microsphere robot with Fe3O4 particles inside, which can achieve magnetic field response, and confirmed that it can transport drug through fluorescence microscope. We have successfully demonstrated the motion mode of hydrogel microrobots driven by a rotating external magnetic field. This driving method allows the microrobots to move in a precise and controllable manner, providing tremendous potential for their use in various applications. Finally, we selected drug LH and loaded it into the hydrogel microrobot for a series of experiments. LH significantly inhibited CRC cells proliferation in a dose- and time-dependent manner. LH inhibited the proliferation, mobility of CRC cells and induced apoptosis. This delivery system can significantly improve the therapeutic effect of drugs on tumors

A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks †

In an Ad hoc sensor network, nodes have characteristics of limited battery energy, self-organization and low mobility. Due to the mobility and heterogeneity of the energy consumption in the hierarchical network, the cluster head and topology are changed dynamically. Therefore, topology control and energy consumption are growing to be critical in enhancing the stability and prolonging the lifetime of the network. In order to improve the survivability of Ad hoc network effectively, this paper proposes a new algorithm named the robust, energy-efficient weighted clustering algorithm (RE2WCA). For the homogeneous of the energy consumption; the proposed clustering algorithm takes the residual energy and group mobility into consideration by restricting minimum iteration times. In addition, a distributed fault detection algorithm and cluster head backup mechanism are presented to achieve the periodic and real-time topology maintenance to enhance the robustness of the network. The network is analyzed and the simulations are performed to compare the performance of this new clustering algorithm with the similar algorithms in terms of cluster characteristics, lifetime, throughput and energy consumption of the network. The result shows that the proposed algorithm provides better performance than others

Ferry Node Identification Model for the Security of Mobile Ad Hoc Network

An opportunistic network is a special type of wireless mobile ad hoc network that does not require any infrastructure, does not have stable links between nodes, and relies on node encounters to complete data forwarding. The unbalanced energy consumption of ferry nodes in an opportunistic network leads to a sharp decline in network performance. Therefore, identifying the ferry node group plays an important role in improving the performance of the opportunistic network and extending its life. Existing research studies have been unable to accurately identify ferry node clusters in opportunistic networks. In order to solve this problem, the concepts of k-core and structural holes have been combined, and a new evaluation indicator, namely, ferry importance rank, has been proposed in this study for analyzing the dynamic importance of nodes in a network. Based on this, a ferry cluster identification model has been designed for accurately identifying the ferry node clusters. The results of the simulations conducted for verifying the performance of the proposed model show that the accuracy of the model to identify the ferry node clusters is 100%

Parameterization optimal control of an unsteady partial differential equations with convection term by an improved three-term spectrum conjugate gradient algorithm

The unsteady partial differential equations (UPDE) with convection term gives a clear descriptions for the solidification process of a slab in dynamic production of continuous casting. To give a suitable setting value of secondary cooling water flow rate for the dynamic control system, this study investigates an optimal control problem (OCP) of UPDE with convection term. Firstly, control vector discretization of OCP and the solution of UPDE are given. Secondly, due to the rapidity for gradient, this paper analyzes the expression of the gradient calculation method based on Hamiltonian function costate system by approximate treatment, matrix calculation and composite trapezoidal integral method. Thirdly, an improved three-term spectrum conjugate gradient algorithm (ITSCGA) is proposed to solve the OCP of UPDE, and the global convergence of the ITSCGA is demonstrated. Lastly, the performance of ITSCGA is demonstrated by experimental simulations. The results demonstrate that the ITSCGA provides a smaller temperature fluctuations, and improves the quality of a slab

Amination of Nitroazoles — A Comparative Study of Structural and Energetic Properties

In this work, 3-nitro-1H-1,2,4-triazole (1) and 3,5-dinitro-1H-pyrazole (2) were C-aminated and N-aminated using different amination agents, yielding their respective C-amino and N-amino products. All compounds were fully characterized by NMR (1H, 13C, 15N), IR spectroscopy, differential scanning calorimetry (DSC). X-ray crystallographic measurements were performed and delivered insight into structural characteristics as well as inter- and intramolecular interactions of the products. Their impact sensitivities were measured by using standard BAM fallhammer techniques and their explosive performances were computed using the EXPLO 5.05 program. A comparative study on the influence of those different amino substituents on the structural and energetic properties (such as density, stability, heat of formation, detonation performance) is presented. The results showed that the incorporation of an N-amino group into a nitroazole ring can improve nitrogen content, heat of formation and impact sensitivity, while the introduction of a C-amino group can enhance density, detonation velocity and pressure. The potential of N-amino and C-amino moieties for the design of next generation energetic materials is explored

Rapid Freezing Enables Aminoglycosides To Eradicate Bacterial Persisters via Enhancing Mechanosensitive Channel MscL-Mediated Antibiotic Uptake

Antibiotics have long been used to successfully kill bacterial pathogens, but antibiotic resistance/tolerance usually has led to the failure of antibiotic therapy, and it has become a severe threat to human health. How to improve the efficacy of existing antibiotics is of importance for combating antibiotic-resistant/tolerant pathogens. Here, we report that 10-s rapid freezing with liquid nitrogen dramatically enhanced the bactericidal action of aminoglycoside antibiotics by 2 to 6 orders of magnitude against many bacterial pathogens in vitro and also in a mouse skin wound model. In particular, such combined treatment was able to effectively kill persister cells of Escherichia coli and Pseudomonas aeruginosa, which are per se tolerant of conventional treatment with bactericidal antibiotics for several hours. We also demonstrated that freezing-induced aminoglycoside potentiation was apparently linked to freezing-induced cell membrane damage that may have activated the mechanosensitive ion channel MscL, which, in turn, was able to effectively uptake aminoglycoside antibiotics in a proton motive force-independent manner. Our report sheds light on the development of a new strategy against bacterial pathogens by combining existing antibiotics with a conventional physical treatment or with MscL agonists.Bacterial persisters exhibit noninherited antibiotic tolerance and are linked to the recalcitrance of bacterial infections. It is very urgent but also challenging to develop antipersister strategies. Here, we report that 10-s freezing with liquid nitrogen dramatically enhances the bactericidal action of aminoglycoside antibiotics by 2 to 6 orders of magnitude against many Gram-negative pathogens, with weaker potentiation effects on Gram-positive bacteria. In particular, antibiotic-tolerant Escherichia coli and Pseudomonas aeruginosa persisters—which were prepared by treating exponential-phase cells with ampicillin, ofloxacin, the protonophore cyanide m-chlorophenyl hydrazone (CCCP), or bacteriostatic antibiotics—can be effectively killed. We demonstrated, as a proof of concept, that freezing potentiated the aminoglycosides' killing of P. aeruginosa persisters in a mouse acute skin wound model. Mechanistically, freezing dramatically increased the bacterial uptake of aminoglycosides regardless of the presence of CCCP, indicating that the effects are independent of the proton motive force (PMF). In line with these results, we found that the effects were linked to freezing-induced cell membrane damage and were attributable, at least partly, to the mechanosensitive ion channel MscL, which was able to directly mediate such freezing-enhanced aminoglycoside uptake. In view of these results, we propose that the freezing-induced aminoglycoside potentiation is achieved by freezing-induced cell membrane destabilization, which, in turn, activates the MscL channel, which is able to effectively take up aminoglycosides in a PMF-independent manner. Our work may pave the way for the development of antipersister strategies that utilize the same mechanism as freezing but do so without causing any injury to animal cells

Core signaling pathways in ovarian cancer stem cell revealed by integrative analysis of multi-marker genomics data.

Tumor recurrence occurs in more than 70% of ovarian cancer patients, and the majority eventually becomes refractory to treatments. Ovarian Cancer Stem Cells (OCSCs) are believed to be responsible for the tumor relapse and drug resistance. Therefore, eliminating ovarian CSCs is important to improve the prognosis of ovarian cancer patients. However, there is a lack of effective drugs to eliminate OCSCs because the core signaling pathways regulating OCSCs remain unclear. Also it is often hard for biologists to identify a few testable targets and infer driver signaling pathways regulating CSCs from a large number of differentially expression genes in an unbiased manner. In this study, we propose a straightforward and integrative analysis to identify potential core signaling pathways of OCSCs by integrating transcriptome data of OCSCs isolated based on two distinctive markers, ALDH and side population, with regulatory network (Transcription Factor (TF) and Target Interactome) and signaling pathways. We first identify the common activated TFs in two OCSC populations integrating the gene expression and TF-target Interactome; and then uncover up-stream signaling cascades regulating the activated TFs. In specific, 22 activated TFs are identified. Through literature search validation, 15 of them have been reported in association with cancer stem cells. Additionally, 10 TFs are found in the KEGG signaling pathways, and their up-stream signaling cascades are extracted, which also provide potential treatment targets. Moreover, 40 FDA approved drugs are identified to target on the up-stream signaling cascades, and 15 of them have been reported in literatures in cancer stem cell treatment. In conclusion, the proposed approach can uncover the activated up-stream signaling, activated TFs and up-regulated target genes that constitute the potential core signaling pathways of ovarian CSC. Also drugs and drug combinations targeting on the core signaling pathways might be able to eliminate OCSCs. The proposed approach can also be applied for identifying potential activated signaling pathways of other types of cancers

Gaseous Products Evolution Analyses for Catalytic Decomposition of AP by Graphene-Based Additives

A quantitative evaluation method has been developed to study the effects of nanoadditives on thermal decomposition mechanisms of energetic compounds using the conventional thermogravimetry coupled with mass spectrometry (TG/MS) technique. The decomposition of ammonium perchlorate (AP) under the effect of several energetic catalysts has been investigated as a demonstration. In particular, these catalysts are transition metal (Cu2+, Co2+ and Ni2+) complexes of triaminoguanidine (TAG), using graphene oxide (GO) as dopant. They have been well-compared in terms of their catalytic effects on the concentration of the released gaseous products of AP. These detailed quantitative analyses of the gaseous products of AP provide a proof that the proton transfer between ∙O and O2 determines the catalytic decomposition pathways, which largely depend on the type of reactive centers of the catalysts. This quantitative method could be applied to evaluate the catalytic effects of any other additives on the thermal decomposition of various energetic compounds