(Methanolato)(pyridine)[N 2,N 2′-(pyridine-2,6-diyldicarbon­yl)diacetohydra­zide(2–)]iron(III) methanol solvate

In the title complex, [Fe(C11H10N5O4)(CH3O)(C5H5N)]·CH4O, the FeIII ion has a distorted penta­gonal-bipyramidal geometry. In the crystal structure, mol­ecules are linked into one-dimensional chains along [1 ] via inter­molecular O—H⋯O and N—H⋯O hydrogen bonds

Scalable Resource Management for Dynamic MEC: An Unsupervised Link-Output Graph Neural Network Approach

Deep learning has been successfully adopted in mobile edge computing (MEC) to optimize task offloading and resource allocation. However, the dynamics of edge networks raise two challenges in neural network (NN)-based optimization methods: low scalability and high training costs. Although conventional node-output graph neural networks (GNN) can extract features of edge nodes when the network scales, they fail to handle a new scalability issue whereas the dimension of the decision space may change as the network scales. To address the issue, in this paper, a novel link-output GNN (LOGNN)-based resource management approach is proposed to flexibly optimize the resource allocation in MEC for an arbitrary number of edge nodes with extremely low algorithm inference delay. Moreover, a label-free unsupervised method is applied to train the LOGNN efficiently, where the gradient of edge tasks processing delay with respect to the LOGNN parameters is derived explicitly. In addition, a theoretical analysis of the scalability of the node-output GNN and link-output GNN is performed. Simulation results show that the proposed LOGNN can efficiently optimize the MEC resource allocation problem in a scalable way, with an arbitrary number of servers and users. In addition, the proposed unsupervised training method has better convergence performance and speed than supervised learning and reinforcement learning-based training methods. The code is available at \url{https://github.com/UNIC-Lab/LOGNN}

Sympathetic feedback cooling in the optomechanical system consisting of two coupled cantilevers

We present sympathetic cooling in an optomechanical system consisting of two coupled cantilevers. The hybridization of the cantilevers creates a symmetric mode, which is feedback cooled, and an anti-symmetric mode not directly controllable by the feedback. The scheme of sympathetic cooling is adopted to cool the anti-symmetric mode indirectly by parametrically coupling to the feedback-cooled symmetric mode, from which the cooling power can be transferred. Experiment shows that the realization of coherent dynamics plays an essential role in sympathetic cooling, in which optimal cooling is achieved when the mechanical dissipation rate and the strength of coupling become comparable. The sympathetic cooling is improved by increasing the strength of mode coupling to enhance the transfer of cooling power. Also, the limit of sympathetic cooling imposed by the capacity of feedback cooling is reached as the effective temperatures of the two modes approach the strong coherent coupling condition. Our research provides the prospect of extending the cooling techniques to coupled mechanical resonators for a broad application in sensing and information processing

Optimization of Traced Neuron Skeleton Using Lasso-Based Model

Reconstruction of neuronal morphology from images involves mainly the extraction of neuronal skeleton points. It is an indispensable step in the quantitative analysis of neurons. Due to the complex morphology of neurons, many widely used tracing methods have difficulties in accurately acquiring skeleton points near branch points or in structures with tortuosity. Here, we propose two models to solve these problems. One is based on an L1-norm minimization model, which can better identify tortuous structure, namely, a local structure with large curvature skeleton points; the other detects an optimized branch point by considering the combination patterns of all neurites that link to this point. We combined these two models to achieve optimized skeleton detection for a neuron. We validate our models in various datasets including MOST and BigNeuron. In addition, we demonstrate that our method can optimize the traced skeletons from large-scale images. These characteristics of our approach indicate that it can reduce manual editing of traced skeletons and help to accelerate the accurate reconstruction of neuronal morphology

Phenotypic characterization of drug resistance and tumor initiating cancer stem cells from human bone tumor osteosarcoma cell line OS-77

The cancer stem cell theory suggest that presence of small subpopulation of cancer stem cells are the major implication in the cancer treatment and also responsible for tumor recurrence. Based on Hoechst 33342 dye exclusion technique, we have identified about 3.3% of cancer stem like side population (SP) cells from human osteosarcoma OS-77 cell line whose prevalence is significantly reduced to 0.3% after treatment with verapamil. The sphere formation assay revealed that osteosarcoma SP cells are highly capable to form tumor spheres (sarcospheres). Further by immunocytochemistry and RT-PCR, we show that OS-77 SP cells have enhanced expression of stem cell surface markers such as CD44, Nanog and ATP-binding cassette (ABC) transporter gene (ABCG2) which contributes to self-renewal and drug resistance, respectively. Our findings help to designing a novel therapeutic drug which could effectively target the cancer stem cells and prevent the tumor relapse.

Resibufogenin inhibits the growth of human osteosarcoma MG-63 cells via mitochondrial pathway

Resibufogenin, a low molecular weight bufanolide steroid compound, is isolated from the secretion of Asiatic toad Bufogargarizansa Cantor. It possessed both pharmacological and toxicological effects that were experimentally shown by in vitro and in vivo studies. However, the molecular mechanism of cell apoptosis induced by resibufogenin remains elusive. Here, we investigated the apoptosis in resibufogenin-treated human osteosarcoma MG-63 cells. The results showed that resibufogenin could inhibit cell proliferation and induce apoptosis in a dose- and time-dependent manner. Additional investigations proved that a disruption of mitochondrial transmembrane potential and an up-regulation of reactive oxygen species (ROS) in resibufogenin-treated cells were occurred. Upon western blot analysis, it was found that the up-regulation of Apaf-1, cleaved PARP, cleaved caspase-3, cleaved caspase-9, and Bax/Bcl-2, varied with different concentration of resibufogenin. Overall findings suggested that resibufogenin could be used as an effective anti-tumor agent in therapy of osteosarcoma

Co

Different loading rates of photocatalysts Co3O4/C3N4 were prepared by calcination method. Their photocatalytic performances were evaluated by the degradation of methyl blue under visible light irradiation. The results show that the introduction of Co3O4 significantly improves the optical absorption properties of C3N4, which is beneficial to the separation of photogenerated electrons and holes on the surface of catalyst. The prepared Co3O4/C3N4 for visible photocatalytic degradation of methyl blue has higher catalytic efficiency than that of pure C3N4 or pure Co3O4. The best cobalt loading rate was 30% when the concentration of methylene blue was 40 mg/L. Recycling rate of 30% Co3O4/C3N4 composite catalyst was studied. After 4 cycles, the degradation rate was only slightly decreased from 86.8% to 82.8%, indicating the catalyst with good photostability and repeatability.nbs