424 research outputs found

    Jacobi pseudo-spectral Galerkin method for second kind Volterra integro-differential equations with a weakly singular kernel

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    The Jacobi pseudo-spectral Galerkin method for the Volterra integro-differential equations of the second kind with a weakly singular kernel is proposed in this paper. We provide a rigorous error analysis for the proposed method, which indicates that the numerical errors (in the Lωα,β2-norm and the L∞-norm) will decay exponentially provided that the source function is sufficiently smooth. Numerical examples are given to illustrate the theoretical results

    Activation of β-catenin and Akt pathways by Twist are critical for the maintenance of EMT associated cancer stem cell-like characters

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    <p>Abstract</p> <p>Background</p> <p>Epithelial-mesenchymal transition (EMT) not only confers tumor cells with a distinct advantage for metastatic dissemination, but also it provides those cells with cancer stem cell-like characters for proliferation and drug resistance. However, the molecular mechanism for maintenance of these stem cell-like traits remains unclear.</p> <p>Methods</p> <p>In this study, we induced EMT in breast cancer MCF7 and cervical cancer Hela cells with expression of Twist, a key transcriptional factor of EMT. The morphological changes associated with EMT were analyzed by immunofluorescent staining and Western blotting. The stem cell-like traits associated with EMT were determined by tumorsphere-formation and expression of ALDH1 and CD44 in these cells. The activation of β-catenin and Akt pathways was examined by Western blotting and luciferase assays.</p> <p>Results</p> <p>We found that expression of Twist induced a morphological change associated with EMT. We also found that the cancer stem cell-like traits, such as tumorsphere formation, expression of ALDH1 and CD44, were significantly elevated in Twist-overexpressing cells. Interestingly, we showed that β-catenin and Akt pathways were activated in these Twist-overexpressing cells. Activation of β-catenin correlated with the expression of CD44. Knockdown of β-catenin expression and inhibition of the Akt pathway greatly suppressed the expression of CD44.</p> <p>Conclusions</p> <p>Our results indicate that activation of β-catenin and Akt pathways are required for the sustention of EMT-associated stem cell-like traits.</p

    Ecophysiological responses of black spruce (Picea mariana) seedlings to nutrient supply, N-P-K ratio and photoperiod at current and elevated CO2 concentration

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    The relationship between plant growth and nitrogen supply is frequently used in growth models to predict growth performance under global climate change scenarios. However, the relationship may be changed under elevated [CO2]. Furthermore, plant responses to nitrogen supply may be modified by N-P-K ratio. Researchers using climate envelope models predict that boreal tree species will migrate northward during progress of the global warming associated with increasing atmospheric CO2 and changes in precipitation. However, changes in photoperiod and nutrient supply associated with the northward migration to higher latitudes may influence survival and growth of the migrated plants

    Auricle shaping using 3D printing and autologous diced cartilage.

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    ObjectiveTo reconstruct the auricle using a porous, hollow, three-dimensional (3D)-printed mold and autologous diced cartilage mixed with platelet-rich plasma (PRP).MethodsMaterialise Magics v20.03 was used to design a 3D, porous, hollow auricle mold. Ten molds were printed by selective laser sintering with polyamide. Cartilage grafts were harvested from one ear of a New Zealand rabbit, and PRP was prepared using 10 mL of auricular blood from the same animal. Ear cartilage was diced into 0.5- to 2.0-mm pieces, weighed, mixed with PRP, and then placed inside the hollow mold. Composite grafts were then implanted into the backs of respective rabbits (n = 10) for 4 months. The shape and composition of the diced cartilage were assessed histologically, and biomechanical testing was used to determine stiffness.ResultsThe 3D-printed auricle molds were 0.6-mm thick and showed connectivity between the internal and external surfaces, with round pores of 0.1 to 0.3 cm. After 4 months, the diced cartilage pieces had fused into an auricular shape with high fidelity to the anthropotomy. The weight of the diced cartilage was 5.157 ± 0.230 g (P &gt; 0.05, compared with preoperative). Histological staining showed high chondrocyte viability and the production of collagen II, glycosaminoglycans, and other cartilaginous matrix components. In unrestricted compression tests, auricle stiffness was 0.158 ± 0.187 N/mm, similar to that in humans.ConclusionAuricle grafts were constructed successfully through packing a 3D-printed, porous, hollow auricle mold with diced cartilage mixed with PRP. The auricle cartilage contained viable chondrocytes, appropriate extracellular matrix components, and good mechanical properties.Levels of evidenceNA. Laryngoscope, 129:2467-2474, 2019

    Reconciling periodic rhythms of large-scale biological networks by optimal control

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    Periodic rhythms are ubiquitous phenomena that illuminate the underlying mechanism of cyclic activities in biological systems, which can be represented by cyclic attractors of the related biological network. Disorders of periodic rhythms are detrimental to the natural behaviours of living organisms. Previous studies have shown that the state transition from one to another attractor can be accomplished by regulating external signals. However, most of these studies until now have mainly focused on point attractors while ignoring cyclic ones. The aim of this study is to investigate an approach for reconciling abnormal periodic rhythms, such as diminished circadian amplitude and phase delay, to the regular rhythms of complex biological networks. For this purpose, we formulate and solve a mixed-integer nonlinear dynamic optimization problem simultaneously to identify regulation variables and to determine optimal control strategies for state transition and adjustment of periodic rhythms. Numerical experiments are implemented in three examples including a chaotic system, a mammalian circadian rhythm system and a gastric cancer gene regulatory network. The results show that regulating a small number of biochemical molecules in the network is sufficient to successfully drive the system to the target cyclic attractor by implementing an optimal control strategy

    Self-Asymmetric Invertible Network for Compression-Aware Image Rescaling

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    High-resolution (HR) images are usually downscaled to low-resolution (LR) ones for better display and afterward upscaled back to the original size to recover details. Recent work in image rescaling formulates downscaling and upscaling as a unified task and learns a bijective mapping between HR and LR via invertible networks. However, in real-world applications (e.g., social media), most images are compressed for transmission. Lossy compression will lead to irreversible information loss on LR images, hence damaging the inverse upscaling procedure and degrading the reconstruction accuracy. In this paper, we propose the Self-Asymmetric Invertible Network (SAIN) for compression-aware image rescaling. To tackle the distribution shift, we first develop an end-to-end asymmetric framework with two separate bijective mappings for high-quality and compressed LR images, respectively. Then, based on empirical analysis of this framework, we model the distribution of the lost information (including downscaling and compression) using isotropic Gaussian mixtures and propose the Enhanced Invertible Block to derive high-quality/compressed LR images in one forward pass. Besides, we design a set of losses to regularize the learned LR images and enhance the invertibility. Extensive experiments demonstrate the consistent improvements of SAIN across various image rescaling datasets in terms of both quantitative and qualitative evaluation under standard image compression formats (i.e., JPEG and WebP).Comment: Accepted by AAAI 2023. Code is available at https://github.com/yang-jin-hai/SAI