519 research outputs found
Wasserstein-infinity stability and mean field limit of discrete interaction energy minimizers
Full text linkIn this paper we give a quantitative stability result for the discrete interaction energy on the multi-dimensional torus, for the periodic Riesz potential. It states that if the number of particles is large and the discrete interaction energy is low, then the particle distribution is necessarily close to the uniform distribution (i.e., the continuous energy minimizer) in the Wasserstein-infinity distance. As a consequence, we obtain a quantitative mean field limit of interaction energy minimizers in the Wasserstein-infinity distance. The proof is based on the application of the author\u27s previous joint work with J. Wang on the stability of continuous energy minimizer, together with a new mollification trick for the empirical measure in the case of singular interaction potentials
Anticancer activities of nanoencapsulated Quercetin in breast cancer cells
No full textBackground: Breast cancer is the second leading cause of cancer-related death in women. Quercetin, a natural flavonoid abundantly present in grapes, red wine, onion, broccoli and other leafy green vegetables, is known to possess potent anti-proliferative effects against various malignant cells, but the low level of water solubility and bioavailability in the body makes administering it in therapeutic doses unrealistic. Therefore, the development of appropriate flavonoid nanocarriers could be of great importance to enhance its solubility and cellular bioavailability. We have successfully synthesized quercetin encapsulated nanostructured lipid carrier (Q-NLC). Our hypothesis is that Q-NLC can enhance quercetin stability, solubility and cellular bioavailability, decrease the viability of breast cancer cells, and induce their apoptosis. This research project can help to develop a novel preventive and therapeutic modality for breast cancer.
Methods: The stability, solubility and cellular bioavailability of quercetin in MCF-7 and MDA-MB-231 breast cancer cells were measured using a high performance liquid chromatography (HPLC) system. Cell viability and apoptosis in MCF-7 and MDA-MB-231 breast cancer cells were measured using a 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay and Annexin-V/PI (propidium iodide) to detect phosphatidylserine exposure on the surface of apoptotic cells, respectively.
Results: Nanoencapsulation significantly increased the stability, solubility, and cellular uptake of quercetin. Q-NLC significantly lowered the proliferation of both MCF-7 and MDA-MB-231 breast cancer cells and induced their apoptosis compared to free quercetin. Cell proliferation decreased significantly in a time- (24h and 48h) and dose-dependent (1 μM to 50 μM) manner.
Conclusion: Q-NLC is a promising approach for the prevention and treatment of breast cancer
Oscillatory Neural Network-Based Ising Machine Using 2D Memristors
No full textNeural networks are increasingly used to solve optimization problems in various fields, including operations research, design automation, and gene sequencing. However, these networks face challenges due to the nondeterministic polynomial time (NP)-hard issue, which results in exponentially increasing computational complexity as the problem size grows. Conventional digital hardware struggles with the von Neumann bottleneck, the slowdown of Moore's law, and the complexity arising from heterogeneous system design. Two-dimensional (2D) memristors offer a potential solution to these hardware challenges, with their in-memory computing, decent scalability, and rich dynamic behaviors. In this study, we explore the use of nonvolatile 2D memristors to emulate synapses in a discrete-time Hopfield neural network, enabling the network to solve continuous optimization problems, like finding the minimum value of a quadratic polynomial, and tackle combinatorial optimization problems like Max-Cut. Additionally, we coupled volatile memristor-based oscillators with nonvolatile memristor synapses to create an oscillatory neural network-based Ising machine, a continuous-time analog dynamic system capable of solving combinatorial optimization problems including Max-Cut and map coloring through phase synchronization. Our findings demonstrate that 2D memristors have the potential to significantly enhance the efficiency, compactness, and homogeneity of integrated Ising machines, which is useful for future advances in neural networks for optimization problems.
Structure and photoluminescence of boron-doped carbon nanoflakes grown by hot filament chemical vapour deposition
No full textBoron-doped carbon nanoflakes were directly synthesized by hot filament chemical vapor deposition, nontoxic boron carbide was used as the boron source. The results of scanning electron microscopy (SEM), micro-Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) indicate that boron is effectively doped in the carbon nanoflakes. The number of defects as well as the density of the carbon nanoflakes is increased due to the doping process. The photoluminescence (PL) properties of carbon nanoflakes with and without boron doping were studied at room temperature, the 325 nm line of He–Cd laser was used as the excitation source. The PL results reveal that the carbon nanoflakes with and without doping of boron can generate both weak blue and strong green PL bands. The results also show a blue shift of PL bands and an enhanced PL intensity after boron doping. This is attributed to an increase in the band gap of carbon nanoflakes upon boron incorporation. These results improve our knowledge of the synthesis and optical properties of graphene-based materials and contribute to the development of graphene-based optoelectronic devices
Determine multiple elements simultaneously in the sera of umbilical cord blood samples - a very simple method
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Seawater carbonate chemistry and molecular pathways, physiological function, biochemical responses, and health status of clams and scallops
No full textIn estuarine ecosystems, bivalves experience large pH fluctuations caused by the anthropogenic elevation of atmospheric CO2 and Cu pollution. This study investigates whether Cu toxicity increases indiscriminately in two bivalve species from different estuarine habitats as a result of elevated Cu bioaccumulation in acidified seawater. This was carried out by evaluating the effects of Cu exposure on two bivalve species (clams and scallops) for 28 d, at a series of gradient pH levels (pH 8.1, 7.8, and 7.6). The results demonstrated an increase in the Cu content in the soft tissues of clams and scallops in acidified seawater. Cu toxicity increased under acidified seawater by affecting the molecular pathways, physiological function, biochemical responses, and health status of clams and scallops. An iTRAQ-based quantitative proteomic analysis showed increased protein turnover, disturbed cytoskeleton and signal transduction pathways, apoptosis, and suppressed energy metabolism pathways in the clams and scallops under joint exposure to ocean acidification and Cu. The integrated biomarker response results suggested that scallops were more sensitive to Cu toxicity and/or ocean acidification than clams. The proteomic results suggested that the increased energy metabolism and suppressed protein turnover rates may contribute to a higher resistivity to ocean acidification in clams than scallops. Overall, this study provides molecular insights into the distinct sensitivities between two bivalve species from different habitats under exposure to ocean acidification and/or Cu. The findings emphasize the aggravating impact of ocean acidification on Cu toxicity in clams and scallops. The results show that ocean acidification and copper pollution may reduce the long-term viability of clams and scallops, and lead to the degradation of estuarine ecosystems
Economic Policy Uncertainty and Bank Stability: An Analysis Based on the Intermediary Effects of Opacity
No full textWith the background of deepening uncertainty about global and Chinese economic policy, the stability of the banking industry is of great strategic significance for promoting the high-quality development of the real economy and maintaining the order of the financial market. This paper uses the panel data of 32 commercial banks in China during the period of 2007–2020 to test the impact of economic policy uncertainty on bank stability and the mediating role of opacity. The research results show that the economic policy uncertainty has a negative impact on bank stability. Opacity plays a partial intermediary role between economic policy uncertainty and bank stability: economic policy uncertainty indirectly affects bank stability by stimulating banks to reduce market exposure and improve earnings opacity
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