Thermal Blood Clot Formation and use in Microfluidic Device Valving Applications

The present invention provides a method of forming a blood-clot microvalve by heating blood in a capillary tube of a microfluidic device. Also described are methods of modulating liquid flow in a capillary tube by forming and removing a blood-clot microvalve

Can Variational Quantum Algorithms Demonstrate Quantum Advantages? Time Really Matters

Applying low-depth quantum neural networks (QNNs), variational quantum algorithms (VQAs) are both promising and challenging in the noisy intermediate-scale quantum (NISQ) era: Despite its remarkable progress, criticisms on the efficiency and feasibility issues never stopped. However, whether VQAs can demonstrate quantum advantages is still undetermined till now, which will be investigated in this paper. First, we will prove that there exists a dependency between the parameter number and the gradient-evaluation cost when training QNNs. Noticing there is no such direct dependency when training classical neural networks with the backpropagation algorithm, we argue that such a dependency limits the scalability of VQAs. Second, we estimate the time for running VQAs in ideal cases, i.e., without considering realistic limitations like noise and reachability. We will show that the ideal time cost easily reaches the order of a 1-year wall time. Third, by comparing with the time cost using classical simulation of quantum circuits, we will show that VQAs can only outperform the classical simulation case when the time cost reaches the scaling of $10^0$-$10^2$ years. Finally, based on the above results, we argue that it would be difficult for VQAs to outperform classical cases in view of time scaling, and therefore, demonstrate quantum advantages, with the current workflow. Since VQAs as well as quantum computing are developing rapidly, this work does not aim to deny the potential of VQAs. The analysis in this paper provides directions for optimizing VQAs, and in the long run, seeking more natural hybrid quantum-classical algorithms would be meaningful.Comment: 18 pages, 7 figure

(E)-N′-[1-(2-Hy­droxy­phen­yl)ethyl­idene]-2-phen­oxy­acetohydrazide–2,2′-(1,1′-azinodiethyl­idyne)diphenol (2/1)

The formula unit of the title mol­ecular complex, 2C16H16N2O3·C16H16N2O2, consists of two (E)-N′-[1-(2-hy­droxy­phen­yl)ethyl­idene]-2-phen­oxy­acetohydrazide mol­ecules and one mol­ecule of 2,2′-(1,1′-azinodiethyl­idyne)diphenol, with the latter located on a crystallographic inversion center. The acetohydrazide mol­ecules are linked into a supermolecular chain along the c axis by inter­molecular N—H⋯O hydrogen bonds. There are also intra­molecular O—H⋯N hydrogen bonds in both the acetohydrazide and diphenol mol­ecules

Mars Atmospheric Entry Integrated Navigation with Partial Intermittent Measurements

Signal degradation suffered by the vehicle is a combination brownout and blackout during Mars atmospheric entry. The communications brownout means that signal fades and blackout means that the signal is lost completely. The communications brownout and blackout periods are analyzed and predicted with an altitude and velocity profiles. In the brownout period, the range measurements between the vehicle and the orbiters are modeled as intermittent measurements with the radio signal arrival probabilities, which are distributed as a Rayleigh distribution of the electron number density around the entry vehicle. A new integrated navigation strategy during the Mars atmospheric entry phase is proposed to consider the probabilities of the radio measurements in the communications brownout and blackout periods under the IMU/beacon scenario based on the information filter with intermittent measurements. Numerical navigation simulations are designed to show the performance of the proposed navigation strategy under the integrated navigation scenario

Fucosyltransferase 1 and 2 play pivotal roles in breast cancer cells.

FUT1 and FUT2 encode alpha 1, 2-fucosyltransferases which catalyze the addition of alpha 1, 2-linked fucose to glycans. Glycan products of FUT1 and FUT2, such as Globo H and Lewis Y, are highly expressed on malignant tissues, including breast cancer. Herein, we investigated the roles of FUT1 and FUT2 in breast cancer. Silencing of FUT1 or FUT2 by shRNAs inhibited cell proliferation in vitro and tumorigenicity in mice. This was associated with diminished properties of cancer stem cell (CSC), including mammosphere formation and CSC marker both in vitro and in xenografts. Silencing of FUT2, but not FUT1, significantly changed the cuboidal morphology to dense clusters of small and round cells with reduced adhesion to polystyrene and extracellular matrix, including laminin, fibronectin and collagen. Silencing of FUT1 or FUT2 suppressed cell migration in wound healing assay, whereas FUT1 and FUT2 overexpression increased cell migration and invasion in vitro and metastasis of breast cancer in vivo. A decrease in mesenchymal like markers such as fibronectin, vimentin, and twist, along with increased epithelial like marker, E-cadherin, was observed upon FUT1/2 knockdown, while the opposite was noted by overexpression of FUT1 or FUT2. As expected, FUT1 or FUT2 knockdown reduced Globo H, whereas FUT1 or FUT2 overexpression showed contrary effects. Exogenous addition of Globo H-ceramide reversed the suppression of cell migration by FUT1 knockdown but not the inhibition of cell adhesion by FUT2 silencing, suggesting that at least part of the effects of FUT1/2 knockdown were mediated by Globo H. Our results imply that FUT1 and FUT2 play important roles in regulating growth, adhesion, migration and CSC properties of breast cancer, and may serve as therapeutic targets for breast cancer

A Missing Key to Understand the Electrical Resonance and the Mechanical Property of Neurons: a Channel-Membrane Interaction Mechanism

The recent study of the interaction between the fatty acyl tails of lipids and the K+ channel establishes the connection between flexoelectricity and the ion channel's dynamics, named Channel-Membrane Interaction (CMI), that may solve the electrical resonance in neurons

Evaluation of oral Lanzhou lamb rotavirus vaccine via passive transfusion with CD4+/CD8+ T lymphocytes

AbstractLanzhou Lamb derived Rotavirus (RV) Vaccine (namely LLR) for children is only used in China. Since there were no reports on evaluation of LLR, even the data of phase IV clinical trial, we proceed the evaluation of LLR through focusing on T-cell to investigate whether LLR could induce the potential function involving in protection as a vaccine. Four groups of nude mice were transfused with CD4+/CD8+ T-cells isolated from LLR-immunized (primed) and LLR-unimmunized (naïve) mice via intraperitonea (i.p.) respectively. Consequently, the adoption mice were challenged with mice-origin wild rotavirus EDIM (Epizootic Diarrhea of Infant Mice) by intragastric administration. Series of fecal/serum samples were collected and viral shedding, then serum IgA/IgG and secreted IgA were assayed. Compared to the mice transfused with T lymphocytes from naïve mice, the nude mice transfused with CD4+ T lymphocytes from primed mice induce fecal and serum IgA increasing more rapidly, and have a shorter duration of virus shedding too. Whereas, no significant difference in virus clearance was found between the mice transfused with CD8+ T lymphocytes isolated from primed and naïve mice. Therefore, we cleared the distinct roles of transfused CD4+/CD8+ T lymphocytes for rotavirus clearance in nude mice, that the viral clearance conducted by CD4+ T lymphocytes. Meanwhile, it has ability to help induction of LLR specific immunogenicity. Comparing with the transfusion of cell from primed and naïve mice, LLR can induce CD4+ T lymphocytes memory which is a potential index to reflect the immunogenicity and protection, while CD8+ T lymphocytes remove rotavirus by CTL with little memory ability

End-to-End Quantum Vision Transformer: Towards Practical Quantum Speedup in Large-Scale Models

The field of quantum deep learning presents significant opportunities for advancing computational capabilities, yet it faces a major obstacle in the form of the "information loss problem" due to the inherent limitations of the necessary quantum tomography in scaling quantum deep neural networks. This paper introduces an end-to-end Quantum Vision Transformer (QViT), which incorporates an innovative quantum residual connection technique, to overcome these challenges and therefore optimize quantum computing processes in deep learning. Our thorough complexity analysis of the QViT reveals a theoretically exponential and empirically polynomial speedup, showcasing the model's efficiency and potential in quantum computing applications. We conducted extensive numerical tests on modern, large-scale transformers and datasets, establishing the QViT as a pioneering advancement in applying quantum deep neural networks in practical scenarios. Our work provides a comprehensive quantum deep learning paradigm, which not only demonstrates the versatility of current quantum linear algebra algorithms but also promises to enhance future research and development in quantum deep learning.Comment: 24pages, 10 figure

Targeting homologous recombination and telomerase in Barrett’s adenocarcinoma: Impact on telomere maintenance, genomic instability, and tumor growth

Homologous recombination (HR), a mechanism to accurately repair DNA in normal cells, is deregulated in cancer. Elevated/deregulated HR is implicated in genomic instability and telomere maintenance, which are critical lifelines of cancer cells. We have previously shown that HR activity is elevated and significantly contributes to genomic instability in BAC. The purpose of this study was to evaluate therapeutic potential of HR inhibition, alone and in combination with telomerase inhibition, in BAC. We demonstrate that telomerase inhibition in BAC cells increases HR activity, RAD51 expression, and association of RAD51 to telomeres. Suppression of HR leads to shorter telomeres as well as markedly reduced genomic instability in BAC cells over time. Combination of HR suppression (whether transgenic or chemical) with telomerase inhibition, causes a significant increase in telomere attrition and apoptotic death in all BAC cell lines tested, relative to either treatment alone. A subset of treated cells also stain positive for β-galactosidase, indicating senescence. The combined treatment is also associated with decline in S-phase and a strong G2/M arrest, indicating massive telomere attrition. In a subcutaneous tumor model, the combined treatment resulted in the smallest tumors, which were even smaller (P=0.001) than those resulted from either treatment alone. Even the tumors removed from these mice had significantly reduced telomeres and evidence of apoptosis. We therefore conclude that although telomeres are elongated by telomerase, elevated RAD51/HR assist in their maintenance/stabilization in BAC cells. Telomerase inhibitor prevents telomere elongation but induces RAD51/HR, which contribute to telomere maintenance/stabilization and prevention of apoptosis, reducing the efficacy of treatment. Combining HR inhibition with telomerase, makes telomeres more vulnerable to degradation and significantly increases/expedites their attrition, leading to apoptosis. We therefore demonstrate that a therapy, targeting HR and telomerase, has potential to prevent both the tumor growth and genomic evolution in BAC