ORY-1001 Suppresses Cell Growth and Induces Apoptosis in Lung Cancer Through Triggering HK2 Mediated Warburg Effect

ORY-1001, an inhibitor of covalent lysine (K)-specific demethylase 1A (KDM1A), has been used as a therapy for the treatment of acute leukemia. However, the underlying mechanisms of anticancer are still not fully elucidated. Here, we report that KDM1A is highly expressed in lung cancers, where it appears to drive aggressive growth. Furthermore, lung cancer patients with higher KDM1A levels have worse survival outcomes than patients with lower KDM1A levels. Interestingly, ORY-1001significantly inhibited the cell proliferation, colony formation, cell cycle, and induced apoptosis, by regulating the Warburg effect through controlling Hexokinases 2 (HK2) expression. In summary, these results indicate that ORY-1001 could inhibit the growth of lung cancer cells via regulating the Warburg effect by controlling HK2

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Characterization of the Interaction between Gallic Acid and Lysozyme by Molecular Dynamics Simulation and Optical Spectroscopy

The binding interaction between gallic acid (GA) and lysozyme (LYS) was investigated and compared by molecular dynamics (MD) simulation and spectral techniques. The results from spectroscopy indicate that GA binds to LYS to generate a static complex. The binding constants and thermodynamic parameters were calculated. MD simulation revealed that the main driving forces for GA binding to LYS are hydrogen bonding and hydrophobic interactions. The root-mean-square deviation verified that GA and LYS bind to form a stable complex, while the root-mean-square fluctuation results showed that the stability of the GA-LYS complex at 298 K was higher than that at 310 K. The calculated free binding energies from the molecular mechanics/Poisson-Boltzmann surface area method showed that van der Waals forces and electrostatic interactions are the predominant intermolecular forces. The MD simulation was consistent with the spectral experiments. This study provides a reference for future study of the pharmacological mechanism of GA

Design of Cooperative Guidance Law Considering Missile Field-of-View Constraint and Impact Point Attitude Constraint

Aiming at the problem of limited field-of-view of air-to-air missile during cooperative attack, a cooperative guidance law with field-of-view angle and impact point attitude constraints is proposed. After the engagement geometric model between the missile and the maneuvering target is established in the vertical plane, the guidance law is designed. Firstly, based on the time-varying sliding mode surface, the guidance law of the normal direction of the line of sight is designed, and the integral obstacle Lyapunov function is selected to ensure that the missile can stably track the target during the attacking process, and the missile can attack the target at the expected impact point angle. The integral obstacle Lyapunov function is selected to prove the convergence of the guidance law. Secondly, on the basis of estimating the remaining time of the attack, a guidance law with time constraints is designed to ensure that the missile hits the target at the preset time. Finally, the feasibility of the guidance law is verified by simulation in three scenarios

Medical Image Denoising Algorithm Based on Sparse Nonlocal Regularized Weighted Coding and Low Rank Constraint

Medical image information may be polluted by noise in the process of generation and transmission, which will seriously hinder the follow-up image processing and medical diagnosis. In medical images, there is a typical mixed noise composed of additive white Gaussian noise (AWGN) and impulse noise. In the conventional denoising methods, impulse noise is first removed, followed by the elimination of white Gaussian noise (WGN). However, it is difficult to separate the two kinds of noises completely in practical application. The existing denoising algorithm of weight coding based on sparse nonlocal regularization, which can simultaneously remove AWGN and impulse noise, is plagued by the problems of incomplete noise removal and serious loss of details. The denoising algorithm based on sparse representation and low rank constraint can preserve image details better. Thus, a medical image denoising algorithm based on sparse nonlocal regularization weighted coding and low rank constraint is proposed. The denoising effect of the proposed method and the original algorithm on computed tomography (CT) image and magnetic resonance (MR) image are compared. It is revealed that, under different σ and ρ values, the PSNR and FSIM values of CT and MRI images are evidently superior to those of traditional algorithms, suggesting that the algorithm proposed in this work has better denoising effects on medical images than traditional denoising algorithms

Robust Reconstruction of Electrocardiogram Using Photoplethysmography: A Subject-Based Model

Electrocardiography and photoplethysmography are non-invasive techniques that measure signals from the cardiovascular system. While the cycles of the two measurements are highly correlated, the correlation between the waveforms has rarely been studied. Measuring the photoplethysmogram (PPG) is much easier and more convenient than the electrocardiogram (ECG). Recent research has shown that PPG can be used to reconstruct the ECG, indicating that practitioners can gain a deep understanding of the patients' cardiovascular health using two physiological signals (PPG and ECG) while measuring only PPG. This study proposes a subject-based deep learning model that reconstructs an ECG using a PPG and is based on the bidirectional long short-term memory model. Because the ECG waveform may vary from subject to subject, this model is subject-specific. The model was tested using 100 records from the MIMIC III database. Of these records, 50 had a circulatory disease. The results show that a long ECG signal could be effectively reconstructed from PPG, which is, to our knowledge, the first attempt in this field. A length of 228 s of ECG was constructed by the model, which was trained and validated using 60 s of PPG and ECG signals. To segment the data, a different approach that segments the data into short time segments of equal length (and that do not rely on beats and beat detection) was investigated. Segmenting the PPG and ECG time series data into equal segments of 1-min width gave the optimal results. This resulted in a high Pearson's correlation coefficient between the reconstructed 228 s of ECG and referenced ECG of 0.818, while the root mean square error was only 0.083 mV, and the dynamic time warping distance was 2.12 mV per second on average.ISSN:1664-042