Formulation of DOX-dimer with bi-functionalized chitooligosaccharide for tumor-specific self-boosted drug release and synergistic chemo/chemodynamic therapy.

The toxic side effects and possible drug resistance of the chemotherapeutics hinder their antitumor efficacy. Here, a pH/reactive oxygen species (ROS) dual-triggered nanodrug was developed for the tumor-specific self-boosted drug release and synergistic chemo/chemodynamic therapy, by formulating ROS-cleavable doxorubicin (DOX)-based dimer (DOX-TK-DOX) with bi-functionalized chitooligosaccharide (COS-Fc-TK) with ferrocenecarboxylic acid (Fc) and thioketal (TK). The resultant DOX-TK-DOX/COS-Fc-TK nanoparticles with a high DOX content of 39.70 % showed tumor-specific self-boosted drug release, which was triggered by highly toxic OH generated via Fc-catalyzed Fenton reaction of the endogenous H2O2 in tumor intracellular microenvironment. As a result, a synergistic chemo/chemodynamic therapy with combination index (CI) of 0.94 was achieved for selective treatment of tumors.

Hierarchical Vision Navigation System for Quadruped Robots with Foothold Adaptation Learning.

Legged robots can travel through complex scenes via dynamic foothold adaptation. However, it remains a challenging task to efficiently utilize the dynamics of robots in cluttered environments and to achieve efficient navigation. We present a novel hierarchical vision navigation system combining foothold adaptation policy with locomotion control of the quadruped robots. The high-level policy trains an end-to-end navigation policy, generating an optimal path to approach the target with obstacle avoidance. Meanwhile, the low-level policy trains the foothold adaptation network through auto-annotated supervised learning to adjust the locomotion controller and to provide more feasible foot placement. Extensive experiments in both simulation and the real world show that the system achieves efficient navigation against challenges in dynamic and cluttered environments without prior information.

Regulation of drug release performance using mixed doxorubicin-doxorubicin dimer nanoparticles as a pH-triggered drug self-delivery system.

A mixed drug self-delivery system (DSDS) with high drug content (>50%) was developed to regulate pH-triggered drug release, based on two doxorubicin (DOX)-DOX dimmers: D-DOXADH and D-DOXcar conjugated with acid-labile dynamic covalent bonds (hydrazone and carbamate, respectively) and stabilized with PEGylated D-DOXADH (D-DOXADH-PEG). Owing to the different stability of the dynamic covalent bonds in the two dimers and the noncovalent interaction between them, pH-triggered drug release could be easily regulated by adjusting the feeding ratios of the two DOX-DOX dimers in the mixed DSDS. Similar in vitro cellular toxicity was achieved with the mixed DSDS nanoparticles prepared with different feeding ratios. The mixed DSDS nanoparticles had a similar DOX content and diameter but different drug releasing rates. The MTT assays revealed that a high anti-tumor efficacy could be achieved with the slow-release mixed DSDS nanoparticles.

Chitosan-based DDSs for pH/hypoxia dual-triggered DOX delivery: Facile morphology modulation for higher in vitro cytotoxicity.

The morphology of the drug delivery systems (DDSs) has been recognized to play an important role in their phagocytosis, cellular interaction and distribution. However, it is a technical challenge to simply prepare the non-spherical nanoscaled DDSs. Here, a facile strategy was developed to fabricate the pH/hypoxia dual-responsive nanowires by adding the maleic acid (MAH) and PEG modified chitosan (PEG-SS-CS-MAH) into aqueous solution of DOX. Compared with the PEG-SS-CS-MAH/DOX nanoparticles (NPs) by adding DOX into the PEG-SS-CS-MAH solution, the PEG-SS-CS-MAH/DOX nanowires (NWs) possessed a higher drug loading capacity of 58% and better pH/hypoxia dual-triggered DOX release performance with higher drug release in the simulated tumor intracellular microenvironment but a much lower premature drug leakage in the simulated normal physiological medium. As a result, higher in vitro anti-tumor efficacy was achieved with the PEG-SS-CS-MAH/DOX NWs, demonstrating their promising potential for tumor chemotherapy.

Search for Light Dark Matter-Electron Scattering in the PandaX-II Experiment.

We report constraints on light dark matter through its interactions with shell electrons in the PandaX-II liquid xenon detector with a total 46.9 tonnes/day exposure. To effectively search for these very low energy electron recoils, ionization-only signals are selected from the data. 1821 candidates are identified within an ionization signal range between 50 and 75 photoelectrons, corresponding to a mean electronic recoil energy from 0.08 to 0.15 keV. The 90% C.L. exclusion limit on the scattering cross section between the dark matter and electron is calculated with systematic uncertainties properly taken into account. Under the assumption of point interaction, we provide the world's most stringent limit within the dark matter mass range from 15 to 30 MeV/c^{2}, with the corresponding cross section from 2.5×10^{-37} to 3.1×10^{-38} cm^{2}.

pH-responsive surface charge reversal carboxymethyl chitosan-based drug delivery system for pH and reduction dual-responsive triggered DOX release.

A facile approach was established to fabricate the pH-responsive surface charge reversal carboxymethyl chitosan-based drug delivery system for pH and reduction dual-responsive triggered DOX release, with a reduction responsive sheddable shell via facile organic solvent-free co-precipitation method. In the proposed DDS, DOX was loaded in the pH responsive core of the poly(2-(diisopropylamino)ethyl methacrylate) (PDPA) fragments, which were bioreducibly conjugated onto the PEGylated carboxymethyl chitosan (PEG-CMCS) backbone as reduction responsive sheddable shielding shell. The proposed PEG-CMCS-SS-PDPA/DOX nanoparticles, with a high drug loading capacity of >36 % with drug-loading only in their cores, showed excellent pH and reduction dual-responsive triggered disintegration and DOX release performance with cumulative release >85 % in the simulated tumor intracellular microenvironment but a low drug leakage <8.5 % in the simulated normal physiological medium within 57 h, lower than all the reported CMCS-based DDSs.

Core-shell-corona chitosan-based micelles for tumor intracellular pH-triggered drug delivery: Improving performance by grafting polycation.

Core-shell-corona chitosan-based micelles were designed for the tumor intracellular pH-triggered doxorubicin (DOX) delivery, via a facile in-situ micellization in an aqueous solution of DOX and polyethylene glycol (PEG) and poly(2-(diisopropylamino) ethyl methacrylate) (PDPA) dual-modified chitosan (PEG-g-CS-g-PDPA). The effect of the PDPA modification on the diameter, drug loading-capacity (DLC) and pH-triggered drug release was investigated for the three different polymerization degrees of PDPA (25, 32, and 42) with a similar modification degree of ~22%. The optimized ones, the core-shell-corona DOX/PEG-g-CS-g-PDPA32 micelles possessed a mean hydrodynamic diameter (Dh) of 211 nm and DLC of 54%, showing an excellent pH-triggered drug release with negligible premature drug leakage in 60 h. Such results indicated that grafting polycation could efficiently improve the performance of the chitosan-based drug delivery system (DDS) for tumor chemotherapy.

Stimuli-responsive hybrid cluster bombs of PEGylated chitosan encapsulated DOX-loaded superparamagnetic nanoparticles enabling tumor-specific disassembly for on-demand drug delivery and enhanced MR imaging.

Facile approach was established to fabricate the hybrid cluster bombs of PEGylated chitosan encapsulated doxorubicin (DOX)-loaded superparamagnetic nanoparticles as tumor-specific theranostics for targeted DOX delivery and magnetic resonance (MR) imaging, by simply co-precipitation of poly(ethylene glycol) modified chitosan (CS-PEG), oleylamine modified Fe3O4 (OA-Fe3O4) nanoparticles and DOX. In presence of OA-Fe3O4, the particle size of the DOX/OA-Fe3O4@CS-PEG cluster bombs decreased to around 80 nm from 300 nm of the DOX/CS-PEG nanoparticles, with high drug-loading capacity (DLC) of 24.3% and saturation magnetization (Ms) of 4.11 emu/g, respectively. The in vitro evaluation results indicated that the blank OA-Fe3O4@CS-PEG clusters showed excellent cytocompatibility, while the DOX/OA-Fe3O4@CS-PEG clusters could be uptaken into HepG2 cells to deliver DOX into the cell nuclei with enhanced anti-cancer efficacy in comparison with free DOX. In the tumor intracellular micro-environment, the stimuli-responsive hybrid cluster bombs disassembled and re-self-assembled into the OA-Fe3O4 nanoparticle clusters with higher Ms for MR imaging-guided diagnosis, owing to the tumor-specific DOX release and dissolution of CS-PEG.

Real-Time ECG Delineation with Randomly Selected Wavelet Transform Feature and Random Walk Estimation.

Detection of Electrocardiogram (ECG) characteristic points can provide critical diagnostic information about heart diseases. We propose a novel feature extraction and machine learning scheme for ECG delineation. A new feature, termed as randomly selected wavelet transform (RSWT), is proposed to effectively represent ECG morphology. With the RSWT feature pool, a regression tree is trained to estimate the probability distribution to the direction toward the target point, relative to the current position. The continual random walk through 1D space will eventually produce a reliable region from which the final position of the target point is derived. The evaluation results on QT database show better detection accuracy compared with other studies while providing real-time processing capability.

Bidirectional Recurrent Neural Network And Convolutional Neural Network (BiRCNN) For ECG Beat Classification.

We propose a novel electrocardiogram (ECG) beat classification algorithm using a combination of Bidirectional Recurrent Neural Network (BiRNN) and Convolutional Neural Network (CNN) named as BiRCNN. Our model is an end-to-end model. The morphological features of each ECG beat is extracted by CNN. Then the features of each beat are considered in the context via BiRNN. The assessment on MIT-BIH Arrhythmia Database (MITDB) resulted in a sensitivity of 98.7% and a positive predictivity of 96.4% on average for the VEB class. For the SVEB class, the sensitivity was 92.8%, which was an over 6% promotion compared with the state-of-the-art method, and the positive predictivity was 81.9% on average. The results demonstrate the superior classification performance of our method.

Region Aggregation Network: Improving Convolutional Neural Network for ECG Characteristic Detection.

Detection of ECG characteristic points serves as the first step in automated ECG analysis techniques. We propose a novel end-to-end deep learning scheme called Region Aggregation Network (RAN) for ECG characteristic points de- tection. A 1D Convolutional Neural Network (CNN) is adopted to automatically process ECG signals. A novel strategy of Region Aggregation is proposed to replace the conventional fully connected layer as regressor. Our work provides robust and accurate detection performance on public ECG database. The evaluation results of our method on QT database show comparable detection accuracy compared with state-of-the-art works.

Constraining Dark Matter Models with a Light Mediator at the PandaX-II Experiment.

We search for nuclear recoil signals of dark matter models with a light mediator in PandaX-II, a direct detection experiment in the China Jinping underground laboratory. Using data collected in 2016 and 2017 runs, corresponding to a total exposure of 54 ton day, we set upper limits on the zero-momentum dark matter-nucleon cross section. These limits have a strong dependence on the mediator mass when it is comparable to or below the typical momentum transfer. We apply our results to constrain self-interacting dark matter models with a light mediator mixing with standard model particles, and set strong limits on the model parameter space for the dark matter mass ranging from 5 GeV to 10 TeV.

Limits on Axion Couplings from the First 80 Days of Data of the PandaX-II Experiment.

We report new searches for solar axions and galactic axionlike dark matter particles, using the first low-background data from the PandaX-II experiment at China Jinping Underground Laboratory, corresponding to a total exposure of about 2.7×10^{4} kg day. No solar axion or galactic axionlike dark matter particle candidate has been identified. The upper limit on the axion-electron coupling (g_{Ae}) from the solar flux is found to be about 4.35×10^{-12} in the mass range from 10^{-5} to 1 keV/c^{2} with 90% confidence level, similar to the recent LUX result. We also report a new best limit from the ^{57}Fe deexcitation. On the other hand, the upper limit from the galactic axions is on the order of 10^{-13} in the mass range from 1 to 10 keV/c^{2} with 90% confidence level, slightly improved compared with the LUX.

Dark Matter Results from 54-Ton-Day Exposure of PandaX-II Experiment.

We report a new search for weakly interacting massive particles (WIMPs) using the combined low background data sets acquired in 2016 and 2017 from the PandaX-II experiment in China. The latest data set contains a new exposure of 77.1 live days, with the background reduced to a level of 0.8×10^{-3} evt/kg/day, improved by a factor of 2.5 in comparison to the previous run in 2016. No excess events are found above the expected background. With a total exposure of 5.4×10^{4} kg day, the most stringent upper limit on the spin-independent WIMP-nucleon cross section is set for a WIMP with mass larger than 100 GeV/c^{2}, with the lowest 90% C.L. exclusion at 8.6×10^{-47} cm^{2} at 40 GeV/c^{2}.

Spin-Dependent Weakly-Interacting-Massive-Particle-Nucleon Cross Section Limits from First Data of PandaX-II Experiment.

New constraints are presented on the spin-dependent weakly-interacting-massive-particle–- (WIMP-)nucleon interaction from the PandaX-II experiment, using a data set corresponding to a total exposure of 3.3×10^{4} kg day. Assuming a standard axial-vector spin-dependent WIMP interaction with ^{129}Xe and ^{131}Xe nuclei, the most stringent upper limits on WIMP-neutron cross sections for WIMPs with masses above 10 GeV/c^{2} are set in all dark matter direct detection experiments. The minimum upper limit of 4.1×10^{-41} cm^{2} at 90% confidence level is obtained for a WIMP mass of 40 GeV/c^{2}. This represents more than a factor of 2 improvement on the best available limits at this and higher masses. These improved cross-section limits provide more stringent constraints on the effective WIMP-proton and WIMP-neutron couplings.

Dark Matter Results from First 98.7 Days of Data from the PandaX-II Experiment.

We report the weakly interacting massive particle (WIMP) dark matter search results using the first physics-run data of the PandaX-II 500 kg liquid xenon dual-phase time-projection chamber, operating at the China JinPing underground laboratory. No dark matter candidate is identified above background. In combination with the data set during the commissioning run, with a total exposure of 3.3×10^{4} kg day, the most stringent limit to the spin-independent interaction between the ordinary and WIMP dark matter is set for a range of dark matter mass between 5 and 1000 GeV/c^{2}. The best upper limit on the scattering cross section is found 2.5×10^{-46} cm^{2} for the WIMP mass 40 GeV/c^{2} at 90% confidence level.