Structure-Dependent Nontraditional Intrinsic Fluorescence of Aliphatic Hyperbranched Polyureas.

The nontraditional intrinsic fluorescence (NTIF) of polymers containing heteroatoms has gained considerable attention due to its promising applications in label-free bioimaging. Aliphatic hyperbranched polyureas (aBPUs), which have recently shown great promise in the field of nanomedicine, bear controllable urea groups distributed on the branch points and thus are potential candidate luminogens. However, their NTIF properties and how their structures influence the NTIF properties have not been illustrated yet. Here, we addressed these issues by synthesizing a series of aBPUs with different degrees of branching (DBs) or different modifications. aBPUs exhibited an obvious NTIF phenomenon and with the increase of DBs, the NTIF enhanced as well. Chemical modifications either at the branching ends or in the interior of aBPUs could affect the NTIF performances, which were highly dependent on the types of modification. Disruption of the intra-/intermolecular hydrogen-bonding interactions decreased the NTIF. In addition, poly(ethylene glycol) (PEG)-modified aBPUs could self-assemble into nanospheres, and the formation of nanoassembly led to 89% enhancement on NTIF compared with the homogeneous solution of aBPUs-PEG in dimethylformamide (DMF). Finally, aBPUs-PEG nanoassembly demonstrated a capability in realizing label-free material imaging in vitro. These results shed light on the rational design of the polymer structures to achieve desired fluorescence with unconventional luminophores.

Efficient Hardware Accelerator Design of Non-Linear Optimization Correlative Scan Matching Algorithm in 2D LiDAR SLAM for Mobile Robots.

Simultaneous localization and mapping (SLAM) is the major solution for constructing or updating a map of an unknown environment while simultaneously keeping track of a mobile robot's location. Correlative Scan Matching (CSM) is a scan matching algorithm for obtaining the posterior distribution probability for the robot's pose in SLAM. This paper combines the non-linear optimization algorithm and CSM algorithm into an NLO-CSM (Non-linear Optimization CSM) algorithm for reducing the computation resources and the amount of computation while ensuring high calculation accuracy, and it presents an efficient hardware accelerator design of the NLO-CSM algorithm for the scan matching in 2D LiDAR SLAM. The proposed NLO-CSM hardware accelerator utilizes pipeline processing and module reusing techniques to achieve low hardware overhead, fast matching, and high energy efficiency. FPGA implementation results show that, at 100 MHz clock, the power consumption of the proposed hardware accelerator is as low as 0.79 W, while it performs a scan match at 8.98 ms and 7.15 mJ per frame. The proposed design outperforms the ARM-A9 dual-core CPU implementation with a 92.74% increase and 90.71% saving in computing speed and energy consumption, respectively. It has also achieved 80.3% LUTs, 84.13% FFs, and 20.83% DSPs saving, as well as an 8.17× increase in frame rate and 96.22% improvement in energy efficiency over a state-of-the-art hardware accelerator design in the literature. ASIC implementation in 65 nm can further reduce the computing time and energy consumption per scan to 5.94 ms and 0.06 mJ, respectively, which shows that the proposed NLO-CSM hardware accelerator design is suitable for resource-limited and energy-constrained mobile and micro robot applications.

Design and Analysis of Area and Energy Efficient Reconfigurable Cryptographic Accelerator for Securing IoT Devices.

Achieving low-cost and high-performance network security communication is necessary for Internet of Things (IoT) devices, including intelligent sensors and mobile robots. Designing hardware accelerators to accelerate multiple computationally intensive cryptographic primitives in various network security protocols is challenging. Different from existing unified reconfigurable cryptographic accelerators with relatively low efficiency and high latency, this paper presents design and analysis of a reconfigurable cryptographic accelerator consisting of a reconfigurable cipher unit and a reconfigurable hash unit to support widely used cryptographic algorithms for IoT Devices, which require block ciphers and hash functions simultaneously. Based on a detailed and comprehensive algorithmic analysis of both the block ciphers and hash functions in terms of basic algorithm structures and common cryptographic operators, the proposed reconfigurable cryptographic accelerator is designed by reusing key register files and operators to build unified data paths. Both the reconfigurable cipher unit and the reconfigurable hash unit contain a unified data path to implement Data Encryption Standard (DES)/Advanced Encryption Standard (AES)/ShangMi 4 (SM4) and Secure Hash Algorithm-1 (SHA-1)/SHA-256/SM3 algorithms, respectively. A reconfigurable S-Box for AES and SM4 is designed based on the composite field Galois field (GF) GF(((22)2)2), which significantly reduces hardware overhead and power consumption compared with the conventional implementation by look-up tables. The experimental results based on 65-nm application-specific integrated circuit (ASIC) implementation show that the achieved energy efficiency and area efficiency of the proposed design is 441 Gbps/W and 37.55 Gbps/mm2, respectively, which is suitable for IoT devices with limited battery and form factor. The result of delay analysis also shows that the number of delay cycles of our design can be reduced by 83% compared with the state-of-the-art design, which shows that the proposed design is more suitable for applications including 5G/Wi-Fi/ZigBee/Ethernet network standards to accelerate block ciphers and hash functions simultaneously.

TIM-3: An emerging target in the liver diseases.

T cell immunoglobulin domain and mucin domain-containing molecule 3 (TIM-3) is found expression in the surface of terminally differentiated T cells and belongs to the TIM family of type Ⅰ transmembrane proteins. It binds to the ligand Galectin-9 and mediates T cell apoptosis. As the research progresses, TIM-3 is also expressed in Th17, NK, monocyte, which binds to ligand and induce immune peripheral tolerance in both mice and man. Numerous researches have demonstrated that TIM-3 influences liver diseases, including liver-associated chronic viral infection, liver fibrosis, liver cancer et al and suggest new approaches to intervention. Currently, targeted therapy of TIM-3 is a new treatment in the field of immunization. Although many studies have proven that TIM-3 has an inhibitory effect in vivo, the specific mechanism is not clear. Herein, we summarize the important role of TIM-3 in the regulation of liver disease and prospects for future clinical research. TIM-3 will provide new targets for improving clinical liver disease.

The effects of the PRISMA statement to improve the conduct and reporting of systematic reviews and meta-analyses of nursing interventions for patients with heart failure.

AIMS: The study aims to evaluate the reporting and methodological quality of systematic reviews and meta-analyses on nursing interventions in the field of heart failure and investigate whether reporting and methodological quality has been improved after PRISMA statement was published. METHODS: Pubmed, Cochrane Database of Systematic Review, and Embase databases were searched from inception of databases to July 31, 2018. Two authors independently extracted data from October 1, 2018, to October 31, 2018. AMSTAR and PRISMA checklists were used to assessed methodological and reporting quality. RESULTS: The 50 English articles satisfied inclusion criteria and were published from 2001 to 2017. After introduction of PRISMA statement, significant improvement in reporting of the following items was found: title, search, risk of bias in individual studies, summary measures, study selection, synthesis of results, summary of evidence for PRISMA checklists, and scientific quality of included studies provided (item 7) for AMSTAR checklists. CONCLUSION: There were higher methodological and reporting quality after publication of PRISMA. We recommend authors, readers, reviewers, and editors to become more acquainted with and to more strictly adhere to the PRISMA and AMSTAR.

Quaternary ammonium-tethered hyperbranched polyurea nanoassembly synergized with antibiotics for enhanced antimicrobial efficacy.

The effective transportation of antibiotics to bacteria embedded within a biofilm consisting of a dense matrix of extracellular polymeric substances is still a challenge in the treatment of bacterial biofilm associated infections. Here, we developed an antibiotic nanocarrier constructed from quaternary ammonium-tethered hyperbranched polyureas (HPUs-QA), which showed high loading capacity for a model antibiotic, rifampicin, and high efficacy in the transportation of rifampicin to biofilms. The rifampicin-loaded HPUs-QA nanoassembly (HPUs-Rif/QA) demonstrated a synergistic antimicrobial effect in killing planktonic bacteria and eradicating the corresponding biofilms. Compared to the treatment of bacteria-infected chronic wounds by either HPUs-QA or rifampicin alone, HPUs-Rif/QA showed superior efficacy in promoting wound healing by more effectively inhibiting bacteria colonization. This study highlights the potential of the HPUs-QA nanoassembly in synergistic action with antibiotics for the treatment of biofilm associated infections.

A High-Accuracy and Energy-Efficient CORDIC Based Izhikevich Neuron With Error Suppression and Compensation.

Bio-inspired neuron models are the key building blocks of brain-like neural networks for brain-science exploration and neuromorphic engineering applications. The efficient hardware design of bio-inspired neuron models is one of the challenges to implement brain-like neural networks, as the balancing of model accuracy, energy consumption and hardware cost is very challenging. This paper proposes a high-accuracy and energy-efficient Fast-Convergence COordinate Rotation DIgital Computer (FC-CORDIC) based Izhikevich neuron design. For ensuring the model accuracy, an error propagation model of the Izhikevich neuron is presented for systematic error analysis and effective error reduction. Parameter-Tuning Error Compensation (PTEC) method and Bitwidth-Extension Error Suppression (BEES) method are proposed to reduce the error of Izhikevich neuron design effectively. In addition, by utilizing the FC-CORDIC instead of conventional CORDIC for square calculation in the Izhikevich model, the redundant CORDIC iterations are removed and therefore, both the accumulated errors and required computation are effectively reduced, which significantly improve the accuracy and energy efficiency. An optimized fixed-point design of FC-CORDIC is also proposed to save hardware overhead while ensuring the accuracy. FPGA implementation results exhibit that the proposed Izhikevich neuron design can achieve high accuracy and energy efficiency with an acceptable hardware overhead, among the state-of-the-art designs.

Automatic pulmonary auscultation grading diagnosis of Coronavirus Disease 2019 in China with artificial intelligence algorithms: A cohort study.

BACKGROUND AND OBJECTIVE: Research on automatic auscultation diagnosis of COVID-19 has not yet been developed. We therefore aimed to engineer a deep learning approach for the automated grading diagnosis of COVID-19 by pulmonary auscultation analysis. METHODS: 172 confirmed cases of COVID-19 in Tongji Hospital were divided into moderate, severe and critical group. Pulmonary auscultation were recorded in 6-10 sites per patient through 3M littmann stethoscope and the data were transferred to computer to construct the dataset. Convolutional neural network (CNN) were designed to generate classifications of the auscultation. F1 score, the area under the curve (AUC) of the receiver operating characteristic curve, sensitivity and specificity were quantified. Another 45 normal patients were served as control group. RESULTS: There are about 56.52%, 59.46% and 78.85% abnormal auscultation in the moderate, severe and critical groups respectively. The model showed promising performance with an averaged F1 scores (0.9938 95% CI 0.9923-0.9952), AUC ROC score (0.9999 95% CI 0.9998-1.0000), sensitivity (0.9938 95% CI 0.9910-0.9965) and specificity (0.9979 95% CI 0.9970-0.9988) in identifying the COVID-19 patients among normal, moderate, severe and critical group. It is capable in identifying crackles, wheezes, phlegm sounds with an averaged F1 scores (0.9475 95% CI 0.9440-0.9508), AUC ROC score (0.9762 95% CI 0.9848-0.9865), sensitivity (0.9482 95% CI 0.9393-0.9578) and specificity (0.9835 95% CI 0.9806-0.9863). CONCLUSIONS: Our model is accurate and efficient in automatically diagnosing COVID-19 according to different categories, laying a promising foundation for AI-enabled auscultation diagnosing systems for lung diseases in clinical applications.

A Novel Pyramid Network with Feature Fusion and Disentanglement for Object Detection.

In order to alleviate the scale variation problem in object detection, many feature pyramid networks are developed. In this paper, we rethink the issues existing in current methods and design a more effective module for feature fusion, called multiflow feature fusion module (MF3M). We first construct gate modules and multiple information flows in MF3M to avoid information redundancy and enhance the completeness and accuracy of information transfer between feature maps. Furtherore, in order to reduce the discrepancy of classification and regression in object detection, a modified deformable convolution which is termed task adaptive convolution (TaConv) is proposed in this study. Different offsets and masks are predicted to achieve the disentanglement of features for classification and regression in TaConv. By integrating the above two designs, we build a novel feature pyramid network with feature fusion and disentanglement (FFAD) which can mitigate the scale misalignment and task misalignment simultaneously. Experimental results show that FFAD can boost the performance in most models.

Aptamer-Functionalized Gold Nanostars for on-Demand Delivery of Anticancer Therapeutics.

Gold nanostars (AuNS) are promising carriers for targeted delivery of therapeutic oligonucleotides, but their potential in fabricating an on-demand drug release system in a facile and robust way remains to be explored. In this paper, we used a model aptamer (HApt), acting not only as a target ligand but also as a natural thermal-responsive material, to decorate AuNS. The prepared gold nanoconstruct, HApt@AuNS, displayed stoichiometric loading capacity of the anthracycline drug doxorubicin (Dox). The on-demand drug release was realized by illuminating nanoconstructs with near-infrared (NIR) light. Furthermore, a higher degree of Dox release from the nanoconstructs was achieved in an acidic environment, compared to neutral conditions. The in vitro experiments showed that Dox-intercalation did not affect the cell uptake efficiency of HApt@AuNS, which could enter cells through clathrin-mediated endocytosis and microtubule-dependent active transport to lysosomes. Dox-loaded HApt@AuNS exhibited intracellular on-demand drug release and enhanced toxicity against cancer cells by NIR-irradiation.

Picroside II Protects SH-SY5Y Cells From Autophagy and Apoptosis Following Oxygen Glucose Deprivation/Reoxygen Injury by Inhibiting JNK Signal Pathway.

To explore the neuroprotective effect of picroside (Picr) II on C-Jun NH2-terminal kinase (JNK) signal pathway after oxygen glucose deprivation/reoxygen (OGD/R) in SH-SY5Y cells. In vitro, SH-SY5Y cells were used to establish the OGD/R model, which was divided into the control group, model group, Picr group, and SP600125 (SP) group. Cellular viability was measured by CCK8. Cytotoxicity was assessed with LDH assay kit. Ad-GFP-mRFP-LC3 was used to monitor autophagosome and autolysosome. Apoptoic cells were detected by Annexin V-FITC/PI apoptosis detection kit. The expressions of phospho-JNK and phospho-c-Jun were determined by western blot (WB) and immunofluorescence. The expressions of phospho-MKK4, phospho-Bcl-2, Bax, Beclin-1, and LC3 I/II were determined by WB. In the control group, only limited apoptosis and autophagy was observed, and the expression of associated proteins was very low. After OGD/R, the cellular viability of SH-SY5Y cells was reduced, whereas the cytotoxicity, apoptosis, and autophagy were increased, accompanied with an increase of phospho-MKK4, phospho-JNK, phospho-c-Jun, phospho-Bcl-2, LC3 II, Beclin-1, and Bax. During the reoxygen, treatment with Picr II or SP600125 could strengthen the cellular viability of SH-SY5Y cells, but repress the cytotoxicity, apoptosis, autophagy, and the expressions of associated protein. OGD/R could induce apoptosis and autophagy of SH-SY5Y cells by activating JNK signal pathway. Picr II could protect SH-SY5Y cells from autophagy and apoptosis following OGD/R by inhibiting JNK signal pathway. Anat Rec, 302:2245-2254, 2019. © 2019 American Association for Anatomy.