Although cisplatin has been a pivotal chemotherapy drug in treating patients with various types of cancer for decades, drug resistance has been a major clinical impediment. In general, cisplatin ...exerts cytotoxic effects in tumor cells mainly through the generation of DNA-platinum adducts and subsequent DNA damage response. Accordingly, considerable effort has been devoted to clarify the resistance mechanisms inside tumor cells, such as decreased drug accumulation, enhanced detoxification activity, promotion of DNA repair capacity, and inactivated cell death signaling. However, recent advances in high-throughput techniques, cell culture platforms, animal models, and analytic methods have also demonstrated that the tumor microenvironment plays a key role in the development of cisplatin resistance. Recent clinical successes in combination treatments with cisplatin and novel agents targeting components in the tumor microenvironment, such as angiogenesis and immune cells, have also supported the therapeutic value of these components in cisplatin resistance. In this review, we summarize resistance mechanisms with respect to a single tumor cell and crucial components in the tumor microenvironment, particularly focusing on favorable results from clinical studies. By compiling emerging evidence from preclinical and clinical studies, this review may provide insights into the development of a novel approach to overcome cisplatin resistance.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) are cornerstone reactions for many renewable energy technologies. Developing cheap yet durable substitutes of precious‐metal ...catalysts, especially the bifunctional electrocatalysts with high activity for both ORR and OER reactions and their streamlined coupling process, are highly desirable to reduce the processing cost and complexity of renewable energy systems. Here, a facile strategy is reported for synthesizing double‐shelled hybrid nanocages with outer shells of Co‐N‐doped graphitic carbon (Co‐NGC) and inner shells of N‐doped microporous carbon (NC) by templating against core–shell metal–organic frameworks. The double‐shelled NC@Co‐NGC nanocages well integrate the high activity of Co‐NGC shells into the robust NC hollow framework with enhanced diffusion kinetics, exhibiting superior electrocatalytic properties to Pt and RuO2 as a bifunctional electrocatalyst for ORR and OER, and hold a promise as efficient air electrode catalysts in Zn–air batteries. First‐principles calculations reveal that the high catalytic activities of Co‐NGC shells are due to the synergistic electron transfer and redistribution between the Co nanoparticles, the graphitic carbon, and the doped N species. Strong yet favorable adsorption of an OOH* intermediate on the high density of uncoordinated hollow‐site C atoms with respect to the Co lattice in the Co‐NGC structure is a vital rate‐determining step to achieve excellent bifunctional electrocatalytic activity.
A new strategy is developed for constructing a hollow nanostructured bifunctional oxygen reduction reaction/oxygen evolution reaction electrocatalyst with integrated high activity and fast kinetics by surface‐stabilized heterogeneous contraction of core–shell metal–organic frameworks. The resultant double‐shelled hybrid nanocages with an outer shell of mesoporous Co‐N‐doped graphitic carbon and an inner shell of microporous N‐doped carbon exhibit superior electrocatalytic performance to noble metals for oxygen reduction and evolution reactions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Let
F
be a local non-Archimedean field of characteristic zero with a finite residue field. Based on Tadić’s classification of the unitary dual of
GL
2
n
(
F
)
, we classify irreducible unitary ...representations of
GL
2
n
(
F
)
that have nonzero linear periods, in terms of Speh representations that have nonzero periods. We also give a necessary and sufficient condition for the existence of a nonzero linear period for a Speh representation.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Abstract
Response lag is an inevitable problem for most electrochemical gas sensors, while the information about gas concentration and trends should be obtained immediately in some specific fields. ...Therefore, focusing on the goal of improving the accuracy and time efficiency of gas concentration prediction, and adopting data-driven method, this paper proposes a novel regression prediction model—Denoising Deep Forest(DDF). Comparative experiment’s results show that Denoising Deep Forest’s MAPE value is 4.43% and R
2
value is 0.991 on ethylene oxide gas leakage detection dataset, which outperforms other common models. Moreover, this paper designs a noise-influence experiment to further test the performance of the models. The results of noise-influence experiment indecate that compared with the common models, Denoising Deep Forest has stronger anti-noise ability and it can maintain the robust performance on data with various noises.
Recent progress in electronic skin or e‐skin research is broadly reviewed, focusing on technologies needed in three main applications: skin‐attachable electronics, robotics, and prosthetics. First, ...since e‐skin will be exposed to prolonged stresses of various kinds and needs to be conformally adhered to irregularly shaped surfaces, materials with intrinsic stretchability and self‐healing properties are of great importance. Second, tactile sensing capability such as the detection of pressure, strain, slip, force vector, and temperature are important for health monitoring in skin attachable devices, and to enable object manipulation and detection of surrounding environment for robotics and prosthetics. For skin attachable devices, chemical and electrophysiological sensing and wireless signal communication are of high significance to fully gauge the state of health of users and to ensure user comfort. For robotics and prosthetics, large‐area integration on 3D surfaces in a facile and scalable manner is critical. Furthermore, new signal processing strategies using neuromorphic devices are needed to efficiently process tactile information in a parallel and low power manner. For prosthetics, neural interfacing electrodes are of high importance. These topics are discussed, focusing on progress, current challenges, and future prospects.
Recent progress in electronic skin research is broadly reviewed, focusing on the technologies required in the following three applications: skin‐attachable electronics, robotics, and prosthetics. Topics such as stretchability, self‐healing, biocompatibility, tactile sensing, chemical and electrophysiological sensing, wireless communication, large‐area integration, neuromorphic signal processing, and neural interfaces are discussed.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Oxide-supported noble metal catalysts have been extensively studied for decades for the water gas shift (WGS) reaction, a catalytic transformation central to a host of large volume processes that ...variously utilize or produce hydrogen. There remains considerable uncertainty as to how the specific features of the active metal-support interfacial bonding-perhaps most importantly the temporal dynamic changes occurring therein-serve to enable high activity and selectivity. Here we report the dynamic characteristics of a Pt/CeO
system at the atomic level for the WGS reaction and specifically reveal the synergistic effects of metal-support bonding at the perimeter region. We find that the perimeter Pt
- O vacancy-Ce
sites are formed in the active structure, transformed at working temperatures and their appearance regulates the adsorbate behaviors. We find that the dynamic nature of this site is a key mechanistic step for the WGS reaction.
Abstract
With the goal of charting plant transcriptional regulatory maps (i.e. transcription factors (TFs), cis-elements and interactions between them), we have upgraded the TF-centred database ...PlantTFDB (http://planttfdb.cbi.pku.edu.cn/) to a plant regulatory data and analysis platform PlantRegMap (http://plantregmap.cbi.pku.edu.cn/) over the past three years. In this version, we updated the annotations for the previously collected TFs and set up a new section, ‘extended TF repertoires’ (TFext), to allow users prompt access to the TF repertoires of newly sequenced species. In addition to our regular TF updates, we are dedicated to updating the data on cis-elements and functional interactions between TFs and cis-elements. We established genome-wide conservation landscapes for 63 representative plants and then developed an algorithm, FunTFBS, to screen for functional regulatory elements and interactions by coupling the base-varied binding affinities of TFs with the evolutionary footprints on their binding sites. Using the FunTFBS algorithm and the conservation landscapes, we further identified over 20 million functional TF binding sites (TFBSs) and two million functional interactions for 21 346 TFs, charting the functional regulatory maps of these 63 plants. These resources are publicly available at PlantRegMap (http://plantregmap.cbi.pku.edu.cn/) and a cloud-based mirror (http://plantregmap.gao-lab.org/), providing the plant research community with valuable resources for decoding plant transcriptional regulatory systems.
Synthetic aperture radar (SAR) imagery has been used as a promising data source for monitoring maritime activities, and its application for oil and ship detection has been the focus of many previous ...research studies. Many object detection methods ranging from traditional to deep learning approaches have been proposed. However, majority of them are computationally intensive and have accuracy problems. The huge volume of the remote sensing data also brings a challenge for real time object detection. To mitigate this problem a high performance computing (HPC) method has been proposed to accelerate SAR imagery analysis, utilizing the GPU based computing methods. In this paper, we propose an enhanced GPU based deep learning method to detect ship from the SAR images. The You Only Look Once version 2 (YOLOv2) deep learning framework is proposed to model the architecture and training the model. YOLOv2 is a state-of-the-art real-time object detection system, which outperforms Faster Region-Based Convolutional Network (Faster R-CNN) and Single Shot Multibox Detector (SSD) methods. Additionally, in order to reduce computational time with relatively competitive detection accuracy, we develop a new architecture with less number of layers called YOLOv2-reduced. In the experiment, we use two types of datasets: A SAR ship detection dataset (SSDD) dataset and a Diversified SAR Ship Detection Dataset (DSSDD). These two datasets were used for training and testing purposes. YOLOv2 test results showed an increase in accuracy of ship detection as well as a noticeable reduction in computational time compared to Faster R-CNN. From the experimental results, the proposed YOLOv2 architecture achieves an accuracy of 90.05% and 89.13% on the SSDD and DSSDD datasets respectively. The proposed YOLOv2-reduced architecture has a similarly competent detection performance as YOLOv2, but with less computational time on a NVIDIA TITAN X GPU. The experimental results shows that the deep learning can make a big leap forward in improving the performance of SAR image ship detection.
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Controlling ferroic orders (ferroelectricity, ferromagnetism and ferroelasticity) by optical methods is a significant challenge due to the large mismatch in energy scales between the order parameter ...coupling strengths and the incident photons. Here, we demonstrate an approach to manipulate multiple ferroic orders in an epitaxial mixed-phase BiFeO3 thin film at ambient temperature via laser illumination. Phase-field simulations indicate that a light-driven flexoelectric effect allows the targeted formation of ordered domains. We also achieved precise sequential laser writing and erasure of different domain patterns, which demonstrates a deterministic optical control of multiferroicity at room temperature. As ferroic orders directly influence susceptibility and conductivity in complex materials, our results not only shed light on the optical control of multiple functionalities, but also suggest possible developments for optoelectronics and related applications.The remote, non-volatile and reversible optical control of ferroic orders is challenging. Here, using laser illumination, multiple orders in epitaxial mixed-phase BiFeO3 are manipulated deterministically using a thermally driven flexoelectric effect.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
With the goal of providing a comprehensive, high-quality resource for both plant transcription factors (TFs) and their regulatory interactions with target genes, we upgraded plant TF database ...PlantTFDB to version 4.0 (http://planttfdb.cbi.pku.edu.cn/). In the new version, we identified 320 370 TFs from 165 species, presenting a more comprehensive genomic TF repertoires of green plants. Besides updating the pre-existing abundant functional and evolutionary annotation for identified TFs, we generated three new types of annotation which provide more directly clues to investigate functional mechanisms underlying: (i) a set of high-quality, non-redundant TF binding motifs derived from experiments; (ii) multiple types of regulatory elements identified from high-throughput sequencing data; (iii) regulatory interactions curated from literature and inferred by combining TF binding motifs and regulatory elements. In addition, we upgraded previous TF prediction server, and set up four novel tools for regulation prediction and functional enrichment analyses. Finally, we set up a novel companion portal PlantRegMap (http://plantregmap.cbi.pku.edu.cn) for users to access the regulation resource and analysis tools conveniently.
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