Structural Engineering of Hierarchical Micro‐nanostructured Ge-C Framework by Controlling the Nucleation for Ultralong Life Li Storage

The rational design of a proper electrode structure with high energy and power densities, long cycling lifespan, and low cost still remains a significant challenge for developing advanced energy storage systems. Germanium is a highly promising anode material for high-performance lithium ion batteries due to its large specific capacity and remarkable rate capability. Nevertheless, poor cycling stability and high price significantly limit its practical application. Herein, a facile and scalable structural engineering strategy is proposed by controlling the nucleation to fabricate a unique hierarchical micro-nanostructured Ge-C framework, featuring high tap density, reduced Ge content, superb structural stability, and a 3D conductive network. The constructed architecture has demonstrated outstanding reversible capacity of 1541.1 mA h g −1 after 3000 cycles at 1000 mA g −1 (with 99.6% capacity retention), markedly exceeding all the reported Ge-C electrodes regarding long cycling stability. Notably, the assembled full cell exhibits superior performance as well. The work paves the way to constructing novel metal-carbon materials with high performance and low cost for energy-related applications

Ultrathin Few-Layer GeP Nanosheets via Lithiation-Assisted Chemical Exfoliation and Their Application in Sodium Storage

2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Ultrathin few-layer materials have attracted intensive research attention because of their distinctive and unique properties. Few-layer GeP (FL-GP) is potentially interesting for application in electronics and optoelectronics because of its appropriate band gap and good stability under ambient conditions. Nevertheless, it is a challenge to achieve ultrathin few-layer or single layer GeP from exfoliation of bulk crystals. Here, a lithiation-assisted chemical exfoliation technique is employed to achieve FL-GP, in which the interlayer spacing can be efficiently enlarged after a preliminary lithium ion intercalation, allowing the bulk crystal to be readily exfoliated in a following ultrasonication. As a result, ultrathin FL-GP is obtained. In a demonstration, the FL-GP/reduced graphene oxide (rGO) demonstrates remarkable sodium storage performance. The FL-GP with a two-dimensional structure shortens the ion transport pathways and alleviates the volume variation during sodiation. Meanwhile, the rGO in the composite improves the conductivity of the whole electrode. The as-prepared FL-GP/rGO electrode exhibits a high capacity of 504.2 mAh g−1 at 100 mA g−1, remarkable rate performance, and superior cycling stability in the half cells. FL-GP/rGO//Na3V2(PO4)3 full cells are also assembled and demonstrated satisfactory electrochemical performance, indicating potential application of the as-prepared anode materials

Case Report: Using Medtronic AP360 mechanical prosthesis in mitral valve replacement for patients with mitral insufficiency after primum atrial septal defect repair to reduce left ventricular outflow tract obstruction risk

BackgroundAtrial septal defect is one of the most common congenital heart diseases in adults. Primum atrial septal defect (PASD) accounts for 4%–5% of congenital heart defects. Patients with PASD frequently suffer mitral insufficiency (MI), and thus, mitral valvuloplasty (MVP) or mitral valve replacement (MVR) is often required at the time of PASD repair. Unfortunately, recurrent unrepairable severe mitral regurgitation can develop in many patients undergoing PASD repair plus MVP in either short- or long-term after the repair surgery, requiring a re-do MVR. In those patients, the risk of left ventricular outflow tract obstruction (LVOTO) has increased.Case presentationWe present five such cases, ranging in age from 24 to 47 years, who had a PASD repair plus MVP or MVR for 14–40 years while suffering moderate to severe mitral regurgitation. Using Medtronic AP360 mechanical mitral prostheses, only one patient experienced mild LVOTO.ConclusionsThe use of Medtronic AP360 mechanical mitral prostheses to perform MVR in patients with MI who had a history of PASD repair can potentially reduce the risk of LVOTO. Long-term follow-up is required to further confirm this clinical benefit associated with AP360 implantation in patients with PASD

Case report:TP53 and RB1 loss may facilitate the transformation from lung adenocarcinoma to small cell lung cancer by expressing neuroendocrine markers

INTRODUCTION: Transformation from lung adenocarcinoma (LUAD) to small cell lung cancer (SCLC) is one of the mechanisms responsible for acquired EGFR-TKIs resistance. Although it rarely happens this event determines a rapid disease deterioration and needs specific treatment. PATIENT AND METHOD: We report a case of 75-year-old LUAD female with a p.L858R mutation in Epidermal Growth Factor Receptor (EGFR) who presented with SCLC transformation after responding to first line osimertinib treatment for only 6 months. To understand the underlying molecular mechanism, we retrospectively sequenced the first (LUAD) and the second (SCLC) biopsy using a 56 multi-gene panel. Immunohistochemistry (IHC) staining and Fluorescence In Situ Hybridization (FISH) was applied to confirm the genetic aberrations identified. RESULTS: EGFR p.E709A and p.L858R, Tumor Protein p53 (TP53) p.A159D and Retinoblastoma 1 (RB1) c.365-1G>A were detected in both the diagnostic LUAD and transformed SCLC samples. A high copy number gain for Proto-Oncogene C-Myc (MYC) and a Phosphoinositide 3-Kinase Alpha (PIK3CA) p.E545K mutation were found in the transformed sample specifically. Strong TP53 staining and negative RB1 staining were observed in both LUAD and SCLC samples, but FISH only identified MYC amplification in SCLC tissue. CONCLUSION: We consider the combined presence of MYC amplification with mutations in TP53 and RB1 as drivers of SCLC transformation. Our results highlight the need to systematically evaluate TP53 and RB1 status in LUAD patients to offer a different therapeutic strategy

Case report: TP53 and RB1 loss may facilitate the transformation from lung adenocarcinoma to small cell lung cancer by expressing neuroendocrine markers

IntroductionTransformation from lung adenocarcinoma (LUAD) to small cell lung cancer (SCLC) is one of the mechanisms responsible for acquired EGFR-TKIs resistance. Although it rarely happens this event determines a rapid disease deterioration and needs specific treatment.Patient and methodWe report a case of 75-year-old LUAD female with a p.L858R mutation in Epidermal Growth Factor Receptor (EGFR) who presented with SCLC transformation after responding to first line osimertinib treatment for only 6 months. To understand the underlying molecular mechanism, we retrospectively sequenced the first (LUAD) and the second (SCLC) biopsy using a 56 multi-gene panel. Immunohistochemistry (IHC) staining and Fluorescence In Situ Hybridization (FISH) was applied to confirm the genetic aberrations identified.ResultsEGFR p.E709A and p.L858R, Tumor Protein p53 (TP53) p.A159D and Retinoblastoma 1 (RB1) c.365-1G>A were detected in both the diagnostic LUAD and transformed SCLC samples. A high copy number gain for Proto-Oncogene C-Myc (MYC) and a Phosphoinositide 3-Kinase Alpha (PIK3CA) p.E545K mutation were found in the transformed sample specifically. Strong TP53 staining and negative RB1 staining were observed in both LUAD and SCLC samples, but FISH only identified MYC amplification in SCLC tissue.ConclusionWe consider the combined presence of MYC amplification with mutations in TP53 and RB1 as drivers of SCLC transformation. Our results highlight the need to systematically evaluate TP53 and RB1 status in LUAD patients to offer a different therapeutic strategy

Glycogenolysis in Acquired Glioma Resistance to Temozolomide: A Role for the [Ca2+]i-dependent Activation of Na,K-ATPase/ERK1/2 Signaling

Understanding the mechanistic basis for temozolomide (TMZ)-induced glioma resistance is an important obstacle in developing an effective form of chemotherapy for this type of tumor. Glycogenolysis is known to play an essential role in cellular proliferation and potassium homeostasis and involves the glycogen phosphorylase isoenzyme BB (GPBB). In this investigation, plasma GPBB was correlated with TMZ-resistance. Elevated plasma GPBB concentrations were found to be more frequent in a TMZ-resistant cohort of patients with poor survival rates. TMZ inhibits cell proliferation and induces TMZ resistance by upregulating the expression of O(6)-methylguanine-DNA methyltransferase (MGMT). This process requires glycogenolysis, which was confirmed herein by treatment with 1,4-dideoxy-1,4-imino-D-arabinitol hydrochloride, a glycogenolysis inhibitor and a special GPBB inhibitor. Acute TMZ treatment leads to upregulation of [Ca2+]i, extracellular-regulated kinase (ERK)1/2 phosphorylation, and chronic TMZ treatment leads to upregulation of the expression of Na,K-ATPase, ERK1/2, and MGMT protein. Upregulation was abolished for each of these by inhibitors of transient receptor potential channel 1 and the inositol trisphosphate receptor. L-channel [Ca2+]i inhibitors and RyR antagonists had no such effect. These results demonstrate that [Ca2+]i-dependent glycogenolysis participates in acquired glioma TMZ-resistance by upregulating MGMT via a Na,K-ATPase/ERK1/2 signaling pathway. GPBB and glycogenolysis may therefore represent novel therapeutic targets for overcoming TMZ-resistant gliomas

Spatiotemporal clustering of flash floods in a changing climate (China, 1950–2015)

The persistence over space and time of flash flood disasters -- flash floods that have caused either economical or life losses, or both -- is a diagnostic measure of areas subjected to hydrological risk. The concept of persistence can be assessed via clustering analyses, performed here to analyse the national inventory of flash floods disasters in China occurred in the period 1950-2015. Specifically, we investigated the spatio-temporal pattern distribution of the flash floods and their clustering behavior by using both global and local methods: the first, based on the Ripley's K-function, and the second on scan statistics. As a result, we could visualize patterns of aggregated events, estimate the cluster duration and make assumptions about their evolution over time, also with respect precipitations trend. Due to the large spatial (the whole Chinese territory) and temporal scale of the dataset (66 years), we were able to capture whether certain clusters gather in specific locations and times, but also whether their magnitude tends to increase or decrease. Overall, the eastern regions in China are much more subjected to flash floods compared to the rest of the country. Detected clusters revealed that these phenomena predominantly occur between July and October, a period coinciding with the wet season in China. The number of detected clusters increases with time, but the associated duration drastically decreases in the recent period. This may indicate a change towards triggering mechanisms which are typical of short-duration extreme rainfall events. Finally, being flash floods directly linked to precipitation and their extreme realization, we indirectly assessed whether the magnitude of the trigger itself has also varied through space and time, enabling considerations in the context of climatic changes

A Method for Intelligent Road Network Selection Based on Graph Neural Network

As an essential role in cartographic generalization, road network selection produces basic geographic information across map scales. However, the previous selection methods could not simultaneously consider both attribute characteristics and spatial structure. In light of this, an intelligent road network selection method based on a graph neural network (GNN) is proposed in this paper. Firstly, the selection case is designed to construct a sample library. Secondly, some neighbor sampling and aggregation rules are developed to update road features. Then, a GNN-based selection model is designed to calculate classification labels, thus completing road network selection. Finally, a few comparative analyses with different selection methods are conducted, verifying that most of the accuracy values of the GNN model are stable over 90%. The experiments indicate that this method could aggregate stroke nodes and their neighbors together to synchronously preserve semantic, geometric, and topological features of road strokes, and the selection result is closer to the reference map. Therefore, this paper could bridge the distance between deep learning and cartographic generalization, thus facilitating a more intelligent road network selection method

DSCU: Accelerating CNN Inference in FPGAs with Dual Sizes of Compute Unit

FPGA-based accelerators have shown great potential in improving the performance of CNN inference. However, the existing FPGA-based approaches suffer from a low compute unit (CU) efficiency due to their large number of redundant computations, thus leading to high levels of performance degradation. In this paper, we show that no single CU can perform best across all the convolutional layers (CONV-layers). To this end, we propose the use of dual sizes of compute unit (DSCU), an approach that aims to accelerate CNN inference in FPGAs. The key idea of DSCU is to select the best combination of CUs via dynamic programming scheduling for each CONV-layer and then assemble each CONV-layer combination into a computing solution for the given CNN to deploy in FPGAs. The experimental results show that DSCU can achieve a performance density of 3.36 × 10−3 GOPs/slice on a Xilinx Zynq ZU3EG, which is 4.29 times higher than that achieved by other approaches