Blocking interaction between SHP2 and PD‐1 denotes a novel opportunity for developing PD‐1 inhibitors

Small molecular PD‐1 inhibitors are lacking in current immuno‐oncology clinic. PD‐1/PD‐L1 antibody inhibitors currently approved for clinical usage block interaction between PD‐L1 and PD‐1 to enhance cytotoxicity of CD8+ cytotoxic T lymphocyte (CTL). Whether other steps along the PD‐1 signaling pathway can be targeted remains to be determined. Here, we report that methylene blue (MB), an FDA‐approved chemical for treating methemoglobinemia, potently inhibits PD‐1 signaling. MB enhances the cytotoxicity, activation, cell proliferation, and cytokine‐secreting activity of CTL inhibited by PD‐1. Mechanistically, MB blocks interaction between Y248‐phosphorylated immunoreceptor tyrosine‐based switch motif (ITSM) of human PD‐1 and SHP2. MB enables activated CTL to shrink PD‐L1 expressing tumor allografts and autochthonous lung cancers in a transgenic mouse model. MB also effectively counteracts the PD‐1 signaling on human T cells isolated from peripheral blood of healthy donors. Thus, we identify an FDA‐approved chemical capable of potently inhibiting the function of PD‐1. Equally important, our work sheds light on a novel strategy to develop inhibitors targeting PD‐1 signaling axis

Atomic Sn–enabled high-utilization, large-capacity, and long-life Na anode

Constructing robust nucleation sites with an ultrafine size in a confined environment is essential toward simultaneously achieving superior utilization, high capacity, and long-term durability in Na metal-based energy storage, yet remains largely unexplored. Here, we report a previously unexplored design of spatially confined atomic Sn in hollow carbon spheres for homogeneous nucleation and dendrite-free growth. The designed architecture maximizes Sn utilization, prevents agglomeration, mitigates volume variation, and allows complete alloying-dealloying with high-affinity Sn as persistent nucleation sites, contrary to conventional spatially exposed large-size ones without dealloying. Thus, conformal deposition is achieved, rendering an exceptional capacity of 16 mAh cm−2 in half-cells and long cycling over 7000 hours in symmetric cells. Moreover, the well-known paradox is surmounted, delivering record-high Na utilization (e.g., 85%) and large capacity (e.g., 8 mAh cm−2) while maintaining extraordinary durability over 5000 hours, representing an important breakthrough for stabilizing Na anode

Graphene‐Like Conjugated Molecule as Hole‐Selective Contact for Operationally Stable Inverted Perovskite Solar Cells and Modules

Further enhancing the operational lifetime of inverted-structure perovskite solar cells (PSCs) is crucial for their commercialization, and the design of hole-selective contacts at the illumination side plays a key role in operational stability. In this work, the self-anchoring benzo[rst]pentaphene (SA-BPP) is developed as a new type of hole-selective contact toward long-term operationally stable inverted PSCs. The SA-BPP molecule with a graphene-like conjugated structure shows a higher photostability and mobility than that of the frequently-used triphenylamine and carbazole-based hole-selective molecules. Besides, the anchoring groups of SA-BPP promote the formation of a large-scale uniform hole contact on ITO substrate and efficiently passivate the perovskite absorbers. Benefiting from these merits, the champion efficiencies of 22.03% for the small-sized cells and 17.08% for 5 × 5 cm2 solar modules on an aperture area of 22.4 cm2 are achieved based on this SA-BPP contact. Also, the SA-BPP-based device exhibits promising operational stability, with an efficiency retention of 87.4% after 2000 h continuous operation at the maximum power point under simulated 1-sun illumination, which indicates an estimated T80 lifetime of 3175 h. This novel design concept of hole-selective contacts provides a promising strategy for further improving the PSC stability.journal articl

The succession of rhizosphere microbial community in the continuous cropping soil of tobacco

Introduction: Flue-cured tobacco is an important economic crop that is not tolerant of continuous cropping and can be influenced by planting soil conditions including rhizosphere microbial communities and soil physicochemical properties. The relationship between rhizosphere microbial communities and soil physicochemical properties under continuous cropping conditions is unclear.Methods: This study investigated the succession of rhizosphere microbial community in continuous tobacco cropping soil for 1, 3, 5, 8, 10, 15, and 30 years. The physicochemical properties of the soil were measured, high-throughput sequencing was performed on the rhizosphere microbial community, and correlation analysis was conducted.Results: The results suggested that continuous cropping could significantly enrich soil available nitrogen, available phosphorus, available potassium, and organic matter. Meanwhile, the alpha diversity of the bacterial community was significantly reduced with continuous cropping, indicating significant changes in the structure of bacterial and fungal communities. Based on linear discriminant analysis effect size (LEfSe), 173 bacterial and 75 fungal genera were identified with significant differences. The bacterial genera, Sphingomonas, Streptomyces, and Microvirga, were significantly positively correlated with continuous cropping years. The fungal genera, Tausonia, Solicocozyma, Pseudomycohila, and Fusarium, also showed significant positive correlation with continuous cropping years. Meanwhile, the fungal genera, Olpidium, Cephaliophora, and Cercophora, presented an opposite correlation. However, there are differences in the correlation between these bacterial and fungal genera related to continuous cropping years and other different soil physicochemical properties.Discussion: In summary, this work could provide a reference for soil management and scientific fertilization of tobacco under continuous cropping conditions

Organic Materials-based Electrochemical Flow Cells for Energy Applications

To meet the 2015 Paris Agreement requirement of limiting global warming to 1.5 °C, the transition from fossil fuels to renewables (solar and wind) necessitates a rapid change of the energy landscape. The decline of the price for electricity from solar panels and wind turbines is so fast over the last decade that green electricity competes economically with electricity generated from coal, oil, and gas. Considering the output from renewable energy sources is electric current, the conversion and storage of green electricity is the key to the paradigm shift. Both conversion and storage imply transformation of electrical energy into chemical energy of molecules. The former means production of multipurpose energetic molecules. Here such a molecule is hydrogen peroxide, a green oxidant, and our aim is to advance its electrochemical production. The latter is concerned with making the chemical energy readily transformable back into electricity in batteries. In electrochemistry, H-cells are usually used in screening materials and mechanistic understanding of relevant processes. However, the results of H-cell studies sometimes do not directly translate to upscaled systems, such as flow cells. Electrochemical flow cells are attracting attention due to the ability to decouple capacity and power, the long operation time, and the decreased diffusion layer thickness and ohmic resistance. Most flow cells today use inorganic materials, and they are expensive and based on unsustainable mining processes in some geographically concentrated regions. Organic materials, on the contrary, are cheap and readily designed via molecular engineering and electro-organic synthesis. In this thesis, organic materials-based flow cells will be constructed for energy conversion and storage studies.    We start with making free-standing poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) films with a thickness >50 μm by vacuum filtration, which then are used in electrochemical production of hydrogen peroxide (H2O2) in a H-cell. Due to some drawbacks listed above, we shifted our focus to flow cells. The cathodic generation of H2O2 is combined with oxygen evolution reaction (OER) using nickel (II) oxide (NiO) to explore the possibility of using a polymer material in a flow cell environment. This flow cell system could reach a faradaic efficiency of 80% and the system loss is analyzed from different angles. However, the OER is kinetically sluggish and would need precious catalysts to drive the reaction. Instead of turning to precious catalysts, we proposed to replace the OER in the device with the oxidation of a water-soluble organic molecule oxidation, 4,5-dihydroxy-1,3-benzenedisulfonic acid disodium salt monohydrate (tiron/BQDS). The tiron oxidation is fast and does not need a catalyst. The tiron transport phenomena are investigated and we find that migration—a less recognized player—has a big role in regulating tiron transport. The last part of the thesis introduces a biomass-based membrane made from cellulose for a tiron-based aqueous organic redox flow battery. The environmentally friendly nanocellulose membranes display reduced crossover of quinone redox couples, higher discharge capacity, and better reusability than the commercial fluoropolymer Nafion™ 115 membranes.    We hope the present thesis, which deals with various aspects of flow cells from organic material design to system transport phenomena, will stimulate more people to work on this fascinating topic, paving the way for electrification of everything by tunable and sustainable organic molecules.

Carbon-coated copper nanoparticles prepared by detonation method and their thermocatalysis on ammonium perchlorate

Carbon-coated copper nanoparticles (CCNPs) were prepared by initiating a high-density charge pressed with a mixture of microcrystalline wax, hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), and copper nitrate hydrate (Cu(NO3)2·3H2O) in an explosion vessel filled with nitrogen gas. The detonation products were characterized by transmission electron microcopy (TEM), high resolution transmission electron microcopy (HRTEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and Raman spectroscopy. The effects of CCNPs on thermal decomposition of ammonium perchlorate (AP) were also investigated by differential scanning calorimeter (DSC). Results indicated that the detonation products were spherical, 25-40 nm in size, and had an apparent core-shell structure. In this structure, the carbon shell was 3-5 nm thick and mainly composed of graphite, C8 (a kind of carbyne), and amorphous carbon. When 5 wt.% CCNPs was mixed with 95 wt.% AP, the high-temperature decomposition peak of AP decreased by 95.97, 96.99, and 96.69 °Cat heating rates of 5, 10, and 20 °C/min, respectively. Moreover, CCNPs decreased the activation energy of AP as calculated through Kissinger’s method by 25%, which indicated outstanding catalysis for the thermal decomposition of AP

A graph deep learning method for landslide displacement prediction based on global navigation satellite system positioning

The accurate prediction of displacement is crucial for landslide deformation monitoring and early warning. This study focuses on a landslide in Wenzhou Belt Highway and proposes a novel multivariate landslide displacement prediction method that relies on graph deep learning and Global Navigation Satellite System (GNSS) positioning. First model the graph structure of the monitoring system based on the engineering positions of the GNSS monitoring points and build the adjacent matrix of graph nodes. Then construct the historical and predicted time series feature matrixes using the processed temporal data including GNSS displacement, rainfall, groundwater table and soil moisture content and the graph structure. Last introduce the state-of-the-art graph deep learning GTS (Graph for Time Series) model to improve the accuracy and reliability of landslide displacement prediction which utilizes the temporal-spatial dependency of the monitoring system. This approach outperforms previous studies that only learned temporal features from a single monitoring point and maximally weighs the prediction performance and the priori graph of the monitoring system. The proposed method performs better than SVM, XGBoost, LSTM and DCRNN models in terms of RMSE (1.35 mm), MAE (1.14 mm) and MAPE (0.25) evaluation metrics, which is provided to be effective in future landslide failure early warning