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Background Patients with non-small cell lung cancer (NSCLC) are diagnosed in advanced stages and with a poor 5-year survival rate. There is a critical need to identify novel biomarkers to improve the therapy and overall prognosis of this disease. Methods Differentially expressed genes (DEGs) were identified from three profiles of GSE101586, GSE101684 and GSE112214 using Venn diagrams. hsa_circ_0043256 were validated using quantitative real-time polymerase chain reaction (RT-qPCR). The circular RNA-microRNA-messenger RNA (circRNA-miRNA-mRNA) regulatory network was constructed with Cytoscape 3.7.0. Hub genes were identified with protein interaction (PPI) and validated with the Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA) databases, and immunohistochemistry. Survival analyses were also performed using a Kaplan-Meier (KM) plotter. The effects of hsa_circ_0043256 on cell proliferation and cell cycles were evaluated by EdU staining and flow cytometry, respectively. Results hsa_circ_0043256, hsa_circ_0029426 and hsa_circ_0049271 were obtained. Following RT-qPCR validation, hsa_circ_0043256 was selected for further analysis. In addition, functional experiment results indicated that hsa_circ_0043256 could inhibit cell proliferation and cell-cycle progression of NSCLC cells in vitro. Prediction by three online databases and combining with DEGs identified from The Cancer Genome Atlas (TCGA), a network containing one circRNAs, three miRNAs, and 209 mRNAs was developed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated DEGs might be associated with lung cancer onset and progression. A PPI network based on the 209 genes was established, and five hub genes (BIRC5, SHCBP1, CCNA2, SKA3, and GINS1) were determined. Following verification of five hub genes using GEPIA database, HPA database, and immunohistochemistry. High expression of all five hub genes led to poor overall survival. Conclusion Our study constructed a circRNA-miRNA-mRNA network of hsa_circ_0043256. hsa_circ_0043256 may be a potential therapeutic target for lung cancer.

The lack of sensitive and robust behavioral assessments of pain in preclinical models has been a major limitation for both pain research and the development of novel analgesics. Here, we demonstrate a novel data acquisition and analysis platform that provides automated, quantitative, and objective measures of naturalistic rodent behavior in an observer-independent and unbiased fashion. The technology records freely behaving mice, in the dark, over extended periods for continuous acquisition of 2 parallel video data streams: (1) near-infrared frustrated total internal reflection for detecting the degree, force, and timing of surface contact and (2) simultaneous ongoing video graphing of whole-body pose. Using machine vision and machine learning, we automatically extract and quantify behavioral features from these data to reveal moment-by-moment changes that capture the internal pain state of rodents in multiple pain models. We show that these voluntary pain-related behaviors are reversible by analgesics and that analgesia can be automatically and objectively differentiated from sedation. Finally, we used this approach to generate a paw luminance ratio measure that is sensitive in capturing dynamic mechanical hypersensitivity over a period and scalable for highthroughput preclinical analgesic efficacy assessment., United States Department of Defense, Defense Advanced Research Projects Agency (DARPA) HR0011-19-2-0022, United States Department of Health & Human Services, National Institutes of Health (NIH) - USA, NIH National Institute of Neurological Disorders & Stroke (NINDS) F31 NS084716-02 R35 NS105076 R01 NS089521 F31 NS108450 R01 NA114202, Bertarelli Foundation, Simons Collaboration on the Global Brain, NIH BRAIN Initiative U19 NS113201 U24 NS109520 R01AT011447, Boston Children's Hospital Technology Development Fund, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 229356/2013-3

Lithium-ion batteries (LIBs) are considered to be indispensable in modern society. Major advances in LIBs depend on the development of new high-performance electrode materials, which requires a fundamental understanding of their properties. First-principles calculations have become a powerful technique in developing new electrode materials for high-energy–density LIBs in terms of predicting and interpreting the characteristics and behaviors of electrode materials, understanding the charge/discharge mechanisms at the atomic scale, delivering rational design strategies for electrode materials, etc. In this review, we present an overview of first-principles calculation methods and highlight their valuable role in contemporary research on LIB cathode materials. This overview focuses on three LIB cathode scenarios, which are divided by their cationic/anionic redox mechanisms. Then, representative examples of rational cathode design based on theoretical predictions are presented. Finally, we present a personal perspective on the current challenges and future directions of first-principles calculations in LIBs.

Background The echinoderm microtubule-associated protein-like-4 anaplastic lymphoma kinase (EML4-ALK) fusion gene was identified in a subset of non-small cell lung cancer (NSCLC) patients. They responded positively to ALK inhibitors. This study aimed to characterize the mechanisms triggered by EML4-ALK to induce NSCLC transformation. Methods HEK293 and NIH3T3 cells were transfected with EML4-ALK variant 3 or pcDNA3.1-NC. H2228 cells were transfected with siRNA-EML4-ALK or siRNA-NC. Cell viability and proliferation were measured by the CCK-8 and EdU methods, respectively. Flow cytometry revealed apoptosis. Gene expression profiles were generated from a signaling pathway screen in EML4-ALK-regulated lung cancer cells and verified by qPCR and Western blotting. The co-immunoprecipitation and immunohistochemistry/ immunofluorescence determined the interaction and colocalization of JAK2-STAT pathway components with EML4-ALK. Results Microarray identified several genes involved in the JAK2-STAT pathway. JAK2 and STAT6 were constitutively phosphorylated in H2228 cells. EML4-ALK silencing downregulated phosphorylation of STAT6. Expression of EML4-ALK in HEK293 and NIH3T3 cells activated JAK2, STAT1, STAT3, STAT5, and STAT6. In EML4-ALK-transfected HEK293 cells and EML4-ALK-positive H2228 cells, activated STAT6 and JAK2 colocalized with ALK. STAT3 and STAT6 were phosphorylated and translocated to the nucleus of H2228 cells following IL4 or IL6 treatment. Apoptosis increased, while cell proliferation and DNA replication decreased in H2228 cells following EML4-ALK knockdown. In contrast, HEK293 cell viability increased following EML4-ALK overexpression, while H2228 cell viability significantly decreased after treatment with ALK or JAK-STAT pathway inhibitors. Conclusions Our data suggest that the aberrant expression of EML4-ALK leads to JAK2-STAT signaling pathway activation, which is essential for the development of non-small cell lung cancer.

Summary In the past several decades, the research communities have witnessed the explosive development of lithium-ion batteries, largely based on the diverse landmark cathode materials, among which the application of manganese has been intensively considered due to the economic rationale and impressive properties. Lithium-manganese-based layered oxides (LMLOs) are one of the most promising cathode material families based on an overall theoretical evaluation covering the energy density, cost, eco-friendship, etc. Unfortunately, the Mn3+ cation introduces severe Jahn–Teller (J–T) effect, which profoundly distorts the localized lattice structure and reduces the electrochemical stability. This perspective presents the principal comprehensions of the J–T effect in LMLOs and offers an outline picture of material design to suppress it. We outline the history of material design and further assess available approaches to address the J–T effect. Finally, we tentatively propose promising design trends with eliminated J–T effect to revive this important cathode material family toward practical applications.

Incident duration models are often developed to assist incident management and traveler information dissemination. With recent advances in data collection and management, enormous achieved incident data are now available for incident model development. However, a large volume of data may present challenges to practitioners, such as data processing and computation. Besides, data that span multiple years may have inconsistency issues because of the data collection environments and procedures. A practical question may arise in the incident modeling community—Is that much data really necessary (“all-in”) to build models? If not, then how many data are necessary? To answer these questions, this study aims to investigate the relationship between the data sample sizes and the reliability of incident duration analysis models. This study proposed and demonstrated a sample size determination framework through a case study using data of over 47,000 incidents. This study estimated handfuls of hazard-based duration models with varying sample sizes. The relationships between sample size and model performance, along with estimate outcomes (i.e., coefficients and significance levels), were examined and visualized. The results showed that the variation of estimated coefficients decreases as the sample size increases, and becomes stabilized when the sample size reaches a critical threshold value. This critical threshold value may be the recommended sample size. The case study suggested a sample size of 6,500 to be enough for a reliable incident duration model. The critical value may vary significantly with different data and model specifications. More implications are discussed in the paper.

The long non-coding RNA Hox transcript antisense intergenic RNA (HOTAIR) plays a critical role in tumorigenesis as well as drug resistance in various cancers. However, the molecular mechanism by which HOTAIR induces gefitinib resistance in non-small cell lung cancer is to date unclear. In the present study, we revealed that HOTAIR is upregulated in gefitinib-resistant lung cancer cells and over-expression of HOTAIR enhances gefitinib resistance in lung cancer cells. In addition, the overexpression of HOTAIR promotes cell cycle progression through epigenetic regulation of EZH2/H3K27. Silencing of EZH2 by either siRNA or inhibitors sensitized the lung cancer cells to gefitinib. Inhibition of EZH2 induces expression of p16 and p21, whereas levels of CDK4, cyclinD1, E2F1, and LSD1 are significantly decreased in PC-9 cells overexpressing HOTAIR. ChIP-PCR experiments indicate that HOTAIR increases H3K27me3 recruitment to the promoter of p16 and p21 in PC-9 lung cancer cells overexpressing HOTAIR. In xenograft mouse models, overexpressing HOTAIR in lung cancer tissues decreased p16 and p21 proteins. Taken together, these data suggest that HOTAIR contributes to gefitinib resistance by regulating EZH2 and p16 and p21. Targeting HOTAIR may be a novel therapeutic strategy for treating gefitinib-resistance in non-small cell lung cancer.

Activation of nociceptor sensory neurons by noxious stimuli both triggers pain and increases capillary permeability and blood flow to produce neurogenic inflammation1,2, but whether nociceptors also interact with the immune system remains poorly understood. Here we report a neurotechnology for selective epineural optogenetic neuromodulation of nociceptors and demonstrate that nociceptor activation drives both protective pain behavior and inflammation. The wireless optoelectronic system consists of sub-millimeter-scale light-emitting diodes embedded in a soft, circumneural sciatic nerve implant, powered and driven by a miniaturized head-mounted control unit. Photostimulation of axons in freely moving mice that express channelrhodopsin only in nociceptors resulted in behaviors characteristic of pain, reflecting orthodromic input to the spinal cord. It also led to immune reactions in the skin in the absence of inflammation and potentiation of established inflammation, a consequence of the antidromic activation of nociceptor peripheral terminals. These results reveal a link between nociceptors and immune cells, which might have implications for the treatment of inflammation.

Titanium-based layered oxides (TLOs) are one of the most promising electrode material families for sodium-ion batteries (NIBs) due to their smooth charge/discharge profiles and excellent cycle performance. However, the reaction mechanism of these materials, especially the reason for the disappearance of multiple voltage plateaus, is still not clear. Herein, two representative TLOs (Na2/3Ni1/3Ti2/3O2 and Na2/3Co1/3Ti2/3O2) with the same P2 crystal structure have been studied to scrutinize those unexplained issues. In situ synchrotron high-energy X-ray diffraction revealed a solid solution reaction mechanism for both, suggesting the absence of rigid phase transitions upon electrochemical cycling. An interesting “spring effect” of the TiO6 octahedron, i.e., the reversible vibration of the central Ti atom inside the local octahedron upon electrochemical redox, was demonstrated by advanced X-ray absorption spectroscopy and theoretical calculations. Such an effect could suppress the rigid phase transitions, and result in smooth charge/discharge profiles and enhanced cycle stability. This work not only accounts for the disappearance of multiple voltage plateaus of TLOs for NIBs, but also provides an effective local-structure viewpoint to increase the cycle stability of electrode materials for other advanced battery systems.

Recently, drone small cells (DSCs) has been brought into significant focus, which is the one key enabler for potentially facilitating terrestrial wireless communication systems. Meanwhile, in ultra-dense unmanned networks, artificial intelligence (AI) has been a useful and efficient tool for control and management of the multi-agents. This paper investigates a downlink interference control problem in ultra-dense unmanned networks with AI-aided approach, that each DSC can adjust its altitude to increase the data-rate. This problem is formulated as a mean field game (MFG) framework, an AI-aided method to make decisions. In this framework, each DSC controls its velocity to minimize the cost over a period, where the cost function is composed by the data-rate and height adjusting consumption. Meanwhile, in this model, we adopt the mean-field approximation (MFA) approach to derive the interference introduced from a large number of DSCs. Besides, the control strategy is described and explained by using the related Hamilton-Jacobi-Bellman (HJB) and Fokker-Planck-Kolmogorov (FPK) equations, respectively. Thus, a finite difference algorithm is proposed to solve the coupled partial differential equations, which can obtain the optimal altitude control strategy. The algorithm outputs show the optimal behaviors of DSCs in different environment scenarios. In additon, the simulation results verify that the proposed control strategy has better average signal to interference plus noise ratio (SINR) compared with the baseline method.

Earth-abundant sodium is a promising alternative to lithium in rechargeable batteries. However, graphite, the commercial anode material of lithium-ion batteries, cannot be used for sodium-ion batteries (SIBs). Herein, carbon block anodes with columnar nanopores constructed from amine-functionalized carbon nanosheets were synthesized using modified polyacrylonitrile as the carbon source through a simple and economical low-temperature pyrolysis process, delivering high reversible capacity, superior rate capability and remarkable cyclic stability. The surface-dominated redox reaction mechanism in Na storage is the origin of the fast kinetics, since the columnar nanopores which are considered as curled and sealed ultrathin nanosheets, like microjars, not only shorten the ion and electron diffusion length, but also expand the redox sites from the surface to the inner part. This is similar to the storage mechanism in supercapacitors. Moreover, density functional theory computations reveal that the high-level amine groups play an important role in Na storage in the low potential region, endowing the block anode material with both high energy and power density.

Reported herein is the investigation of a unique cathode candidate for Li–S batteries, i.e. Ni3S2/(N, S)-RGO-type hybrid materials, which are expected to optimize battery performance by elevating the utilization of sulfur and chemically confining the adsorption/diffusion of polysulfide. Versatile structural and compositional characterizations confirmed the uniform growth and strong chemical coupling of nanostructured Ni3S2 on the N/S co-doped RGO matrix. Rich physical and chemical properties were revealed, namely, the large specific surface area and pore volume, which are beneficial for polysulfide capture, and the 3D conductive network supporting rapid charge transfer to the Ni3S2-polysulfide interface to improve the intrinsic equilibrium of the polysulfide. Specifically, the integration of ∼28.2 wt% of Ni3S2 produced a highly pleated composite with the largest BET specific surface area (618 m2 g−1) and pore volume (1.73 cm3 g−1) among the hybrids studied. This typical material also performed the best in the battery test, recording ultra-high cycling stability over 1000 cycles at the current density of 3C with the capacity decay of 0.023% per cycle. As the sulfur loading per unit area became as dense as 5.8 mg cm−2, the specific capacities were measured as 6.72 mA h cm−2 (at 0.05C), while the capacity retention for the 200-cycle test (at 1C) was still preserved above 72.5%.

Lung cancer is the leading cause of cancer-related deaths worldwide. Hypoxia is a crucial microenvironmental factor in lung adenocarcinoma (LUAD). However, the prognostic value based on hypoxia and immune in LUAD remains to be further clarified. The hypoxia-related genes (HRGs) and immune-related genes (IRGs) were downloaded from the public database. The RNA-seq expression and matched complete clinical data for LUAD were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was applied to model construction. Hypoxia expression profiles, immune cell infiltration, functional enrichment analysis, Tumor Immune Dysfunction and Exclusion (TIDE) score and the somatic mutation status were analyzed and compared based on the model. Moreover, immunofluorescence (IF) staining in human LUAD cases to explore the expression of hypoxia marker and immune checkpoint. A prognostic model of 9 genes was established, which can divide patients into two subgroups. There were obvious differences in hypoxia and immune characteristics in the two groups, the group with high-risk score value showed significantly high expression of hypoxia genes and programmed death ligand-1 (PD-L1), and maybe more sensitive to immunotherapy. Patients in the high-risk group had shorter overall survival (OS). This model has a good predictive value for the prognosis of LUAD. We constructed a new HRGs and IRGs model for prognostic prediction of LUAD. This model may benefit future immunotherapy for LUAD.

Safety Performance Functions (SPFs) can be used to predict the number of crashes for highway facilities by site characteristics, including traffic exposures and other specific site factors. The traditional approach to developing SPFs relies on factors that are observed in the data and has an unstated assumption that the relationships between safety performance and observed factors are stationary. However, there might be factors that are not captured by the data but also have significant impacts on roadway safety performance. These factors can lead to significant unobserved heterogeneity in safety performance at different sites. Failure to capture such unobserved heterogeneity in developing SPFs may result in biases and decrease the predictive accuracy. Given the interactions between highway traffic and roadway environments, the unobserved heterogeneity is likely related to the geographic space of the highway network. This study employs a spatial modeling approach, namely Geographically Weighted Negative Binomial Regression (GWNBR), to incorporate spatial heterogeneity into SPF model estimation. The GWNBR model can generate a local SPF for every site instead of a global SPF for one entire jurisdiction (e.g., a state) from the traditional approach. Local SPFs (or l-SPFs) are high-resolution and may be difficult for practitioners to use. To support the implementation of l-SPFs, this study proposes a method to aggregate l-SPFs to various geographic levels. This study first uses the 2014-2018 geo-referenced crash data from Alabama to develop l-SPFs for two-way STOP-controlled (TWST) three-leg intersections on rural two-lane two-way (TLTW) roadways in the state. The results show that l-SPFs vary substantially across Alabama. For example, the coefficients of traffic volume (AADT) on major roads range from 0.126 to 1.203 across different areas of the state. Then, an aggregation method based on K-means clustering is demonstrated to aggregate l-SPFs to various geographic levels of interest. The l-SPFs and their aggregation provide geographic flexibility in developing countermeasures and allocating funds to improve traffic safety considering local conditions.

Intensifying nitrogen (N) deposition disturbs the growth of grassland plants due to an imbalance between their carbon (C) and N metabolism. However, it's unclear how plant physiological strategies restore balance. We investigated the effects of multiple N addition levels (0-25 g N m

Multi-modality magnetic resonance imaging (MRI) can reveal distinct patterns of tissue in the human body and is crucial to clinical diagnosis. But it still remains a challenge to obtain diverse and plausible multi-modality MR images due to expense, noise, and artifacts. For the same lesion, different modalities of MRI have big differences in context information, coarse location, and fine structure. In order to achieve better generation and segmentation performance, a dual-scale multi-modality perceptual generative adversarial network (DualMMP-GAN) is proposed based on cycle-consistent generative adversarial networks (CycleGAN). Dilated residual blocks are introduced to increase the receptive field, preserving structure and context information of images. A dual-scale discriminator is constructed. The generator is optimized by discriminating patches to represent lesions with different sizes. The perceptual consistency loss is introduced to learn the mapping between the generated and target modality at different semantic levels. Moreover, generative multi-modality segmentation (GMMS) combining given modalities with generated modalities is proposed for brain tumor segmentation. Experimental results show that the DualMMP-GAN outperforms the CycleGAN and some state-of-the-art methods in terms of PSNR, SSMI, and RMSE in most tasks. In addition, dice, sensitivity, specificity, and Hausdorff95 obtained from segmentation by GMMS are all higher than those from a single modality. The objective index obtained by the proposed methods are close to upper bounds obtained from real multiple modalities, indicating that GMMS can achieve similar effects as multi-modality. Overall, the proposed methods can serve as an effective method in clinical brain tumor diagnosis with promising application potential.

The current study was to evaluate the predicted role of dietary fresh fish and processed fish intake for risk of glioma. Databases of Web of Science, PubMed, and Wan Fang Med Online were retrieved up to Jan 31th, 2018. Eligible studies were identified based on defined inclusion criteria. Summarized results of relative risk (RR) with corresponding 95% confidence intervals (CI) were calculated using a random effects model. Sensitivity analysis and publication bias were also performed. The final analysis in this report included a total of 9 articles. The summarized RR and 95%CI from 8 studies for dietary fresh fish intake and glioma risk was 0.823 (95%CI= 0.698-0.970), with no evidence of significant between-study heterogeneity (I2=43.6%, P=0.088). Moreover, positive associations were also found both in Caucasian populations and Asia populations. Seven studies were used to assess the relationship between dietary processed fish intake and the risk of glioma. Significantly increased risk of glioma was found for the highest category of dietary processed fish intake [summarized RR= 1.554, 95%CI= 1.169-2.066, I2= 72.1%, P= 0.001], especially among Caucasian populations. No publication bias was found. In summary, findings from this meta-analysis concluded that dietary fresh fish intake could reduce the risk of glioma. However, very high processed fish intake had a significant association with increased glioma risk.

Two-dimensional (2D) triphosphides, as an important family of 2D materials, have attracted more attention. Here, by using density functional theory (DFT) computations, we explored the remaining XP3 monolayers (X = the metal of group IIIA-VA), and then proposed two novel 2D triphosphides, antimony triphosphide (SbP3) and gallium triphosphide (GaP3) monolayer. SbP3 and GaP3 monolayer are structurally stable semiconductors with indirect bandgaps of 2.36 eV and 1.45 eV, respectively. They not only show strong light absorption coefficients (up to 105 cm−1) in the visible and ultraviolet regions, but also their band edge positions straddle the redox potentials of water, making them promising catalysts for water splitting. Under strain, SbP3 monolayer can effectively reduce the bandgap and GaP3 monolayer can achieve the transition from indirect to direct bandgap, which can improve the photocatalytic efficiency accordingly. Our work would stimulate the fabrication of SbP3 and GaP3 monolayer and explore their potential applications in electronic and optoelectronic devices.

The Internet of Things (IoT) technology has recently drawn more attention due to its ability to achieve the interconnections of massive physic devices. However, how to provide a reliable power supply to energy-constrained devices and improve the energy efficiency in the wireless powered IoT (WP-IoT) is a twofold challenge. In this paper, we develop a novel wireless power transmission (WPT) system, where an unmanned aerial vehicle (UAV) equipped with radio frequency energy transmitter charges the IoT devices. A machine learning framework of echo state networks together with an improved ${k}$ -means clustering algorithm is used to predict the energy consumption and cluster all the sensor nodes at the next period, thus automatically determining the charging strategy. The energy obtained from the UAV by WPT supports the IoT devices to communicate with each other. In order to improve the energy efficiency of the WP-IoT system, the interference mitigation problem is modeled as a mean field game, where an optimal power control policy is presented to adapt and analyze the large number of sensor nodes randomly deployed in WP-IoT. The numerical results verify that our proposed dynamic charging policy effectively reduces the data packet loss rate, and that the optimal power control policy greatly mitigates the interference, and improve the energy efficiency of the whole network.

Perovskite materials have been attracting much attention in recent years, especially in the field of energy conversion. However, the inherent disadvantages constrict the development of perovskites. Though many modification strategies have been proposed, the fundamental connection between those modifications and electronic properties is not clear. In this work, we investigated a series of Ruddlesden–Popper (RP) perovskites to explore the relationship between chemical components and their electronic properties. We revealed the influence of the components at A and B sites on band gaps and band edge positions by first-principles computations. After summarizing the design rules for RP perovskites, we proposed three new ones, MgSrMnO4, Mg2SrMn2O7 and MgSr2Mn2O7. Computed electronic properties demonstrate that Mg2SrMn2O7 has the suitable band gap and optimal light absorption, while MgSrMnO4 also has the optimal band edge position at the same time. These two new perovskites have desirable potential for application in the field of luminous energy conversion. Therefore, the rules of band engineering can provide guidance for further development of RP perovskites for photovoltaic or photocatalytic applications.

Hydrogen production by electrocatalytic water splitting is currently the most attractive route, but the development of electrocatalysts with high activity, long durability and low cost is still a big challenge. Here, by combining algorithm screening and density functional theory (DFT) computations, we developed a method to predict two-dimensional (2D) metal-free materials with metallicity as efficient electrocatalysts for the hydrogen evolution reaction (HER). From all metal-free compounds in the Materials Project database, we obtained 18 layered materials without band gaps as candidates for the HER. After being exfoliated into monolayers, a stable metal-free material, a C3N monolayer, proved to be an efficient HER electrocatalyst according to computations. With this strategy, we can adjust the screening conditions with the target to find promising materials, which overcomes the obstacles of traditional trial-and-error methods and greatly saves computational resource. We hope that this work would inspire the development of a new research paradigm and promote the discovery of more functional materials.

Sodium ion (Na+) storage and kinetics are of great importance for the development of high-performance sodium ion batteries. Herein, we report a composite of ultrafine V2O3 nanoparticles evenly anchored into three-dimensional S,N co-doped rGO conductive networks as a promising anode material for sodium ion batteries. Such a subtle architecture effectively connects isolated V2O3 nanoparticles into a structure with integrity, suppresses their aggregation and introduces more active sites, which significantly facilitates Na+ storage and the kinetics. Electrochemical analysis, in situ X-ray diffraction and density functional theory computations verified the Na+ storage mechanism, where one Na+ inserts into per V2O3 formula unit without crystallographic phase transition, coupling with small variations in the unit cell volume. In addition, V2O3 has preferable ability for interfacial Na+ storage, which was validated by strong Na+ adsorption on the (113) crystal plane. When used as an anode material for sodium ion batteries, this composite exhibited admirable rate capability and ultralong cycle durability. Furthermore, full cells of V2O3/S,N co-doped rGO//Na3V2(PO4)3@rGO also showed excellent electrochemical performance, demonstrating prospective applications to sodium ion batteries.

SUMMARYThe lack of robust quantifiable behavioral assessments of pain in pre-clinical models, especially of ongoing pain, has been a major limitation for both pain neurobiology research and development of novel analgesics. Current methods typically require extensive animal-human observer interaction and are often followed by manual, thus subjective, scorings, which are susceptible to bias and variability, and are labor-intensive and time-consuming. Here we demonstrate that, by leveraging modern machine vision and machine learning tools, quantifiable features of the spontaneous behavior, or the “body language” of an animal recorded in a dark and observer-free environment from a bottom-up view, can be directly used to automatically detect and infer both the internal state of pain and analgesia in an animal, and from surface contact measurements the presence of mechanical hypersensitivity, in an objective manner. This approach minimizes animal handling, reduces numbers of animals needed and the potential for biased assessment, making it a useful tool for exploring the biology of pain and other neurological disorders, one readily scalable for pre-clinical drug efficacy assessment.

Background: The echinoderm microtubule-associated protein-like-4 anaplastic lymphoma kinase (EML4-ALK) fusion gene was identified in a small subset of non-small cell lung cancer (NSCLC) patients, who responded positively to ALK inhibitors. The aim of this study was to characterize the mechanism of NSCLC transformation by EML4-ALK.Methods: HEK293 and NIH3T3 cells were transfected with EML4-ALK-V3 or pcDNA3.1-NC, and H2228 cells were transfected with siRNA-EML4-ALK or siRNA-NC. Cell viability and proliferation were measured by CCK-8 and EDU methods, respectively. Apoptosis was detected by flow cytometry. Gene expression profiles were generated from a signal pathway screen of EML4-ALK-regulated lung cancer cell transformation and verified by qPCR and western blotting. The interaction and colocalization of JAK2-STAT pathway components and EML4-ALK were determined by co-immunoprecipitation (Co-IP) and immunohistochemistry/ immunofluorescence, respectively. Results: Several genes involved in the JAK2-STAT pathway were identified by Microarray.JAK2 and STAT6 were constitutively phosphorylated in H2228 cells, which was downregulated by EML4-ALK silencing. Ectopic expression of EML4-ALK in HEK293 and NIH3T3 cells resulted in activating of JAK2 and STAT1, STAT3, STAT5, and STAT6. In EML4-ALK-transfected HEK293 and EML4-ALK-positive H2228 cells, activated STAT6 and JAK2 colocalized with ALK.STAT3 and STAT6 were found to be phosphorylated and translocated to the nucleus of H2228 cells following IL4 or IL6 treatment. Apoptosis increased and cell proliferation and DNA replication decreased in H2228 cells following EML4-ALK knockdown. In contrast, HEK293 cell viability increased following EML4-ALK over-expression, while H2228 cells viability significantly decreased after treatment with ALK or JAK-STAT pathway inhibitors.Conclusions: Taken together, our data suggest that aberrant expression of EML4-ALK leads to JAK2-STAT signaling pathway activation, an essential part of the development of non-small cell lung cancer.

Lithium-oxygen (Li-O 2 ) batteries are considered as one of the most promising energy storage systems due to their ultra-high theoretical capacity. However, most currently studied Li-O 2 batteries are based on the reduction/oxidation of Li 2 O 2 and involve highly reactive superoxide and peroxide species that would cause serious degradation of cathodes, especially carbon-based materials. It is of great importance to explore lithium-oxygen reactions and find new Li-O 2 chemistry which can restrict or even avoid the negative influence of superoxide/peroxide species. Here, inspired by enzyme-catalyzed oxygen reduction/oxidation reactions, we introduce a copper(I) complex 3N-Cu I (3N=1,4,7-trimethyl-1,4,7-triazacyclononane) to Li-O 2 batteries and successfully modulate the reaction pathway to a moderate one on reversible cleavage/formation of O-O bonds. This work demonstrates that the reaction pathways of Li-O 2 batteries could be modulated by introducing an appropriate soluble catalyst, which is another powerful choice to construct better Li-O 2 batteries.

Based on the literature review, this paper constructs the evaluation index system of coastal cities’ competitiveness. At the same time, the representative index data reflecting the competitiveness of coastal cities are collected. The evaluation model of coastal cities’ competitiveness is established by using the method of global factor analysis. Through the operation analysis, three representative global common factors are obtained, which are comprehensive economic competitiveness factor, trade competitiveness factor, and living standard factor. Research shows that combined with the characteristics of coastal cities, trade competitiveness factors have the greatest impact on urban competitiveness, followed by comprehensive economic competitiveness factors and people’s living standards factors. According to the contribution rate of global principal component common factor, the factor score function is obtained by regression method, and then the influence weight of the competitiveness indicators of each city is clarified. Through this study, it provides a theoretical basis for formulating the development strategy of promoting the competitiveness of coastal cities.

Carbon (C) assimilation and allocation play a crucial role in determining plant responses to environmental stress such as herbivory. However, the pattern how these grasses allocate assimilated C under increasing herbivory intensity hasn't been fully understand. In this study, we quantified photosynthetic C assimilation and allocation of newly assimilated C among tissues and metabolic processes (structural growth, storage, and defense) under different grazing intensities using 13C tracing of a dominant grass species, Leymus chinensis. Light grazing promoted utilization of newly-assimilated 13C (more than 90% 13C allocated to aboveground tissues on first day after labeling), photosynthetic rate, and reduced mean residence time of 13C of L. chinensis . The photosynthetic capacity and regulation of chlorophyll fluorescence thereby C assimilation were constrained under medium and heavy grazing. Light grazing also increased accumulation of non-structural carbohydrates (NSC) in stems for energy supply to leaf regeneration. As herbivory pressure increased, 13C tracing showed preferential allocation of newly assimilated C to belowground tissues (16–27% 13C on first day after labeling), while upregulating leaf defenses by increasing secondary metabolites and in root storage by NSC accumulation. Although the significant changes showed in C allocation to storage and secondary metabolism of L. chinensis , there are no difference in structural growth (defined as structural biomass= biomass - NSC – secondary metabolites) among grazing intensities. Overall, L. chinensis adopted a conservative C-allocation strategy (upregulated C storage and secondary metabolism) that emphasized long-term survival under increasing herbivory. Light grazing was an optimal grazing intensity that promoted structural growth and C allocation of L. chinensis , which could sustain and even increase grassland productivity. These characteristics of the plant’s C allocation strategy provide new insights into the C budget of grassland ecosystems and increase our understanding of the role of C fixation and partitioning when plants respond to environmental challenges.

Grazing can affect the grassland microclimate, soil properties, and litter quality, thereby affecting litter decomposition. However, it is still unclear which grazing intensity provides the most suitable environment for litter decomposition, and which factors play the dominant role in shoot and root litter decomposition. To investigate the effect of grazing on shoot and root litter decomposition, and the dominant factors in each decomposition period, we conducted a 17-month (from May 2016 to September 2017) litter bag experiment under five grazing intensities (control, light grazing, medium grazing, heavy grazing, and extremely heavy grazing, based on local grazing pressure standard) in a temperate grassland in Inner Mongolia, China. We divided the litter decomposition process into three stages according to the seasons. In the first growing season, the decomposition rate of shoot litter was faster under light grazing, probably because better soil environment was beneficial for microbes, and the high precipitation promoted leaching loss of soluble components. In the non-growing season, snow cover played an important role in litter decomposition. In the second growing season, the accumulation of macroelements (nitrogen, N; phosphorus, P) and microelements (magnesium, Mg; manganese, Mn) accelerated litter decomposition. Heavy and extremely heavy grazing intensities promoted the breakdown of cellulose in shoot litter. Medium grazing intensity could promote refractory substances decomposition in root litter. But the mass loss rate of root litter was inhibited by grazing, which was regulated by MBC/MBN. Our results indicate that different grazing intensities had different effects on the decomposition of shoot and root litter. At each stage of decomposition, the dominant factors of shoot and root litter decomposition were different and directly or indirectly affected by grazing and season.

The productivity of terrestrial ecosystems is limited by soil fertility, such assoil phosphorus (P). The decomposition of litter is the main process that affects nutrient cycling. To understand the characteristics of litter decomposition and nutrient release under P addition, we conducted a 2-year litter bag experiment at P addition rates (0–12.5 g P m−2 yr−1). All litter decomposed faster during the second growing season due to highly concentrated precipitation, and Stipa grandis litter decomposed faster (1.02–1.63 times) than Leymus chinensis under P treatments. The decomposition of L. chinensis and mixed litter was more thoroughly at 1 g P m−2 yr−1, while S. grandis decomposed more under 5 g P m−2 yr−1. P addition promoted nitrogen (N) and P immobilization and all litter reached its maximum at 12.5 g P m−2 yr−1. Phosphorus addition increased β-glucosidase production at 5 g P m−2 yr−1, but leucine aminopeptidase production was promoted at high P. The ratio of leucine aminopeptidase to phosphatase increased over time, indicating the N deficiency and P saturation during late stages of decomposition. Our results show that Inner Mongolia's grasslands was limited by P availability and that precipitation was important in the region's decomposition processes.

As modern society develops, the need for clean energy becomes increasingly important on a global scale. Because of this, the exploration of novel materials for energy storage and utilization is urgently needed to achieve low-carbon economy and sustainable development. Among these novel materials, metal–organic frameworks (MOFs), a class of porous materials, have gained increasing attention for utilization in energy storage and conversion systems because of ultra-high surface areas, controllable structures, large pore volumes and tunable porosities. In addition to pristine MOFs, MOF derivatives such as porous carbons and nanostructured metal oxides can also exhibit promising performances in energy storage and conversion applications. In this review, the latest progress and breakthrough in the application of MOF and MOF-derived materials for energy storage and conversion devices are summarized, including Li-based batteries (Li-ion, Li–S and Li–O2 batteries), Na-ion batteries, supercapacitors, solar cells and fuel cells.

Total saikosaponin yield in Bupleurum chinense DC. roots depends on the root biomass production and the saikosaponin content in roots, which are both affected by abiotic factors. Bupleurum chinense is relatively shade-tolerant. To test how total saikosaponin yield responds to light conditions, different light intensities (500, 200, and 50 μmol m−2 s−1) were established in artificial climate incubators. Responses of plant morphological and physiological characteristics and of saikosaponin synthesis to different light intensities were measured to find suitable light conditions for improving total saikosaponin yield. Among these light conditions, moderately low light intensity (MLI, 200 μmol m−2 s−1) produced plants with the highest leaf area, chlorophyll content, effective quantum yield of PSII (ΦPSII), photochemical quenching coefficient (qP), electron transport rate (ETR), maximum carboxylation efficiency (Vcmax), maximum electron transport rate (Jmax), and triose phosphate utilization rate (VTPU), which suggests a well-functioning photosynthetic apparatus capable of fully utilizing the limited light energy. Moreover, the plants had the highest root–shoot ratio, saikosaponin content, and total saikosaponin yield, which indicates that they allocated more resources to storage and defensive adaptations. Under extremely low light intensity (ELI, 50 μmol m−2 s−1), more energy was partitioned to photoprotection, and strong oxidation resistance developed, but saikosaponin accumulation and root biomass were lowest due to greatly reduced carbon assimilation. The MLI improved both the quantity and the quality of herbal extracts from B. chinense: the total saikosaponin yield was 1.3 times the corresponding value of the control (500 μmol m−2 s−1), and lower illumination levels were counterproductive. Our results suggest that B. chinense would be suitable for introducing to an agroforestry system.

Background Metastasis is the leading cause of cancer mortality and is a major hurdle for lung cancer treatment. Invadopodia, which are cancer-specific protrusive structures, play a crucial role in the metastatic cascade through degradation of the basement membrane and surrounding stroma. Cortactin, a critical component of invadopodia, frequently used as an invadopodia marker, a universally important player in invadopodia function, and is frequently overexpressed in cancer, but the exact mechanism of regulation is not yet fully understood. Methods The expression level of CTTN in human non-small cell lung cancer (NSCLC) tissues was detected by qRT-PCR. Cell migration, invasion and invadopodia formation were assessed in vitro by wound-healing, transwell assay and immunofluorescence, respectively. The dual-luciferase reporter assay was used to identify the direct target of miR-182. Results Hepatocyte growth factor (HGF) and phorbol 12,13-dibutyrate (PDBu) can induce CTTN expression, motility, and invasion ability, as well as invadopodia formation in non-small cell lung cancer (NSCLC). Moreover, miR-182 suppressed metastasis and invadopodia formation by targeting CTTN in NSCLC. Our qRT-PCR results showed that CTTN expression was inversely correlated with miR-182 expression that suppressed invadopodia formation via suppression of the Cdc42/N-WASP pathway. Furthermore, miR-182 negatively regulated invadopodia function, and suppressed extracellular matrix(ECM) degradation in lung cancer cells by inhibiting cortactin. Conclusion Collectively, our results demonstrated that miR-182 targeted CTTN gene in NSCLC and suppressed lung cancer invadopodia formation, and thus suppressed lung cancer metastasis. This suggests a therapeutic application of miR-182 in NSCLC. Electronic supplementary material The online version of this article (10.1186/s13046-018-0824-1) contains supplementary material, which is available to authorized users.

Giant-cell carcinoma of the lung (GCCL) is a rare histological form of poorly differentiated non-small-cell lung cancer, which is classified as a subtype of pulmonary sarcomatoid carcinomas. In this case report, we describe the case of a 50-year-old Chinese male who presented with a pulmonary nodule in the right upper lobe of his lung. After thoracoscopic lobectomy, a histopathologic diagnosis of GCCL was made. He did well postoperatively, showing no local recurrence or distal disease in a 7-year follow-up period. Furthermore, for this case, we also analyzed 295 tumor-related driver genes with high-throughput sequencing technology. We found that treatment using MEK inhibitor, CDK 4/6 inhibitor, and TP53 inhibitor may provide a new therapeutic direction for GCCL. Therefore, complete tumor excision is the best choice of treatment strategy at the early stage of GCCL and gene target therapy may be a new therapeutic option for this disease.

Rechargeable batteries and supercapacitors are widely investigated as the most important electrochemical energy storage devices nowadays due to the booming energy demand for electric vehicles and hand-held electronics. The large surface-area-to-volume ratio and internal surface areas endow two-dimensional (2D) materials with high mobility and high energy density; therefore, 2D materials are very promising candidates for Li ion batteries and supercapacitors with comprehensive investigations. In 2011, a new kind of 2D transition metal carbides, nitrides and carbonitrides, MXene, were successfully obtained from MAX phases. Since then about 20 different kinds of MXene have been prepared. Other precursors besides MAX phases and even other methods such as chemical vapor deposition (CVD) were also applied to prepare MXene, opening new doors for the preparation of new MXene. Their 2D nature and good electronic properties ensure the inherent advantages as electrode materials for electrochemical energy storage. In this review, we summarize the recent progress in the development of MXene with emphasis on the applications to electrochemical energy storage. Also, future perspective and challenges of MXene-based materials are briefly discussed regrading electrochemical energy storage.

Developing highly active non-noble catalysts for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is essential for overall water splitting. In this work, by means of first-principles computations, we screened a series of transition metal atom anchored C2N monolayers (TMx@C2N, TM = Ti, Mn, Fe, Co, Ni, Cu, Mo, Ru, Rh, Pd, Ag, Ir, Pt, or Au) as electrocatalysts for both HER and OER. Almost all TMx@C2N composites show metallic properties, indicating outstanding charge transfer for efficient electrochemical procedures. Ti1@C2N, Mn1@C2N, Co2@C2N, Ni2@C2N, Cu2@C2N, Mo1@C2N, Ru2@C2N and Ir1@C2N exhibit high catalytic activity toward the HER. Among them, Ti1@C2N would be the best HER catalyst since both N and Ti atoms are active sites. Unfortunately, Ti1@C2N exhibits no OER activity. Instead, only Mn1@C2N could perform as a bifunctional electrocatalyst with N and Mn atoms as active sites for the HER and OER, respectively. This work would open a new door for the development of non-noble metal bifunctional electrocatalysts for overall water splitting and also shed light on C2N-supported nanomaterials as advanced catalysts.

Li-containing NASICONs (Na super ionic conductors) usually have high ionic conductivity and can serve as solid electrolytes for Li batteries. In this work, we screened the Materials Project database and found seven kinds of LixM2(PO4)3 (M = Bi, Ge, In, Mo, Sb, Sc, and Zr) which could be applied as solid electrolytes for Li batteries. The most thermodynamically stable phases of each series of LixM2(PO4)3 were investigated through density functional theory computations. The results indicate that all these materials are wide-band-gap semiconductors with the band gap ranging from 3.55 to 4.88 eV. Meanwhile, the width of their electrochemical window is not directly related to the band gap; instead, it is mainly determined by the chemical potential of Li ions in these materials. Ab initio molecular dynamics simulations indicate that NASICONs with more Li ions or monoclinic symmetry possess higher Li ion conductivity at room temperature, among which Li3Bi2(PO4)3 has the highest conductivity of ∼10−3 S cm−1. Comprehensively considering the stability, the width of the electrochemical window, the band gap and the ionic conductivity, we propose that Li3Sc2(PO4)3 could be a very promising solid electrolyte for Li batteries.

Nitrogen fixation is one of the most essential processes in chemistry. Developing more effective nitrogen fixation systems to catalyze the reaction under mild conditions is one of the most attractive but long-standing challenges. In this work, by means of first-principles computations, we systematically investigated the catalytic performance of transition metal atom-anchored C2N monolayer electrocatalysts (TMx@C2N, x = 1 or 2; TM = Ti, Mn, Fe, Co, Cu, Mo, Ru, Rh, Pd, Ag, Ir, Pt, or Au) for N2 fixation. The natively N edged uniform holes could fix the TM atoms firmly in TM–Nx configurations, which is beneficial for the N2 fixation. Among them, Mo2@C2N exhibits the best catalytic performance for the reduction of N2 to NH3 with a maximum free energy change of 0.41 eV and an energy barrier of 0.51 eV, indicating that Mo2@C2N is a promising catalyst with high catalytic activity for the reduction of N2 to NH3. We believe that this work could provide a new idea for the design of N2 fixation catalysts and shed light on C2N monolayers as excellent substrates for catalysis.