The accumulation of protein aggregates in neurons is a typical pathological hallmark of the motor neuron disease amyotrophic lateral sclerosis (ALS) and of frontotemporal dementia (FTD). In many cases, these aggregates are composed of the 43 kDa TAR DNA-binding protein (TDP 43). Using a yeast model for TDP 43 proteinopathies, we observed that the vacuole  markedly contributed to the degradation of TDP 43. This clearance occurred via TDP 43-containing vesicles fusing with the vacuole through the concerted action of the endosomal-vacuolar  pathway and autophagy. In line with its dominant role in the clearance of TDP 43, endosomal-vacuolar pathway activity protected cells from the detrimental effects of TDP 43. In contrast, enhanced autophagy contributed to TDP 43 cytotoxicity, despite being involved in TDP 43 degradation. TDP 43’s interference with endosomal-vacuolar pathway activity may have two deleterious consequences. First, it interferes with its own degradation via this pathway, resulting in TDP 43 accumulation. Second, it affects vacuolar proteolytic activity, which requires endosomal-vacuolar trafficking. We speculate that the latter contributes to aberrant autophagy. In sum, we propose that ameliorating endolysosomal pathway activity enhances cell survival in TDP 43-associated diseases. Our study highlights the pivotal role of endolysosomal pathway activity in TDP 43 proteinopathies. Whereas previous studies focused on the role of autophagy in the clearance of cytotoxic TDP 43, we propose that the endolysosomal pathway is more important than autophagy for the survival of cells accumulating detrimental TDP 43. In both pathways, protein substrates (such as TDP 43) are sequestered into vesicles, either multivesicular bodies (MVBs) or autophagosomes . These vesicles fuse with the lysosomal membrane and subsequently release their content into the lysosomal lumen, where protein degradation occurs via proteases such as Pep4/Cathepsin D. Both vesicular pathways are interconnected. In mammalian cells (but not in yeast), some MVBs fuse with autophagosomes, leading to the formation of amphisomes which then fuse with lysosomes. Moreover, the endolysosomal pathway is required for directing important lysosomal proteases, thus decisively contributing to proteolytic capacity of this organelle.Our study raises a number of questions regarding TDP 43 degradation and cytotoxicity. For instance, in cells accumulating cytoplasmic TDP 43, different types of potentially cytotoxic TDP 43 species can be expected, e.g., monomers, oligomers, and different classes of protein aggregates.Which kinds of TDP 43 species are recruited into MVBs for degradation via the endosomal-vacuolar pathway, and which kinds of TDP 43 species are sequestered into Atg8-labelled cellular compartments for elimination via autophagy?For steric reasons, one would expect that MVBs contain smaller TDP 43 species than autophagosomes, which could easily enclose large protein aggregates. It is possible that the endosomal-vacuolar pathway is involved in the clearance of more cytotoxic species than autophagy. This could explain why loss of this pathway is more detrimental for TDP 43-expressing cells than loss of autophagy.What is the molecular machinery that determines whether TDP 43 is degraded via the endosomal-vacuolar pathway or via autophagy (or via the ubiquitin-proteasome system)?It is tempting to speculate that the ubiquitylation pattern of TDP 43 plays an important role. Lysine 63 (K63) polyubiquitin chains could favor the endosomal-vacuolar pathway, while K48 polyubiquitin chains could facilitate degradation via the proteasome, and both chains could be substrates for ubiquitin-dependent autophagy.What is the molecular machinery that recruits TDP 43 into MVBs for degradation via the endosomal-vacuolar pathway?Whereas there is a significant amount of information regarding the molecular machinery involved in recruiting protein aggregates into autophagosomes, the mechanisms that enable the recruitment of cytosolic proteins into MVBs remain largely unknown.Autophagy has been shown to be a cytoprotective mechanism to eliminate deleterious protein aggregates. Therefore, pharmacological induction of autophagy has been proposed to be an efficient mechanism to prevent neuronal loss in neurodegenerative disorders. However, this approach was not successful in our yeast TDP 43 model. In contrast, it increased cytotoxicity.Does the observed inhibitory effect of TDP 43 on endosomal-vacuolar pathway activity and vacuolar proteolytic activity reprogram  autophagy towards cytotoxicity?If this holds true, a therapeutic approach that addresses both endosomal-vacuolar pathway activity and autophagic turnover should be much more effective than targeting autophagy alone.Resolving these questions in yeast TDP 43 proteinopathy models and their validations in higher model systems  will improve our understanding of the molecular mechanisms of devastating TDP 43-associated human disorders.


L/IH = 6000 as relative humidity (RH) consecutively changes between 11% and 95%; small hysteresis of 8% RH; reliable repeatability and stability. In addition, a detailed mechanism analysis is performed to investigate the difference in water adsorption and ions transfer under various RH levels. Notably, the one-step supramolecular assembly method to prepare Pyr-rGO provides a new insight into developing novel functional humidity sensing materials with enhanced device performance.A facile one-step supramolecular assembly method is adopted to modify reduced graphene oxide (rGO) with functional organic molecule pyranine for achieving comprehensive humidity sensing performance. The fabricated humidity sensor based on pyranine modified-reduced graphene oxide (Pyr-rGO) exhibits excellent sensing performance with ultrafast (<2 s) and ultrahigh response of I So far, several effective methods are proposed to fabricate humidity sensors while it still remains a challenge to make the fabrication more facile. For the whole sensor fabricating process, the selection of sensing materials is the most critical stage. Great efforts have been made to investigate the different sensing characteristics of various materials, including ceramics5, metal oxide6, composites and organic polymers9. Nevertheless, it is hard to simultaneously realize the comprehensive humidity sensing properties such as rapid & high response, small hysteresis and reliable stability10. For instance, the ceramics materials possess excellent physical and chemical stability but the practical application is restricted since the need of auxiliary heat cleaning process. Thus, it is of great importance to explore a superior humidity sensing material which can endeavor more comprehensive properties.Humidity sensors have increasingly aroused interests due to the wide application in various realms, such as the indoor humidity measurement, industrial and agricultural environmental monitoring11. Several methods have been explored to prepare graphene such as mechanical exfoliation12, chemical vapor deposition14, and epitaxial growth15, but the most effective approach should be the chemical reduction mainly because the potential for the relatively low-cost and large-scale fabrication from the view of practical application16. Unfortunately, the pristine reduced graphene oxide (rGO) without proper modification is not satisfying when applied as sensors, exhibiting slow response and low sensitivity towards gas or humidity changes18. Moreover, the rGO nanosheets tend to irreversibly aggregate during the chemical reduction process, limiting the further devices fabrication. Hence, it is necessary to modify rGO with appropriate method.Graphene, a fascinating material with perfect 2D atom-thin structure, large specific surface areas and excellent electronic properties, has been considered as a promising candidate for extensive applications including humidity sensing19, electrostatic forces20, and π-π stacking21, is an alternative approach which will maximize the remain of inherent properties of rGO22. In addition, supramolecular assembly modification allows more possibilities for functional “guests” such as inorganic ions, organic molecules or nanoparticles18, which can be specific to enhance the dispersibility or humidity sensing performance of the as-prepared material.Covalent chemical modification of rGO is widely used and indeed the sensing properties can be enhanced prominently, but usually a complex reaction process is required and the instinct structure and electrical properties of rGO will be damaged to some degree. To realize the mild and effective modification of rGO, a facile supramolecular assembly modification based on non-covalent interactions such as hydrogen bondingL/IH = 6000) response. In addition, the humidity sensing mechanism under different RH levels has also been investigated in detail. It is worthy to mention that the one-step supramolecular assembly method has the potential for facilely preparing the novel functional materials with enhanced humidity sensing performance.In this work, we present a facile one-step supramolecular assembly method to modify rGO with functional organic molecule pyranine to form pyranine modified- reduced graphene oxide (Pyr-rGO) for achieving high performance humidity sensing materials. The as-prepared sensors exhibit excellent comprehensive humidity sensing properties including ultrafast (<2 s) and ultrahigh  compared to GO (ID/IG = 1.15), suggesting that the reduction process enhanced the defect content or edge area28. Interestingly, Pyr-rGO showed the same ID/IG value as rGO, proving that the supramolecular assembly modification is a mild approach without causing further disruption of rGO structure.Raman spectroscopy was used to analyze the structural changes during the supramolecular assembly and reduction process. As indicated in Fig. 29. Hence, the impedance of Pyr-rGO sensors at different RH levels was tested with frequency ranged from 50 Hz to 100000 Hz. As can be seen from Fig. It is generally known that the response of humidity sensors is dependent on the testing frequency which should be determined first before investigating the humidity sensing propertiesL) and 95% RH (IH), respectively. By calculation  and an ultrafast response time (<2 s). In addition, the recovery time could be controlled within 6 s for such a high-expansion response of Pyr-rGO sensors. It was noteworthy that the Pyr-rGO sensors also exhibited remarkable repeatability, and the response remained highly stable (IL/IH = 6000) with no attenuation in the impedance (IL and IH) even after 100 cycle continuous response-recovery test  with a long response time for more than 50 s. Moreover, the repeatability of rGO sensors was unqualified that the response and impedance (IL and IH) attenuated significantly after the five-cycle test as shown in Fig. For humidity sensors, the response, response-recovery time and repeatability are the key parameters to directly determine the accuracy and efficiency in practical test. Figure ion Fig. , the Pyrest Fig. . The PyrIn practical humidity sensing applications, the humidity hysteresis phenomenon is also an important parameter to evaluate the practicability of sensors, which is unavoidable but expected to be minimized. The reason for the existence of humidity hysteresis is that different energy is required during the humidification and dehumidification process. Larger desorption energy is always needed than adsorption energy, signifying the corresponding impedance cannot return to the adsorption impedance at the same time, and thus forms the humidity hysteresis. Figure 31. Figure ct represents the resistance of charge transfer, the constant phase element (CPE) stands for the sensing film capacitance (CPE1) and electrode/sensing film interface capacitance (CPE2).Complex impedance spectra (CIS) can be adopted to investigate the sensing mechanism of humidity sensors1). As well-known, the impedance of a CPE is generally defined as Equation (32At low RH range (11% and 33%), the CIS ran in almost straight lines and thus the EC model in this case could be described as a CPE , the curve of CIS was part of semicircle, which was mainly generated from the intrinsic impedance of the sensing film. It could be described by a simplified EC model comprising a resister and a capacitor connected in parallel37. Therefore, the EC model shown in Fig. 4b3 was suitable for the sensing mechanism of Pyr-rGO at this stage. At high RH range, apart from the chemical adsorption, the physical adsorption has upgraded as the main adsorption method. Thus, more serial water layers are formed to further accelerate the ions transfer, and the water molecules can permeate into the Pyr-rGO film to induce the electrolytic conduction. Therefore, the impedance continuously decreases sharply at high RH range.At high RH range , the CIS exhibited a semicircle shape with a short straight line at low frequency region. As the RH increased, the straight line grew longer while part of the semicircle disappeared. Actually, the short straight line represented Warburg impedance, caused by the ions diffusion at sensing material/electrode interfacei.e. pyranine, realized the synergetic functionalization to enhance the dispersibility and humidity sensing properties. The fabricated Pyr-rGO humidity sensors exhibited comprehensive sensing performance such as ultrafast response (<2 s) and ultrahigh response (IL/IH = 6000) as RH alternately changed between 11% and 95%; small hysteresis of 8% RH; reliable repeatability and stability. Further, the complex impedance spectra under different RH was discussed and the corresponding equivalent circuits were built to investigate the humidity sensing mechanism in detail, verifying that different water molecules adsorption and ion transfer were adopted in different RH levels. Notably, we believe that the Pyr-rGO represents a new platform for developing novel functional materials in ultra-sensitive humidity sensors and shows the potential for facile one-step humidity sensing materials preparation.In summary, the Pyr-rGO based humidity sensing materials were prepared through a facile one-step supramolecular assembly method. The modification of rGO by organic molecule, i.e. Trisodium 8-hydroxypyrene-1,3,6-trisulphonate, >85%) and hydrazine hydrate (>98%) were purchased from Alfa Aesar. Ammonium hydroxide (28% NH3 in H2O), lithium chloride (≥99%), magnesium chloride (99.99%), magnesium nitrate (≥99%), sodium chloride (≥99%), potassium nitrate (≥99%), and potassium chloride (≥99%) were all purchased from Sigma-Aldrich. All the chemicals were analytical grade and used as received without further purifications.GO flakes were obtained from XianFeng NANO Co., Ltd. Pyranine (GO flakes were dispersed into deionized (DI) water under vigorous ultra-sonication for an hour to prepare a brown GO dispersion of 1 mg/mL. 5 mL GO dispersion (1 mg/mL) was transferred into a 50 mL round-bottom flask and diluted by 15 ml DI water. Subsequently, 80 μL ammonium hydroxide (30%) and 10 mL hydrazine hydrate (0.1%) were added respectively and heated at 95 °C for 1 h in oil bath. After cooling to ambient temperature, the mixture was filtrated to dry and then re-dispersed into 20 mL DI water under mild sonication for 5 min to prepare 0.25 mg/mL rGO dispersion.5 mL GO dispersion (1 mg/mL) was transferred into a 50 mL round-bottom flask and diluted by 15 ml DI water. Pyranine (100 mg), ammonium hydroxide and hydrazine hydrate  were added into the dispersion respectively under mild stir for 30 mins and then the mixture was further stirred at 95 °C for 1 h in oil bath. After cooling to ambient temperature, the dispersion was transferred to a 50 mL centrifuge tube and washed by DI water under 10 mins centrifugation at 12000 r/min for three times. The residuum was then re-dispersed into 20 mL DI water to prepare 0.25 mg/mL Pyr-rGO dispersion.In the fabrication of humidity sensors, a facile Drop & Dry method was applied by dropping approximately 5 μL Pyr-rGO dispersion on Ag-Pd Interdigital electrodes (IEs) and then dried on heating plate in air at 50 °C for 10 min. Finally, a thin sensing film was formed on the surface of IEs and thus the humidity sensors were prepared for testing as shown in Fig. 2, Mg(NO3)2, NaCl, KCl, and KNO3 with corresponding relative humidity (RH) of 11%, 33%, 54%, 75%, 85%, and 95% respectively. To ensure the accuracy of RH, 10 h stabilization of the flasks was necessary to get fully liquid-gas equilibrium before humidity sensing test and the ambient RH was maintained at 25% by an automatic drier. The ideal flow chart of the humidity sensing test was indicated in Supplementary Figure All the humidity sensing tests were performed by a humidity sensing system  at an operating temperature of 25 °C. The voltage in humidity test was 1 V AC, and the testing frequency varied from 50 Hz to 100000 Hz. The humidity gradient was controlled by several erlenmeyer flasks filled with different saturated salt solutions which were LiCl, MgClThe humidity sensing materials were characterized by several techniques. The morphology was characterized by transmission electron microscope (TEM) . The surface properties were examined by FT-IR , Raman-scattering spectroscopy (HORIBA Jobin Yvon Raman microscope (LabRAM HR800) and X-ray photoelectron spectra .Supplementary information


We developed new technology for precise seawater temperature control to examine warming effects on communities of bacteria, microbial eukaryotes (protists) and metazoans. Despite highly contrasting phylogenies, size spectra and diversity levels, the three community types responded similarly to seawater warming treatments of +3°C and +5°C, highlighting the critical and overarching importance of temperature in structuring communities. Temperature effects were detectable at coarse taxonomic resolutions and many taxa responded positively to warming, leading to increased abundances at the community-level. Novel field-based experimental approaches are essential to improve mechanistic understanding of how ocean warming will alter the structure and functioning of diverse marine communities.Temperature variability is a major driver of ecological pattern, with recent changes in average and extreme temperatures having significant impacts on populations, communities and ecosystems. In the marine realm, very few experiments have manipulated temperature  Recent alterations in environmental conditions, principally caused by human activities, have rendered this goal more pressing since a better understanding of ecological processes is necessary to improve our ability to detect and predict the impact of future changes ,2. The mClimate change is driving the redistribution of species, reorganization of communities and restructuring of entire ecosystems at global scales ,12. WarmMarine communities are particularly useful models for global change ecology studies because (i) they are often extremely diverse and comprise highly divergent taxa, from microbes to metazoans; (ii) they often comprise taxa that are short-lived and fast growing and thereby responsive to experimentation; and (iii) they are dominated by ectotherms that are strongly influenced by their surrounding environment and thermal variability. In contrast to both terrestrial ,21 and fin situ temperature manipulations within natural marine habitats that support complex communities and diverse species pools. We tested the following hypotheses: (i) that increased temperature will alter patterns of diversity and community structure across multiple diverse biological groupings (i.e. from unicellular microorganisms through to metazoans), and (ii) that the pervasive community-level effects of increased temperature will be detectable at coarse taxonomic resolutions.We developed a novel experimental tool to conduct 2.(a)in situ with a heated settlement panel system (HSPS). Briefly, the HSPS comprised three sets of 10 replicate panels  mounted onto a fibreglass lattice frame . The first set of 10 panels were each heated with an electrical heat pad fixed to the underside of a stainless steel plate, and controlled by a series of microprocessors linked to a temperature sensor embedded onto each panel surface. The second set of 10 panels were heated in a similar way and a third set of 10 panels served as experimental controls held at ambient seawater temperature . The desired temperature increase for each treatment  was programmed into a shore-based control unit , which maintained constant communications to the microprocessor units to precisely control temperatures over the panels.Seawater temperature was elevated in situ seawater temperature within a highly-dynamic coastal marine habitat, with the desired warming treatments of +3°C and +5°C above ambient sea temperature maintained for 40 days (a–e). Temperatures over the experimental panels precisely tracked natural variability in ambient sea temperature, which was of the order of 3°C throughout the experiment and was related to tidal cycles and storm events  and the target treatments were maintained within ±0.2°C throughout the experiment .The field experiment was conducted within a marina in Plymouth, UK, between 10 October and 18 November 2013. An experimental settling surface (polyester fabric with a 700 µm pore size) was mounted onto each panel to provide a surface for colonization by marine organisms. A glass microscope slide was also secured to each panel, ensuring that it was mounted against the settling surface and within the heated boundary layer. The HSPS was deployed horizontally, suspended from a pontoon at approximately 2 m depth, with the plate surfaces facing downwards. Microbial and metazoan communities were sampled after 18 and 40 days, respectively, which allowed adequate time for biofilms and sessile invertebrates to cover more than 50% of all microscope slides/panel surfaces. Previous work has shown that assemblages of bacteria and protists associated with submerged substrata in marine habitats reach maturity within this timeframe –26, whil 40 days a–e. Tempm events . Experim(b)in situ manipulation, microbial diversity was assessed by biofilm DNA extraction and bacterial 16S and eukaryote 18S rRNA gene high-throughput sequencing. Biofilms were removed from five replicate microscope slides (selected at random from each treatment) using a sterile razor blade before DNA was extracted and stored at −20°C. Standard PCR and sequencing techniques were employed  and QIIME [2 subunits. The metazoan taxa within each 1 × 1 mm grid-square were identified to the lowest taxonomic level possible  and the total number of subunits within which each taxon occurred was summed for each sample to quantify areal cover. The total abundance  of each taxon was also recorded.After 18 days of nd QIIME  was usednd QIIME ,31. In snd QIIME  and remo(c)p < 0.05) pairwise tests were conducted to determine which treatments differed from one another. Univariate community-level metrics were examined with permutational ANOVA. Similarity matrices based on Euclidean distances between untransformed abundance and richness values were constructed prior to conducting 999 unique unrestricted permutations to test for differences between treatments. Where significant differences in multivariate community structure between warming treatments were detected (at p < 0.05), SIMPER analysis was conducted to determine which OTUs/taxa contributed most to the observed differences. All statistical procedures were conducted using PRIMER v7 software [Community-level response patterns were analysed using multivariate statistics. The relative abundances of the OTUs determined by molecular methods and the abundance/cover of taxa identified with traditional taxonomic approaches were analysed separately but in a directly comparable way. Abundance data were initially square-root transformed to down-weight the influence of highly abundant taxa before constructing Bray–Curtis similarity matrices. PERMANOVA  was usedsoftware  with thesoftware .3.a–c). PERMANOVA [d,e), as communities developed under warmed conditions were significantly different from those held at ambient temperature (f) and PERMANOVA tests did not detect significant between-treatment variability , suggesting that multivariate community structure, rather than multivariate dispersion (i.e. variability between plates), was impacted by increased seawater temperature.In total, 2465 and 388 distinct OTUs were determined for bacteria and protists, respectively, and 12 distinct metazoan taxa (mostly bryozoa and ascidia) were identified. Multivariate analyses showed that communities comprising bacteria, protists and metazoans responded analogously to warming, in that communities held under ambient conditions were distinct from those that had developed under the warming treatments a–c. PERMERMANOVA  tests shperature . For metperature f and PERiability . For alla–c) with, on average, communities comprising three to six times as many organisms/marker genes in the +5°C treatments compared with the controls. Variability between temperature treatments was significant for the bacteria and metazoan communities, but not for the microbial eukaryotes owing to high within-treatment variability . While this trend was apparent for all the groups, statistically significant differences between treatments were observed only for protists . For the protist communities, OTUs closely related to the diatom Melosira varians and the dinoflagellate Paradinium poucheti were less abundant at higher temperatures, whereas several other taxa  showed the opposite pattern and were important discriminators between treatments . The metazoan communities were dominated by colonial and solitary ascidians and cheilostome bryozoans, which were all more abundant on warmed panels compared with controls . The UK-native ascidians Diplosoma listerianum and Ciona intestinalis, and the non-native ascidian Corella eumyota, were major contributors to the observed dissimilarity between the communities, and were all more abundant on panels held at +3°C and +5°C compared with those held at ambient temperature .With regards to the responses of individual OTUs/taxa to warming, a SIMPER analysis was conducted to determine the variables that were the principal contributors to the observed dissimilarity in community structure between the treatments. For the bacterial communities, Community-level responses to increased temperature were examined across a range of taxonomic resolutions by consolidating species/OTU-level data according to their taxonomic position . For bacteria, partitioning in multivariate community structure by treatment was evident through to aggregation to order level . Order-level communities held at ambient temperature and at +5°C were significantly different, with overall dissimilarity at 21.8% , and, andin s between the temperature treatments, suggesting a high rate of turnover for these taxon-rich communities. Bacterial communities were particularly diverse and the number of unique taxa associated with each treatment was high (i.e. 250–400 OTUs); replacements of species in response to warming suggests some degree of selectivity or adaptation to temperature at the community-level. For the metazoans, however, there was no evidence of species turnover as multivariate communities based on presence/absence data did not differ between temperature treatments. Rather, shifts in metazoan community structure were related to changes in abundance rather than turnover of species or higher-order taxa. The higher richness of bacteria and protist communities and the greater diversity of the available species pool compared with metazoans may suggest that species turnover, and perhaps functional redundancy, in response to warming is comparatively limited for metazoans.The rate and trajectory of microbial biofilm development is likely to have mediated, to some degree, the development of macroscopic metazoan communities, as settlement of sessile invertebrates is known to be influenced by biofilm community structure ,54. For The most effective and reliable way of determining causation is through controlled experimentation , but manWhile other anthropogenic stressors, such as ocean acidification  and eutr


We propose and analyze nonlinear coupler based on a pair of single mode graphene-coated nanowires. Nonlinear wave interactions in such structure are analyzed by the coupled mode equations derived from the unconjugated Lorentz reciprocity theorem. We show that the routing of plasmons in the proposed structure can be controlled by the input power due to the third order nonlinear response of graphene layer. Our findings show that graphene nonlinearity can be exploited in tunable nanoplasmonic circuits based on low-loss, edgeless cylindrical graphene waveguides. Light control at the nanoscale is one of the important aims of the rapidly developing research field of nanophotonics. Conventional silicon-based photonic circuits cannot localize and manipulate light at the nanoscale due to the diffraction nature of light3689Graphene has nontrivial nonlinear properties. As an example, strong four wave mixing was experimentally observed in graphene, indicating that it exhibits third order nonlinear response17In this paper, we study the nonlinear coupling in a pair of single mode graphene coated nanowires. We first review the properties of the linear modes in a pair of graphene coated nanowires. Then, we derive the coupled mode equations for nonlinear coupling in the structure based on the unconjugated Lorentz reciprocity theorem and solve them numerically. Finally, we demonstrate the power-dependent behaviour of the GNW coupler that allows to route the output by input intensity, and we discuss the influence of structural parameters on coupling.R are covered by graphene, which is held in place by Van der Waals forceε = 2.5, and the spacing between the wires is d. For simplicity, it is assumed that the structure is placed in free space.Schematics of the structure is shown in σ = σ(1) + σ(3)|Eτ|2, where Eτ is the electric field tangential to the graphene surface. The linear surface conductivity σ(1) is a superposition of an interband and an intraband contributions, which are described by the Kubo formulaGraphene is characterized by its surface conductivity as e is electron charge, μc is chemical potential, kB is Boltzmann constant, τ is scattering time, and T is temperature. We assume that μc = 0.5, τ = 10 ps, corresponding to low loss high quality graphene1620T = 300 K.where σ(3) isThe third order nonlinear conductivityvf ≈ c/300 is the Fermi velocity.where A single graphene coated nanowire can support different order modes, which can be classified by azimuthal mode profileLB = π/Δβ with Δβ = βa − βs, βa and βs are propagation constants of odd and even modes, respectively.When two single-mode GNWs are placed parallel and are close enough, the hybridisation of the modes creates antisymmetric (odd) mode and symmetric (even) mode, as shown in the inset in em, hm} exp(−αmz) exp(iβmz), where βm is the wavenumber, αm is the attenuation of the m-th mode, {em, hm} are transverse profiles of electric and magnetic fields, and m is either “a” or “s”, denoting the antisymmetric or symmetric mode.The linear modes in GNW pair can be described as {z-invariant graphene plasmonic waveguide, the reciprocity theoremTo describe the nonlinear interactions, we aim to derive coupled mode equations23x0 denotes the position of graphene layer on the cross section of waveguide, JNL is the nonlinear surface current in graphene, {E, H} are the electromagnetic field in the presence of nonlinear current JNL, {eq, hq} is the q-th eigen mode of the waveguide, and S is the entire cross-section of the waveguide where the fields are present.where JNL does not modify the mode profile but only its amplitude, we can write electromagnetic field {E, H} in such waveguide as a superposition of linear modes. Considering the fact that GNW pair in this paper only supports two modes, we haveAssuming that the presence of As and Aa are the amplitude of even and odd modes with a dependence on z. Expressions for the magnetic field H can be written in a similar way.in which z component of electric field is much larger than other tangential field components. Then, the induced nonlinear surface current has only z-component and it is expressed asSince the even and odd modes originate from the hybridization of TM modes in a single GNWSubstituting (4) into (5), we haveAs(z). Substituting (4) and (6) into (3) and letting z-direction, we have amplitude equation for As asWe first consider the amplitude evolution of even mode where the nonlinear coupling coefficients areγ2, γ4 and γ5 vanish after integration. The amplitude equation for the odd mode Aa could be derived in a similar way. As a result, the coupled mode equations for the nonlinear coupling can be derived asDue to the field symmetry of even and odd modes, ηi can be calculated from (8) by replacing es,z− by ea,z−.where R = 50 nm, d = 150 nm and the working frequency is 30 THz. We calculate eigen mode profiles and their mode indices numerically using commercial simulation package COMSOL. We found that the mode indices of odd and even modes are 21.50 and 20.08, respectively, and this leads to the beat length LB of 3.52 μm.To show a particular example, we consider a pair of graphene coated nanowires with P0 is launched into the left nanowire. The input power in P0 = 0.01 mW, which is low enough so that all nonlinear terms in equations are negligible, i.e. at least 10 times smaller than linear terms. As the wave propagates, the energy couples from the left nanowire to the right one, with complete energy transfer after propagating a distance of LB. We note that the total energy decreases with propagation due to intrinsic loss in graphene. When the input power is large enough, the coupling changes due to graphene nonlinear response. P0 = 2.9 mW. After propagating a distance of LB, most of the energy still flows in the left nanowire with little coupling to the right waveguide. At the distance about LB/2, a small portion of energy is coupled into the right wire, and then coupled back to left wire while propagating toward LB.Pc0, = 2.29 mW, equal output power from both wires can be achieved. When P0 further increased to 2.9 mW, the power is predominantly localized in the left nanowire. It is worth noting that in our simulations, when the input power is 3 mW, the maximum electric field in graphene is 3 × 107 V/m, which is well below the breakdown threshold of grapheneTo further demonstrate the power dependence of the coupler performance, LB and vice versa, which can be inferred from LB, a longer coupler length means longer nonlinear interaction region, leading to larger nonlinear phase shift in the coupler and as a result smaller input power is required to achieve the nonlinear switching. At the same time, the length of the coupler cannot be too large, because of graphene absorption and finite plasmon propagation length. Thus we choose an intermediate spacing d = 150 nm in this work, which gives LB that is shorter than the graphene plasmon decay length, and long enough so that the nonlinear effects allow to observe the switching in the coupler.The spacing d has an important impact on the switching power. In conclusion, we have studied the nonlinear plasmon coupling in a pair of single mode graphene coated nanowires. Based on unconjugated Lorentz reciprocity theorem, we derived the coupled mode equations describing nonlinear wave propagation in such a structure. We demonstrated that the nonlinear switching of plasmons between the waveguides can be achieved by changing the input power, and due to the large third order nonlinearity and tight field confinement, relatively low power is sufficient for achieving efficient switching. Our results shows nonlinearity of graphene could be exploited as a new degree of freedom for designing active plasmonic devices based on cylindrical graphene structure.J and guided by a GNW pair satisfies Maxwell’s equationElectromagnetic wave excited by surface current x0 is the position vector of graphene layer on the waveguide cross section. The electric and magnetic fields {eq, hq} of the q-th eigen mode of GNW pair satisfies the source free Maxwell’s equations:where hq, eq}, respectively. Then, we multiply H, E}, and combining them we arrive at the reciprocity theorem in the formWe multiply By integrating both parts of this equation over a suitable volume and applying the divergence theorem, taking into account the bounded nature of guided wave, we derive J = σ(1)Eτ on the surface of nanowire.Finite element method (FEM) calculations for the linear modes in GNW pair are performed with the help of COMSOL Multiphysics modal analysis with perfectly matched layer (PML) enclosing the structure. Graphene is modelled as an electric field-induced surface current How to cite this article: Gao, Y. and Shadrivov, I. V. Nonlinear coupling in graphene-coated nanowires. Sci. Rep.6, 38924; doi: 10.1038/srep38924 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


We propose a novel plasmonic Bragg reflector (PBR) based on graphene with multiple-step silicon structure. The monolayer graphene bears locally variable optical properties by modulation of electric fields, and the periodical change of effective refractive index on graphene can be obtained by external bias voltage in the mid-infrared region. Through patterning the PBR units into multiple-step structures, we can decrease the insertion loss and suppress the rippling in transmission spectra. By introducing the defect into the multiple-step PBRs, the multiple resonance modes are formed inside the stopband by increasing the step number. This work may pave the ways for the further development of ultra-compact low-cost hyperspectral sensors in the mid-infrared region. Recently, graphene has become a popular research field and has attracted an increasing amount of attention . GraphenIn this paper, the plasmonic Bragg reflector (PBR) structure based on graphene with multiple-step units are numerically presented in the mid-infrared region. External bias voltages are applied to control the optical properties of the graphene, and the periodical modulation of effective refractive index on graphene is obtained to form a forbidden band on transmitted spectrum. The insertion loss is lower and the rippling in transmission is suppressed by increasing the step number of multiple-step structures. Furthermore, multiple peaks appear in the stopband while the defect introduces into the multiple-step PBRs. The finite element method (FEM) has been utilized to perform simulation work.biasV is applied between graphene and silicon grating, the periodic induced electric field can be obtained and modulated in graphene due to the periodic grating structure. This theoretic structure is not hard to build up experimentally. The grating silica/silicon substrate can be fabricated via electron beam lithography. The monolayer graphene can be prepared by the chemical vapor deposition method and then placed on the grating substrate. When a broadband mid-infrared irradiation is incident on the structure from the left interface, SPPs will be excited and propagate along the graphene layer. According the Bragg condition, only a narrowband of the spectrum can pass through the graphene waveguide and the rest will be reflected away., We set d(y), i.e., d1 and d2 labeled in 2 thin layer, which is a periodic step function of y, and it is far less than the width of the trench in the grating. We assume the field is given by the equation E(y) = εSiO2V/d(y); here, V = biasV, and εSiO2 is the relative permittivity of SiO2. Then, the surface charge density of graphene can be approximated by n(y) = [ε0E(y)]/e = ε0εSiO2V/ed(y); here, ε0 is the vacuum permittivity, and e is the elementary charge. Further, we can modulate the Fermi level according to fE(y) = fħν(sπn)1/2; here, fν = 106 m/s is the Fermi velocity of the electron in the graphene, and ħ is the reduced Planck constant. The Fermi level affects the scattering of electrons, characterized by the relaxation time τ = fμE(y)/feν2; here, μ is the carrier mobility. According to Kubo formula, the optical properties of a monolayer graphene can be characterized by a complex surface conductivity Gσ [The schematic of the PBR structure we proposed is shown in ivity σG :σG(y)=2Bk is the Boltzmann constant, T is the temperature, and w is the angular frequency of optical excitation. The first term and the second term correspond to intraband transitions and interband transitions, respectively, where bε and Gt are typically chosen as 2.5 and 1 nm, respectively. The optical parameters of other involved materials are εAir = 1, εSiO2 = 3.9, and εSi = 11.7 in the spectral region of interest. In our study, the values of voltages and the parameters of the structure are dependent on each other and should be reasonably chosen.In our work, the permittivity of graphene layer ,22,23 ca2-Si multi-layer structure. According to Maxwell’s equations and the boundary conditions, the general dispersion relation for the graphene waveguide in the multilayer structures can be solved by the following equation:η0 is the intrinsic impedance of free space. If ε1 = ε2= ε, the effective refractive can be reduced from Equation (3) as follows:We regard the structure as an Air-Graphene-SiOeffN  with bias voltage V and wavelength λ is well depicted in μ = 2 m2·V−1·s−1, and the real parts are invariant while the imaginary parts decrease dramatically as μ increases.The relation of the effective refractive eff-HN) and a low reflective index (eff-LN), as shown in biasV increases. Here, the parameters are set as d1 = 5 nm, d2 = 10 nm, w = 40 nm, and Ʌ = 80 nm.The loss of the graphene-based structure is mainly caused by the imaginary part of complex permittivity of graphene. Here, we firstly consider the real part of complex permittivity of graphene and its lossless style. When SPPs propagate in periodically modulating media, we can regard the graphene-based silica grating structure as a Bragg reflector made of alternating layers with a high reflective index (effN in the groove depth [N changing with deferent SiO2 thickness d and wavelength λ. After comparing the transmission spectra in Furthermore, we design the PBR units into the multi-step pattern to deal with the high insertion loss and severe rippling in the transmission spectra resulting from the abrupt change of ve depth ,25. The t = 100 nm, and the gate voltage gV = 2.2 V. From In order to make the practical application of this ideal platform more extensive, we designed one defect structure in the multiple-step PBR reflectors to realize the filtering, as shown in effN of graphene. This corresponds to the preceding statement. Another conspicuous feature is that the effect decreases with the increase in carrier mobility when it exceeds 20 m2·V−1·s−1. Thus, we can consider the losses negligible in this case, and it can be realized by using proper doping or compensating the gain media. In tλ and rλ in the case of biasV = 3.2 V in order to visualize the propagating principle of the excited SPPs.Finally, we need to consider the material losses of graphene. As shown in We have here presented some plasmonic Bragg reflectors based on graphene to realize the tunable low-loss filtering effect in the broadband multiple-step structures, and PBRs feasibilities have been adequately verified by FEM. By modulating the bias voltages of graphene, we can turn the transmission spectrum according to our need. Moreover, the transmission can reach above 80%, which means the losses are quite low as long as the carrier mobility is large enough. In addition, by designing the PRB units into multi-step structures, we can mitigate the insertion loss and suppress the rippling in transmission spectra. We introduced the defect structure in the multiple-step PBR reflectors to realize multiple filtering phenomena. These proposed designs were easily carried out in experiment. We hope they can help pave new ways in actively tunable sensoring applications.


This study aims at assessing how bilinguals select words in the appropriate language in production and recognition while minimizing interference from the non-appropriate language. Two prominent models are considered which assume that when one language is in use, the other is suppressed. The Inhibitory Control (IC) model suggests that, in both production and recognition, the amount of inhibition on the non-target language is greater for the stronger compared to the weaker language. In contrast, the Bilingual Interactive Activation (BIA) model proposes that, in language recognition, the amount of inhibition on the weaker language is stronger than otherwise. To investigate whether bilingual language production and recognition can be accounted for by a single model of bilingual processing, we tested a group of native speakers of Dutch (L1), advanced speakers of English (L2) in a bilingual recognition and production task. Specifically, language switching costs were measured while participants performed a lexical decision (recognition) and a picture naming (production) task involving language switching. Results suggest that while in language recognition the amount of inhibition applied to the non-appropriate language increases along with its dominance as predicted by the IC model, in production the amount of inhibition applied to the non-relevant language is not related to language dominance, but rather it may be modulated by speakers' unconscious strategies to foster the weaker language. This difference indicates that bilingual language recognition and production might rely on different processing mechanisms and cannot be accounted within one of the existing models of bilingual language processing. When a speaker of more than one language  processes a language, words from the non-relevant language might be activated and interfere. This can happen while speaking, but also during writing, listening and reading. The ability to confine processing to the relevant language is called “language control” and is essential for successful communication. Despite the importance of this phenomenon, research on language control has predominantly concentrated on language production  word production and visual (but not spoken) word recognition. In spoken word production, language control refers to the capacity of a bilingual person to speak in the intended language, while avoiding interferences from the non-intended language. In visual word recognition, language control indicates the ability to understand the meaning of written words belonging to a certain language, while reducing interference from the non-target language. These processes are far from being effortless. Indeed, it is generally agreed that when a word from the intended language is processed, also words from the irrelevant language are coactivated and might interfere during processing  in the former and on the activation level of the language node of the relevant language (language node of the stronger language inhibits words of the weaker language to a greater extent than vice versa) in the latter.Briefly, the different predictions with regard to the IC and the BIA model described in this paper derive from the fact that the amount of inhibition depends on the activation level of the words of the repetition trials  and switch trials . Responses on switch trials are usually less accurate and slower compared to repetition trials, and this difference is known as language “switching costs”  language control in recognition is dominance-related (as the IC model predicts) or dominance-reversed (as the BIA model predicts) and from this at assessing, more generally, whether (2) language control in bilingual recognition and production rely on the same mechanisms. To do it, we tested one group of unbalanced bilinguals  in both a recognition and a production task involving language switching. As to recognition, participants were administered a bilingual lexical decision task; regarding production, participants performed a bilingual picture naming task. In both tasks, switching costs in L1 and L2 were measured. Moreover, to assess languages' baseline strength of activation (believed to be a reflection of language dominance), a “single-language” block was included in the picture naming task, in which pictures had to be named in either L1 or L2 separately.Concerning the predictions, we expect one of two possible outcomes: (1) If the amount of inhibition of the non-relevant language strongly depends on language dominance, we expect to find asymmetrical switching costs in both the lexical decision and the picture naming task. In this framework, if the magnitude of inhibition is dominance-related (as the IC model predicts), then switching costs are expected to be larger for switching to the stronger than for switching to the weaker language in both tasks. If, however, language inhibition in recognition is dominance-reversed (as predicted by the BIA model), switching costs in the lexical decision tasks are expected to be larger for the weaker than for the stronger language. (2) Alternatively, if asymmetric inhibition is applied only in cases of extreme dominance difference between two languages (such in the case of low proficient L2 speakers), then switching costs are expected to be symmetrical in both the recognition and the production task.For the present study, we recruited 32 native speakers of Dutch  from the student population of the University of Groningen . Participants were tested in Dutch and English and were paid for their participation. All participants were right-handed, had normal or corrected to normal vision and had never been diagnosed with reading, learning or language disability. Before the experiment, participants gave their written consent and filled out the Language Experience and Proficiency Questionnaire  and English at school as a second language (L2) for a minimum of 6 years . On a daily basis, speakers were mostly exposed more to Dutch (57%) than to English (34%) or to other languages (9%). To screen for language skills, participants were asked to self-rate their ability to speak, understand and read in Dutch and English based on a ten-point scale, where 0 = no knowledge and 10 = perfect knowledge. Overall, results revealed that participants considered themselves excellent users of Dutch  and good users of English . Their L2 proficiency level was tested using the grammar part of the paper-based Oxford Placement Test Allan, . The teshttp://celex.mpi.nl/), words were matched for word form and lemma frequency  as well as for letter orthographic length . Words were also matched according to their orthographic neighborhood density within each language , between the two languages  and across other languages . The values for the orthographic neighborhood density were taken from the Cross Linguistic Easy Access Resource for Phonological and Orthographic Neighborhood Densities database . Half of the pseudowords were created starting from the selected Dutch words and the other half from the selected English words by using the multilingual pseudoword generator Wuggy . The neighborhood size difference between pseudowords and words was kept as minimal as possible . Finally, words and pseudowords had the same orthographic length.With concern to pseudowords, they were created by modifying the first or the last subsyllabic elements of the words selected for the lexical decision task. Apart from this change, pseudowords maintained the subsyllabic structure of the words they were generated from  against a black background. Pictures had a size of 197 × 281 pixel and were presented against a colored (green or blue) background. Stimuli were presented using the software E-Prime Professional version 2.0  and 2/3 of words . Half of the words belonged to the L1 and the other half to the L2. Participants were told that words' language membership was irrelevant for the task.L2-L1-L1-L2 and L1-L1-L1-L2) and to exclude effects of backwards inhibition on switch trials (note the difference between L1-L2-L1-L2 and L1-L1-L1-L2), for a review on backward inhibition see Koch et al. . For example, in the chunk L1-L1-L1-L2, the first three members belonged to the same language (L1) and the last one to the other language (L2). Each of the four elements had to be classified as existing words, irrespective of language membership. Only the last two elements of the chunk were included in the analysis . We used this system to make sure that every repetition trial was coming from a “pure” repetition trial , while the fourth element was in a different category. For example, in a word-word-word-pseudoword chunk, the first three elements had to be classified as existing words and the fourth one as a non-existing word. If the first three components were words, they always belonged to the same language , while the following pseudoword was generated either from the same language  or from a different one . If the first three components of the chunk were pseudowords, they could have been generated from both the L1 and the L2 and the following word was either in the L1 or in the L2. Only the last two elements of the chunk were included in the analysis .If two items  had occurred together in a specific chunk, this items' combination was not repeated twice; additionally, their translations  and their derived pseudowords  were never presented together within a chunk. To avoid orthographic priming, items sharing more similar orthographic patterns (such as the pseudowords derived from the item words) never occurred in the same chunk. Moreover, a given item was never seen within the next 5 trials and the same type of chunk never occurred more than twice in a row. Because of these constraints, the order of the trials was unpredictable. Four lists of the task were created, two starting with a word-word-word-pseudoword and the other two with a pseudoword-pseudoword-pseudoword-word chunk type. Each participant was administered with one list only. The language of instructions for the lexical decision task was Dutch. Before the main experiment, participants were given a practice session of 24 trials. Practice items were not included in the main experiment.In the picture naming task, participants had to name a presented picture either in their L1 (Dutch) or in their L2 (English). The language to be used was signaled by the background color of the screen . The assignment of the color cue to the response language was counterbalanced across participants. The picture naming task consisted of a single-language followed by a mixed- language block. In the single-language block, pictures had to be named in either L1 or L2 separately. It included a total of 56 trials: Half of the items had to be named in the L1 and the other half in the L2. For each language, the 14 pictures were randomly presented for two times consecutively. The order of languages' presentation was counterbalanced across participants. The language of instruction corresponded to the language in which the upcoming task had to be performed (English for the upcoming L2 part and Dutch for the following L1 part).The mixed-language block involved two kinds of trials, repetition and switch trials. In a repetition trial, a given picture had to be named in the same language as in the trial before . In a switch trial, a presented picture had to be named in a different language compared to the trial before . The mixed-language block was composed by 112 trials: Half of them had to be named in the L1 and the other half in the L2. Trials were organized in pseudo-randomized language chunks composed of 75% repetition and 25% switch trials . For example, the language chunk L1-L1-L1-L2 implied that the three consecutive pictures had to be named in the L1 and the fourth one in the L2. For the analysis, only the second part of the language chunk was used (X-X-L1-L2). The same chunk type was never displayed more than two times in a row. Each picture was seen eight times within the mixed-language block, which is once in each position of the language chunk  of the two language chunks (L1-L1-L1-L2 and L2-L2-L2-L1). The same picture was not seen within 5 trials. Again the order of the items was unpredictable. Four lists of mixed-language block were created: two starting with a L1-L1-L1-L2 and the other two with a L2-L2-L2-L1 chunk type. Each participant saw only one list. In the mixed language block, the language of instructions was Dutch.Participants were given one practice sessions before each language part of the single-language block  and one practice session before the mixed-language block, in which the two chunk types were trained . Practice trials did not appear in the experimental sessions. On average, the experiment (including instructions and breaks) lasted 30 min.The dependent variables of the present study were accuracy rates and reaction times. Before the statistical analyses, we cleaned the dataset based on participants' and items' error rates. Because of low accuracy scores (<66%), one participant and two items were removed from subsequent analyses . Accuracy rates for all other participants and items ranged, respectively from 73 to 100% and from 79 to 100%.Both correct and incorrect responses were included in the accuracy rates' analyses, whereas only correct responses were used to analyse reaction times. We deemed a response as incorrect in the case of wrong button pressing for the lexical decision task (4.5% of the data) and in the case of microphone miss-triggering  and selection of the wrong word and/or language for the picture naming task (9.8% of the data). In both tasks, missing responses were classified as incorrect.After exclusion of the incorrect responses, we screened reaction times for extreme values. Extremely fast (<150 ms) or particularly slow  reaction times were removed from the dataset (0.03% of the data). All the analyses were carried out in GNU-R version 3.2.2  in the lexical decision and in the picture naming tasks. Consider first the lexical decision task. Mean accuracy rates and reaction times are illustrated in Table SE = 0.10, z = 3.35, p < 0.01). A response change  yielded significantly less accurate responses compared to when the same response was repeated . The significant interaction of Language by Category , indicated that compared to pseudowords, words were responded more accurately in the L1 than in the L2. Specifically, while accuracy rates did not differ significantly for pseudowords generated from the L1 and those generated from the L2 (p > 0.05), L1 words were responded more accurately than L2 words . Finally, we found a significant interaction between Condition and Response repetition , indexing that a change of response affected language repetition and switch trials differently. In particular, compared to a situation in which the same response is repeated , a change of response  yielded significantly lower accuracy rates for repetition trials , but not so for switch trials (p > 0.05).The analysis of the accuracy rates revealed that responses were significantly more accurate in words than in pseudowords  and that response change yielded slower responses compared to response repetition . The main effects of Language and Condition were not significant (p > 0.05). However, the significant interactions of Language by Category  and of Condition by Category  revealed that compared to pseudowords, words were responded faster in the L1 than in the L2 and in repetition compared to switch trials. Both the interactions of Category by Response repetition and of Condition by Response repetition were also significant , indicating that a response change was more costly for repetition compared to switch trials and for words than for pseudowords. Both the three-way interactions between Language, Condition and Category and between Condition, Category and Response repetition were significant . All the other interactions were not significant (p > 0.05).As expected, the analysis of the reaction times showed that pseudowords were responded significantly slower than words  and in repetition compared to switch trials . The effect of Response repetition was also significant , indicating that responses were significantly slower if the preceding trial was a pseudoword compared to a word. This effect was smaller for switch compared to repetition trials . The three-way interaction between Language, Condition and Response repetition was also significant . No other interaction was significant (p > 0.05). Words were further divided based on the category of the preceding trial (Response repetition: yes vs. no).To investigate these interactions, we split the data into words and pseudowords. With regard to words, we found that responses were faster in the L1 than in the L2  and in repetition compared to switch trials . The difference between repetition and switch trials was larger for L1 compared to L2 words , that is asymmetrical switching costs. In particular, the effect of language switching was significant for the L1 , but not for the L2 (p > 0.05). With reference to words preceded by pseudowords , responses were faster in the L1 compared to the L2 . No other main effect or interaction was significant (p > 0.05) in this condition. Concerning pseudowords, items generated from the L1 were responded equally fast as those generated from the L2 (p < 0.05). All the other main effects and interactions were also not significant (p > 0.05).When the same response was repeated , words were responded faster in the L1 relative to L2  compared to response change . Changing response was particularly costly for words and repetition trials than for pseudowords and switch trials, respectively. The effect of Language was influential for words, in that L1 words were responded faster and more accurately than L2 words, but not for pseudowords. The effect of Condition also affected words only, with responses on switch trials being slower and less accurate than on repetition trials. This difference was significant for the L1 and not significant for the L2, i.e., asymmetrical switching costs.Consider now the picture naming task. Mean accuracy rates and reaction times are presented in Table p > 0.05). In the mixed-language block, responses were significantly more accurate in the L2 than in the L1  and in repetition compared to switch trials . The marginal significant interaction of Language by Condition  indicates that compared to repetition trials, switch trials tended to be less accurate in the L1 than in the L2. The accuracy rates' difference between the single- and the mixed-language blocks was not significant (p > 0.05). However, there was a significant interaction between Language and Block , indicating that compared to the single-language block, mixed-language block responses were more accurate for the L2 than for the L1. Specifically, while the L2 was responded to significantly better in the mixed- compared to the single-language block , L1 accuracy rates was not influenced by the type of block (p > 0.05).The analysis of the accuracy rates showed that in the single-language block responses in L1 and L2 were equally accurate (p > 0.05) and that in the mixed-language block, responses were faster in the L2 than in the L1 . Overall, participants responded slower on repetition trials of the mixed-language block compared to trials in the single-language block , i.e., mixing costs. This difference was greater for the L1 than for the L2, as indicated by the significant interaction of Language and Block . In particular, while L1 responses were significantly slower in the mixed- compared to the single-language block , L2 responses were not affected by the type of block (p > 0.05). In the mixed language block, switch trials were responded to slower than repetition trials , and this effect was comparable for the L1 and the L2 (p > 0.05), which means that we found symmetrical switching costs. However, given the relatively small number of trials used in this task, we performed an additional analysis in order to assess whether the observed data might have suffered from unwanted biases. To do so, we used Bayesian hypothesis testing that allows for rigorous quantification of statistical evidence  language inhibition in recognition is dominance-related (as the IC predicts) or dominance-reversed (as the BIA predicts) and from this at investigating whether (2) language control in bilingual recognition and production rely on the same or different mechanisms. To address these issues, we measured language switching costs in a group of native speakers of Dutch (L1)-proficient learners of English (L2) performing a bilingual lexical decision and a bilingual picture naming task.We regard to the main research question, we found that language switching costs for words were larger for the L1 compared to the L2, i.e., asymmetrical switching costs. More precisely, responses were significantly slower on switch than on repetition trials for the L1, but not for the L2 where reaction times in switch and repetition trials were comparable. This result replicates Jackson et al.  study, wWhy did we find language switching costly for the L1, but not for the L2? Before answering this question, it is important to understand the role of language strength of activation in word recognition. As proposed by the BIA model the speed with which a word is recognized depends on its baseline activation level, with more frequent words (such as L1 words) being recognized faster than less frequent words (such as L2 words). Additionally, the speed with which a word is recognized also depends on its relation to other words in the lexicon . This assumption is line with the IC model predictions, according to which the magnitude of inhibition depends on languages' activation strength. Yet, this is in contrast with the BIA model proposal that the L1 language node inhibits L2 words to a greater extent than vice versa  replicates previous studies on bilingual recognition . In particular, prior practice of the items in the lexical decision task might have strengthened the weaker language to a greater extent than the stronger language, leading to a change in their dominance relation in the picture naming task. However, a comparison with a similar study suggests that the results obtained in the picture naming task are likely to be due to the nature of the task rather than to different practice effects for the two languages. Specifically, in a recent study by Mosca and Clahsen , languagThus, why did we find ceiling performance in the production, but not in the recognition task? The reason might lie in the difference between the processes supporting language production and recognition. Indeed, while language recognition is mostly supported by a bottom-up mechanism, language control in production is a mainly top-down process (see next session for further discussion on bottom-up vs. top-down control). As Yeung and Monsell  observedFurthermore, Monsell et al.  showed tIn the single-language block, we found that responses in the L1 were on average faster than in the L2, but that the difference was not significant. Comparable performance in the two languages might indicate that our participants were fairly balanced bilinguals. However, this assumption is in contrast to their performance in the lexical decision task, where participants responded faster to L1 words than L2 ones.Similar performances in L1 and L2 might be due to the order in which languages were presented in the single-language block. Recall that half of the participants named pictures first in the L1 and then in the L2 and the other half named pictures in the opposite order. Several studies investigating the effect of language order in language production have shown that, presented two separate language blocks, L1 naming is hampered if preceded by L2 naming. However, this negative effect is not found in the L2, where performance seems to benefit from the previous naming in the L1  do not report faster responses in the weaker than in the stronger language , language recognition is a predominantly bottom-up process . This difference was already captured in a paper describing the developmental Bilingual Interactive Activation (BIA-d) model by Grainger et al. . AccordiA way to understand the processes underpinning language control in production and recognition is by considering that top-down and bottom-up attentions are commonly deemed as two different types of information processing  in the production, but not in the recognition task.Similarly, the different language switching pattern found in the recognition and the production task could be ascribed to the difference between top-down and bottom-up mechanisms. In the recognition task, asymmetrical switching costs might be attributed to the fact that since words are more activated in L1 than in L2, L1 words need to be inhibited more than L2 words, leading to larger reactivation costs for the L1 relative to the L2. In the picture naming task, symmetrical switching costs for the stronger and the weaker language could be explained either by a strategic process of costs' minimization  or by a modulation of language inhibition over time . However, more studies are needed to assess whether the difference between language control in production and recognition are to be attributed to the fact that they are mainly supported by two different mechanisms of information processing. A more systematic way to address this issue would be, for example, by including a single-language block for the recognition task, so to compare language mixing costs in recognition and production. Alternatively, it could be useful to use a language-specific recognition task, in which only words are used and where speakers have to decide whether a given word belongs to either L1 or L2. This type of task would be more comparable to a picture naming task since only existing words are used and language membership is relevant for the task.The aim of this study was to investigate bilingual language control in reception and production. In particular, we asked whether language control in bilingual perception relies on the same mechanism as in bilingual production and whether these two processes can be incorporated into a single bilingual language control model. To investigate this issue, we considered two prominent models of bilinguals language control, according to which, when one language is in use, the other is suppressed. The (IC) model Green, , 1998 suTo investigate the mechanisms underpinning language control in production and recognition, we tested native speakers of Dutch (L1)-highly proficient speakers of English (L2) in a lexical decision and a picture naming task with language switching. Participants reported being more proficient and more exposed to the L1 compared to the L2. Results from the bilingual lexical decision task confirmed that L1 and L2 were processed differently. Specifically, we found that language switching was costly only for the L1 but not for the L2. We suggested that when L2 words are presented, L1 competitors need to inhibited. If during L2 processing, L1 words are suppressed, reactivating the L1 on a switch trial will lead to L1 switching costs. However, when L1 words are presented, the target word is fast recognized and words from the weaker L2 will not have enough time/strength to compete. In this case, the inhibition applied to the weaker L2 competitors will be relatively small or absent, yielding to undetectable L2 switching costs when the L2 becomes relevant again.These results are in contrast with the BIA model, according to which switching costs are dominance-reversed, but they are in line with the dominance-related IC model, in that we measured switching costs in the stronger L1, and only a tendency toward switching cost in the L2.In contrast to the lexical decision task, in the picture naming task we measured the same amount of switching costs for the L1 and the L2. Symmetrical switching costs between a stronger and a weaker language cannot be accounted for by a conservative dominance-related account of language control. We suggested that symmetrical switching costs in bilinguals with a relatively small difference between L1 and L2 proficiency level might be related to speakers' temporary adjustment to the task. Specifically, we assume that in the production task, the language control system strategically adapts to the task either by minimizing the effort of switching between languages  or by adjusting the amount of language inhibition during the task . Importantly, whilst it remains unclear whether language switching costs can be considered a direct test toward or against a specific model (e.g., Bobb and Wodniecka, This study was carried out in accordance with the recommendations of the Ethics Committee of the University of Potsdam with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Ethics Committee of the University of Potsdam.MM: Conception, design, and programming of the experiment. Acquisition, analysis, and interpretation of the data. Draft and revision of the manuscript. Final approval of the version to be published and of the content and the accuracy or integrity of any part of the work. KdB: Conception of the experiment. Draft and revision of the manuscript. Final approval of the version to be published as well as of the content and the accuracy or integrity of any part of the work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This resulted in GNRs with various widths in a highly controllable manner, where the on/off current ratio was inversely proportional to ribbon width. The field-effect mobility decreased with decreasing GNR widths due to carrier scattering at the GNR edges. These results demonstrate the formation of a bandgap in GNRs due to enhanced carrier confinement in the transverse direction and edge effects when the GNR width is reduced.There has been growing interest in developing nanoelectronic devices based on graphene because of its superior electrical properties. In particular, patterning graphene into a nanoribbon can open a bandgap that can be tuned by changing the ribbon width, imparting semiconducting properties. In this study, we report the effect of ribbon width on electrical transport properties of graphene nanoribbons (GNRs). Monolayer graphene sheets and Si nanowires (NWs) were prepared by chemical vapor deposition and a combination of nanosphere lithography and metal-assisted electroless etching from a Si wafer, respectively. Back-gated GNR field-effect transistors were fabricated on a heavily p-doped Si substrate coated with a 300 nm-thick SiO In pa V−1 s−1 . In spit4 in GNR FETs with sub-5 nm widths at room temperature [As graphene is intrinsically a semimetal with zero bandgap, the formation of a bandgap is necessary to achieve a sufficiently high on/off current ratio when used as a channel in a field-effect transistor (FET). Several routes to bandgap tuning in graphene have been reported, such as chemical doping of graphene, application of a vertical electric field in bilayer graphene, and patterning graphene into a narrow ribbon structure –11. Amonperature . The fabperature –15, blocperature , and useperature –19 on grperature –24. In t2 gas flow to increase the Cu grain size and ensure the removal of native oxide and a smooth Cu surface. Graphene was grown on Cu foil at 1000 °C using a mixture of 20 sccm of CH4 and 50 sccm of H2 by low-pressure chemical vapor deposition (CVD) [2 substrate, the surface of the graphene on Cu was coated with poly(methyl methacrylate)  as a transfer medium. The PMMA-coated samples were baked at 60 °C for 5 min. The Cu was wet-etched using a copper etchant , resulting in graphene/PMMA films floating on the etchant. These films were then collected onto Si/SiO2 substrates, and the PMMA layers were removed with acetone, yielding Si/SiO2/graphene.Cu foil (Alfa Aesar) was used as a substrate for graphene growth. The Cu foil was annealed at 1000 °C for 30 min under 10 sccm of Hon (CVD) , 25. To 2O2:H2SO4) at 100 °C. Then, the substrate was rinsed with deionized water and spin-coated with the PS bead suspension at 3000 rpm to form a monolayer of PS beads on the Si substrate. The large-area ordered and close-packed monolayer assembly of PS beads on the Si substrate was transformed into a non-close-packed arrangement by reducing the diameter of the PS spheres using O2 reactive ion etching (RIE). The e-beam evaporator was used to deposit 40 nm-thick Ag films as catalysts to form Si NWs from the substrate, and the substrate was subsequently sonicated in chloroform for 20 min to remove the PS spheres. Wet etching was performed at 50 °C in a solution of 4.5 M HF and 0.5 M H2O2 for 20–30 min, yielding vertically aligned Si NW arrays. Finally, the Ag films were removed by immersion in boiling aqua regia (3:1 of HCl:HNO3) at 100 °C for 20 min.Si NWs were prepared by nanosphere lithography, which is a technique for generating hexagonally close-packed nanoscale patterns of nanometer-sized PS spheres on a Si wafer. PS beads with different diameters of 100, 300, and 460 nm were dispersed in methanol with Triton X-100 as a surfactant. To make the surface of the Si substrate hydrophilic, the substrate was immersed in a piranha solution (1:3 of 30% H2 layer (gate dielectric) was used as a starting material to fabricate GNR FETs. First, the source/drain pads were patterned by photolithography, followed by deposition of Ti/Au as the electrode metal on the graphene by e-beam evaporation. The channel length of the FETs was 8 μm. The Si NWs were raked out from the vertically aligned Si NW arrays prepared on the Si substrate and dissolved in isopropyl alcohol (IPA). This Si NW suspension was sonicated for 10 min and centrifuged at 2500 rpm for 10 min. Then, the Si NWs were aligned on graphene between the two electrodes by a dielectrophoresis method. The assembly of Si NWs was performed by dispensing a dilute suspension of the Si NWs onto the substrates with applied voltages of ± 10 V at frequencies of 1–100 kHz . O2 plasma etching was used to selectively etch an unprotected graphene region away and leave a ribbon structure of graphene underneath the Si NW mask, leading to the formation of GNRs. After that, the NW mask was removed by sonication in IPA, resulting in GNR FETs.A large-area monolayer graphene on a heavily p-doped Si substrate (bottom gate) coated with a 300 nm-thick SiOThe monolayer graphene was characterized by Raman spectroscopy  using a laser with an excitation wavelength of 532 nm. The morphological properties of graphene, Si NWs, and GNRs were investigated by optical microscopy , field-emission scanning electron microscopy , and atomic force microscopy . The electrical characteristics of the GNR FETs were studied with a semiconductor parameter analyzer .−1 with a full width at half maximum of ~ 33 cm−1 was observed. The peak intensity ratio of the 2D and G bands was equal to 2, indicating high-quality monolayer graphene. The weak peak located at 1345 cm−1 corresponded to the D band of graphitic carbon species, the intensity of which was associated with the level of defects in the crystalline structure of the graphene layers. This weak D band confirmed the high quality of the synthesized graphene films. Figure 2 layer.Raman spectroscopy was performed to confirm the formation of graphene and to obtain information about the quality and the number of graphene layers. Figure 2 RIE process, which results in the formation of PS bead arrays that are no longer close-packed  of GNRs has an exponential relationship with the on/off current ratio of GNR FETs (Ion/Ioff  =  C exp(Eg/kT)) [Eg = α/W), where α is between 0.3 and 1.5 [The electrical characteristics of GNR FETs with various widths were measured at room temperature. As shown in Fig. (Eg/kT)) , 33. The and 1.5 , 33. As gm is the transconductance, L is the channel length, W is the channel width, and C is the gate capacitance per unit channel length of a GNR. Since the fringe effect on capacitance at the ribbon edges of the GNRs must be considered due to the narrow ribbon widths of the GNRs, a simulation model based on finite element analysis reported previously was employed to obtain the capacitance [2 V−1 s−1, respectively, at room temperature, due to the carrier scattering at GNR edges. These mobilities are comparable to those reported previously [acitance , 34, 35.eviously –38.kT << Eg, where k is the Boltzmann constant and T is absolute temperature. This confirms that structuring a graphene sheet into a ribbon can open the bandgap.Figure IDS–VGS curves on ribbon width; (3) the field-effect mobility decreased with decreasing width of the GNR; and (4) the bandgap increased with increasing on/off current ratio by narrowing the width of the GNR. These results demonstrate the opening of the bandgap in graphene due to enhanced carrier confinement in the transverse direction and the edge effect in the ribbon structure.In summary, GNRs with different widths were fabricated in a highly controllable manner, and their electrical transport properties were investigated. The GNRs were prepared from CVD-grown graphene sheets by using etch masks based on Si NWs synthesized from Si substrates by a combination of nanosphere lithography and metal-assisted chemical etching, and aligned between two electrodes by an electric-field-assisted alignment method, producing GNR FETs. The ribbon widths of the GNRs were controlled by changing the diameters of the Si NWs and the graphene etching times. The electrical transport characteristics of GNRs were found to be highly dependent on the GNR width: (1) the on/off current ratio was inversely proportional to GNR width; (2) the electrical properties of the GNR FETs showed a strong temperature dependence of the


The prognostic value of programmed death-ligand 1 (PD-L1) in gastric cancer (GC) remains controversial. To clarify this problem, we performed a meta-analysis of research studies identified in the PubMed, EMBASE and the Cochrane Library databases. A total of 1,901 patients in 10 studies were enrolled in this meta-analysis, and the pooled hazard ratio (HR) of 1.64  indicated that PD-L1 expression is associated with a shorter overall survival (OS). The pooled odds ratios (ORs) indicated that PD-L1 expression was associated with tumour size  and lymph node status . However, PD-L1 had no correlation with gender, age, cancer location, differentiation, depth of invasion, and tumour stage. This meta-analysis indicates that PD-L1 expression is a valuable predictor of the prognosis of patients with GC. PD-L1 expression could be used for identifying a subgroup of patients, who would potentially benefit from targeted therapy against PD-1 or PD-L1. Well-designed large-cohort studies are needed to confirm these findings. Gastric cancer is the one of the most common cancers around the worldProgrammed death 1 (PD-1), which belongs to the CD28 family, is a receptor expressed on the surface of activated T cells that regulates their proliferation and activation91011Data on the prevalence and prognostic significance of PD-L1 expression in GC is very limited and remains controversial. We performed a meta-analysis to assess whether PD-L1 expression was correlated with the clinicopathological features and prognosis of GC patients.In the present study, 136 articles were identified by the initial search strategy. Through reading the study titles and abstracts, 118 records were removed because of duplicate studies and non-relevance with the theme. After we reviewed the full texts of the 18 potentially eligible articles in detail, 10 trials meeting the inclusion criteria were included in the final analysis. A flowchart depicting the study selection is shown in The characteristics of the included studies are shown in We evaluated the correlation between PD-L1 expression and OS among the 1,901 patients from all ten included studies. The pooled HR for OS showed that PD-L1 expression was associated with poor OS  in GC with a 64% increase in the risk for mortality . In addiP = 0.23)  were PD-L1 expression positive, and 228 (36.1%) of 631 female patients were PD-L1 expression positive. The pooled OR indicated no significant correlation between PD-L1 expression and gender  .The correlation between PD-L1 expression and age was analysed in two studies, including a total of 674 patients. Eighty patients (34.5%) were PD-L1 expression positive, among a total of 232 older patients (≥70 years), and 154 (34.8%) of 442 younger patients (<70 years) were PD-L1 expression positive. No significant association was found between PD-L1 expression and gender  .Four out of the ten studies, including 425 patients, examined the relationship between PD-L1 expression and cancer location. Of 71 cardia patients, 41 (57.7%) were PD-L1 expression positive, and 178 patients (50.3%) were PD-L1 expression positive among 354 patients with gastric body and antrum cancers. The pooled OR indicated that PD-L1 expression had no clear correlation with cancer location .Seven studies, including 1143 patients, were analysed for the correlation between PD-L1 expression and tumour differentiation. Of 655 poorly differentiated tumours, 291 (44.4%) were PD-L1 expression positive, and 216 (44.3%) of 488 moderately/well-differentiated cases were PD-L1 expression positive. No significant association was found between PD-L1 expression and tumour differentiation  .The relationship between PD-L1 expression and tumour size was evaluated in four studies including 409 patients. One hundred and thirteen (58.9%) patients were PD-L1 expression positive out of a total of 192 patients with large tumours (≥5 cm), and 94 (43.3%) out of a total of 217 patients with small tumours (<5 cm) were PD-L1 expression positive. Increased PD-L1 expression was found to be significantly associated with large tumour size  .Five studies with a total of 1,211 patients were analysed for the relationship between PD-L1 expression and the depth of tumour invasion. Positive PD-L1 expression was found in 255 (36%) out of 709 T3–4 level tumour invasion patients, while 116 (23.1%) out of 502 T1–2 level tumour invasion patients were PD-L1 expression positive. No significant relationship was detected between PD-L1 expression and the depth of tumour invasion  .Six studies comprising 987 patients were evaluated for the correlation between PD-L1 expression and lymph node metastasis. Of 679 patients with positive lymph node metastasis, 276 (40.6%) were PD L1 expression positive, and 95 (30.8%) of 308 patients with negative lymph node metastasis were PD-L1 expression positive. The combined OR for the positive lymph node metastasis group versus the negative lymph node metastasis group was 2.17  .Four studies, including 1104 patients, were analysed for the association between PD-L1 expression and TNM stage. Two hundred and twenty-two (40.9%) of 543 stage III–IV patients were PD-L1 expression positive and 152 (27.1%) out of 561 stage I-II patients were PD-L1 expression positive. No significant association was found between PD-L1 expression and stage  .2 = 71%), the depth of tumour invasion , lymph node status , and tumour stage . Thus, a random-effects model was employed for the analysis. The other analyses above were carried out using a fixed effects model.Heterogeneity was observed in the analysis of PD-L1 expression with histological differentiation  expressionBiomarker-driven selection of immunotherapy responders improves therapeutic efficacy, minimizes unnecessary exposure and reduces the financial burden on health systems. Recent studies show that high levels of PD-L1 expression are associated with higher clinical activity in patients with various cancer types treated with PD-1/PD-L1-targeted therapyEfforts were made to conduct a comprehensive analysis, but there are limitations to our study. First, the cut-off values distinguishing positive and negative PD-L1 expression determined by IHC varied in different studies, which might cause heterogeneity among the overall results. The subgroup results should have addressed some of these concerns. Second, the distinct antibodies of PD-L1 expression among diverse studies might also impact the accurate estimation of the prognosis for gastric cancer. Standardized methods and definitions of PD-L1 positivity are clearly needed to facilitate studies of PD-L1 as a prognosis biomarker. Hence, a large multicenter study using the same antibody and cutoff for PD-L1 expression may be helpful to obtain more accurate results. Third, not all of the HRs with 95% CI was directly extracted from the studies, so we based our study on the data extracted from Kaplan-Meier curves, which compromises the precision of the data. Fourth, most of the eligible studies failed to provide data regarding progression free survival, so we only extracted OS data in our meta-analysis. Fifth, this meta-analysis was limited to articles published in English, possibly resulting in a publication bias. Despite the above limitations, this meta-analysis demonstrates the correlation between PD-L1 expression and the clinicopathological factors of GC. The results may lead to improvements in the outcomes of anti-PD-1/PD-L1 therapy due to this convenient stratification method.In conclusion, our result indicated that PD-L1 overexpression is related to a poor prognosis, large tumours and the presence of lymph node metastasis. This information might prove to be helpful in screening candidates for anti-PD-1/PD-L1 therapy. Well-designed large cohort studies are needed to confirm these findings.Two authors (Zhang MH and Liu HT) independently carried out a comprehensive systematic search of published articles using the PubMed, EMBASE, and Cochrane databases, and any discrepancy was resolved by mutual discussion. The deadline for included articles was April 2016. The following keywords were used: (“PD-L1” or “B7-H1” or “CD274” or “Programmed Cell Death 1 Ligand 1 Protein) and (“gastric cancer” or “gastric neoplasms” or “stomach neoplasms”) with the limit “human”. Additional searches through Google Scholar and a manual search through the reference lists of relevant reviews were also performed.The criteria for inclusion were set out as the following: (1) All patients were histologically confirmed as GC; (2) PD-L1 expression was measured in GC tissue using immunohistochemistry; (3) Studies provided the correlation between PD-L1 and overall survival; (4) These studies provided a correlation between PD-L1 and clinicopathological features, including at least two parameters; (5) Studies provided sufficient information to estimate HR about OS; (6) Articles published as a full paper in English. Studies that failed to meet the inclusion criteria were excluded. When duplicate publications were identified, only the newest or most informative single article was selected.The data were extracted independently by two reviewers (Zhang MH and Liu HT), and any disagreements between the two reviewers were resolved by consensus involving a third reviewer (Dong YD). The following information was extracted from each included trial: name of the first author, year of publication, country, number of patients, TNM stage, IHC evaluation method, antibody, cut-off, PD-L1-positive expression, clinicopathological parameters and the hazard ratios (HRs) and 95% confidence intervals (CIs) for OS. If the HRs were not directly reported, we contacted the authors of the primary studies for additional data. If the authors did not respond, we extracted data from survival curves.A quality assessment was independently conducted for all of the included studies by two investigators (Wang Y and Zhao S) using the Newcastle–Ottawa Quality Assessment Scale (NOS), and any disagreements were resolved by discussion and consensus. The NOS comprises the following three parameters of quality: selection, comparability and outcome assessment. The maximum possible score is nine points, and NOS scores greater than six are considered indicative of high-quality studieset al.2. Statistically significant heterogeneity was defined as a chi-squared P value < 0.1 or an I2 statistic >50%. If heterogeneity was observed, we used a random-effects model to reduce the impact of heterogeneity on the results. If heterogeneity was not observed, a fixed-effects model was used. The potential publication bias was assessed by Egger’s and Begg’s tests. All of the statistical analyses were performed using Review Manager Version 5.3  and STATA version 12.0 . P values < 0.05 were considered to indicate statistical significance. All P values and 95% CIs were two-sided.Hazard ratios (HRs) and their 95% CIs were combined to measure the effective value. If HRs and corresponding 95% CIs were not available, we calculated these data points from available numerical data using the methods reported by Parmar How to cite this article: Zhang, M. et al. The clinicopathological and prognostic significance of PD-L1 expression in gastric cancer: a meta-analysis of 10 studies with 1,901 patients. Sci. Rep.6, 37933; doi: 10.1038/srep37933 (2016).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.