Dictyostelium belongs to a supergroup of eukaryotes not covered in previous studies.Spliceosomal introns are a common feature of eukaryotic genomes. To approach a comprehensive understanding of intron evolution on Earth, studies should look beyond repeatedly studied groups such as animals, plants, and fungi. The slime mold Dictyostelium discoideum and 202 precise intron losses in Dictyostelium purpureum. Consistent with these observations, Dictyostelium discoideum was found to have significantly more copies of reverse transcriptase genes than Dictyostelium purpureum. We also found that the lost introns are significantly further from the 5′ end of genes than the conserved introns. Adjacent introns were prone to be lost simultaneously in Dictyostelium discoideum. In both Dictyostelium species, the exonic sequences flanking lost introns were found to have a significantly higher GC content than those flanking conserved introns. Together, these observations support a reverse-transcription model of intron loss in which intron losses were caused by gene conversion between genomic DNA and cDNA reverse transcribed from mature mRNA. We also identified two imprecise intron losses in Dictyostelium discoideum that may have resulted from genomic deletions. Ninety-eight putative intron gains were also observed. Consistent with previous studies of other lineages, the source sequences were found in only a small number of cases, with only two instances of intron gain identified in Dictyostelium discoideum.We found 441 precise intron losses in Dictyostelium species have similar mechanisms of intron loss.Although they diverged very early from animals and fungi, The online version of this article (doi:10.1186/s12862-015-0567-y) contains supplementary material, which is available to authorized users. The second model of intron loss is simple genomic deletion. In this model, each individual intron is lost independently and without bias with respect to its position within a gene. In this model, introns might occasionally be lost precisely but are typically accompanied by insertions and/or deletions in the flanking exonic sequences. The final model is one in which introns are lost during non-homologous end joining (NHEJ) repair of DNA double-strand breaks. As the repair process generally requires microhomology between the break sites, this model predicts that there should be short direct repeats at the two ends of the lost intron. Besides this, the same predictions are shared between the NHEJ repair model and the genomic deletion model. The first model has been widely supported by studies that are carried on animals, fungi, and plants [Arabidopsis thaliana was different from that predicted by the first model but consistent with the third model in which introns are lost during DNA double-strand break repair [With the exception of the relics of certain endosymbiotic nuclei , all eukd plants , 21–25. k repair , 26. Shok repair , supportk repair .Plasmodium, a model lineage of the supergroup SAR  [Dictyostelium belongs to another supergroup of eukaryotes, Amoebozoa [Dictyostelium can form differentiated multicellular structures by aggregating thousands of solitary amoebae in response to starvation [Dictyostelium discoideum, has been used as a model organism to study multicellularity, cell differentiation, signal transduction, cell migration, and development for many years [Dictyostelium has two characteristics which make them helpful for the further study on intron evolution. The first one is the enrichment of simple sequence repeats (SSRs) in the Dictyostelium genomes [Dictyostelium species is the 16 documented new genes gained from bacteria by horizontal gene transfer (HGT) after their divergence from plants and animals, but prior to the divergence among themselves [Dictyostelium discoideum and Dictyostelium purpureum and explored the mechanisms underlying these variations.For a comprehensive understanding of intron evolution on Earth, studies should cover all major eukaryotic lineages. However, a considerable bias exists toward a limited number of model organisms in animals, plants, and fungi , 29–36, hizaria) , 38. Themoebozoa , 38. Dicarvation . The mosny years . At the  genomes , 49. Acc genomes , these Semselves , 49. We Dictyostelium discoideum, Dictyostelium purpureum, Polysphondylium pallidum, Dictyostelium fasciculatum, and Entamoeba histolytica . Along with each of the two intron losses, three flanking nucleotides of coding sequences were deleted . Although SSRs are abundant in Dictyostelium genomes [In the two ted Fig. . No shor genomes , 49, the genomes . As the Dictyostelium support the reverse-transcription model. Among the 441 precise intron losses in Dictyostelium discoideum and the 202 losses in Dictyostelium purpureum, we identified 31 and three pairs of adjacent intron losses, respectively. Here, three adjacent introns were considered as two pairs. The losses of adjacent introns might be either due to the simultaneous loss of adjacent introns or independent losses of different introns happen to be neighboring in position. For this reason, we performed in silico resampling analysis by randomly drawing 441 introns from the pool of both the 441 lost introns and the 15,510 extant introns of Dictyostelium discoideum. This resampling has been repeated for a total of 10,000 times and an occurrence of 31 or more pairs of adjacent introns was never observed (P = 0). In Dictyostelium purpureum, 202 introns were re-sampled for 10,000 times and three or more pairs of adjacent introns were obtained in 1,038 times (P = 0.1). Similar results were observed in re-sampling analyses that replaced the extant introns by conserved introns. Furthermore, we calculated the probability distribution of the losses of adjacent introns with the assumption that each intron was lost independently [Dictyostelium discoideum, which indicates that adjacent introns tend to be lost simultaneously . As the extant introns are biased to the 5′ end of genes, most of the 3′-most introns will be in the middle or at 5′ side of genes. The absolute positions of lost introns will not be at the 3′ end of genes. Therefore, we compared the positions of the lost introns and the conserved introns. As shown in Fig. Previous surveys of the of genes , 51. We U test, P = 0.004 and 0.033, respectively, for Dictyostelium discoideum and Dictyostelium purpureum). However, their differences are very small . Compared with vertebrates, the introns of Dictyostelium discoideum and Dictyostelium purpureum are very short. Therefore, we are cautious in interpreting these size differences as evidence of the reverse-transcription model.We also found that the lost introns are significantly shorter than the conserved introns  or only the conserved introns (P = 3 × 10−20). The genomes of these two species are similar in size, with sizes of 34 and 33 Mb, respectively [We observed a large difference in the rate of intron loss between these two species; whereas ectively . TherefoDictyostelium discoideum are generally shorter; thus, the genomic DNAs are more suitable substrates of the recombination process than those of Dictyostelium purpureum. Whereas Dictyostelium discoideum has a mean intron length shorter than that of Dictyostelium purpureum , globally, its introns are significantly longer than those of Dictyostelium purpureum . Therefore, we compared the GC content relative to the exonic sequences flanking conserved introns rather than the absolute values. As shown in Fig. Furthermore, the high GC content of the exonic sequences flanking lost introns can be explained in two ways. The first explanation is that intron losses preferentially occurred at gene conversion hotspots, where GC contents are higher regardless of whether intron losses have occurred. If this is the case, the exonic regions flanking the extant introns of discordant positions should also have higher GC contents than the exonic sequences flanking conserved introns. For example, gene In the above comparisons, the GC contents of 100-bp regions from each side of the discordant and conserved intron positions were surveyed. Adjusting the surveyed sequence length to 50 bp and 200 bp yielded similar but less robust results. Longer sequences indicate that more nucleotides surveyed are likely to lie beyond the conversion tracts . CountinDictyostelium discoideum and Dictyostelium purpureum diverged approximately 400 million years ago (Mya), it is possible that the changes in GC contents and the intron loss were independent from each other but are correlated by chance. For this reason, we analyzed the relationship between GC content and intron loss in six species that diverged from their sister species more recently: Arabidopsis thaliana , Caenor17.2 Mya ), C. rem17.2 Mya ), Rattus22.6 Mya ), Brassi30.8 Mya ), and Dr47.6 Mya ). The inications , 32, 66.Dictyostelium discoideum was defined as a putative intron gain only when the absence of the intron at the position was confirmed in Dictyostelium purpureum, P. pallidum, Dictyostelium fasciculatum, and E. histolytica. In this way, 40 putative intron gains were detected in Dictyostelium discoideum and 58 in Dictyostelium purpureum. As noted by Logsdon et al. [Dictyostelium genomes and further against the nucleotide collection of NCBI using BLAST. The BLAST results were filtered with an E-value threshold of 10−10, a coverage threshold of 80 %, and a similarity threshold of 0.85. Source sequences have been found for only two new introns in Dictyostelium discoideum: the second intron of gene DDB_G0275263 and the fourth intron of gene DDB_G0273471 , from its 5′ splice site (GT) to a position located 37 bp upstream of its 3′ end. We investigated whether this region is an alternatively spliced intron of gene DDB_G0276095 using the transcriptome of Dictyostelium discoideum. No RNA-Seq reads could be mapped across the source region of gene DDB_G0276095. It seems that a cryptic 3′ splice site of the parental intron has been activated in the new intron. The source sequence of the fourth intron of gene DDB_G0273471 is the 3′ end of the coding sequence and a 64 bp unannotated untranslated region of gene DDB_G0267666 (transcript: DDB0231999). No short direct repeats exist at the boundaries of the two new introns, indicating that they were unlikely to have been gained during the repair of DNA double-strand breaks [Referring to previous publications reporting that recurrent intron losses are common in eukaryotic evolution , 58, we n et al. , a strond breaks . The soud breaks  could acDictyostelium discoideum and Dictyostelium purpureum diverged 400 million years ago [Drosophila persimilis and Drosophila pseudoobscura diverged only two Mya, researchers failed to identify the source sequences for six of the seven introns gained after their divergence [Daphnia pulex [Caenorhabditis elegans [Dictyostelium genomes, we are confident that there are intron gains. By HGT, Dictyostelium had gained 16 genes from bacteria. As bacterial genes are definitely intronless, all the introns in these 16 genes were gained after the divergence of the Amoebozoa from the plants and animals. Within these genes, nine introns have been annotated in Dictyostelium discoideum and 19 introns have been annotated in Dictyostelium purpureum. Among them, there are seven pairs of introns at orthologous positions and 14 introns at discordant positions. The sequences of all these introns were used as queries to search against the two Dictyostelium genomes and further against the nucleotide collection of NCBI using BLAST. The BLAST results were filtered with an E-value threshold of 10−10, a coverage threshold of 80 %, and a similarity threshold of 0.85. Putative source sequences for two pairs of orthologous introns had been obtained. However, these source sequences have been rejected after alignment of them with the intron sequences and manual scrutiny. For the difficulty in finding intron sources, another possibility is that exogenous sequences such as viruses have contributed sequences for most intron gains but have not yet been covered in any genome sequencing projects [The proposed models of intron gains  clearly ears ago , the seqvergence . Even moia pulex . One pos elegans . Due to projects . In the Dictyostelium belongs to a supergroup, Amoebozoa, which diverged from animals and fungi very early in the evolutionary history of eukaryotes. In spite of this ancient divergence, our results indicate that its mechanism of intron loss is similar to that of animals and fungi. Most introns were lost in the process of gene conversion between the genomic DNA and cDNA reverse transcribed from mature mRNA.Dictyostelium discoideum, Dictyostelium purpureum, P. pallidum, and Dictyostelium fasciculatum were downloaded from DictyBase [E. histolytica  were downloaded from the AmoebaDB [The genome sequences and annotation files of ictyBase , 70 in MAmoebaDB , 72. We −10 and an identity threshold of 0.25, 7,503 pairs of one-to-one orthologous proteins were detected between Dictyostelium discoideum and Dictyostelium purpureum. Each pair of orthologous genes were independently aligned using ClustalW and MUSCLE [Dictyostelium discoideum and Dictyostelium purpureum within 45 bp at each side of less than 0.5, which is the first quartile of the similarities of all the aligned orthologous mRNAs. The consistent results obtained using ClustalW and MUSCLE were retained, including 6,432 conservative intron positions in 4,150 genes and 2,058 discordant intron positions in 1,605 groups of orthologous genes, with 679 unique introns in Dictyostelium discoideum and 1,379 unique introns in Dictyostelium purpureum. The orthologous genes in P. pallidum, Dictyostelium fasciculatum, and E. histolytica were detected and aligned using the same methods.Using the BLAST reciprocal best hits with an E-value threshold of 10d MUSCLE , 74 withDictyostelium discoideum (SRP023109), Dictyostelium purpureum (SRP001567), P. pallidum (SRP004023) and E. histolytica (SRP017935), which were downloaded from the Sequence Read Archive of NCBI [In most genome annotations, some errors are inevitable. The mis-annotation of exonic segments as introns would result in false-positive results of intron gain if the mis-annotated segments happened to be new insertions. Similarly, if a mis-annotated segment were deleted in another species, the simple deletion would be mis-recognized as an intron loss. Therefore, we re-annotated the introns at discordant positions using the transcriptome data of  of NCBI . The RNA of NCBI . FinallyThe loss and gain of introns were distinguished using Dollop (version 3.69) . An intrArabidopsis thaliana, Arabidopsis lyrata, Brassica rapa, Thellungiella parvula, Drosophila willistoni, Drosophila melanogaster, Caenorhabditis briggsae, Caenorhabditis remanei, Caenorhabditis elegans, Caenorhabditis japonica, Rattus norvegicus, Mus musculus are reported in Additional file Brassica rapa, Arabidopsis thaliana and Rattus norvegicus were retrieved from references [Drosophila willistoni were those published in [Drosophila willistoni and Drosophila melanogaster.The version numbers of the genome sequences and source databases of ferences , 32, 66,ished in . We updaDrosophila willistoni and Drosophila melanogaster, and 12,613 between C. briggsae and C. remanei. Only hits with an E value below 10−10 and with identity higher than 25 % were considered. Each pair of orthologous genes was aligned using ClustalW and MUSCLE [Drosophila willistoni and Drosophila melanogaster and 54,871 conserved introns between C. briggsae and C. remanei, which were used for further study.Using the BLAST reciprocal best hits, 7,744 pairs of one-to-one orthologous proteins were detected between C. briggsae and C. remanei within 45 bp at each side of less than 0.57, which is the first quartile of the similarities of all aligned orthologous mRNAs. Therefore, we obtained 4,827 discordant introns in 3,625 genes between the two Caenorhabditis species. We used C. elegans and C. japonica as related species to predict lost introns, only those introns existing in both C. elegans and C. japonica were used for further study. We then used the transcriptome data of C. briggsae (SRP034522), C. remanei (SRP040962) and C. elegans (SRP000401) to re-annotate the introns at discordant intron positions. Finally, we obtained 1,225 and 664 cases of intron losses in 1,026 and 572 genes of C. briggsae and C. remanei, respectively.Sequences surrounding discordant intron positions with low-quality alignments were discarded. The low quality was based on a similarity between Drosophila willistoni and Drosophila melanogaster was established as 0.5, which was lower than the first quartile (0.64). This value was used to best locate the corresponding lost introns found by Yenerall et al. [Drosophila willistoni.The threshold value of the similarity of coding sequences between l et al. ; in thisDictyostelium discoideum were used as the background dataset in this study. The total number of genes used in calculating the background distribution of GO terms was 12,098, and the threshold P-value of 0.01 was used in the identification of specific enrichments. The GO annotations are not been assigned to the genes of Dictyostelium purpureum. So they were represented by their orthologs in Dictyostelium discoideum in GO enrichment analysis. The 443 lost introns in Dictyostelium discoideum and 202 lost introns in Dictyostelium purpureum were mapped to 586 genes of Dictyostelium discoideum. These 586 intron-lost genes were compared with whole background sets. In same way, the putative gained introns of these two species were mapped to 86 intron-gained genes of Dictyostelium discoideum, which were compared with background sets for GO enrichments.GO enrichment analysis was performed using GOTermFinder . The GO U test, in our comparisons of the data.As almost all the data are not normally distributed, we used nonparametric analyses, like Mann–Whitney All supporting data are included as additional files in the form of Additional files


In order to test recently predicted ballistic nanofriction (ultra-low drag and enhanced lubricity) of gold nanocrystals on graphite at high surface speeds, we use the quartz microbalance technique to measure the impact of deposition of gold nanocrystals on graphene. We analyze our measurements of changes in frequency and dissipation induced by nanocrystals using a framework developed for friction of adatoms on various surfaces. We find the lubricity of gold nanocrystals on graphene to be even higher than that predicted for the ballistic nanofriction, confirming the enhanced lubricity predicted at high surface speeds. Our complementary molecular dynamics simulations indicate that such high lubricity is due to the interaction strength between gold nanocrystals and graphene being lower than previously assumed for gold nanocrystals and graphite. A simple phenomenological formula, F = μN, where μ is the coefficient of friction and N is the normal force, governs macroscopic friction. Nanoscale contacts between surface asperities are assumed to determine μ, but the fundamental science of friction at nanoscale, nanotribology, is still in its infancy and many unsolved problems remain.2One of the most promising discoveries in nanotribology is structural lubricity2567811121415fAsin(2πft), where Aosc is the amplitude, f is the resonant frequency and t is the elapsed time. The oscillation amplitude is given by Aosc = C × Q × V, where C = 1.3 pm/V, Q is the quality factor, and V is the driving oscillation voltage25τs, which is the characteristic time required for sliding adsorbates to stop, by the formulaRecent calculations have shown that gold nanocrystals on graphite possess unusually low friction182218τs = ρ/ξ, where ξ is the drag coefficient and ρ is the mass per unit area of adsorbates. QCMs along with this formalism have been exploited to determine the frictional behavior of weakly adsorbed monatomic gases like Xe and Kr2526283031The slip time is related to the drag coefficient as We observe that depositing gold nanocrystals on graphene-coated QCMs decreases the resonance frequency and increases the energy dissipation. The measured changes of frequency and dissipation induced by gold nanocrystals are used to determine the slip time of the nanocrystals on graphene using the framework previously developed for friction of adatoms2512 crystals/cm2 as shown in 10 defects/cm2. As such, we expect the responses of the graphene QCM to be dominated by the interaction of nanocrystals with the graphene lattice. In AFM images, nanocrystals appear to be disk-shaped with large apparent lateral diameter and smaller height with the height ranging from 2.8 to 4.0 nm. The apparent shape is due to the convolution between the nanocrystals and the AFM tip shape. As shown in Gold is deposited using electron beam evaporation after stabilizing a QCM coated with graphene and a control QCM without graphene in an ultra-high vacuum (UHV) environment. The areal density of nanocrystals is determined using an AFM after QCM measurements to be 1.01 ± 0.02 × 10t ≅ 5.2 × 104 sec and gold is deposited for 605 seconds at a rate of 1.6 ng/(cm2 sec), as determined by the frequency shift of the control QCM using the Sauerbrey equation−6 upon gold deposition. On the other hand, the dissipation of the control QCM does not change as observed previouslyf of the graphene QCM is given by the formulaPrecise knowledge of the change in frequency and dissipation enables us to determine the slip time of the gold nanocrystals using the formalism developed for viscous energy dissipation induced by adsorbates on QCMs25f is the resonant frequency, N is the total number of nanocrystals on graphene, ω is the angular resonant frequency of the crystal, ms is the average mass of an individual sliding nanocrystal, A is the active area of the crystal, Zq is the acoustic impedance of AT-cut quartz (8.8 × 106 kg m−2 s−1), and τs = ms/ξ is the slip time for sliding crystals, with ξ being the drag coefficient. Similarly, the shift in the inverse quality factor of the QCM iswhere τs can be calculated from the ratio of the shifts in frequency and dissipation for the graphene QCM:We assume all adsorbed nanocrystals participate in sliding, and, thus, contribute to the observed change in frequency and dissipation, justified by the low defect density of the graphene used for our study. The slip time −22 kg undergoing the ballistic friction behavior−22 kg. We find that this value is 17% smaller than the value calculated from the amount of gold deposited on the control QCM. Such discrepancy is not surprising since the sticking coefficient of gold on graphite has been determined to be less than 1 below monolayer coverage at room temperature3, consistent with our AFM measurements.We find the slip time to be 8.9 ns, with an oscillation amplitude of 11.4 nm and a peak surface speed of 35.6 cm/sec using our data. The measured slip time is over an order of magnitude higher than the slip time predicted for a smaller gold nanocrystal with a mass of 1.5 × 10Aosc, in the range of 1.5 to 11.4 nm, which is accessible to our QCMs. The peak surface speeds vary from 4.7 to 35.6 cm/sec in this experimentally observable window. The slip time as a function of the oscillation amplitude can be determined again by using Δf and Δ(1/Q) as discussed above. The slip time decreases at lower speeds but the predicted transition to a much lower slip time is not seen. This indicates that the predicted transition to high lubricity occurs below 4.7 cm/sec.It is important to note that nanocrystals do not collide with each other during our measurements. The motion between gold nanocrystals and graphene QCM can be described by a differential equationv2 is the velocity of nanocrystals and v1 is the velocity of graphene QCM. As such, v1 = v0 cos(ωt), where v0 is the amplitude of the QCM surface velocity. The solution to this differential equation is given by:where Relative velocity of gold nanocrystal on the graphene QCM isRelative displacement, d, isThis can be written aswhere the phase, ϕ, is given byTherefore, the amplitude of the motion of nanocrystals on the graphene QCM is proportional to the maximum amplitude of the surface velocity of the graphene QCM. The maximum sliding amplitude of nanocrystals with respect to graphene is 3.1 nm with the surface velocity amplitude of 35.6 cm/sec, the maximum used for our experiment. The range of diameters of nanocrystals determines the maximum phase angle range. We estimate the range of the phase to be 20 degrees using the diameter distribution of ±1 nm observed in previous measurements with similar deposition parametersThe question remains on why we observe the enhanced lubricity that exceeds the previous prediction1818ξ increases with the interaction strength and ε being lower than 22 meV can explain the observed lubricity that exceed the previous prediction. Since the measured quantities determine the slip time rather than the drag coefficient, we calculate the drag coefficient using the average mass and slip time as well as the expected variation in diameters. We find the drag coefficient to be 8.6 ± 6.1 × 10−14 kg/s at the peak surface speed of 35.6 cm/sec. Therefore, our simulation reproduces the experimentally-measured drag with ε ≈ 6 ~ 15 meV as shown in 30where ε is the depth of the potential well or the interaction strength, σ is the distance at which the interatomic potential is zero, and r is the distance between atoms. The ballistic friction of gold nanocrystals on graphite was predicted using σ = 2.74 Å and ε = 22 meV183738In-situ high-resolution microscopy should be able to directly confirm these distances and verify our analysis. Furthermore, the precision of our measurement of the drag coefficient is limited by the distribution in the size of nanocrystals. Future experiments with more control over nanocrystals will improve the capability to determine their drag coefficients using the QCM technique.In summary, we have measured the changes in frequency and dissipation induced by depositing gold nanocrystals on QCMs covered with graphene. Nanocrystals increase the dissipation of the QCM coated with graphene while leaving the dissipation of the control QCM without graphene unaffected. The measured change in dissipation and frequency induced by the gold nanocrystals can be understood in the framework developed for friction of adatoms on metal surfaces. The determined slip time of gold nanocrystals is found to be over an order of magnitude higher than the value predicted for the ballistic friction of gold nanocrystals on graphite, confirming the enhanced lubricity predicted at high surface speeds. We perform molecular dynamics calculations and show that the observed lubricity, which exceeds the previous prediction, is due to the interaction strength between gold nanocrystals and graphene being lower than estimated in the previous modeling studies. As discussed above, specific sliding distances can be inferred from our analysis of the experimental data. 2/Ar at 350 °C for 3 hours at atmospheric pressure in order to clean the surfaces of the QCMsdg ratio of 0.074 and a graphene defect density of 1.9 × 1010 defects/cm2 −9 Torr. The crystals are vacuum annealed in situ at 180 °C for 8 hours prior to experiments.The control and graphene QCM are as 5 MHz AT-cut QCM blanks (ICM Mfg.). Electrodes are patterned on both sides using a 10 nm Cr adhesion layer followed by 100 nm of Cu, and then 80 nm of Au using thermal evaporation. The graphene-coated QCM is prepared by transferring graphene grown by low-pressure chemical vapor deposition on copperfF ≈ 5 MHz. A previous study found that graphene nanoribbons, which are ~100 nm2 in size, exhibit high lubricity on reconstructed, well-ordered gold surfaces and that the reconstruction was critical to the observed effectQCM experiments are performed in UHV. Nanocrystals are formed by evaporating gold on graphene via e-beam evaporationτ is extracted from the ring down curve and Q is determined via the relationship Q = πτf, where f is the fundamental frequency of the QCM.Frequency and electronic amplitude are continuously monitored for both QCMs using an Agilent 53220A frequency counter. Quality factors of both the control and graphene QCM are determined by ring-down measurements using a Tektronix 2024B oscilloscope. The ring down time constant 2 (800 nm) and Si3N4 (16 nm) in which thin (<1 um) windows are etched with KOH. After deposition of the graphene and gold, the bottom side of the windows is etched by placing the chip over HF vapor to remove the oxide, leaving a thin nitride membrane. Samples are imaged in a Titan 80–300 FEG S/TEM at 300 kV at high spot size (low beam current) to minimize beam-induced damage on the sample.To image gold nanocrystals on graphene with TEM, gold is deposited onto CVD graphene on electron-transparent substrates in the same manner as described above for the QCM devices. The substrates consist of Si with thermally grown SiOAFM images are acquired in air at room temperature using a Bruker Dimension 5000 atomic force microscope operating in tapping mode in ambient conditions. We use the Supersharp silicon AFM tips fabricated by Mikromasch with tip radius of <1 nm for imaging (Mikromasch Hr’Res-10/Cr-Au).int = 4ε[(σ/r)12 − (σ/r)6], where ε is the interaction strength, σ is the distance at which the interatomic potential is zero, and r is the distance between atoms. We ran simulations at a range of interaction strengths, ε, to explore the effect of this parameter. The simulations are performed using LAMMPS simulation softwareThe all atom simulations consist of a single gold nanocrystal on graphene. The nanocrystal is modeled as Au atoms in a truncated-octahedron geometry with approximate diameters between 2 and 4.5 nm. The nanocrystal is placed such that its (111) surface is in contact with graphene that has in-plane dimensions of 14.0 nm × 7.1 nm. The interatomic interactions within the gold are described by the Embedded Atom Model (EAM)First, simulations are run with no externally applied force to characterize the diffusion behavior of the system. Diffusion speed for each nanoparticle diameter is calculated from the approximately linear slope of the increase in the center of mass displacement of the nanocrystal with time. During production simulations, the graphene is translated laterally at speeds between 10 and 500 m/s. The center of mass of the gold nanocrystal and force acting on it are recorded and then averaged over time intervals of 0.5 ns. The drag coefficient is then calculated from ξ = F/∆v, where F is the average force on the gold nanocrystal in the direction that the graphene is translated and Δv is the difference between the sliding speed of the nanoparticle and the graphene in that same direction. The drag coefficient is calculated from the simulation only when the difference in the speed of the nanocrystal and graphene is greater than the diffusion speed for a given nanoparticle size, i.e. when the nanocrystal is sliding relative to the graphene.How to cite this article: Lodge, M. S. et al. Lubricity of gold nanocrystals on graphene measured using quartz crystal microbalance. Sci. Rep.6, 31837; doi: 10.1038/srep31837 (2016).


Immune checkpoint inhibition has shifted treatment paradigms in non-small cell lung cancer (NSCLC). Conflicting results have been reported regarding the immune infiltrate and programmed death-ligand 1 (PD-L1) as a prognostic marker. We correlated the immune infiltrate and PD-L1 expression with clinicopathologic characteristics in a cohort of resected NSCLC.A tissue microarray was constructed using triplicate cores from consecutive resected NSCLC. Immunohistochemistry was performed for CD8, FOXP3 and PD-L1. Strong PD-L1 expression was predefined as greater than 50% tumor cell positivity. Matched nodal samples were assessed for concordance of PD-L1 expression.Of 522 patients, 346 were node-negative (N0), 72 N1 and 109 N2; 265 were adenocarcinomas (AC), 182 squamous cell cancers (SCC) and 75 other. Strong PD-L1 expression was found in 24% cases. In the overall cohort, PD-L1 expression was not associated with survival. In patients with N2 disease, strong PD-L1 expression was associated with significantly improved disease-free (DFS) and overall survival (OS) in multivariate analysis . In this resected cohort only 5% harboured EGFR mutations, whereas 19% harboured KRAS and 23% other. KRAS mutated tumors were more likely to highly express PD-L1 compared to EGFR (22% vs 3%). A stromal CD8 infiltrate was associated with significantly improved DFS in SCC , but not AC, whereas FOXP3 was not prognostic. Matched nodal specimens (N = 53) were highly concordant for PD-L1 expression (89%).PD-L1 expression was not prognostic in the overall cohort. PD-L1 expression in primary tumor and matched nodal specimens were highly concordant. The observed survival benefit in N2 disease requires confirmation. Recent years have seen a cascade of novel immunological agents with proven efficacy in multiple malignancies.–5 In parGiven that PD-L1 is inducible and may reflect homeostatic responses to immune activation , the immTo clarify the influence of PD-L1 expression and the stromal CD8+ lymphocyte infiltrate as prognostic factors in this patient cohort, we comprehensively profiled the immune microenvironment in a large retrospective cohort of resected NSCLC using a tissue microarray (TMA). Furthermore, we sought to clarify whether PD-L1 status was maintained in matched nodal samples from a subset of patients with tissue available from locoregionally advanced diseaseConsecutive patients undergoing curative surgery for NSCLC during the period from 1992 to 2010 at the Austin Hospital, Victoria, Australia were captured in a prospectively maintained database. Clinicopathologic data were reviewed and collated. The revised 2010 AJCC staging manual was used for classification of stage. The projLung cancer specimens were histologically reviewed by an experienced pathologist. Representative areas of tumor tissue were selected and marked, prior to being sampled for the TMA. One millimeter cores of formalin fixed paraffin embedded (FFPE) tissues in triplicate from a consecutive series of surgically resected lobectomy and pneumonectomy specimens were used for the TMA.FFPE TMA specimens were heated at 60°C for 1 hour and subjected to a series of xylene and ethanol washes to remove paraffin. Antigen retrieval was performed with TRS buffer pH 9 (Dako) by heating in a microwave. The following primary antibodies were used in this study; Anti-FOXP3 mouse IgG1, Abcam cat# ab22510 at 17.0 μg/ml, Anti-CD4 rabbit IgG, Cell Marque cat# 104R-15 at 1.0 μg/ml, Anti-CD8 mouse IgG1 clone C8/144B, Dako cat# IS623, ready to use and Anti-PD-L1 rabbit IgG (E1L3N) cat # 13684, Cell Signaling Technology at 7.0 μg/ml. HRP system was used to detect signal. For all T cell markers tonsil tissue was used as a positive control and for PD-L1 placenta was the positive control.After staining, slides were scanned using a high resolution scanner  at 20x magnification. T cell markers were scored on a scale of 0–3 based on the percentage of positively stained cells, as a proportion of the total nucleated cells, in both the stromal peri-tumoral compartment and within the tumour itself, for the entire core (4 high powered fields) by one observer (MA), as described elsewhere. A high sGene mutation status was determined using Sequenom’s MassArray LungCarta panel as previously described.  All mutaSurvival analyses were performed to evaluate the association between marker expression and survival endpoints. Overall survival (OS) was determined from the date of surgery to the date of death. Disease-free survival (DFS) was determined from the date of surgery to the date of first relapse, and in cases of non-cancer related death, were censored at the time of death.Marginal, stratified and by-group univariate analyses on OS and DFS were performed for CD8+ infiltrate, FOXP3 and PD-L1. P-values were computed using log-rank test, while hazard ratios (HR) and confidence intervals (CI) were derived from Cox’s model.From univariate analyses, the following variables were chosen for the multivariate analysis: age, sex, pneumonectomy status, nodal stage, histology, smoking status, CD8+, FOXP3, and PD-L1. Interactions between CD8+, FOXP3, PD-L1 and nodal stage, histology and smoking were considered. Cox's proportional hazard model was used for OS and DFS separately. Variables were further selected by backward elimination based on Wald type test. The hierarchical structure of variables was maintained so that if interaction of a variable appears in the model, its main effect was preserved. After the backward selection procedure, proportional hazard assumptions were validated for each variable using Shoenfeld's test.survival (version 2.38–3).All analyses were performed on the R platform (version 3.1.3) using package There were 527 patients in the entire cohort; 509 patients were assessable for CD8 status, 413 for FOXP3 status and 420 for PD-L1. Individual cores were excluded for analysis if there was significant necrosis or artefact. For the entire cohort, the median follow-up was 117 months and median overall survival was 46 months. Three hundred and forty-six patients were N0, 72 patients were N1 and 109 patients were N2. The median survival was 71, 32 and 14 months for N0, N1 and N2 disease respectively. As many of these cases occurred prior to 2004  only 51 patients received chemotherapy . The median age was 67 and 51% of patients had died of disease recurrence. Smoking data were available for 507 patients. Smokers were classified as never smokers, light smokers (<25 packet years smoking) or heavy smokers (≥25 packet years smoking). There were 35 never smokers, 87 smokers and 385 heavy smokers. Most patients were Caucasian (96%).EGFR mutations were found in 27 cases and KRAS mutations were detected in 100 cases. Other mutations  were detected in 126 patients. Ninety-eight patients underwent pneumonectomy, with the remaining patients treated with lobectomy. Utilizing a prespecified cutoff of 5% membranous staining, 43.6% of tumors were PD-L1 positive. Using a more stringent cutoff of 50%, 100 cases (23.8%) were classified as strongly positive (PD-L1+). Overall, apart from a tendency for slightly younger patients to be PD-L1+, there were no significant differences in strong PD-L1 expression by nodal status, pneumonectomy, smoking status, histology or molecular status .EGFR mutant NSCLC was associated with inferior prognosis , than EGFR wild-type NSCLC although these numbers were limited. KRAS status was not prognostic in the univariate or multivariate models. A test for interaction with CD8+ confirmed that strong PD-L1 status was not correlated with CD8+ expression.Only three of 27 never smokers had strong PD-L1 expression on their tumors. In smokers, strong PD-L1 expression was associated with a significantly improved OS  . There wIn multivariate analysis PD-L1 expression was an independent predictor of improved OS and DFS , in patiOverall, there were no significant differences in CD8+ expression by nodal status, pneumonectomy status, smoking status, histology or molecular status. Given that previous studies have shown prognostic differences associated with tumoral compared to stromal TIL, we further characterised the TIL using a similar score. Patients with a stromal CD8+ score of 3, without a corresponding high tumoral infiltrate were compared to tumors without a high stromal infiltrate. On stratified univariate analysis , there wThere were no significant differences in OS between heavy, light and never smokers and CD8+ TILs. When stratified according to histology, high stromal CD8+ TILs was associated with significantly improved prognosis in squamous tumours  but not in adenocarcinomas . These findings were confirmed in multivariate analysis, with CD8+ expression being significantly associated with improved DFS but not OS . The KapThe FOXP3 score was dichotomized into FOXP3+ high (score of 2–3) and FOXP3+ low (score of 0–1) and analyzed for survival endpoints. In all patients, FOXP3 status was not associated with survival. In patients with N2 disease, there was a significantly improved DFS with high FOXP3 infiltrate , but no other associations were observed. FOXP3 positive status was strongly correlated with both increasing nodal stage and PD-L1 expression with significantly more strongly PD-L1 positive tumors also containing FOXP3 TILs .In order to clarify whether PD-L1 status was maintained in nodal specimens, PD-L1 status was evaluated in a matched cohort of primary and mediastinal nodal samples from patients with N2 disease (n = 53). The concordance for reported PD-L1 status was 89%. The major cause of discordance was due to strong PD-L1 expression in the lymph node but absent or little expression within the primary sample in 4 (8%) samples.EGFR mutations are both predictive but also favourably prognostic and it is important to determine the prognostic significance of PD-L1 in association with other immune cell infiltrates. These data demonstrate that tumoral PD-L1 expression was not prognostic in the overall cohort. Stromal CD8+ expression was prognostic in squamous cell histology but not adenocarcinoma. Although FOXP3 status was not independently prognostic, its expression was strongly correlated with advanced nodal stage and strong PD-L1 expression. Novel findings, include the strong concordance noted between primary tumors and their matched nodal primaries (in to date the largest published series of matched tumors) and a suggestion of poorer survival in never smokers with PD-L1 expression compared to smokers.Abrogation of the the PD-1/PD-L1 checkpoint using monoclonal antibodies is associated with not only improvement in response rates but also overall survival. Some predictive markers, such as Strong tumoral expression of PD-L1 was demonstrated in 24% of cases, a finding consistent with the reported literature, with a The discrepant results in the N1 population of patients could not be explained by anomalies in the cohort, as standard prognostic factors such as age and nodal status were clearly prognostic in the multivariate model . Rather,EGFR mutant tumors appeared to have a markedly worse prognosis than wild-type patients, although caution must be taken when interpreting these data in light of the small number of never smokers and EGFR mutations. Interestingly, most studies reporting PD-L1 as a negative prognostic marker have come from Asian populations, where a high percentage of never smokers and EGFR mutations exist, whereas those reporting PD-L1 as a favourable prognostic marker have been predominantly in Caucasian smokers Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


Long interspersed element-1 (LINE-1 or L1) retrotransposition induces insertional mutations that can result in diseases. It was recently shown that the copy number of L1 and other retroelements is stable in induced pluripotent stem cells (iPSCs). However, by using an engineered reporter construct over-expressing L1, another study suggests that reprogramming activates L1 mobility in iPSCs. Given the potential of human iPSCs in therapeutic applications, it is important to clarify whether these cells harbor somatic insertions resulting from endogenous L1 retrotransposition. Here, we verified L1 expression during and after reprogramming as well as potential somatic insertions driven by the most active human endogenous L1 subfamily (L1Hs). Our results indicate that L1 over-expression is initiated during the reprogramming process and is subsequently sustained in isolated clones. To detect potential somatic insertions in iPSCs caused by L1Hs retotransposition, we used a novel sequencing strategy. As opposed to conventional sequencing direction, we sequenced from the 3′ end of L1Hs to the genomic DNA, thus enabling the direct detection of the polyA tail signature of retrotransposition for verification of true insertions. Deep coverage sequencing thus allowed us to detect seven potential somatic insertions with low read counts from two iPSC clones. Negative PCR amplification in parental cells, presence of a polyA tail and absence from seven L1 germline insertion databases highly suggested true somatic insertions in iPSCs. Furthermore, these insertions could not be detected in iPSCs by PCR, likely due to low abundance. We conclude that L1Hs retrotransposes at low levels in iPSCs and therefore warrants careful analyses for genotoxic effects. OCT4, SOX2, C-MYC and KLF4. These reprogrammed cells, termed ‘induced pluripotent stem cells’ (iPSCs), are capable of unlimited self-renewal and display full pluripotency invivoIt is now possible to reprogram fully differentiated somatic cells back to the embryonic state by forced expression of certain transcriptional factors such as The long interspersed element-1 (LINE-1 or L1) is a retrotransposon of about 6 kb long which replicates itself by a ‘copy paste’ mechanism It has been previously reported that both the expression and the frequency of retrotransposition of L1 are higher in human iPSC clones than in the parental fibroblast cells The IMR90 cell line  was obtained from the American Type Culture Collection. The NHDF1 cell line  which was originally obtained from Lonza  was a gift of Dr Lowry  OCT4, C-MYC, SOX-2, LIN28 and KLF4 were either cloned in the pMX  or FRh11  vector 4 fibroblasts were seeded per well in a gelatin-coated 6 well-plate. The following day, the cells were transduced with the same equivalent of p24 amounts of each viral stock in the presence of 8 µg/mL of polybrene  for two hours, after which, the medium was replaced with fresh fibroblast medium and the cells were allowed to expand. Three days post-transduction, 5×104 transduced cells were seeded on an irradiated mouse fibroblasts (iMEFs) feeder layer in a 60 mm dish and cultured in fibroblast medium for a day. The culture medium was then switched to human iPSC medium: Knock-out DMEM (Life Technologies) containing 20% Knockout Serum Replacement (Life Technologies), 2 mM Glutamax (Life Technologies), 0.1 mM non-essential amino acids (Life Technologies), 0.1 mM β-mercaptoethanol , and 50 ng/ml of recombinant human basic fibroblast growth factor (Life Technologies). 0.5 mM valproic acid (Sigma-Aldrich) was supplemented for the first 7 days only. Medium was replaced every day for up to three weeks. Around week 3 post-seeding on the feeder layer, iPSC colonies were isolated based on morphological criteria and expanded in mTeSR1 (Stem Cell Technologies) medium on matrigel (BD Biosciences) coated plates. Some clones were then characterized as previously described OCT4, SOX2, C-MYC and KLF4 after which we followed the protocol as described above. At each of the following time point , all the cells were trypsinized and collected. Irradiated MEFs were removed from the mixed population by positive selection and only human cells undergoing reprogramming were isolated. RNA was then extracted for each sample by using the RNeasy kit .The cDNA of the reprogramming factors 6 iPSCs  were resuspended in a mixture of DMEM/F12 (Life Technologies) and Matrigel (BD Biosciences) at a ratio of 2∶1. The cell mixtures were then injected intramuscularly into the hind legs of Nod-SCID mice and the animals were monitored once a week. Teratomas were allowed to develop until they would reach approximately 1 cm in size. The animals were then sacrificed and the teratomas were extracted, fixed with 10% formalin, embedded in paraffin, sectioned, and stained with hematoxylin and eosin. The presence of derivative tissues of the mesoderm, ectoderm and endoderm was then confirmed by a pathophysiologist.Expression of pluripotency gene markers and vector expression silencing assessment have previously been described for the clones used in this study GAAGGTGAAGGTCGGAGT 3′, (AS) 5′ GAAGATGGTGATGGGATTTC, (P) 5′ HEX-CAAGCTTCCCGTTCTCAGCC-BHQ-1 3′ . Total RNA extracts from iPSC18 clone were a kind gift of Dr Kathrin Plath  while the rest of the total RNA samples were isolated using the RNeasy kit (QIAGEN). The Wilcoxon rank sum test was used to assess whether L1 over-expression for each tested sample was significantly higher than that of the parental cells.Expression levels of L1 were assessed on total RNA extracts from the different fibroblast cells that were undergoing the reprogramming process or from isolated human iPSC clones and the corresponding parental cells. We used published L1 specific primers and probe previously described Genomic DNA was isolated using the DNeasy Blood & Tissue Kit (QIAGEN). The protocol for L1Hs DNA library preparations was adapted from Ewing et al by using the primers listed below 5931)L1HsTAILSP1A2 (ACGGGAGATATACCTAATGCTAGATGACACA-L16015G MID1 (for HFF)CGTATCGCCTCCCTCGCGCCATCAGACGAGTGCGTTGCACATGTACCCTAAAACTTAGA-L16015G MID2 (hiPS #7)CGTATCGCCTCCCTCGCGCCATCAGACGCTCGACATGCACATGTACCCTAAAACTTAGA-L16015G MID3 (hiPS #11)CGTATCGCCTCCCTCGCGCCATCAGAGACGCACTCTGCACATGTACCCTAAAACTTAGA-L16015G MID4 (hiPS #19)CGTATCGCCTCCCTCGCGCCATCAGAGCACTGTAGTGCACATGTACCCTAAAACTTAGA-L16015G MID6 (NHDF1)CGTATCGCCTCCCTCGCGCCATCAGATATCGCGAGTGCACATGTACCCTAAAACTTAGA-L16015G MID9 (H1-hESC)CGTATCGCCTCCCTCGCGCCATCAGTAGTATCAGCTGCACATGTACCCTAAAACTTAGPrimer ACGTATCGCCTCCCTCGCGCCATCAGPrimer BCTATGCGCCTTGCCAGCCCGCTCAGB1-N5TCTGTCTATGCGCCTTGCCAGCCCGCTCAGNNNNNTCTGTB2-N5CTTCTCTATGCGCCTTGCCAGCCCGCTCAGNNNNNCTTCTB3-N5CTGCACTATGCGCCTTGCCAGCCCGCTCAGNNNNNCTGCAB4-N5TGCCTCTATGCGCCTTGCCAGCCCGCTCAGNNNNNTGCCTB5-N5TCTCACTATGCGCCTTGCCAGCCCGCTCAGNNNNNTCTCAB6-N5CAGAGCTATGCGCCTTGCCAGCCCGCTCAGNNNNNCAGAGB7-N5TTGAACTATGCGCCTTGCCAGCCCGCTCAGNNNNNTTGAAB8-N5CTTTGCTATGCGCCTTGCCAGCCCGCTCAGNNNNNCTTTGThe resulting 454 DNA sequencing data was first processed as follows before alignment on the human reference genome build 19. Based on the MID sequence barcode, each DNA sequence was assigned its original sample identity i.e. HHF, hiPSC #7, hiPSC #11, hiPSC #19, NHDF1 and H1-hESC. The 454 primers A and B as well as the degenerative sequences were then trimmed for all sequences. By using a specific script for BLAT alignment, the trimmed sequences were then compared to the human reference genome build 19 as described below. The deep sequencing datasets have been deposited in the European Nucleotide Archive (accession number PRJEB6145).http://genome.ucsc.edu.After alignment on the human reference genome, sequences which matched unambiguously annotated L1 insertions from the L1-polyA to the genomic region were identified as reference L1s. These sequences were further categorized as L1Hs or from older families based on the RepeatMasker annotations from the UCSC genome browser, Sequences that matched the human reference genome on two unambiguous and distinct locations  indicated potential non-reference L1 insertions. In order to be considered further, the genomic part of the flanking region of each sequence should display more than 90% identity when compared to the reference genome. . These sequences were used for identification of non-reference germline and somatic insertions.To identify non-reference germline insertions: Each insertion site (i) either was present in the HFF library (ii) or was previously annotated in any of the five non-reference L1 databases To identify potential somatic insertions in iPSC clones: each non-reference insertion (i) was absent in the HFF library (ii) was present in only one iPSC clone library at a time (iii) was absent from the five published L1 insertion libraries The sequencing depth for each sample was calculated based on the average number of sequences detected per reference L1Hs identified.The presence of non-reference germline insertions was verified via site-specific PCR as described by Ewing et al To verify potential somatic insertions in iPSCs, we used the same protocol as described above. PCR yielded negative results in HFF as expected but did not give positive results in the corresponding iPSC clone. We therefore resorted to nested-PCR, a more sensitive method as described by Baillie et al used to identify somatic insertions This study was approved by the University of California at Los Angeles human Embryonic Stem Cell Research Oversight (ESCRO) committee  and the University of California at Los Angeles Animal Research Committee .OCT4, SOX2, C-MYC, NANOG, and KLF4 from the γ-retroviral vector pMX OCT4, SOX2, C-MYC and KLF4 encoded by the FRh11 lentiviral vector To confirm that L1 is over-expressed as detected by others we assessed total L1 expression in the hiPSC18 clone by using published primers and probe OCT4, SOX2, C-MYC and KLF4 were expressed from either the FRh11 vector as used in our previous experiments or the pMX vector as used to generate the hiPSC18 clone Next, we investigated whether the increase in L1 expression was triggered during the reprogramming process. The cDNA of the four reprogramming factors Recently, through whole genome sequencing, it was shown that retroelements such as L1 and other repetitive sequences have stable copy numbers in mouse and human iPSCs It has previously been shown that each individual possesses approximately 800 germline L1Hs insertions Having validated the detection of non-reference germline insertions in HFF, we then addressed the issue of whether the two iPSC clones #7 and #11 derived from HFF harbored somatic L1 insertions as a result of L1 over-expression. We did not take into account any potential somatic insertions from a third iPSC clone derived from HFF (hiPSC #19 clone) since it gave rise to only ectodermic tissues during in vivo iPSCs differentiation into teratomas and therefore may not be a fully reprogrammed clone . We idenThe high rate of positive detection for read count of one for germline insertions (24/26 i.e. more than 92%) was similar to those previously reported for germline insertions Next, we further addressed the possibility of these insertions being germline insertions originating from contaminating DNA. We had already verified that the potential somatic insertions were absent from five different databases of non-reference germline insertions derived from at least 80 individuals (the dbRIP and the four other published databases) Assessing genomic stability of iPSCs is of utmost importance before their use in regenerative medicine. Here, we showed that overexpression of the endogenous mutagen L1 was triggered during reprogramming and that overexpression was sustained in isolated iPSC clones later as previously shown High throughput sequencing of the L1Hs subfamily resulted in the identification of seven potential L1Hs somatic insertions in two iPSC clones. There are several indications that our insertions were new somatic retrotranposition events: (1) they all had a polyA tail sequence, a key signature of retrotransposition as observed by others Why could we not positively detect these seven somatic insertions in the corresponding iPSC clone? Our high rate of PCR validation in confirming the total germline insertions indicates that our validation approach is successful in confirming new insertions (∼94% success), which would predict PCR confirmation for about 6 of our 7 somatic insertions. One explanation for not detecting these insertions is low abundance in the culture at the time of DNA extraction. Germline retrotransposition insertions are present in all cells whereas somatic retrotransposition insertions occur spontaneously at any time resulting in mosaicism Our results are consistent with those of a previous study where L1 mobility was detected in iPSCs using an exogenous L1 reporter but are in contrast to those of two other studies which showed stable number of repetitive sequences such as L1 in human or mouse iPSCs by whole genome sequencing Our findings suggest that endogenous L1Hs are capable of retrotransposition in human iPSCs, albeit in low numbers and that these cells harbor somatic insertions at low levels. Our work highlights the importance of careful examination of human iPSCs to detect any possible L1 insertion that may lead to adverse effects.Figure S1iPSC clones can form teratomas with the 3 distinctive germ layers. Approximately 106 iPSC cells were resuspended in a mixture of DMEM/F12 and matrigel. The cell mixtures were then injected intramuscularly into the hind legs of Nod-SCID mice and teratomas allowed to develop until they reach approximately 1 cm in size. The teratomas were then extracted and fixed with 10% formalin. Then they were embedded in paraffin, sectioned, and stained with hematoxylin and eosin. Tissues derived from the mesoderm, ectoderm and endoderm were confirmed by a pathophysiologist. Results are shown for (A) hiPSC #7 (B) hiPSC #11 and (C) hiPSC #19.(TIF)Click here for additional data file.Table S1Summary of total sequences obtained after 454 sequencing and depth coverage.(XLSX)Click here for additional data file.Table S2Non-reference germline L1Hs detected in HFF.(XLSX)Click here for additional data file.Table S3PCR validation results and primers for non-reference germline L1Hs in HFF.(XLSX)Click here for additional data file.Table S4Non-reference potential somatic L1Hs detected in iPSCs.(XLSX)Click here for additional data file.Table S5Non-reference germline L1Hs detected in NHDF1 and hESC.(XLSX)Click here for additional data file.


Enfacement is an illusion wherein synchronous visual and tactile inputs update the mental representation of one’s own face to assimilate another person’s face. Emotional facial expressions, serving as communicative signals, may influence enfacement by increasing the observer’s motivation to understand the mental state of the expresser. Fearful expressions, in particular, might increase enfacement because they are valuable for adaptive behavior and more strongly represented in somatosensory cortex than other emotions. In the present study, a face was seen being touched at the same time as the participant’s own face. This face was either neutral, fearful, or angry. Anger was chosen as an emotional control condition for fear because it is similarly negative but induces less somatosensory resonance, and requires additional knowledge  to effectively guide behavior. We hypothesized that seeing a fearful face (but not an angry one) would increase enfacement because of greater somatosensory resonance. Surprisingly, neither fearful nor angry expressions modulated the degree of enfacement relative to neutral expressions. Synchronous interpersonal visuo-tactile stimulation led to assimilation of the other’s face, but this assimilation was not modulated by facial expression processing. This finding suggests that dynamic, multisensory processes of self-face identification operate independently of facial expression processing. The mental self-face representation comprises an important part of both self-identity and the mental representation of one’s own body . Indeed,While the studies described above focused on visual self-recognition, more recent accounts of self-recognition have attempted to explain how the mental self-representation, including the self-face, is constructed and updated over time via the convergence of multimodal inputs . This liBeing interpersonal by definition, enfacement might be influenced by the social and emotional context of the IMS experience. Supporting this notion, the strength of the enfacement illusion is positively correlated with participants’ empathic traits, specifically the tendencies to adopt another’s point of view and to share others’ emotions and feelings . In addiEmotional facial expressions convey an intention to communicate, and may thus motivate greater effort on the part of the observer to understand the affective state of the other person. Fear is particularly important as a communicative signal because it usually indicates the presence of an immediate threat. Efficient and accurate recognition of a fearful facial expression confers both a private advantage to the observer by warning her of a potential threat to herself and a social benefit by facilitating an appropriate reaction to the distress of her companion. One might predict that enfacement would be especially susceptible to fearful facial expressions because they carry such valuable information for the adaptive behavior of the observer.Perhaps because they are important for both personal safety and social interaction, seeing fearful faces produces greater resonance in somatosensory cortex than seeing other emotional expressions –20. SomaTo summarize, an observer who sees a fearful face might be more motivated to understand the other’s affective state because of the value of the information that person is communicating. Achieving this understanding would entail simulating the other’s emotional state, thereby activating somatosensory cortex. During synchronous IMS, the somatosensory activation evoked by a fearful face, in combination with the somatosensory resonance induced by seeing another’s face touched in synchrony with one’s own ,23,24, mThe present experiment examined whether varying the emotional content of faces would affect the strength of the enfacement effect. In each experimental session, participants saw a fearful, an angry, or a neutral face being touched with a cotton swab either synchronously or asynchronously with a cotton swab touching their own face. Before and after this period of IMS, the participants watched a video of the same person’s face  gradually morphing into their own face, and stopped the morph video as soon as it began to look more like their own face than the other person’s face. We did not vary the emotional expression of the other person in the morph video because our hypothesis was based on a fear-specific enhancement of somatosensory resonance. Thus, the crucial time for presentation of the emotional expression was the period in which participants saw the other person being touched while feeling touch on their own face. The difference in the amount of the other person’s face in the frame where the participant stopped the morph video before and after synchronous IMS was taken as a measure of enfacement. The asynchronous IMS session controlled for any effects of exposure to uncorrelated visual and tactile stimulation, as well as any effect of mere familiarity with the other person’s face. A questionnaire was also used to assess the subjective strength of the enfacement illusion. It was predicted that enfacement would be comparable for neutral and angry faces, whereas seeing a fearful face would strengthen the enfacement effect due to enhanced somatosensory resonance and greater motivation to understand the other’s affective state. Instead, neither fearful nor angry expressions influenced the strength of the enfacement effect. This result is discussed in light of an asymmetric relationship between the processing of facial identity and facial expressions –30M = 25.06 years old, SD = ±1.83 years; Anger group: M = 25.06 years old, SD = ±2.21 years; Neutral group: M = 23.50 years old, SD = ±2.43 years). Participants in the Neutral group were only slightly younger on average than participants in the Fear group, t(34) = 2.17, p = .037, and the Anger group, t(34) = 2.01, p = .053. Each group saw a different emotional expression  during IMS. All participants had normal or corrected-to normal vision, reported normal tactile perception, and were naïve to the purpose of the experiment.Fifty-four female volunteers between 19 and 32 years old were recruited from the University of Bologna and randomly assigned to one of three experimental groups, resulting in three groups of 18 participants each  for use as the other-faces. Participant and other-face photographs were matched in luminance. These photographs were then blended in Abrosoft Fantamorph 4 to create dynamic morph videos that progressed from 100% other-face to 100% self-face. The morph videos were 100 s long and progressed at a rate of 1% change in face per second, resulting in a prolonged and subtle morph. Each participant’s face was morphed with two of the other-faces. Note that both the faces of the participants and the other-faces had neutral expressions in the morph videos. Additionally, a camcorder was used to record videos of the other-faces being stroked on the left cheek with a cotton swab. Each video was in full color and 120 s long with strokes occuring approximately every 2 s. While being touched, each volunteer maintained a facial expression  for approximately 10 s, and this segment was then looped to produce the full 120 s video . To makeM = 24.64 years old, SD = ±9.59 years). These volunteers did not differ in age from the participants in the main experiment, t(77) = -0.08, p = .940. Volunteers in the pilot study categorized the emotional expressions in the videos  and rated emotion intensity . They also rated the attractiveness of the faces in the neutral photographs  and how much the person in each video resembled their corresponding photograph .  and IMS mode (synchronous or asynchronous) as within-subjects variables and facial expression  as a between-subjects variable. The key dependent variable was the amount of the other’s face contained in the frame where participants stopped the morph video. Responses to the questionnaire items also served as a subjective measures of the enfacement illusion.F = 10.96, p = .002, showing that, overall, participants stopped the morph videos sooner (at a frame containing less of their own face and more of the other person’s face) after IMS than before.A 2 x 2 x 3 mixed factors ANOVA with time (pre- or post-IMS) and IMS mode (synchronous or asynchronous) as within-subjects factors and the other’s facial expression during IMS  as a between-subjects factor was conducted on the amount of the other person’s face in the frame where participants stopped the morph video. This yielded a main effect of time, F = 8.96, p = .004. Paired samples t-tests were then used to make post-hoc comparisons. A Bonferroni correction was applied to control for multiple comparisons. The corrected significance level is p < .013. Participants stopped the morph video at a frame containing more of the other person’s face after synchronous IMS  than they did before synchronous IMS , t(53) = -4.92, p < .001, indicating that the experience of concurrent visual and tactile stimulation led them to accept more features of the other’s face as their own. Importantly, in sessions with asynchronous IMS, there was no difference in the amount of the other person’s face in the frame where participants stopped the morph video before  and after  IMS, t(53) = -0.61, p = .542, ruling out the possibility that mere exposure to the other’s face with incongruent visual and tactile input could produce the same effect. These results are consistent with previous enfacement studies [M = 47.42%, SE = ±1.51%) and asynchronous  IMS sessions, t(53) = -0.91, p = .368. The difference between post-IMS morph video stopping points in the synchronous  and asynchronous  IMS sessions was also non-significant, t(53) = 1.55, p = .128. Though one might expect enfacement to be reflected in a difference between the frame that participants chose after synchronous and asynchronous IMS, the crucial comparisons are between the post-IMS morph video judgment and the corresponding pre-IMS baseline judgment made in a single experimental session.More importantly, there was an interaction between time and IMS mode,  studies . Pre-IMSF = 2.84, p = .068, no interaction between facial expression and time, F = 0.38, p = .685, or IMS mode, F = 0.84, p = .439, and, critically, no three-way interaction between emotion, time, and IMS, F = 1.09, p = .344. Contrary to our hypothesis, fearful faces did not increase enfacement relative to angry or neutral faces. In fact, the size of the enfacement effect was the same regardless of the emotion expressed by the other person during synchronous IMS  = 8.96, p = .004, with a larger pre/post-IMS difference in the synchronous IMS session  than in the asynchronous IMS session . There was neither a main effect of facial expression, F = 0.38, p = .685, nor an interaction between IMS mode and facial expression, F = 1.09, p = .344. These findings parallel our original analysis, indicating that any differences in baseline morph video judgments between groups did not obscure an effect of facial expression on the size of the enfacement illusion.To check whether differences in baseline, pre-IMS morph video judgments between groups might have obscured differences in the magnitude of enfacement between facial expression conditions, we performed a 2 (IMS mode) x 3  mixed factors ANOVA on the difference between the amount of the other person’s face in the frame participants chose before and after IMS. This approach mitigates the baseline differences between groups. The analysis revealed a significant main effect of IMS mode, Shapiro-Wilk tests revealed that enfacement questionnaire responses were not normally distributed, so non-parametric tests were used for all analyses of the questionnaire data. Due to a computer error, questionnaire responses were not collected after the synchronous IMS session for one participant, so analyses are based on the responses of the remaining 53 participants. Two other participants failed to provide a valid response to one of the questionnaire items , so analyses of these questionnaire items are based on the data from the remaining 52 participants.First, responses to each of the 14 questionnaire items were averaged across emotion conditions to look for a main effect of IMS mode (synchronous vs. asychronous), with higher ratings of agreement predicted in the synchronous session than in the asynchronous session. Ratings were compared using a series of one-tailed Wilcoxon signed-rank tests with a Bonferroni correction to control the family-wise error rate. Participants gave higher ratings of agreement to 10 of the 14 illusion questionnaire items after synchronous relative to asynchronous IMS , indicatTo test for an interaction between IMS mode and emotional expression, we calculated the differences between participants’ ratings of each questionnaire item in the synchronous and asynchronous sessions (synchronous rating—asynchronous rating). These difference scores reflect the amount of enfacement that each participant experienced. We then used Bonferroni-corrected Kruskal-Wallis tests to look for differences in the strength of the enfacement illusion between the groups that viewed fearful, angry, and neutral faces. No differences between emotion conditions were significant, again showing that enfacement was not influenced by the other person’s facial expression.not increase enfacement because anger is a more complex social emotion that requires additional contextual information to be properly understood [In the enfacement paradigm, synchronous interpersonal visual and tactile inputs update the self-face representation, causing the other person’s face to be assimilated. We hypothesized that seeing a fearful face being touched in synchrony with one’s own face would increase enfacement because of greater motivation to understand the affective state of the other person, a process that would involve enhanced somatosensory resonance. We also predicted that seeing an angry face being touched in synchrony with one’s own face would derstood , and becderstood . Contrarneutral expressions. The emotion manipulation only occurred in the IMS video. Our intention was not to show a direct influence of the emotional content of the self/other morph on self-face recognition, but to investigate whether seeing a fearful face would enhance somatosensory resonance, thereby strengthening the enfacement illusion induced by synchronous IMS. Instead, we found that varying the other person’s facial expression did not influence the strength of enfacement. Moreover, these earlier studies found an effect of positive interpersonal dimensions on self-face recognition from self/other morphs, whereas the present study investigated the effect of negative emotional expressions on the synchronous IMS procedure that induces enfacement.Previous studies have shown that visual self-face recognition from self/other morphs is influenced by the affective valence of the other person’s face, especially in terms of positive interpersonal dimensions such as attractiveness and trustworthiness ,16. In cResponses to the enfacement questionnaire further confirmed that participants experienced an illusion of enfacement, but this effect was not influenced by the other person’s facial expression. Participants gave higher ratings of agreement to 10 of the 14 questionnaire items after synchronous IMS compared to asynchronous IMS, including statements assessing both self-identification  and physical similarity  [visual self-face recognition after inducing an illusion with synchronous IMS. Modulation of somatosensory cortical activity by fearful facial expressions might not be expected to have as clear an effect in this paradigm as it does in a tactile detection paradigm.Cardini and colleagues  found thAdditionally, Maister and colleagues  demonstrA long-standing view of face perception holds that facial identity and facial expressions are processed independently ,32, alloThe asymmetric relationship between facial identity and facial expression processing may also shed light on why fearful expressions did not affect enfacement, in spite of their significance for adaptive behavior. Fearful expressions usually signal the presence of an immediate threat in the observer’s environment. Recognizing and reacting appropriately to fearful faces would therefore be critical for personal survival. Though this might make fearful faces especially salient, it does not necessarily follow that they should impact the process of visual self-face recognition, or even facial identity processing in general. As mentioned earlier, facial identity recognition might be hindered if it were easily influenced by dynamic facial expressions.Though the present study did not find an effect of fearful or angry facial expressions on enfacement, it does not rule out the possibility that other facial expressions might modulate the illusion. In contrast to the asymmetric interaction model of facial identity and facial expression processing, some studies have found that happy facial expressions can facilitate the identification of faces as familiar –44. HoweOne might argue that visuo-motor congruence was not balanced across the three facial expression conditions in this experiment. Although even the neutral IMS videos included mild facial movements such as eye blinks that would likely have been incompatible with the participant’s own, these movements are not as sustained as those produced in the emotional facial expression videos. Studies on similar embodiment illusions typically induced by visuo-tactile synchrony have shown that visuo-motor congruence can also impact the assimilation of external bodies or body parts –49. ThusAnother potential limitation of our study is that we did not measure participants’ empathic traits, so we cannot exclude the possibility that the groups may have differed in this respect. A previous study found that people with higher levels of both cognitive and emotional components of empathy tend to be more susceptible to the enfacement illusion . EmpathyIn conclusion, the results of the present study suggest that negative emotional facial expressions do not modulate the extent to which another’s face is assimilated into the self-face representation following synchronous interpersonal visuo-tactile stimulation. Together with the results from a previous study showing that enfacement can enhance fear recognition , our resS1 Dataset(XLSX)Click here for additional data file.S1 Supplementary Materials(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.


A new physical model of the gate controlled Schottky barrier height (SBH) lowering in top-gated graphene field-effect transistors (GFETs) under saturation bias condition is proposed based on the energy conservation equation with the balance assumption. The theoretical prediction of the SBH lowering agrees well with the experimental data reported in literatures. The reduction of the SBH increases with the increasing of gate voltage and relative dielectric constant of the gate oxide, while it decreases with the increasing of oxide thickness, channel length and acceptor density. The magnitude of the reduction is slightly enhanced under high drain voltage. Moreover, it is found that the gate oxide materials with large relative dielectric constant (>20) have a significant effect on the gate controlled SBH lowering, implying that the energy relaxation of channel electrons should be taken into account for modeling SBH in GFETs. Therefore the behavior of carriers in graphene is similar to massless Dirac fermions with speed of 10Hot-electron phenomena are important in all semiconductor devices, which are governed by inelastic interactions between carriers and phonons. Elastic and inelastic collisions are the dominant mechanisms for momentum and energy relaxations, respectively. Hot-electron phenomena in semiconductor devices can be analyzed by using the continuity equation, momentum conservation equation, and energy conservation equation910The aim of this study is to provide an explanation for gate-controlled Schottky barrier of a metal-graphene transistor on a silicon substrate reported in ref. EG equals to zero in x = 0, and the electric field outside the graphene layer is set as zero due to the screen effect by channel electrons. In other words, such a structure shown in EG = 0. Similar to the surface potential method for metal-oxide-semiconductor field effect transistor (MOSFET)The device architecture of a top-gated graphene field-effect transistor can be simplified as the structure shown in x, x is the coordinate along the channel  is the channel surface potential at x, p-type graphene, one obtainswhere Egg is the band gap of the graphene and Egg = 0 for monolayer graphene, qϕB0 is the SBH , nA is the donor doping areal density in the graphene layer, kB is the Boltzmann constant, T is the temperature, and nig is the intrinsic carrier areal concentration of graphene. Thus the derivation of Eq. p-type graphene under depletion approximation can be written aswhere V(0) = Vsat , V(ΔL) = VD , E(0) = Esat (Esat is the saturation channel electric field)Using the boundary conditions where LE, the length of the saturation region ΔL is required, the channel potential can be solved at x = ΔL,In order to determine the effective channel length L is the channel length), Substituting Note that the lateral electric field along the channel in the source region can be treated as the gradual channel approximationFor simplicity, the lateral electric field in the drain region along the channel can be treated to be linear15LE = L – ΔL is the effective channel length. Solving Eq.where Thus the following is obtained:tox = 100 nm, tox = 1nm, Assuming that Furthermore, assuming that In a field-effect transistor, a lateral electric field in the channel not only results in a drift motion of electrons in the channel, but also changes their disordered thermal motion (the electron energy or electron temperature). Thus, the correlation between the electron temperature and lattice temperature in the channel of a transistor under the saturation bias conditions is given as16μe is the mobility of electrons, τe is the ER time of electrons, v is the electron velocity, TL is the lattice temperature (device temperature), and Ech is the lateral electric field along the channel. Based on the gradual channel approximation, the effective SBH seen by the channel electrons when they obtain energy from the ER process can be written aswhere qϕB is the effective SBH. Eq. where n-type graphene, we just need to replace all (NA) with (-ND) in above equations. Then the similar equations for n-type graphene can be obtained.On the other hand, for For the source-drain current, the following equation of Schottky diode current-voltage relationshipS is the contact area between the source (drain) electrode and the channel (graphene), h is the Planck constant, and m* is the effective mass of graphene. Therefore the source-drain current with consideration of the channel electrons ER can be written aswhere 2, Si, and the published electron affinity of SiO2 and Si are 3.9, 11.9, 0.9 eV and 4.05 eV, respectively . International units have been used in all calculations.In our simulation, main parameters are given as following. The dielectric constant of 2.4 is used for grapheneet al thought that such a SBH lowering effect should originate from the image potential in silicon nanowire field effect transistors (FET), where as the experimentally extracted SBH of 0.5 eV is smaller than that of 0.55 eV from the simulation8It was experimentally reported that the effective SBH between graphene and silicon in a graphene device strongly depends on the gate voltagets is the thickness of the nanowire, εs is its dielectric constant of the graphene, qϕBi is the effective SBH with consideration of the image force, the C1, C2, and C3 are fitting parameters. And the channel surface electric field is24where where andUsing the parameters inC1, C2, and C3 are just fitting parameters in the former studies8VD, significant larger that the above theoretically calculation value, which denotes that the image force can not give a good explanation on the experimental data of the gate controlled SBH.Therefore, the hot-electron effect is adopted to theoretically investigate the gate controlled SBH in graphene. In the following results, the different effects of the image potential and the ER of channel electrons on the SBH lowering are shown, and the comparison of simulation results with experimental results of silicon nano-wire FETs is given.VG = 0, it could be found that the VD = 0 V and VD = 1 V is around 0.02 eV according to the experimental data from Fig. 7 of ref. VD = 1 V and VG = 0. It is easily found in orce Eq.  and the orce Eq. ), respecAccording to Eq.VG, and the adjusted R-Square is 0.95308 for linearly fitting of VG, which demonstrates that the SBH lowering caused by the ER of channel electrons agrees better with the experimental results.p-Si contacts, the maximum field graphene/p-Si contact under the abrupt approximation can be written as16For the SBH lowering in the graphene/Eg = 1.12 eV is the band gap of silicon. For a Schottky junction, the reduction in SBH caused by the ER of electrons is Emax), whereas the SBH caused by the image force is Emax).where Emax in comparison with the curve of Emax. The adjusted R-Square is 0.99584 when we linearly fit Emax to Emax to n-type doping in monolayer graphene is around 1 × 1013 cm−2p-type doping in bilayer and monolayer graphene is around 2 × 1013 cm−2p-type silicon is used in the following calculations. It should be noted that the electron velocity in a graphene can reach 1 × 106 m/s1, thus the distance of electron transport in the graphene during 1 ps is 1 μm. For the energy balance conditions, all channel length used in the following calculations is larger than 1 μm. And VFB = 0 is chosen in the all calculations of this work.In the following, we will discuss the detailed influence of the ER of channel electrons on the gate controlled SBH lowering. It should be noted that the saturation density of 11 cm−2) have almost no effect on the effective SBH, but a change in doping density for larger acceptor doping in graphene (>1 × 1011 cm−2) could significantly affect the effective SBH.Though the models presented in the previous literature work31In conclusion, the effect of the ER (Energy Relaxation) of channel electrons on the SBH between graphene and electrode in a GFET has been theoretically investigated and physically modeled. The theoretical calculations agree well with experimental data reported in ref. How to cite this article: Mao, L.-F. et al. Physical Modeling of Gate-Controlled Schottky Barrier Lowering of Metal-Graphene Contacts in Top-Gated Graphene Field-Effect Transistors. Sci. Rep.5, 18307; doi: 10.1038/srep18307 (2015).


The induced SOI leads to a pronounced low-temperature weak anti-localization effect and to a spin-relaxation time two to three orders of magnitude smaller than in graphene on conventional substrates. To interpret our findings we have performed first-principle electronic structure calculations, which confirm that carriers in graphene on WS2 experience a strong SOI and allow us to extract a spin-dependent low-energy effective Hamiltonian. Our analysis shows that the use of WS2 substrates opens a possible new route to access topological states of matter in graphene-based systems.Interfacial interactions allow the electronic properties of graphene to be modified, as recently demonstrated by the appearance of satellite Dirac cones in graphene on hexagonal boron nitride substrates. Ongoing research strives to explore interfacial interactions with other materials to engineer targeted electronic properties. Here we show that with a tungsten disulfide (WS Routes towards inducing strong spin–orbit coupling in graphene have been hindered by detrimental effects on its electronic properties and material quality. Here, the authors demonstrate a possible solution by exploiting interfacial interactions between graphene and a tungsten disulfide substrate. Like hexagonal boron nitride (hBN)μ∼50,000–60,000 cm2 V–1 s–1 have been recently reported for graphene on WS2)  ref. . Transit2 devices with ab initio electronic structure calculations. Specifically, we perform systematic magnetotransport measurements to show that when transferred onto WS2 substrates graphene exhibits a pronounced and robust weak anti-localization (WAL) effect throughout the explored carrier density and temperature range, down to 250 mK. The detection of WAL provides a direct demonstration of the SOI enhancement in graphene due to the interfacial interactions with WS2 substrate. In the attempt to estimate quantitatively the magnitude of SOI enhancement, we show that the magnetotransport data can be fit to the theory of WAL for graphene in the presence of SOI, from which we determine the spin-relaxation time (τso). We find that the value of τso (∼2.5–5 ps) in graphene on WS2 is 100–1,000 times shorter than τso in pristine graphene on SiO2 or hBN. This very strong enhancement of SOI found experimentally is consistent with the result of our ab initio calculations, which indicate that hybridization with the WS2 substrate orbitals is responsible for the SOI induced in graphene, and estimate the SOI strength under the conditions of the experiments to be ∼5 meV. Finally, we show that the results of our calculations close to the K and K′ points can be mapped onto a long-wavelength effective Hamiltonian, which, depending on the values of the parameter, describes a topologically insulating state. We therefore conclude that the possibility of using interfacial interactions to induce a strong SOI in graphene while preserving the high quality of the material opens a new possible route to create and investigate a topological insulating state in graphene.Here we address these issues by combining a study of low-temperature quantum transport in graphene-on-WS2 devices used in our experiments. The devices are assembled in a multi–terminal Hall bar configuration, placed on a highly doped Si wafer that acts as a gate electrode and is coated with 280 nm SiO2  Sweeping the gate voltage down for Vg<8 V, on the contrary, results in an increase  Hall effect and by looking at the slope dσ/dVg, and obtain in both cases μ∼13,000 cm2 V–1 s–1 at T=4.2 K. Since no effort has yet been put into optimizing the fabrication process, these values confirm the very good quality of graphene-on-WS2 devices found in earlier workWe start by characterizing the basic transport properties of the graphene-on-WSSiO2 see . Figure r on top 21. . The random conductance fluctuations, whose reproducibility is shown in Vg values are averagedVg spacing should be chosen to shift the Fermi level by Thouless energy of the system. It is expected that the root mean square amplitude of the fluctuations decreases as N−1/2 , eventually making the sharp conductance peak at B=0 T due to WAL visible, if the strength of SOI is sufficient. This is indeed what the experiments show  peak at 0 T refs , 25. In nts show .Vg range investigated. Its amplitude grows on lowering temperature T , DeB/ħ (D is the carrier diffusion constant) and F(x)=ln(x)+ψ(1/2+1/x) with the digamma function ψ(x). In fitting the data, we constrain all characteristic times to be independent of temperature, except for τφ, which increases on lowering T, as physically expected in the T range investigated. τφ>>τiv, which is the one physically relevant at low T, and reproduces the experimental results quantitatively . This internal consistency of the hierarchy of characteristic times extracted from fitting the data with 2 interface τso is 100–1,000 times shorter than τso for pristine graphene on SiO2 41τso decreases with increasing τ, the Dyakonov–Perel mechanism  may be invoked2 or hBN substrates, previous work has shown that neither scenario convincingly accounts for the observations2, despite the much larger strength of SOI, the interpretation of spin relaxation within the canonical schemes poses similar problems: τso decreases slightly on increasing τ  with τso obtained for graphene on WS2. This close correspondence between two a priori unrelated quantities is remarkable: it strongly suggests that the microscopic processes responsible for scattering between the two valleys are the same processes that cause spin flip in graphene on WS2.Determining the precise nature of the WSng τ see , ruling iO2 refs , 29, hBN2-induced SOI in graphene, and to verify that the large enhancement of the SOI strength we have discovered experimentally is indeed expected theoretically. Supercell electronic structure calculations were performed for a large number of crystal approximants to the incommensurate graphene-on-WS2 system.  is a Pauli matrix vector that acts on the sub lattice degree of freedom in graphene's Dirac continuum model Hamiltonian H0, s= is a Pauli matrix vector that acts on spin and τz=±1 for K and K′ valleys  depend on the supercell commensurability between graphene and WS2 triangular lattices  to the shortening of the spin-relaxation time extracted from the experiments, our results show that the two larger SOI parameters exceed the scale of the SOI in isolated graphene sheets by two to three orders of magnitude342.As a quantitative estimate of the parameters Δ, λ is larger than Δ, the system becomes a topological insulator with gap larger by one to two orders of magnitude than that based on the intrinsic SOI in graphene originally proposed by Kane and Meleλ≈5 meV and λR≈1 meV) should be therefore be viewed as a prediction that graphene on WS2 is a topological insulator. This is an exciting conclusion, because a SOI strength of a few meV brings the possibility to realize a topologically insulating state in graphene closer to what can be realistically achieved experimentally. Care should be taken, however, because the precise values of the parameters Δ, λ and λR may depend on the details of the calculations scheme employed. In particular, even if in our calculations the SOI strength was always found to have a few meV scale irrespective of the approximations made, it is difficult to conclude that Δ>λ in all cases (see 2 relax). At this stage it seems that a reliable determination of the parameters in 2 is a topological insulator or not will require more experiments. Specifically, this may be possible through a careful investigation of the Shubnikov–de Haas oscillations in very-high-mobility devices, capable of detecting a splitting in their frequency and of investigating its precise gate voltage dependence.The general form of the Hamiltonian in 2 that we observe for all investigated values of gate voltage—and hence position of the Fermi energy—is a large effect, close to two orders of magnitude. It directly shows the relevance of interfacial interactions. Demonstrating the ability to combine the control given by these interactions with the high electronic quality inferred from the experiments is a key result: although clearly more optimization is needed, finding that a drastic increase in SOI strength can be achieved without compromising the electronic quality of graphene offers the possibility to improve the system quality even further. To this end, strategies already exist that largely benefit from the expertise developed for graphene and hBN, such as encapsulating graphene between two WS2 crystalsThe increase in spin–obit interaction strength induced in graphene by proximity with WS2 flakes were exfoliated onto a highly doped silicon substrate acting as a gate covered by a SiO2, from high-quality single crystals of WS2 grown by chemical vapour transport method. These exfoliated WS2 flakes were annealed at 200 degrees for 3 h in an inert atmosphere, after which a specific WS2 flake with atomically flat and clean surface was identified through imaging with an atomic force microscope. Transfer of graphene onto the selected WS2 flake was achieved by means of (by now) common techniquesW=2.5 μm, and three pairs of Hall probes  of that of graphene. Supercells with different moiré periodicities were then constructed by repeating these unit cells correspondingly and by aligning the lattice vectors of WS2 with that of graphene without further ionic relaxation. The separation between graphene and WS2 was fixed to a number of different values ranging from 2.3 to 3.3 Å for each supercell. A Monkhorst-Pack k-point meshFully relativistic density functional theory calculations were performed using the Vienna ab-initio Simulation Package with projector-augmented wave pseudopotentials under the generalized gradient approximation50How to cite this article: Wang, Z. et al. Strong interface-induced spin-orbit interaction in graphene on WS2. Nat. Commun. 6:8339 doi: 10.1038/ncomms9339 (2015).Supplementary Figures 1-5, Supplementary Notes 1-7 and Supplementary References